Package ‘imager’

May 11, 2020

Type Package
Title Image Processing Library Based on 'CImg'
Version 0.42.3
Author Simon Barthelme [aut],
David Tschumperle [ctb],
Jan Wijffels [ctb],
Haz Edine Assemlal [ctb],
Shota Ochi [cre]
Maintainer Shota Ochi <shotaochi1990@gmail.com>
Description Fast image processing for images in up to 4 dimensions (two spatial
dimensions, one time/depth dimension, one colour dimension). Provides most
traditional image processing tools (filtering, morphology, transformations,
etc.) as well as various functions for easily analysing image data using R. The
package wraps 'CImg', <http://cimg.eu>, a simple, modern C++ library for image
processing.
License LGPL-3
Imports Rcpp (>=
0.11.5),methods,stringr,png,jpeg,readbitmap,grDevices,purrr,downloader,igraph
Depends R (>= 2.10.0),magrittr
URL http://dahtah.github.io/imager, https://github.com/dahtah/imager
BugReports https://github.com/dahtah/imager/issues
SystemRequirements fftw3,libtiff,C++11
LinkingTo Rcpp
LazyData true
RoxygenNote 7.1.0
Suggests knitr, rmarkdown,ggplot2,dplyr,scales,
testthat,OpenMPController,raster,spatstat, magick,Cairo
VignetteBuilder knitr
NeedsCompilation yes
Repository CRAN
Date/Publication 2020-05-11 16:40:06 UTC

1
2 R topics documented:

R topics documented:
add.colour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
as.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
as.cimg.array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
as.cimg.data.frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
as.cimg.function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
as.cimg.raster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
as.data.frame.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
as.data.frame.imlist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
as.data.frame.pixset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
as.igraph.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
as.igraph.pixset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
as.imlist.list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
as.pixset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
as.raster.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
at . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
autocrop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
bbox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
blur_anisotropic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
boats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
boundary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
boxblur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
boxblur_xy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
bucketfill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
cannyEdges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
capture.plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
center.stencil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
ci . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
cimg.dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
cimg.extract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
cimg.use.openmp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
cimg2im . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
circles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
clean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
colorise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
common_pixsets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
contours . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
coord.index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
correlate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
crop.borders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
deriche . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
diffusion_tensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
displacement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
display . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
display.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
R topics documented: 3

display.list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
distance_transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
draw_circle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
draw_rect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
draw_text . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
erode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
extract_patches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
FFT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
flatten.alpha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
frames . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
get.locations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
get.stencil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
get_gradient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
get_hessian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
grab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
grayscale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
grow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
gsdim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
haar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
highlight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
hough_circle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
hough_line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
idply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
iiply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
ilply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
im2cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
imager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
imager.combine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
imager.replace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
imager.subset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
imappend . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
imchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
imcoord . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
imdirac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
imdraw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
imeval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
imfill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
imgradient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
imhessian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
iminfo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
imlap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
imlist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
imnoise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
implot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
imrep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
imrotate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
imsharpen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
imshift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4 R topics documented:

imsplit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
imsub . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
imwarp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
im_split . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
index.coord . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
inpaint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
interact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
interp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
is.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
is.imlist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
is.pixset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
isoblur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
label . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
liply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
load.dir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
load.example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
load.image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
load.video . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
magick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
make.video . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
map_il . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
medianblur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
mirror . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
mutate_plyr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
nfline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
pad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
patchstat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
patch_summary_cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
periodic.part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
permute_axes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
pixel.grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
pixset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
play . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
plot.cimg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
plot.imlist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
px.flood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
px.na . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
px.remove_outer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
RasterPackage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
renorm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
resize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
resize_doubleXY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
RGBtoHSL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
rm.alpha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
rotate_xy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
save.image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
split_connected . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
squeeze . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
add.colour 5

stencil.cross . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
vanvliet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
warp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
watershed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
where . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
%inr% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

Index 129

add.colour Add colour channels to a grayscale image or pixel set

Description
Add colour channels to a grayscale image or pixel set

Usage
add.colour(im, simple = TRUE)

add.color(im, simple = TRUE)

Arguments
im a grayscale image
simple if TRUE just stack three copies of the grayscale image, if FALSE treat the image
as the L channel in an HSL representation. Default TRUE. For pixel sets this
option makes no sense and is ignored.

Value
an image of class cimg

Functions
• add.color: Alias for add.colour

Author(s)
Simon Barthelme

Examples
grayscale(boats) #No more colour channels
add.colour(grayscale(boats)) #Image has depth = 3 (but contains only grays)
6 as.cimg

as.cimg Convert to cimg object

Description
Imager implements various converters that turn your data into cimg objects. If you convert from a
vector (which only has a length, and no dimension), either specify dimensions explicitly or some
guesswork will be involved. See examples for clarifications.

Usage
as.cimg(obj, ...)

## S3 method for class 'numeric'

as.cimg(obj, ...)

## S3 method for class 'logical'

as.cimg(obj, ...)

## S3 method for class 'double'

as.cimg(obj, ...)

## S3 method for class 'cimg'

as.cimg(obj, ...)

## S3 method for class 'vector'

as.cimg(obj, x = NA, y = NA, z = NA, cc = NA, dim = NULL, ...)

## S3 method for class 'matrix'

as.cimg(obj, ...)

Arguments
obj an object
... optional arguments
x width
y height
z depth
cc spectrum
dim a vector of dimensions (optional, use instead of xyzcc)

Methods (by class)

• numeric: convert numeric
• logical: convert logical
as.cimg.array 7

• double: convert double

• cimg: return object
• vector: convert vector
• matrix: Convert to matrix

Author(s)
Simon Barthelme

See Also
as.cimg.array, as.cimg.function, as.cimg.data.frame

Examples
as.cimg(1:100,x=10,y=10) #10x10, grayscale image
as.cimg(rep(1:100,3),x=10,y=10,cc=3) #10x10 RGB
as.cimg(1:100,dim=c(10,10,1,1))
as.cimg(1:100) #Guesses dimensions, warning is issued
as.cimg(rep(1:100,3)) #Guesses dimensions, warning is issued

as.cimg.array Turn an numeric array into a cimg object

Description
If the array has two dimensions, we assume it’s a grayscale image. If it has three dimensions we
assume it’s a video, unless the third dimension has a depth of 3, in which case we assume it’s a
colour image,

Usage
## S3 method for class 'array'
as.cimg(obj, ...)

Arguments
obj an array
... ignored

Examples
as.cimg(array(1:9,c(3,3)))
as.cimg(array(1,c(10,10,3))) #Guesses colour image
as.cimg(array(1:9,c(10,10,4))) #Guesses video
8 as.cimg.data.frame

as.cimg.data.frame Create an image from a data.frame

Description

This function is meant to be just like as.cimg.data.frame, but in reverse. Each line in the data
frame must correspond to a pixel. For example, the data fame can be of the form (x,y,value) or
(x,y,z,value), or (x,y,z,cc,value). The coordinates must be valid image coordinates (i.e., positive
integers).

Usage

## S3 method for class 'data.frame'

as.cimg(obj, v.name = "value", dims, ...)

Arguments

obj a data.frame
v.name name of the variable to extract pixel values from (default "value")
dims a vector of length 4 corresponding to image dimensions. If missing, a guess will
be made.
... ignored

Value

an object of class cimg

Author(s)

Simon Barthelme

Examples

#Create a data.frame with columns x,y and value

df <- expand.grid(x=1:10,y=1:10) %>% dplyr::mutate(value=x*y)
#Convert to cimg object (2D, grayscale image of size 10*10
as.cimg(df,dims=c(10,10,1,1)) %>% plot
as.cimg.function 9

as.cimg.function Create an image by sampling a function

Description

Similar to as.im.function from the spatstat package, but simpler. Creates a grid of pixel coordinates
x=1:width,y=1:height and (optional) z=1:depth, and evaluates the input function at these values.

Usage

## S3 method for class '`function`'

as.cimg(
obj,
width,
height,
depth = 1,
spectrum = 1,
standardise = FALSE,
dim = NULL,
...
)

Arguments

obj a function with arguments (x,y), or (x,y,cc), or (x,y,z), etc. Must be vectorised;
see examples.
width width of the image (in pixels)
height height of the image (in pixels)
depth depth of the image (in pixels). Default 1.
spectrum number of colour channels. Defaut 1.
standardise coordinates are scaled and centered (see doc for pixel.grid)
dim a vector of image dimensions (can be used instead of width, height, etc.)
... ignored

Value

an object of class cimg

Author(s)

Simon Barthelme
10 as.cimg.raster

Examples
im = as.cimg(function(x,y) cos(sin(x*y/100)),100,100)
plot(im)
#The following is just a rectangle at the center of the image
im = as.cimg(function(x,y) (abs(x) < .1)*(abs(y) < .1) ,100,100,standardise=TRUE)
plot(im)
#Since coordinates are standardised the rectangle scales with the size of the image
im = as.cimg(function(x,y) (abs(x) < .1)*(abs(y) < .1) ,200,200,standardise=TRUE)
plot(im)
#A Gaussian mask around the center
im = as.cimg(function(x,y) dnorm(x,sd=.1)*dnorm(y,sd=.3) ,dim=dim(boats),standardise=TRUE)
im = im/max(im)

plot(im*boats)
#A Gaussian mask for just the red channel
fun = function(x,y,cc) ifelse(cc==1,dnorm(x,sd=.1)*dnorm(y,sd=.3),0)
im = as.cimg(fun,dim=dim(boats),standardise=TRUE)
plot(im*boats)

as.cimg.raster Convert a raster object to a cimg object

Description
R’s native object for representing images is a "raster". This function converts raster objects to cimg
objects.

Usage
## S3 method for class 'raster'
as.cimg(obj, ...)

Arguments
obj a raster object
... ignored

Value
a cimg object

Author(s)
Simon Barthelme
as.data.frame.cimg 11

Examples
rst <- as.raster(matrix((1:4)/4,2,2))
as.cimg(rst) %>% plot(int=FALSE)
all.equal(rst,as.raster(as.cimg(rst)))

as.data.frame.cimg Convert a pixel image to a data.frame

Description

This function combines the output of pixel.grid with the actual values (stored in $value)

Usage

## S3 method for class 'cimg'

as.data.frame(x, ..., wide = c(FALSE, "c", "d"))

Arguments

x an image of class cimg

... arguments passed to pixel.grid
wide if "c" or "d" return a data.frame that is wide along colour or depth (for example
with rgb values along columns). The default is FALSE, with each pixel forming
a separate entry.

Value

a data.frame

Author(s)

Simon Barthelme

Examples

#First five pixels

as.data.frame(boats) %>% head(5)
#Wide format along colour axis
as.data.frame(boats,wide="c") %>% head(5)
12 as.data.frame.pixset

as.data.frame.imlist Convert image list to data.frame

Description
Convert image list to data.frame

Usage
## S3 method for class 'imlist'
as.data.frame(x, ..., index = "im")

Arguments
x an image list (an imlist object)
... Passed on to as.data.frame.cimg
index Name of the column containing the index (or name) of the image in the list.
Default: "im"

Examples
#Transform the image gradient into a data.frame
gr <- imgradient(boats,"xy") %>% setNames(c("dx","dy")) %>% as.data.frame
str(gr)

as.data.frame.pixset Methods to convert pixsets to various objects

Description
Methods to convert pixsets to various objects

Usage
## S3 method for class 'pixset'
as.data.frame(x, ..., drop = FALSE)

Arguments
x pixset to convert
... ignored
drop drop flat dimensions

See Also
where
as.igraph.cimg 13

Examples

px <- boats > 250

#Convert to array of logicals
as.logical(px) %>% dim
#Convert to data.frame: gives all pixel locations in the set
as.data.frame(px) %>% head
#Drop flat dimensions
as.data.frame(px,drop=TRUE) %>% head

as.igraph.cimg Form a graph from an image

Description

In this graph representation, every pixel is a vertex connected to its neighbours. The image values
along edges are stored as graph attributes (see examples).

Usage

## S3 method for class 'cimg'

as.igraph(x, mask = px.all(channel(im, 1)), ...)

Arguments

x an image (must be 2D, 3D not implemented yet)

mask optional: a pixset. if provided, pixels are only connected if they are both in the
pixset.
... ignored

Value

a graph (igraph format) with attributes value.from, value.to and dist

Author(s)

Simon Barthelme

See Also

as.igraph.pixset
14 as.igraph.pixset

Examples
library(igraph)
im <- imfill(5,5)
G <- as.igraph(im)
plot(G)
#Shortest-path distance from pixel 1 to all other pixels
d <- igraph::distances(G,1) %>% as.vector
as.cimg(d,dim=gsdim(im)) %>% plot(interpolate=FALSE)
#Notice that moving along the diagonal has the same cost
#as moving along the cardinal directions, whereas the Euclidean distance
#is actually sqrt(2) and not 1.
#Modify weight attribute, to change the way distance is computed
igraph::E(G)$weight <- G$dist
d2 <- igraph::distances(G,1) %>% as.vector
as.cimg(d2,dim=gsdim(im)) %>% plot(interpolate=FALSE)
#More interesting example
im <- grayscale(boats)
G <- as.igraph(im)
#value.from holds the value of the source pixel, value.to the sink's
#set w_ij = (|v_i - v_j|)/d_ij
igraph::E(G)$weight <- (abs(G$value.from - G$value.to))/G$dist
igraph::distances(G,5000) %>% as.vector %>%
as.cimg(dim=gsdim(im)) %>% plot

as.igraph.pixset Form an adjacency graph from a pixset

Description
Return a graph where nodes are pixels, and two nodes are connected if and only if both nodes are in
the pixset, and the pixels are adjacent. Optionnally, add weights corresponding to distance (either 1
or sqrt(2), depending on the orientation of the edge). The graph is represented as an igraph "graph"
object

Usage
## S3 method for class 'pixset'
as.igraph(x, weighted = TRUE, ...)

Arguments
x a pixset
weighted add weight for distance (default TRUE)
... ignored

Value
an igraph "graph" object
as.imlist.list 15

See Also

as.igraph.cimg

Examples
library(igraph)
#Simple 3x3 lattice
px <- px.all(imfill(3,3))
as.igraph(px) %>% plot
#Disconnect central pixel
px[5] <- FALSE
as.igraph(px) %>% plot
#Form graph from thresholded image
im <- load.example("coins")
px <- threshold(im) %>% fill(5)
G <- as.igraph(px)
#Label connected components
v <- (igraph::clusters(G)$membership)
as.cimg(v,dim=dim(px)) %>% plot
#Find a path across the image that avoids all
#the coins
G <- as.igraph(!px)
start <- index.coord(im,data.frame(x=1,y=100))
end <- index.coord(im,data.frame(x=384,y=300))
sp <- igraph::shortest_paths(G,start,end,output="vpath")
path <- sp$vpath[[1]] %>% as.integer %>% coord.index(im,.)

as.imlist.list Convert various objects to image lists

Description

Convert various objects to image lists

Usage

## S3 method for class 'list'

as.imlist(obj, ...)

as.imlist(obj, ...)

## S3 method for class 'imlist'

as.imlist(obj, ...)

## S3 method for class 'cimg'

as.imlist(obj, ...)
16 as.pixset

Arguments
obj an image list
... ignored

Value
a list

Methods (by class)

• list: convert from list
• imlist: Convert from imlist (identity)
• cimg: Convert from image

Examples
list(a=boats,b=boats*2) %>% as.imlist

as.pixset Methods to convert various objects to pixsets

Description
Methods to convert various objects to pixsets

Usage
as.pixset(x, ...)

## S3 method for class 'cimg'

as.pixset(x, ...)

## S3 method for class 'pixset'

as.cimg(obj, ...)

Arguments
x object to convert to pixset
... ignored
obj pixset to convert

Methods (by class)

• cimg: convert cimg to pixset
• pixset: convert pixset to cimg
as.raster.cimg 17

Examples
#When converting an image to a pixset, the default is to include all pixels with non-zero value
as.pixset(boats)
#The above is equivalent to:
boats!=0

as.raster.cimg Convert a cimg object to a raster object for plotting

Description
raster objects are used by R’s base graphics for plotting. R wants hexadecimal RGB values for plot-
ting, e.g. gray(0) yields #000000, meaning black. If you want to control precisely how numerical
values are turned into colours for plotting, you need to specify a colour scale using the colourscale
argument (see examples). Otherwise the default is "gray" for grayscale images, "rgb" for colour.
These expect values in [0..1], so the default is to rescale the data to [0..1]. If you wish to over-ride
that behaviour, set rescale=FALSE.

Usage
## S3 method for class 'cimg'
as.raster(
x,
frames,
rescale = TRUE,
colourscale = NULL,
colorscale = NULL,
col.na = rgb(0, 0, 0, 0),
...
)

Arguments
x an image (of class cimg)
frames which frames to extract (in case depth > 1)
rescale rescale so that pixel values are in [0,1]? (subtract min and divide by range).
default TRUE
colourscale a function that returns RGB values in hexadecimal
colorscale same as above in American spelling
col.na which colour to use for NA values, as R rgb code. The default is "rgb(0,0,0,0)",
which corresponds to a fully transparent colour.
... ignored
18 at

Value

a raster object

Author(s)

Simon Barthelme

See Also

plot.cimg, rasterImage

Examples

#A raster is a simple array of RGB values

as.raster(boats) %>% str
#By default as.raster rescales input values, so that:
all.equal(as.raster(boats),as.raster(boats/2)) #TRUE
#Setting rescale to FALSE changes that
as.raster(boats,rescale=FALSE) %>% plot
as.raster(boats/2,rescale=FALSE) %>% plot
#For grayscale images, a colourmap should take a single value and
#return an RGB code
#Example: mapping grayscale value to saturation
cscale <- function(v) hsv(.5,v,1)
grayscale(boats) %>% as.raster(colourscale=cscale) %>% plot

at Return or set pixel value at coordinates

Description

Return or set pixel value at coordinates

Usage

at(im, x, y, z = 1, cc = 1)

at(im, x, y, z = 1, cc = 1) <- value

color.at(im, x, y, z = 1)

color.at(im, x, y, z = 1) <- value

autocrop 19

Arguments
im an image (cimg object)
x x coordinate (vector)
y y coordinate (vector)
z z coordinate (vector, default 1)
cc colour coordinate (vector, default 1)
value replacement

Value
pixel values

Functions
• at<-: set value of pixel at a location
• color.at: return value of all colour channels at a location
• color.at<-: set value of all colour channels at a location

Author(s)
Simon Barthelme

Examples
im <- as.cimg(function(x,y) x+y,50,50)
at(im,10,1)
at(im,10:12,1)
at(im,10:12,1:3)
at(im,1,2) <- 10
at(im,1,2)
color.at(boats,x=10,y=10)
im <- boats
color.at(im,x=10,y=10) <- c(255,0,0)
#There should now be a red dot
imsub(im, x %inr% c(1,100), y %inr% c(1,100)) %>% plot

autocrop Autocrop image region

Description
Autocrop image region

Usage
autocrop(im, color = color.at(im, 1, 1), axes = "zyx")
20 bbox

Arguments
im an image
color Colour used for the crop. If missing, the colour is taken from the top-left pixel.
Can also be a colour name (e.g. "red", or "black")
axes Axes used for the crop.

Examples
#Add pointless padding
padded <- pad(boats,30,"xy")
plot(padded)
#Remove padding
autocrop(padded) %>% plot
#You can specify the colour if needs be
autocrop(padded,"black") %>% plot
#autocrop has a zero-tolerance policy: if a pixel value is slightly different from the one you gave
#the pixel won't get cropped. A fix is to do a bucket fill first
padded <- isoblur(padded,10)
autocrop(padded) %>% plot
padded2 <- bucketfill(padded,1,1,col=c(0,0,0),sigma=.1)
autocrop(padded2) %>% plot

bbox Compute the bounding box of a pixset

Description
This function returns the bounding box of a pixset as another pixset. If the image has more than one
frame, a bounding cube is returned. If the image has several colour channels, the bounding box is
computed separately in each channel. crop.bbox crops an image using the bounding box of a pixset.

Usage
bbox(px)

crop.bbox(im, px)

Arguments
px a pixset
im an image

Value
a pixset object
blur_anisotropic 21

Functions
• crop.bbox: crop image using the bounding box of pixset px

Author(s)
Simon Barthelme

Examples
im <- grayscale(boats)
px <- im > .85
plot(im)
highlight(bbox(px))
highlight(px,col="green")
crop.bbox(im,px) %>% plot

blur_anisotropic Blur image anisotropically, in an edge-preserving way.

Description
Standard blurring removes noise from images, but tends to smooth away edges in the process. This
anisotropic filter preserves edges better.

Usage
blur_anisotropic(
im,
amplitude,
sharpness = 0.7,
anisotropy = 0.6,
alpha = 0.6,
sigma = 1.1,
dl = 0.8,
da = 30,
gauss_prec = 2,
interpolation_type = 0L,
fast_approx = TRUE
)

Arguments
im an image
amplitude Amplitude of the smoothing.
sharpness Sharpness.
anisotropy Anisotropy.
22 boats

alpha Standard deviation of the gradient blur.

sigma Standard deviation of the structure tensor blur.
dl Spatial discretization.
da Angular discretization.
gauss_prec Precision of the diffusion process.
interpolation_type
Interpolation scheme. Can be 0=nearest-neighbor | 1=linear | 2=Runge-Kutta
fast_approx If true, use fast approximation (default TRUE)

Examples

im <- load.image(system.file('extdata/Leonardo_Birds.jpg',package='imager'))
im.noisy <- (im + 80*rnorm(prod(dim(im))))
blur_anisotropic(im.noisy,ampl=1e4,sharp=1) %>% plot

boats Photograph of sailing boats from Kodak set

Description

This photograph was downloaded from http://r0k.us/graphics/kodak/kodim09.html. Its size was

reduced by half to speed up loading and save space.

Usage

boats

Format

an image of class cimg

Source

http://r0k.us/graphics/kodak/kodim09.html
boundary 23

boundary Find the boundary of a shape in a pixel set

Description
Find the boundary of a shape in a pixel set

Usage
boundary(px, depth = 1, high_connexity = FALSE)

Arguments
px pixel set
depth boundary depth (default 1)
high_connexity if FALSE, use 4-point neighbourhood. If TRUE, use 8-point. (default FALSE)

Examples
px.diamond(10,30,30) %>% boundary %>% plot
px.square(10,30,30) %>% boundary %>% plot
px.square(10,30,30) %>% boundary(depth=3) %>% plot
px <- (px.square(10,30,30) | px.circle(12,30,30))
boundary(px,high=TRUE) %>% plot(int=TRUE,main="8-point neighbourhood")
boundary(px,high=TRUE) %>% plot(int=FALSE,main="4-point neighbourhood")

boxblur Blur image with a box filter (square window)

Description
Blur image with a box filter (square window)

Usage
boxblur(im, boxsize, neumann = TRUE)

Arguments
im an image
boxsize Size of the box window (can be subpixel).
neumann If true, use Neumann boundary conditions, Dirichlet otherwise (default true,
Neumann)
24 boxblur_xy

See Also

deriche(), vanvliet().

Examples

boxblur(boats,5) %>% plot(main="Dirichlet boundary")

boxblur(boats,5,TRUE) %>% plot(main="Neumann boundary")

boxblur_xy Blur image with a box filter.

Description

This is a recursive algorithm, not depending on the values of the box kernel size.

Usage

boxblur_xy(im, sx, sy, neumann = TRUE)

Arguments

im an image
sx Size of the box window, along the X-axis.
sy Size of the box window, along the Y-axis.
neumann If true, use Neumann boundary conditions, Dirichlet otherwise (default true,
Neumann)

See Also

blur().

Examples

boxblur_xy(boats,20,5) %>% plot(main="Anisotropic blur")

bucketfill 25

bucketfill Bucket fill

Description
Bucket fill

Usage
bucketfill(
im,
x,
y,
z = 1,
color,
opacity = 1,
sigma = 0,
high_connexity = FALSE
)

Arguments
im an image
x X-coordinate of the starting point of the region to fill.
y Y-coordinate of the starting point of the region to fill.
z Z-coordinate of the starting point of the region to fill.
color a vector of values (of length spectrum(im)), or a colour name (e.g. "red"). If
missing, use the colour at location (x,y,z).
opacity opacity. If the opacity is below 1, paint with transparency.
sigma Tolerance for neighborhood values: spread to neighbours if difference is less
than sigma (for grayscale). If there are several channels, the sum of squared
differences is used: if it below sigma^2, the colour spreads.
high_connexity Use 8-connexity (only for 2d images, default FALSE).

See Also
px.flood

Examples
#Change the colour of a sail
boats.new <- bucketfill(boats,x=169,y=179,color="pink",sigma=.2)
layout(t(1:2))
plot(boats,main="Original")
plot(boats.new,main="New sails")
26 cannyEdges

#More spreading, lower opacity, colour specified as vector

ugly <- bucketfill(boats,x=169,y=179,color=c(0,1,0),sigma=.6,opacity=.5)
plot(ugly)

cannyEdges Canny edge detector

Description

If the threshold parameters are missing, they are determined automatically using a k-means heuris-
tic. Use the alpha parameter to adjust the automatic thresholds up or down The thresholds are
returned as attributes. The edge detection is based on a smoothed image gradient with a degree of
smoothing set by the sigma parameter.

Usage

cannyEdges(im, t1, t2, alpha = 1, sigma = 2)

Arguments

im input image
t1 threshold for weak edges (if missing, both thresholds are determined automati-
cally)
t2 threshold for strong edges
alpha threshold adjusment factor (default 1)
sigma smoothing

Author(s)

Simon Barthelme

Examples
cannyEdges(boats) %>% plot
#Make thresholds less strict
cannyEdges(boats,alpha=.4) %>% plot
#Make thresholds more strict
cannyEdges(boats,alpha=1.4) %>% plot
capture.plot 27

capture.plot Capture the current R plot device as a cimg image

Description
Capture the current R plot device as a cimg image

Usage
capture.plot()

Value
a cimg image corresponding to the contents of the current plotting window

Author(s)
Simon Barthelme

Examples
##interactive only:
##plot(1:10)
###Make a plot of the plot
##capture.plot() %>% plot

center.stencil Center stencil at a location

Description
Center stencil at a location

Usage
center.stencil(stencil, ...)

Arguments
stencil a stencil (data.frame with coordinates dx,dy,dz,dc)
... centering locations (e.g. x=4,y=2)

Examples
stencil <- data.frame(dx=seq(-2,2,1),dy=seq(-2,2,1))
center.stencil(stencil,x=10,y=20)
28 ci

channels Split a colour image into a list of separate channels

Description
Split a colour image into a list of separate channels

Usage
channels(im, index, drop = FALSE)

Arguments
im an image
index which channels to extract (default all)
drop if TRUE drop extra dimensions, returning normal arrays and not cimg objects

Value
a list of channels

See Also
frames

Examples
channels(boats)
channels(boats,1:2)
channels(boats,1:2,drop=TRUE) %>% str #A list of 2D arrays

ci Concatenation for image lists

Description
Allows you to concatenate image lists together, or images with image lists. Doesn’t quite work like
R’s "c" primitive: image lists are always *flat*, not nested, meaning each element of an image list
is an image.

Usage
ci(...)
cimg 29

Arguments
... objects to concatenate

Value
an image list

Author(s)
Simon Barthelme

Examples

l1 <- imlist(boats,grayscale(boats))
l2 <- imgradient(boats,"xy")
ci(l1,l2) #List + list
ci(l1,imfill(3,3)) #List + image
ci(imfill(3,3),l1,l2) #Three elements, etc.

cimg Create a cimg object

Description
cimg is a class for storing image or video/hyperspectral data. It is designed to provide easy inter-
action with the CImg library, but in order to use it you need to be aware of how CImg wants its
image data stored. Images have up to 4 dimensions, labelled x,y,z,c. x and y are the usual spatial
dimensions, z is a depth dimension (which would correspond to time in a movie), and c is a colour
dimension. Images are stored linearly in that order, starting from the top-left pixel and going along
*rows* (scanline order). A colour image is just three R,G,B channels in succession. A sequence of
N images is encoded as R1,R2,....,RN,G1,...,GN,B1,...,BN where R_i is the red channel of frame i.
The number of pixels along the x,y,z, and c axes is called (in that order), width, height, depth and
spectrum. NB: Logical and integer values are automatically converted to type double. NAs are not
supported by CImg, so you should manage them on the R end of things.

Usage
cimg(X)

Arguments
X a four-dimensional numeric array

Value
an object of class cimg
30 cimg.dimensions

Author(s)

Simon Barthelme

Examples
cimg(array(1,c(10,10,5,3)))

cimg.dimensions Image dimensions

Description

Image dimensions

Usage

width(im)

height(im)

spectrum(im)

depth(im)

nPix(im)

Arguments

im an image

Functions

• width: Width of the image (in pixels)

• height: Height of the image (in pixels)
• spectrum: Number of colour channels
• depth: Depth of the image/number of frames in a video
• nPix: Total number of pixels (prod(dim(im)))
cimg.extract 31

cimg.extract Various shortcuts for extracting colour channels, frames, etc

Description
Various shortcuts for extracting colour channels, frames, etc
Extract one frame out of a 4D image/video

Usage
frame(im, index)

imcol(im, x)

imrow(im, y)

channel(im, ind)

R(im)

G(im)

B(im)

Arguments
im an image
index frame index
x x coordinate of the row
y y coordinate of the row
ind channel index

Functions
• frame: Extract frame
• imcol: Extract a particular column from an image
• imrow: Extract a particular row from an image
• channel: Extract an image channel
• R: Extract red channel
• G: Extract green channel
• B: Extract blue channel

Author(s)
Simon Barthelme
32 cimg.use.openmp

Examples

#Extract the red channel from the boats image, then the first row, plot
rw <- R(boats) %>% imrow(10)
plot(rw,type="l",xlab="x",ylab="Pixel value")
#Note that R(boats) returns an image
R(boats)
#while imrow returns a vector or a list
R(boats) %>% imrow(1) %>% str
imrow(boats,1) %>% str

cimg.use.openmp Control CImg’s parallelisation

Description

On supported architectures CImg can parallelise many operations using OpenMP. Use this function
to turn parallelisation on or off.

Usage

cimg.use.openmp(mode = "adaptive")

Arguments

mode Either "adaptive","always" or "none". The default is adaptive (parallelisation for

large images only).

Value

NULL (function is used for side effects)

Author(s)

Simon Barthelme

Examples

cimg.use.openmp("never") #turn off parallelisation

cimg2im 33

cimg2im Convert cimg to spatstat im object

Description
The spatstat library uses a different format for images, which have class "im". This utility converts
a cimg object to an im object. spatstat im objects are limited to 2D grayscale images, so if the image
has depth or spectrum > 1 a list is returned for the separate frames or channels (or both, in which
case a list of lists is returned, with frames at the higher level and channels at the lower one).

Usage
cimg2im(img, W = NULL)

Arguments
img an image of class cimg
W a spatial window (see spatstat doc). Default NULL

Value
an object of class im, or a list of objects of class im, or a list of lists of objects of class im

Author(s)
Simon Barthelme

See Also
im, as.im

circles Add circles to plot

Description
Base R has a function for plotting circles called "symbols". Unfortunately, the size of the circles is
inconsistent across devices. This function plots circles whose radius is specified in used coordinates.

Usage
circles(x, y, radius, bg = NULL, fg = "white", ...)
34 clean

Arguments
x centers (x coordinate)
y centers (y coordinate)
radius radius (in user coordinates)
bg background colour
fg foreground colour
... passed to polygon, e.g. lwd

Value
none, used for side effect

Author(s)
Simon Barthelme

See Also
hough_circle

clean Clean up and fill in pixel sets (morphological opening and closing)

Description
Cleaning up a pixel set here means removing small isolated elements (speckle). Filling in means
removing holes. Cleaning up can be achieved by shrinking the set (removing speckle), followed by
growing it back up. Filling in can be achieved by growing the set (removing holes), and shrinking
it again.

Usage
clean(px, ...)

fill(px, ...)

Arguments
px a pixset
... parameters that define the structuring element to use, passed on to "grow" and
"shrink"

Functions
• fill: Fill in holes using morphological closing
colorise 35

Author(s)

Simon Barthelme

Examples
im <- load.example("birds") %>% grayscale
sub <- imsub(-im,y> 380) %>% threshold("85%")
plot(sub)
#Turn into a pixel set
px <- sub==1
layout(t(1:2))
plot(px,main="Before clean-up")
clean(px,3) %>% plot(main="After clean-up")
#Now fill in the holes
px <- clean(px,3)
plot(px,main="Before filling-in")
fill(px,28) %>% plot(main="After filling-in")

colorise Fill in a colour in an area given by a pixset

Description

Paint all pixels in pixset px with the same colour

Usage

colorise(im, px, col, alpha = 1)

Arguments

im an image
px either a pixset or a formula, as in imeval.
col colour to fill in. either a vector of numeric values or a string (e.g. "red")
alpha transparency (default 1, no transparency)

Value

an image

Author(s)

Simon Barthelme
36 common_pixsets

Examples
im <- load.example("coins")
colorise(im,Xc(im) < 50,"blue") %>% plot
#Same thing with the formula interface
colorise(im,~ x < 50,"blue") %>% plot
#Add transparency
colorise(im,~ x < 50,"blue",alpha=.5) %>% plot
#Highlight pixels with low luminance values
colorise(im,~ . < 0.3,"blue",alpha=.2) %>% plot

common_pixsets Various useful pixsets

Description
These functions define some commonly used pixsets. px.left gives the left-most pixels of an image,
px.right the right-most, etc. px.circle returns an (approximately) circular pixset of radius r, embed-
ded in an image of width x and height y Mathematically speaking, the set of all pixels whose L2
distance to the center equals r or less. px.diamond is similar but returns a diamond (L1 distance less
than r) px.square is also similar but returns a square (Linf distance less than r)

Usage
px.circle(r, x = 2 * r + 1, y = 2 * r + 1)

px.diamond(r, x = 2 * r + 1, y = 2 * r + 1)

px.square(r, x = 2 * r + 1, y = 2 * r + 1)

px.left(im, n = 1)

px.top(im, n = 1)

px.bottom(im, n = 1)

px.right(im, n = 1)

px.borders(im, n = 1)

px.all(im)

px.none(im)

Arguments
r radius (in pixels)
x width (default 2*r+1)
common_pixsets 37

y height (default 2*r+1)

im an image
n number of pixels to include

Value
a pixset

Functions
• px.circle: A circular-shaped pixset
• px.diamond: A diamond-shaped pixset
• px.square: A square-shaped pixset
• px.left: n left-most pixels (left-hand border)
• px.top: n top-most pixels
• px.bottom: n bottom-most pixels
• px.right: n right-most pixels
• px.borders: image borders (to depth n)
• px.all: all pixels in image
• px.none: no pixel in image

Author(s)
Simon Barthelme

Examples
px.circle(20,350,350) %>% plot(interp=FALSE)
px.circle(3) %>% plot(interp=FALSE)
r <- 5
layout(t(1:3))
plot(px.circle(r,20,20))
plot(px.square(r,20,20))
plot(px.diamond(r,20,20))
#These pixsets are useful as structuring elements
px <- grayscale(boats) > .8
grow(px,px.circle(5)) %>% plot
#The following functions select pixels on the left, right, bottom, top of the image
im <- imfill(10,10)
px.left(im,3) %>% plot(int=FALSE)
px.right(im,1) %>% plot(int=FALSE)
px.top(im,4) %>% plot(int=FALSE)
px.bottom(im,2) %>% plot(int=FALSE)
#All of the above
px.borders(im,1) %>% plot(int=FALSE)
38 contours

contours Return contours of image/pixset

Description
This is just a light interface over contourLines. See help for contourLines for details. If the image
has more than one colour channel, return a list with the contour lines in each channel. Does not
work on 3D images.

Usage
contours(x, nlevels, ...)

Arguments
x an image or pixset
nlevels number of contour levels. For pixsets this can only equal two.
... extra parameters passed to contourLines

Value
a list of contours

Author(s)
Simon Barthelme

See Also
highlight

Examples
boats.gs <- grayscale(boats)
ct <- contours(boats.gs,nlevels=3)
plot(boats.gs)
#Add contour lines
purrr::walk(ct,function(v) lines(v$x,v$y,col="red"))
#Contours of a pixel set
px <- boats.gs > .8
plot(boats.gs)
ct <- contours(px)
#Highlight pixset
purrr::walk(ct,function(v) lines(v$x,v$y,col="red"))
coord.index 39

coord.index Coordinates from pixel index

Description
Compute (x,y,z,cc) coordinates from linear pixel index.

Usage
coord.index(im, index)

Arguments
im an image
index a vector of indices

Value
a data.frame of coordinate values

Author(s)
Simon Barthelme

See Also
index.coord for the reverse operation

Examples
cind <- coord.index(boats,33)
#Returns (x,y,z,c) coordinates of the 33rd pixel in the array
cind
all.equal(boats[33],with(cind,at(boats,x,y,z,cc)))
all.equal(33,index.coord(boats,cind))

correlate Correlation/convolution of image by filter

Description
The correlation of image im by filter flt is defined as: res(x, y, z) = sumi,j,k im(x + i, y + j, z +
k) ∗ f lt(i, j, k). The convolution of an image img by filter flt is defined to be: res(x, y, z) =
sumi,j,k img(x − i, y − j, z − k) ∗ f lt(i, j, k)
40 crop.borders

Usage
correlate(im, filter, dirichlet = TRUE, normalise = FALSE)

convolve(im, filter, dirichlet = TRUE, normalise = FALSE)

Arguments
im an image
filter the correlation kernel.
dirichlet boundary condition. Dirichlet if true, Neumann if false (default TRUE, Dirich-
let)
normalise compute a normalised correlation (ie. local cosine similarity)

Functions
• convolve: convolve image with filter

Examples
#Edge filter
filter <- as.cimg(function(x,y) sign(x-5),10,10)
layout(t(1:2))
#Convolution vs. correlation
correlate(boats,filter) %>% plot(main="Correlation")
convolve(boats,filter) %>% plot(main="Convolution")

crop.borders Crop the outer margins of an image

Description
This function crops pixels on each side of an image. This function is a kind of inverse (centred)
padding, and is useful e.g. when you want to get only the valid part of a convolution

Usage
crop.borders(im, nx = 0, ny = 0, nz = 0, nPix)

Arguments
im an image
nx number of pixels to crop along horizontal axis
ny number of pixels to crop along vertical axis
nz number of pixels to crop along depth axis
nPix optional: crop the same number of pixels along all dimensions
deriche 41

Value
an image

Author(s)
Simon Barthelme

Examples
#These two versions are equivalent
imfill(10,10) %>% crop.borders(nx=1,ny=1)
imfill(10,10) %>% crop.borders(nPix=1)

#Filter, keep valid part

correlate(boats,imfill(3,3)) %>% crop.borders(nPix=2)

deriche Apply recursive Deriche filter.

Description
The Deriche filter is a fast approximation to a Gaussian filter (order = 0), or Gaussian derivatives
(order = 1 or 2).

Usage
deriche(im, sigma, order = 0L, axis = "x", neumann = FALSE)

Arguments
im an image
sigma Standard deviation of the filter.
order Order of the filter. 0 for a smoothing filter, 1 for first-derivative, 2 for second.
axis Axis along which the filter is computed ( ’x’ , ’y’, ’z’ or ’c’).
neumann If true, use Neumann boundary conditions (default false, Dirichlet)

Examples
deriche(boats,sigma=2,order=0) %>% plot("Zeroth-order Deriche along x")
deriche(boats,sigma=2,order=1) %>% plot("First-order Deriche along x")
deriche(boats,sigma=2,order=1) %>% plot("Second-order Deriche along x")
deriche(boats,sigma=2,order=1,axis="y") %>% plot("Second-order Deriche along y")
42 displacement

diffusion_tensors Compute field of diffusion tensors for edge-preserving smoothing.

Description
Compute field of diffusion tensors for edge-preserving smoothing.

Usage
diffusion_tensors(
im,
sharpness = 0.7,
anisotropy = 0.6,
alpha = 0.6,
sigma = 1.1,
is_sqrt = FALSE
)

Arguments
im an image
sharpness Sharpness
anisotropy Anisotropy
alpha Standard deviation of the gradient blur.
sigma Standard deviation of the structure tensor blur.
is_sqrt Tells if the square root of the tensor field is computed instead.

displacement Estimate displacement field between two images.

Description
Estimate displacement field between two images.

Usage
displacement(
sourceIm,
destIm,
smoothness = 0.1,
precision = 5,
nb_scales = 0L,
iteration_max = 10000L,
is_backward = FALSE
)
display 43

Arguments
sourceIm Reference image.
destIm Reference image.
smoothness Smoothness of estimated displacement field.
precision Precision required for algorithm convergence.
nb_scales Number of scales used to estimate the displacement field.
iteration_max Maximum number of iterations allowed for one scale.
is_backward If false, match I2(X + U(X)) = I1(X), else match I2(X) = I1(X - U(X)).

display Display object using CImg library

Description
CImg has its own functions for fast, interactive image plotting. Use this if you get frustrated with
slow rendering in RStudio.

Usage
display(x, ...)

Arguments
x an image or a list of images
... ignored

See Also
display.cimg, display.imlist

display.cimg Display image using CImg library

Description
Press escape or close the window to exit.

Usage
## S3 method for class 'cimg'
display(x, ..., rescale = TRUE)
44 display.list

Arguments

x an image (cimg object)

... ignored
rescale if true pixel values are rescaled to [0-1] (default TRUE)

Examples

##Not run: interactive only

##display(boats,TRUE) #Normalisation on
##display(boats/2,TRUE) #Normalisation on, so same as above
##display(boats,FALSE) #Normalisation off
##display(boats/2,FALSE) #Normalisation off, so different from above

display.list Display image list using CImg library

Description

Click on individual images to zoom in.

Usage

## S3 method for class 'list'

display(x, ...)

Arguments

x a list of cimg objects

... ignored

Examples

##Not run: interactive only

## imgradient(boats,"xy") %>% display
distance_transform 45

distance_transform Compute Euclidean distance function to a specified value.

Description
The distance transform implementation has been submitted by A. Meijster, and implements the arti-
cle ’W.H. Hesselink, A. Meijster, J.B.T.M. Roerdink, "A general algorithm for computing distance
transforms in linear time.", In: Mathematical Morphology and its Applications to Image and Signal
Processing, J. Goutsias, L. Vincent, and D.S. Bloomberg (eds.), Kluwer, 2000, pp. 331-340.’ The
submitted code has then been modified to fit CImg coding style and constraints.

Usage
distance_transform(im, value, metric = 2L)

Arguments
im an image
value Reference value.
metric Type of metric. Can be <tt> 0=Chebyshev | 1=Manhattan | 2=Euclidean | 3=Squared-
euclidean </tt>.

Examples
imd <- function(x,y) imdirac(c(100,100,1,1),x,y)
#Image is three white dots
im <- imd(20,20)+imd(40,40)+imd(80,80)
plot(im)
#How far are we from the nearest white dot?
distance_transform(im,1) %>% plot

draw_circle Draw circle on image

Description
Add circle or circles to an image. Like other native CImg drawing functions, this is meant to be
basic but fast. Use implot for flexible drawing.

Usage
draw_circle(im, x, y, radius, color = "white", opacity = 1, filled = TRUE)
46 draw_rect

Arguments

im an image
x x coordinates
y y coordinates
radius radius (either a single value or a vector of length equal to length(x))
color either a string ("red"), a character vector of length equal to x, or a matrix of
dimension length(x) times spectrum(im)
opacity scalar or vector of length equal to length(x). 0: transparent 1: opaque.
filled fill circle (default TRUE)

Value

an image

Author(s)

Simon Barthelme

See Also

implot

Examples
draw_circle(boats,c(50,100),c(150,200),30,"darkgreen") %>% plot
draw_circle(boats,125,60,radius=30,col=c(0,1,0),opacity=.2,filled=TRUE) %>% plot

draw_rect Draw rectangle on image

Description

Add a rectangle to an image. Like other native CImg drawing functions, this is meant to be basic
but fast. Use implot for flexible drawing.

Usage

draw_rect(im, x0, y0, x1, y1, color = "white", opacity = 1, filled = TRUE)
draw_text 47

Arguments
im an image
x0 x coordinate of the bottom-left corner
y0 y coordinate of the bottom-left corner
x1 x coordinate of the top-right corner
y1 y coordinate of the top-right corner
color either a vector, or a string (e.g. "blue")
opacity 0: transparent 1: opaque.
filled fill rectangle (default TRUE)

Value
an image

Author(s)
Simon Barthelme

See Also
implot,draw_circle

Examples
draw_rect(boats,1,1,50,50,"darkgreen") %>% plot

draw_text Draw text on an image

Description
Like other native CImg drawing functions, this is meant to be basic but fast. Use implot for flexible
drawing.

Usage
draw_text(im, x, y, text, color, opacity = 1, fsize = 20)

Arguments
im an image
x x coord.
y y coord.
text text to draw (a string)
color either a vector or a string (e.g. "red")
opacity 0: transparent 1: opaque.
fsize font size (in pix., default 20)
48 erode

Value

an image

Author(s)

Simon Barthelme

See Also

implot,draw_circle,draw_rect

Examples
draw_text(boats,100,100,"Some text",col="black") %>% plot

erode Erode/dilate image by a structuring element.

Description

Erode/dilate image by a structuring element.

Usage

erode(im, mask, boundary_conditions = TRUE, real_mode = FALSE)

erode_rect(im, sx, sy, sz = 1L)

erode_square(im, size)

dilate(im, mask, boundary_conditions = TRUE, real_mode = FALSE)

dilate_rect(im, sx, sy, sz = 1L)

dilate_square(im, size)

mopening(im, mask, boundary_conditions = TRUE, real_mode = FALSE)

mopening_square(im, size)

mclosing_square(im, size)

mclosing(im, mask, boundary_conditions = TRUE, real_mode = FALSE)

erode 49

Arguments

im an image
mask Structuring element.
boundary_conditions
Boundary conditions. If FALSE, pixels beyond image boundaries are considered
to be 0, if TRUE one. Default: TRUE.
real_mode If TRUE, perform erosion as defined on the reals. If FALSE, perform binary
erosion (default FALSE).
sx Width of the structuring element.
sy Height of the structuring element.
sz Depth of the structuring element.
size size of the structuring element.

Functions

• erode_rect: Erode image by a rectangular structuring element of specified size.

• erode_square: Erode image by a square structuring element of specified size.
• dilate: Dilate image by a structuring element.
• dilate_rect: Dilate image by a rectangular structuring element of specified size
• dilate_square: Dilate image by a square structuring element of specified size
• mopening: Morphological opening (erosion followed by dilation)
• mopening_square: Morphological opening by a square element (erosion followed by dila-
tion)
• mclosing_square: Morphological closing by a square element (dilation followed by erosion)
• mclosing: Morphological closing (dilation followed by erosion)

Examples
fname <- system.file('extdata/Leonardo_Birds.jpg',package='imager')
im <- load.image(fname) %>% grayscale
outline <- threshold(-im,"95%")
plot(outline)
mask <- imfill(5,10,val=1) #Rectangular mask
plot(erode(outline,mask))
plot(erode_rect(outline,5,10)) #Same thing
plot(erode_square(outline,5))
plot(dilate(outline,mask))
plot(dilate_rect(outline,5,10))
plot(dilate_square(outline,5))
50 extract_patches

extract_patches Extract image patches and return a list

Description

Patches are rectangular (cubic) image regions centered at cx,cy (cz) with width wx and height
wy (opt. depth wz) WARNINGS: - values outside of the image region are subject to boundary
conditions. The default is to set them to 0 (Dirichlet), other boundary conditions are listed below. -
widths and heights should be odd integers (they’re rounded up otherwise).

Usage

extract_patches(im, cx, cy, wx, wy, boundary_conditions = 0L)

extract_patches3D(im, cx, cy, cz, wx, wy, wz, boundary_conditions = 0L)

Arguments

im an image
cx vector of x coordinates for patch centers
cy vector of y coordinates for patch centers
wx vector of patch widths (or single value)
wy vector of patch heights (or single value)
boundary_conditions
integer. Can be 0 (Dirichlet, default), 1 (Neumann) 2 (Periodic) 3 (mirror).
cz vector of z coordinates for patch centers
wz vector of coordinates for patch depth

Value

a list of image patches (cimg objects)

Functions

• extract_patches3D: Extract 3D patches

Examples
#2 patches of size 5x5 located at (10,10) and (10,20)
extract_patches(boats,c(10,10),c(10,20),5,5)
FFT 51

FFT Compute the Discrete Fourier Transform of an image

Description

This function is equivalent to R’s builtin fft, up to normalisation (R’s version is unnormalised, this
one is). It calls CImg’s implementation. Important note: FFT will compute a multidimensional Fast
Fourier Transform, using as many dimensions as you have in the image, meaning that if you have a
colour video, it will perform a 4D FFT. If you want to compute separate FFTs across channels, use
imsplit.

Usage

FFT(im.real, im.imag, inverse = FALSE)

Arguments

im.real The real part of the input (an image)

im.imag The imaginary part (also an image. If missing, assume the signal is real).
inverse If true compute the inverse FFT (default: FALSE)

Value

a list with components "real" (an image) and "imag" (an image), corresponding to the real and
imaginary parts of the transform

Author(s)

Simon Barthelme

Examples

im <- as.cimg(function(x,y) sin(x/5)+cos(x/4)*sin(y/2),128,128)

ff <- FFT(im)
plot(ff$real,main="Real part of the transform")
plot(ff$imag,main="Imaginary part of the transform")
sqrt(ff$real^2+ff$imag^2) %>% plot(main="Power spectrum")
#Check that we do get our image back
check <- FFT(ff$real,ff$imag,inverse=TRUE)$real #Should be the same as original
mean((check-im)^2)
52 flatten.alpha

flatten.alpha Flatten alpha channel

Description

Flatten alpha channel

Usage

flatten.alpha(im, bg = "white")

Arguments

im an image (with 4 RGBA colour channels)

bg background: either an RGB image, or a vector of colour values, or a string (e.g.
"blue"). Default: white background.

Value

a blended image

Author(s)

Simon Barthelme

See Also

rm.alpha

Examples

#Add alpha channel

alpha <- Xc(grayscale(boats))/width(boats)
boats.a <- imlist(boats,alpha) %>% imappend("c")
flatten.alpha(boats.a) %>% plot
flatten.alpha(boats.a,"darkgreen") %>% plot
frames 53

frames Split a video into separate frames

Description
Split a video into separate frames

Usage
frames(im, index, drop = FALSE)

Arguments
im an image
index which channels to extract (default all)
drop if TRUE drop extra dimensions, returning normal arrays and not cimg objects

Value
a list of frames

See Also
channels

get.locations Return coordinates of subset of pixels

Description
Typical use case: you want the coordinates of all pixels with a value above a certain threshold

Usage
get.locations(im, condition)

Arguments
im the image
condition a function that takes scalars and returns logicals

Value
coordinates of all pixels such that condition(pixel) == TRUE
54 get.stencil

Author(s)
Simon Barthelme

Examples
im <- as.cimg(function(x,y) x+y,10,10)
get.locations(im,function(v) v < 4)
get.locations(im,function(v) v^2 + 3*v - 2 < 30)

get.stencil Return pixel values in a neighbourhood defined by a stencil

Description
A stencil defines a neighbourhood in an image (for example, the four nearest neighbours in a 2d im-
age). This function centers the stencil at a certain pixel and returns the values of the neighbourhing
pixels.

Usage
get.stencil(im, stencil, ...)

Arguments
im an image
stencil a data.frame with values dx,dy,[dz],[dcc] defining the neighbourhood
... where to center, e.g. x = 100,y = 10,z=3,cc=1

Value
pixel values in neighbourhood

Author(s)
Simon Barthelme

Examples
#The following stencil defines a neighbourhood that
#includes the next pixel to the left (delta_x = -1) and the next pixel to the right (delta_x = 1)
stencil <- data.frame(dx=c(-1,1),dy=c(0,0))
im <- as.cimg(function(x,y) x+y,w=100,h=100)
get.stencil(im,stencil,x=50,y=50)

#A larger neighbourhood that includes pixels upwards and

#downwards of center (delta_y = -1 and +1)
stencil <- stencil.cross()
im <- as.cimg(function(x,y) x,w=100,h=100)
get.stencil(im,stencil,x=5,y=50)
get_gradient 55

get_gradient Compute image gradient.

Description
Compute image gradient.

Usage
get_gradient(im, axes = "", scheme = 3L)

Arguments
im an image
axes Axes considered for the gradient computation, as a C-string (e.g "xy").
scheme = Numerical scheme used for the gradient computation: 1 = Backward finite dif-
ferences 0 = Centered finite differences 1 = Forward finite differences 2 = Using
Sobel masks 3 = Using rotation invariant masks 4 = Using Deriche recursive
filter. 5 = Using Van Vliet recursive filter.

Value
a list of images (corresponding to the different directions)

See Also
imgradient

get_hessian Return image hessian.

Description
Return image hessian.

Usage
get_hessian(im, axes = "")

Arguments
im an image
axes Axes considered for the hessian computation, as a character string (e.g "xy").
56 grab

grab Select image regions interactively

Description

These functions let you select a shape in an image (a point, a line, or a rectangle) They either return
the coordinates of the shape (default), or the contents. In case of lines contents are interpolated.
Note that grabLine does not support the "pixset" return type.

Usage

grabLine(im, output = "coord")

grabRect(im, output = "coord")

grabPoint(im, output = "coord")

Arguments

im an image
output one of "im","pixset","coord","value". Default "coord"

Value

Depending on the value of the output parameter. Either a vector of coordinates (output = "coord"),
an image (output = "im"), a pixset (output = "pixset"), or a vector of values (output = "value").
grabLine and grabPoint support the "value" output mode and not the "im" output.

Author(s)

Simon Barthelme

See Also

display

Examples
##Not run: interactive only
##grabRect(boats)
##grabRect(boats,TRUE)
grayscale 57

grayscale Convert an RGB image to grayscale

Description
This function converts from RGB images to grayscale

Usage
grayscale(im, method = "Luma", drop = TRUE)

Arguments
im an RGB image
method either "Luma", in which case a linear approximation to luminance is used, or
"XYZ", in which case the image is assumed to be in sRGB color space and CIE
luminance is used.
drop if TRUE returns an image with a single channel, otherwise keep the three chan-
nels (default TRUE)

Value
a grayscale image (spectrum == 1)

Examples
grayscale(boats) %>% plot
#In many pictures, the difference between Luma and XYZ conversion is subtle
grayscale(boats,method="XYZ") %>% plot
grayscale(boats,method="XYZ",drop=FALSE) %>% dim

grow Grow/shrink a pixel set

Description
Grow/shrink a pixel set through morphological dilation/erosion. The default is to use square or
rectangular structuring elements, but an arbitrary structuring element can be given as input. A
structuring element is a pattern to be moved over the image: for example a 3x3 square. In "shrink"
mode, a element of the pixset is retained only if and only the structuring element fits entirely within
the pixset. In "grow" mode, the structuring element acts like a neighbourhood: all pixels that are
in the original pixset *or* in the neighbourhood defined by the structuring element belong the new
pixset.
58 gsdim

Usage
grow(px, x, y = x, z = x, boundary = TRUE)

shrink(px, x, y = x, z = x, boundary = TRUE)

Arguments
px a pixset
x either an integer value, or an image/pixel set.
y width of the rectangular structuring element (if x is an integer value)
z depth of the rectangular structuring element (if x is an integer value)
boundary are pixels beyond the boundary considered to have value TRUE or FALSE (de-
fault TRUE)

Functions
• shrink: shrink pixset using erosion

Examples
#A pixel set:
a <- grayscale(boats) > .8
plot(a)
#Grow by a 8x8 square
grow(a,8) %>% plot
#Grow by a 8x2 rectangle
grow(a,8,2) %>% plot
#Custom structuring element
el <- matrix(1,2,2) %>% as.cimg
all.equal(grow(a,el),grow(a,2))
#Circular structuring element
px.circle(5) %>% grow(a,.) %>% plot
#Sometimes boundary conditions matter
im <- imfill(10,10)
px <- px.all(im)
shrink(px,3,bound=TRUE) %>% plot(main="Boundary conditions: TRUE")
shrink(px,3,bound=FALSE) %>% plot(main="Boundary conditions: FALSE")

gsdim Grayscale dimensions of image

Description
Shortcut, returns the dimensions of an image if it had only one colour channel

Usage
gsdim(im)
haar 59

Arguments

im an image

Value

returns c(dim(im)[1:3],1)

Author(s)

Simon Barthelme

Examples
imnoise(dim=gsdim(boats))

haar Compute Haar multiscale wavelet transform.

Description

Compute Haar multiscale wavelet transform.

Usage

haar(im, inverse = FALSE, nb_scales = 1L)

Arguments

im an image
inverse Compute inverse transform (default FALSE)
nb_scales Number of scales used for the transform.

Examples
#Image compression: set small Haar coefficients to 0
hr <- haar(boats,nb=3)
mask.low <- threshold(abs(hr),"75%")
mask.high <- threshold(abs(hr),"95%")
haar(hr*mask.low,inverse=TRUE,nb=3) %>% plot(main="75% compression")
haar(hr*mask.high,inverse=TRUE,nb=3) %>% plot(main="95% compression")
60 hough_circle

highlight Highlight pixel set on image

Description
Overlay an image plot with the contours of a pixel set. Note that this function doesn’t do the image
plotting, just the highlighting.

Usage
highlight(px, col = "red", ...)

Arguments
px a pixel set
col color of the contours
... passed to the "lines" function

Author(s)
Simon Barthelme

See Also
colorise, another way of highlighting stuff

Examples
#Select similar pixels around point (180,200)
px <- px.flood(boats,180,200,sigma=.08)
plot(boats)
#Highlight selected set
highlight(px)
px.flood(boats,18,50,sigma=.08) %>% highlight(col="white",lwd=3)

hough_circle Circle detection using Hough transform

Description
Detects circles of known radius in a pixset. The output is an image where the pixel value at (x,y)
represents the amount of evidence for the presence of a circle of radius r at position (x,y). NB: in
the current implementation, does not detect circles centred outside the limits of the pixset.

Usage
hough_circle(px, radius)
hough_line 61

Arguments
px a pixset (e.g., the output of a Canny detector)
radius radius of circle

Value
a histogram of Hough scores, with the same dimension as the original image.

Author(s)
Simon Barthelme

Examples
im <- load.example('coins')
px <- cannyEdges(im)
#Find circles of radius 20
hc <- hough_circle(px,20)
plot(hc)
#Clean up, run non-maxima suppression
nms <- function(im,sigma) { im[dilate_square(im,sigma) != im] <- 0; im}
hc.clean <- isoblur(hc,3) %>% nms(50)
#Top ten matches
df <- as.data.frame(hc.clean) %>%
dplyr::arrange(desc(value)) %>% head(10)
with(df,circles(x,y,20,fg="red",lwd=3))

hough_line Hough transform for lines

Description
Two algorithms are used, depending on the input: if the input is a pixset then the classical Hough
transform is used. If the input is an image, then a faster gradient-based heuristic is used. The
method returns either an image (the votes), or a data.frame. In both cases the parameterisation
used is the Hesse normal form (theta,rho), where a line is represented as the set of values such that
cos(theta)*x + sin(theta)*y = rho. Here theta is an angle and rho is a distance. The image form
returns a histogram of scores in (rho,theta) space, where good candidates for lines have high scores.
The data.frame form may be more convenient for further processing in R: each line represents a pair
(rho,theta) along with its score. If the ’shift’ argument is true, then the image is assumed to start at
x=1,y=1 (more convenient for plotting in R). If false, the image begins at x=0,y=0 and in both cases
the origin is at the top left.

Usage
hough_line(im, ntheta = 100, data.frame = FALSE, shift = TRUE)
62 idply

Arguments
im an image or pixset
ntheta number of bins along theta (default 100)
data.frame return a data.frame? (default FALSE)
shift if TRUE, image is considered to begin at (x=1,y=1).

Value
either an image or a data.frame

Author(s)
Simon Barthelme

Examples

#Find the lines along the boundary of a square

px <- px.square(30,80,80) %>% boundary
plot(px)
#Hough transform
hough_line(px,ntheta=200) %>% plot

df <- hough_line(px,ntheta=800,data.frame=TRUE)
#Plot lines with the highest score
plot(px)
with(subset(df,score > quantile(score,.9995)),nfline(theta,rho,col="red"))

plot(boats)
df <- hough_line(boats,ntheta=800,data=TRUE)

idply Split an image along axis, map function, return a data.frame

Description
Shorthand for imsplit followed by purrr::map_df

Usage
idply(im, axis, fun, ...)

Arguments
im image
axis axis for the split (e.g "c")
fun function to apply
... extra arguments to function fun
iiply 63

Examples
idply(boats,"c",mean) #mean luminance per colour channel

iiply Split an image, apply function, recombine the results as an image

Description
This is just imsplit followed by purrr::map followed by imappend

Usage
iiply(im, axis, fun, ...)

Arguments
im image
axis axis for the split (e.g "c")
fun function to apply
... extra arguments to function fun

Examples
##' #Normalise colour channels separately, recombine
iiply(boats,"c",function(v) (v-mean(v))/sd(v)) %>% plot

ilply Split an image along axis, apply function, return a list

Description
Shorthand for imsplit followed by purrr::map

Usage
ilply(im, axis, fun, ...)

Arguments
im image
axis axis for the split (e.g "c")
fun function to apply
... extra arguments for function fun
64 imager

Examples
parrots <- load.example("parrots")
ilply(parrots,"c",mean) #mean luminance per colour channel

im2cimg Convert an image in spatstat format to an image in cimg format

Description
as.cimg.im is an alias for the same function

Usage
im2cimg(img)

Arguments
img a spatstat image

Value
a cimg image

Author(s)
Simon Barthelme

imager imager: an R library for image processing, based on CImg

Description
CImg by David Tschumperle is a C++ library for image processing. It provides most common
functions for image manipulation and filtering, as well as some advanced algorithms. imager makes
these functions accessible from R and adds many utilities for accessing and working with image
data from R. You should install ImageMagick if you want support for image formats beyond PNG
and JPEG, and ffmpeg if you need to work with videos (in which case you probably also want to
take a look at experimental package imagerstreams on github). Package documentation is available
at http://dahtah.github.io/imager/.
imager.combine 65

imager.combine Combining images

Description
These functions take a list of images and combine them by adding, multiplying, taking the parallel
min or max, etc. The max. in absolute value of (x1,x2) is defined as x1 if (|x1| > |x2|), x2 otherwise.
It’s useful for example in getting the most extreme value while keeping the sign. "parsort","parrank"
and "parorder" aren’t really reductions because they return a list of the same size. They perform
a pixel-wise sort (resp. order and rank) across the list. parvar returns an unbiased estimate of the
variance (as in the base var function). parsd returns the square root of parvar.

Usage
add(x, na.rm = FALSE)

wsum(x, w, na.rm = FALSE)

average(x, na.rm = FALSE)

mult(x, na.rm = FALSE)

parmax(x, na.rm = FALSE)

parmax.abs(x)

parmin.abs(x)

parmin(x, na.rm = FALSE)

enorm(x)

parmed(x, na.rm = FALSE)

parvar(x, na.rm = FALSE)

parsd(x, na.rm = FALSE)

parall(x)

parany(x)

equal(x)

which.parmax(x)

which.parmin(x)
66 imager.combine

parsort(x, increasing = TRUE)

parorder(x, increasing = TRUE)

parrank(x, increasing = TRUE)

Arguments
x a list of images
na.rm ignore NAs (default FALSE)
w weights (must be the same length as the list)
increasing if TRUE, sort in increasing order (default TRUE)

Functions
• add: Add images
• wsum: Weighted sum of images
• average: Average images
• mult: Multiply images (pointwise)
• parmax: Parallel max over images
• parmax.abs: Parallel max in absolute value over images,
• parmin.abs: Parallel min in absolute value over images,
• parmin: Parallel min over images
• enorm: Euclidean norm (i.e. sqrt(A^2 + B^2 + ...))
• parmed: Median
• parvar: Variance
• parsd: Std. deviation
• parall: Parallel all (for pixsets)
• parany: Parallel any (for pixsets)
• equal: Test equality
• which.parmax: index of parallel maxima
• which.parmin: index of parallel minima
• parsort: pixel-wise sort
• parorder: pixel-wise order
• parrank: pixel-wise rank

Author(s)
Simon Barthelme
imager.replace 67

See Also
imsplit,Reduce

Examples
im1 <- as.cimg(function(x,y) x,50,50)
im2 <- as.cimg(function(x,y) y,50,50)
im3 <- as.cimg(function(x,y) cos(x/10),50,50)
l <- imlist(im1,im2,im3)
add(l) %>% plot #Add the images
average(l) %>% plot #Average the images
mult(l) %>% plot #Multiply
wsum(l,c(.1,8,.1)) %>% plot #Weighted sum
parmax(l) %>% plot #Parallel max
parmin(l) %>% plot #Parallel min
parmed(l) %>% plot #Parallel median
parsd(l) %>% plot #Parallel std. dev
#parsort can also be used to produce parallel max. and min
(parsort(l)[[1]]) %>% plot("Parallel min")
(parsort(l)[[length(l)]]) %>% plot("Parallel max")
#Resize boats so the next examples run faster
im <- imresize(boats,.5)
#Edge detection (Euclidean norm of gradient)
imgradient(im,"xy") %>% enorm %>% plot
#Pseudo-artistic effects
l <- map_il(seq(1,35,5),~ boxblur(im,.))
parmin(l) %>% plot
average(l) %>% plot
mult(l) %>% plot
#At each pixel, which colour channel has the maximum value?
imsplit(im,"c") %>% which.parmax %>% table
#Same thing using parorder (ties are broken differently)!!!
imsplit(im,"c") %>% { parorder(.)[[length(.)]] } %>% table

imager.replace Replace part of an image with another

Description
These replacement functions let you modify part of an image (for example, only the red channel).
Note that cimg objects can also be treated as regular arrays and modified using the usual [] operator.

Usage
channel(x, ind) <- value

R(x) <- value

G(x) <- value

68 imager.subset

B(x) <- value

frame(x, ind) <- value

Arguments
x an image to be modified
ind an index
value the image to insert

Functions
• channel<-: Replace image channel
• R<-: Replace red channel
• G<-: Replace green channel
• B<-: Replace blue channel
• frame<-: Replace image frame

See Also
imdraw

Examples
boats.cp <- boats
#Set the green channel in the boats image to 0
G(boats.cp) <- 0
#Same thing, more verbose
channel(boats.cp,2) <- 0
#Replace the red channel with noise
R(boats.cp) <- imnoise(width(boats),height(boats))
#A new image with 5 frames
tmp <- imfill(10,10,5)
#Fill the third frame with noise
frame(tmp,3) <- imnoise(10,10)

imager.subset Array subset operator for cimg objects

Description
Internally cimg objects are 4D arrays (stored in x,y,z,c mode) but often one doesn’t need all di-
mensions. This is the case for instance when working on grayscale images, which use only two.
The array subset operator works like the regular array [] operator, but it won’t force you to use all
dimensions. There are easier ways of accessing image data, for example imsub, channels, R, G, B,
and the like.
imappend 69

Arguments

x an image (cimg object)

drop if true return an array, otherwise return an image object (default FALSE)
... subsetting arguments

See Also

imsub, which provides a more convenient interface, autocrop, imdraw

Examples
im <- imfill(4,4)
dim(im) #4 dimensional, but the last two ones are singletons
im[,1,,] <- 1:4 #Assignment the standard way
im[,1] <- 1:4 #Shortcut
as.matrix(im)
im[1:2,]
dim(boats)
#Arguments will be recycled, as in normal array operations
boats[1:2,1:3,] <- imnoise(2,3) #The same noise array is replicated over the three channels

imappend Combine a list of images into a single image

Description

All images will be concatenated along the x,y,z, or c axis.

Usage

imappend(imlist, axis)

Arguments

imlist a list of images (all elements must be of class cimg)

axis the axis along which to concatenate (for example ’c’)

See Also

imsplit (the reverse operation)

70 imchange

Examples
imappend(list(boats,boats),"x") %>% plot
imappend(list(boats,boats),"y") %>% plot
purrr::map(1:3, ~imnoise(100,100)) %>% imappend("c") %>% plot
boats.gs <- grayscale(boats)
purrr::map(seq(1,5,l=3),function(v) isoblur(boats.gs,v)) %>% imappend("c") %>% plot
#imappend also works on pixsets
imsplit(boats > .5,"c") %>% imappend("x") %>% plot

imchange Modify parts of an image

Description

A shortcut for modifying parts of an image, using imeval syntax. See doc for imeval first. As part
of a pipe, avoids the creating of intermediate variables.

Usage

imchange(obj, where, fo, env = parent.frame())

Arguments

obj an image or imlist

where where to modify. a pixset, or a formula (in imeval syntax) that evaluates to a
pixset.
fo a formula (in imeval syntax) used to modify the image part
env evulation environment (see imeval)

Value

a modified image

Author(s)

Simon Barthelme

See Also

imeval
imcoord 71

Examples
#Set border to 0:
imchange(boats,px.borders(boats,10),~ 0) %>% plot
#Eq. to
im <- boats
im[px.borders(im,10)] <- 0
#Using formula syntax
imchange(boats,~ px.borders(.,10),~ 0)
#Replace with grayscale ramp
imchange(boats,~ px.borders(.,10),~ xs) %>% plot
#Kill red channel in image
imchange(boats,~ c==1,~ 0) %>% plot
#Shit hue by an amount depending on eccentricity
load.example("parrots") %>%
RGBtoHSL %>%
imchange(~ c==1,~ .+80*exp(-(rho/550)^2) ) %>%
HSLtoRGB %>%
plot

imcoord Coordinates as images

Description

These functions return pixel coordinates for an image, as an image. All is made clear in the exam-
ples (hopefully)

Usage

Xc(im)

Yc(im)

Zc(im)

Cc(im)

Arguments

im an image

Value

another image of the same size, containing pixel coordinates

72 imdirac

Functions
• Xc: X coordinates
• Yc: Y coordinates
• Zc: Z coordinates
• Cc: C coordinates

See Also
as.cimg.function, pixel.grid

Examples
im <- imfill(5,5) #An image
Xc(im) #An image of the same size, containing the x coordinates of each pixel
Xc(im) %>% imrow(1)
Yc(im) %>% imrow(3) #y is constant along rows
Yc(im) %>% imcol(1)
#Mask bits of the boats image:
plot(boats*(Xc(boats) < 100))
plot(boats*(dnorm(Xc(boats),m=100,sd=30))) #Gaussian window

imdirac Generates a "dirac" image, i.e. with all values set to 0 except one.

Description
This small utility is useful to examine the impulse response of a filter

Usage
imdirac(dims, x, y, z = 1, cc = 1)

Arguments
dims a vector of image dimensions, or an image whose dimensions will be used. If
dims has length < 4 some guesswork will be used (see examples and ?as.cimg.array)
x where to put the dirac (x coordinate)
y y coordinate
z z coordinate (default 1)
cc colour coordinate (default 1)

Value
an image
imdraw 73

Author(s)
Simon Barthelme

Examples
#Explicit settings of all dimensions
imdirac(c(50,50,1,1),20,20)
imdirac(c(50,50),20,20) #Implicit
imdirac(c(50,50,3),20,20,cc=2) #RGB
imdirac(c(50,50,7),20,20,z=2) #50x50 video with 7 frames
#Impulse response of the blur filter
imdirac(c(50,50),20,20) %>% isoblur(sigma=2) %>% plot
#Impulse response of the first-order Deriche filter
imdirac(c(50,50),20,20) %>% deriche(sigma=2,order=1,axis="x") %>% plot
##NOT RUN, interactive only
##Impulse response of the blur filter in space-time
##resp <- imdirac(c(50,50,100),x=25,y=25,z=50) %>% isoblur(16)
###Normalise to 0...255 and play as video
##renorm(resp) %>% play(normalise=FALSE)

imdraw Draw image on another image

Description
Draw image on another image

Usage
imdraw(im, sprite, x = 1, y = 1, z = 1, opacity = 1)

Arguments
im background image
sprite sprite to draw on background image
x location
y location
z location
opacity transparency level (default 1)

Author(s)
Simon Barthelme

See Also
imager.combine, for different ways of combining images
74 imeval

Examples
im <- load.example("parrots")
boats.small <- imresize(boats,.5)
#I'm aware the result is somewhat ugly
imdraw(im,boats.small,x=400,y=10,opacity=.7) %>% plot

imeval Evaluation in an image context

Description
imeval does for images what "with" does for data.frames, namely contextual evaluation. It provides
various shortcuts for pixel-wise operations. imdo runs imeval, and reshapes the output as an image
of the same dimensions as the input (useful for functions that return vectors). imeval takes inspi-
ration from purrr::map in using formulas for defining anonymous functions using the "." argument.
Usage is made clear (hopefully) in the examples. The old version of imeval used CImg’s internal
math parser, but has been retired.

Usage
imeval(obj, ..., env = parent.frame())

imdo(obj, form)

Arguments
obj an image, pixset or imlist
... one or more formula objects, defining anonymous functions that will be evalu-
ated with the image as first argument (with extra contextual variables added to
the evaluation context)
env additional variables (defaults to the calling environment)
form a single formula

Functions
• imdo: run imeval and reshape

Author(s)
Simon Barthelme

See Also
imchange, which modifies specific parts of an image
imeval 75

Examples

## Computing mean absolute deviation

imeval(boats, ~ mean(abs(.-median(.))))
##Equivalent to:
mean(abs(boats-median(boats)))
##Two statistics
imeval(boats,mad= ~ mean(abs(.-median(.))),sd= ~ sd(.))
##imeval can precompute certain quantities, like the x or y coord. of each pixel
imeval(boats,~ x) %>% plot
##same as Xc(boats) %>% plot
## Other predefined quantities:
##w is width, h is height
imeval(boats,~ x/w) %>% range
##It defines certain transformed coordinate systems:
##Scaled x,y,z
## xs=x/w
## ys=y/h
##Select upper-left quadrant (returns a pixset)
imeval(boats,~ xs<.5 & ys < .5) %>% plot
##Fade effect
imeval(boats,~ xs*.) %>% plot
## xc and yc are another set of transformed coordinates
## where xc=0,yc=0 is the image center
imeval(boats,~ (abs(xc)/w)*.) %>% plot

##rho, theta: circular coordinates. rho is distance to center (in pix.), theta angle
##Gaussian mask with sd 10 pix.
blank <- imfill(30,30)
imeval(blank,~ dnorm(rho,sd=w/3)) %>% plot(int=FALSE)
imeval(blank,~ theta) %>% plot
##imeval is made for interactive use, meaning it
##accesses the environment it got called from, e.g. this works:
f <- function()
{
im1 <- imfill(3,3,val=1)
im2 <- imfill(3,3,val=3)

imeval(im1,~ .+im2)
}
f()
##imeval accepts lists as well
map_il(1:3, ~ isoblur(boats,.)) %>%
imeval(~ xs*.) %>%
plot

##imeval is useful for defining pixsets:

##here, all central pixels that have value under the median
grayscale(boats) %>%
imeval(~ (. > median(.)) & rho < 150) %>%
plot
##other abbreviations are defined:
##s for imshift, b for isoblur, rot for imrotate.
76 imfill

##e.g.
imeval(boats, ~ .*s(.,3)) %>% plot

#The rank function outputs a vector

grayscale(boats) %>% rank %>% class
#Auto-reshape into an image
grayscale(boats) %>% imdo(~ rank(.)) %>% plot
#Note that the above performs histogram normalisation

#Also works on lists

imsplit(boats,"c") %>% imdo( ~ rank(.)) %>% imappend("c") %>% plot

imfill Create an image of custom size by filling in repeated values

Description
This is a convenience function for quickly creating blank images, or images filled with a specific
colour. See examples. If val is a logical value, creates a pixset instead.

Usage
imfill(x = 1, y = 1, z = 1, val = 0, dim = NULL)

Arguments
x width (default 1)
y height (default 1)
z depth (default 1)
val fill-in values. Either a single value (for grayscale), or RGB values for colour, or
a character string for a colour (e.g. "blue")
dim dimension vector (optional, alternative to specifying x,y,z)

Value
an image object (class cimg)

Author(s)
Simon Barthelme

Examples

imfill(20,20) %>% plot #Blank image of size 20x20

imfill(20,20,val=c(1,0,0)) %>% plot #All red image
imfill(20,20,val="red") %>% plot #Same, using R colour name
imfill(3,3,val=FALSE) #Pixset
imfill(dim=dim(boats)) #Blank image of the same size as the boats image
imgradient 77

imgradient Compute image gradient

Description
Light interface for get_gradient. Refer to get_gradient for details on the computation.

Usage
imgradient(im, axes = "xy", scheme = 3)

Arguments
im an image of class cimg
axes direction along which to compute the gradient. Either a single character (e.g.
"x"), or multiple characters (e.g. "xyz"). Default: "xy"
scheme numerical scheme (default ’3’, rotation invariant)

Value
an image or a list of images, depending on the value of "axes"

Author(s)
Simon Barthelme

Examples
grayscale(boats) %>% imgradient("x") %>% plot
imgradient(boats,"xy") #Returns a list

imhessian Compute image hessian.

Description
Compute image hessian.

Usage
imhessian(im, axes = c("xx", "xy", "yy"))

Arguments
im an image
axes Axes considered for the hessian computation, as a character string (e.g "xy"
corresponds to d/(dx*dy)). Can be a list of axes. Default: xx,xy,yy
78 iminfo

Value

an image, or a list of images

Examples
imhessian(boats,"xy") %>% plot(main="Second-derivative, d/(dx*dy)")

iminfo Return information on image file

Description

This function calls ImageMagick’s "identify" utility on an image file to get some information. You
need ImageMagick on your path for this to work.

Usage

iminfo(fname)

Arguments

fname path to a file

Value

a list with fields name, format, width (pix.), height (pix.), size (bytes)

Author(s)

Simon Barthelme

Examples
## Not run:
someFiles <- dir("*.png") #Find all PNGs in directory
iminfo(someFiles[1])
#Get info on all files, as a data frame
info <- purrr::map_df(someFiles,function(v) iminfo(v) %>% as.data.frame)

## End(Not run)
imlap 79

imlap Compute image Laplacian

Description
The Laplacian is the sum of second derivatives, approximated here using finite differences.

Usage
imlap(im)

Arguments
im an image

Examples
imlap(boats) %>% plot

imlist Image list

Description
An imlist object is simply a list of images (of class cimg). For convenience, some generic functions
are defined that wouldn’t work on plain lists, like plot, display and as.data.frame DEPRECATION
NOTE: in v0.30 of imager, the original behaviour of the "imlist" function was to take a list and turn
it into an image list. This behaviour has now been changed to make "imlist" be more like "list". If
you wish to turn a list into an image list, use as.imlist.

Usage
imlist(...)

Arguments
... images to be included in the image list

See Also
plot.imlist, display.imlist, as.data.frame.imlist

Examples
imlist(a=imfill(3,3),b=imfill(10,10))
imsplit(boats,"x",6)
imsplit(boats,"x",6) %>% plot
80 imnoise

imnoise Generate (Gaussian) white-noise image

Description

A white-noise image is an image where all pixel values are drawn IID from a certain distribution.
Here they are drawn from a Gaussian.

Usage

imnoise(x = 1, y = 1, z = 1, cc = 1, mean = 0, sd = 1, dim = NULL)

Arguments

x width
y height
z depth
cc spectrum
mean mean pixel value (default 0)
sd std. deviation of pixel values (default 1)
dim dimension vector (optional, alternative to specifying x,y,z,cc)

Value

a cimg object

Author(s)

Simon Barthelme

Examples

imnoise(100,100,cc=3) %>% plot(main="White noise in RGB")

imnoise(100,100,cc=3) %>% isoblur(5) %>% plot(main="Filtered (non-white) noise")
imnoise(dim=dim(boats)) #Noise image of the same size as the boats image
implot 81

implot Plot objects on image using base graphics

Description
This function lets you use an image as a canvas for base graphics, meaning you can use R functions
like "text" and "points" to plot things on an image. The function takes as argument an image and an
expression, executes the expression with the image as canvas, and outputs the result as an image (of
the same size).

Usage
implot(im, expr, ...)

Arguments
im an image (class cimg)
expr an expression (graphics code to execute)
... passed on to plot.cimg, to control the initial rendering of the image (for example
the colorscale)

Value
an image

Author(s)
Simon Barthelme

See Also
plot, capture.plot

Examples
## Not run:
b.new <- implot(boats,text(150,50,"Boats!!!",cex=3))
plot(b.new)
#Draw a line on a white background
bg <- imfill(150,150,val=1)
implot(bg,lines(c(50,50),c(50,100),col="red",lwd=4))%>%plot
#You can change the rendering of the initial image
im <- grayscale(boats)
draw.fun <- function() text(150,50,"Boats!!!",cex=3)
out <- implot(im,draw.fun(),colorscale=function(v) rgb(0,v,v),rescale=FALSE)
plot(out)

## End(Not run)
82 imrotate

imrep Replicate images

Description
Kinda like rep, for images. Copy image n times and (optionally), append.

Usage
imrep(x, n = 1, axis = NULL)

Arguments
x an image
n number of replications
axis axis to append along (one of NULL, "x","y","z","c"). Default: NULL

Value
either an image or an image list

Author(s)
Simon Barthelme

Examples
#Result is a list
imrep(boats,3) %>% plot
#Result is an image
imrep(boats,3,"x") %>% plot
#Make an animation by repeating each frame 10x
#map_il(1:5,~ isoblur(boats,.) %>% imrep(10,"z")) %>%
# imappend("z") %>% play

imrotate Rotate an image along the XY plane.

Description
If cx and cy aren’t given, the default is to centre the rotation in the middle of the image. When cx
and cy are given, the algorithm used is different, and does not change the size of the image.

Usage
imrotate(im, angle, cx, cy, interpolation = 1L, boundary = 0L)
imsharpen 83

Arguments
im an image
angle Rotation angle, in degrees.
cx Center of rotation along x (default, image centre)
cy Center of rotation along y (default, image centre)
interpolation Type of interpolation. One of 0=nearest,1=linear,2=cubic.
boundary Boundary conditions. One of 0=dirichlet, 1=neumann, 2=periodic

See Also
imwarp, for flexible image warping, which includes rotations as a special case

Examples
imrotate(boats,30) %>% plot
#Shift centre to (20,20)
imrotate(boats,30,cx=20,cy=20) %>% plot

imsharpen Sharpen image.

Description
The default sharpening filter is inverse diffusion. The "shock filter" is a non-linear diffusion that
has better edge-preserving properties.

Usage
imsharpen(im, amplitude, type = "diffusion", edge = 1, alpha = 0, sigma = 0)

Arguments
im an image
amplitude Sharpening amplitude (positive scalar, 0: no filtering).
type Filtering type. "diffusion" (default) or "shock"
edge Edge threshold (shock filters only, positive scalar, default 1).
alpha Window size for initial blur (shock filters only, positive scalar, default 0).
sigma Window size for diffusion tensor blur (shock filters only, positive scalar, default
0).

Examples
layout(t(1:2))
plot(boats,main="Original")
imsharpen(boats,150) %>% plot(main="Sharpened")
84 imsplit

imshift Shift image content.

Description
Shift image content.

Usage
imshift(
im,
delta_x = 0L,
delta_y = 0L,
delta_z = 0L,
delta_c = 0L,
boundary_conditions = 0L
)

Arguments
im an image
delta_x Amount of displacement along the X-axis.
delta_y Amount of displacement along the Y-axis.
delta_z Amount of displacement along the Z-axis.
delta_c Amount of displacement along the C-axis.
boundary_conditions
can be: - 0: Zero border condition (Dirichlet). - 1: Nearest neighbors (Neu-
mann). - 2: Repeat Pattern (Fourier style).

Examples
imshift(boats,10,50) %>% plot

imsplit Split an image along a certain axis (producing a list)

Description
Use this if you need to process colour channels separately, or frames separately, or rows separately,
etc. You can also use it to chop up an image into blocks. Returns an "imlist" object, which is
essentially a souped-up list.

Usage
imsplit(im, axis, nb = -1)
imsub 85

Arguments
im an image
axis the axis along which to split (for example ’c’)
nb number of objects to split into. if nb=-1 (the default) the maximum number of
splits is used, i.e. split(im,"c") produces a list containing all individual colour
channels.

See Also
imappend (the reverse operation)

Examples
im <- as.cimg(function(x,y,z) x+y+z,10,10,5)
imsplit(im,"z") #Split along the z axis into a list with 5 elements
imsplit(im,"z",2) #Split along the z axis into two groups
imsplit(boats,"x",-200) %>% plot #Blocks of 200 pix. along x
imsplit(im,"z",2) %>% imappend("z") #Split and reshape into a single image
#You can also split pixsets
imsplit(boats > .5,"c") %>% plot

imsub Select part of an image

Description
imsub selects an image part based on coordinates: it allows you to select a subset of rows, columns,
frames etc. Refer to the examples to see how it works

Usage
imsub(im, ...)

subim(im, ...)

Arguments
im an image
... various conditions defining a rectangular image region

Details
subim is an alias defined for backward-compatibility.

Value
an image with some parts cut out
86 imwarp

Functions
• subim: alias for imsub

Author(s)
Simon Barthelme

Examples
parrots <- load.example("parrots")
imsub(parrots,x < 30) #Only the first 30 columns
imsub(parrots,y < 30) #Only the first 30 rows
imsub(parrots,x < 30,y < 30) #First 30 columns and rows
imsub(parrots, sqrt(x) > 8) #Can use arbitrary expressions
imsub(parrots,x > height/2,y > width/2) #height and width are defined based on the image
#Using the %inr% operator, which is like %in% but for a numerical range
all.equal(imsub(parrots,x %inr% c(1,10)),
imsub(parrots,x >= 1,x <= 10))
imsub(parrots,cc==1) #Colour axis is "cc" not "c" here because "c" is an important R function
##Not run
##imsub(parrots,x+y==1)
##can't have expressions involving interactions between variables (domain might not be square)

imwarp Image warping

Description
Image warping consists in remapping pixels, ie. you define a function M(x,y,z) -> (x’,y’,z’) that
displaces pixel content from (x,y,z) to (x’,y’,z’). Actual implementations rely on either the forward
transformation M, or the backward (inverse) transformation M^-1. In CImg the forward implemen-
tation will go through all source (x,y,z) pixels and "paint" the corresponding pixel at (x’,y’,z’). This
will result in unpainted pixels in the output if M is expansive (for example in the case of a scaling
M(x,y,z) = 5*(x,y,z)). The backward implementation will go through every pixel in the destination
image and look for ancestors in the source, meaning that every pixel will be painted. There are two
ways of specifying the map: absolute or relative coordinates. In absolute coordinates you specify M
or M^-1 directly. In relative coordinates you specify an offset function D: M(x,y) = (x,y) + D(x,y)
(forward) M^-1(x,y) = (x,y) - D(x,y) (backward)

Usage
imwarp(
im,
map,
direction = "forward",
coordinates = "absolute",
boundary = "dirichlet",
interpolation = "linear"
)
imwarp 87

Arguments
im an image
map a function that takes (x,y) or (x,y,z) as arguments and returns a named list with
members (x,y) or (x,y,z)
direction "forward" or "backward" (default "forward")
coordinates "absolute" or "relative" (default "relative")
boundary boundary conditions: "dirichlet", "neumann", "periodic". Default "dirichlet"
interpolation "nearest", "linear", "cubic" (default "linear")

Details
Note that 3D warps are possible as well. The mapping should be specified via the "map" argument,
see examples.

Value
a warped image

Author(s)
Simon Barthelme

See Also
warp for direct access to the CImg function

Examples
im <- load.example("parrots")
#Shift image
map.shift <- function(x,y) list(x=x+10,y=y+30)
imwarp(im,map=map.shift) %>% plot
#Shift image (backward transform)
imwarp(im,map=map.shift,dir="backward") %>% plot

#Shift using relative coordinates

map.rel <- function(x,y) list(x=10+0*x,y=30+0*y)
imwarp(im,map=map.rel,coordinates="relative") %>% plot

#Scaling
map.scaling <- function(x,y) list(x=1.5*x,y=1.5*y)
imwarp(im,map=map.scaling) %>% plot #Note the holes
map.scaling.inv <- function(x,y) list(x=x/1.5,y=y/1.5)
imwarp(im,map=map.scaling.inv,dir="backward") %>% plot #No holes

#Bending
map.bend.rel <- function(x,y) list(x=50*sin(y/10),y=0*y)
imwarp(im,map=map.bend.rel,coord="relative",dir="backward") %>% plot #No holes
88 index.coord

im_split Split an image along a certain axis (producing a list)

Description
Split an image along a certain axis (producing a list)

Usage
im_split(im, axis, nb = -1L)

Arguments
im an image
axis the axis along which to split (for example ’c’)
nb number of objects to split into. if nb=-1 (the default) the maximum number of
splits is used ie. split(im,"c") produces a list containing all individual colour
channels

See Also
imappend (the reverse operation)

index.coord Linear index in internal vector from pixel coordinates

Description
Pixels are stored linearly in (x,y,z,c) order. This function computes the vector index of a pixel given
its coordinates

Usage
index.coord(im, coords, outside = "stop")

Arguments
im an image
coords a data.frame with values x,y,z (optional), c (optional)
outside what to do if some coordinates are outside the image: "stop" issues error, "NA"
replaces invalid coordinates with NAs. Default: "stop".

Value
a vector of indices (NA if the indices are invalid)
inpaint 89

Author(s)
Simon Barthelme

See Also
coord.index, the reverse operation

Examples
im <- as.cimg(function(x,y) x+y,100,100)
px <- index.coord(im,data.frame(x=c(3,3),y=c(1,2)))
im[px] #Values should be 3+1=4, 3+2=5

inpaint Fill-in NA values in an image

Description
Fill in NA values (inpainting) using a Gaussian filter, i.e. replace missing pixel values with a
weighted average of the neighbours.

Usage
inpaint(im, sigma)

Arguments
im input image
sigma std. deviation of the Gaussian (size of neighbourhood)

Value
an image with missing values filled-in.

Author(s)
Simon Barthelme

Examples
im <- boats
im[sample(nPix(im),1e4)] <- NA
inpaint(im,1) %>% imlist(im,.) %>%
setNames(c("before","after")) %>% plot(layout="row")
90 interact

interact Build simple interactive interfaces using imager

Description
To explore the effect of certain image manipulations, filter settings, etc., it’s useful to have a basic
interaction mechanism. You can use shiny for that, but imager provides a lightweight alternative.
The user writes a function that gets called every time a user event happens (a click, a keypress, etc.).
The role of the function is to process the event and output an image, which will then be displayed.
You can exit the interface at any time by pressing Esc. See examples for more. This feature is
experimental!!!

Usage
interact(fun, title = "", init)

Arguments
fun a function that takes a single argument (a list of user events) and returns an
image to be plotted. The image won’t be rescaled before plotting, so make sure
RGB values are in [0,1].
title a title for the window (default "", none)
init initial image to display (optional)

Value
an image, specifically the last image displayed

Author(s)
Simon Barthelme

Examples
#Implement a basic image gallery:
#press "right" and "left" to view each image in a list
gallery <- function(iml)
{
ind <- 1
f <- function(state)
{
if (state$key=="arrowleft")
{
ind <<- max(ind-1,1)
}
if (state$key=="arrowright")
{
ind <<- min(ind+1,length(iml))
interp 91

}
iml[[ind]]
}
interact(f)
}
##Not run (interactive only)
##map_il(1:10,~ isoblur(boats,.)) %>% gallery

interp Interpolate image values

Description
This function provides 2D and 3D (linear or cubic) interpolation for pixel values. Locations need
to be provided as a data.frame with variables x,y,z, and c (the last two are optional).

Usage
interp(im, locations, cubic = FALSE, extrapolate = TRUE)

Arguments
im the image (class cimg)
locations a data.frame
cubic if TRUE, use cubic interpolation. If FALSE, use linear (default FALSE)
extrapolate allow extrapolation (to values outside the image)

Examples

loc <- data.frame(x=runif(10,1,width(boats)),y=runif(10,1,height(boats))) #Ten random locations

interp(boats,loc)

is.cimg Checks that an object is a cimg object

Description
Checks that an object is a cimg object

Usage
is.cimg(x)

Arguments
x an object
92 is.pixset

Value
logical

is.imlist Check that an object is an imlist object

Description
Check that an object is an imlist object

Usage
is.imlist(x)

Arguments
x an object

Value
logical

is.pixset Check that an object is a pixset object

Description
Check that an object is a pixset object

Usage
is.pixset(x)

Arguments
x an object

Value
logical
isoblur 93

isoblur Blur image isotropically.

Description
Blur image isotropically.

Usage
isoblur(im, sigma, neumann = TRUE, gaussian = TRUE, na.rm = FALSE)

Arguments
im an image
sigma Standard deviation of the blur (positive)
neumann If true, use Neumann boundary conditions, Dirichlet otherwise (default true,
Neumann)
gaussian Use a Gaussian filter (actually van Vliet-Young). Default: 0th-order Deriche
filter.
na.rm if TRUE, ignore NA values. Default FALSE, in which case the whole image is
NA if one of the values is NA (following the definition of the Gaussian filter)

See Also
deriche,vanvliet,inpaint,medianblur

Examples
isoblur(boats,3) %>% plot(main="Isotropic blur, sigma=3")
isoblur(boats,10) %>% plot(main="Isotropic blur, sigma=10")

label Label connected components.

Description
The algorithm of connected components computation has been primarily done by A. Meijster, ac-
cording to the publication: ’W.H. Hesselink, A. Meijster, C. Bron, "Concurrent Determination of
Connected Components.", In: Science of Computer Programming 41 (2001), pp. 173–194’.

Usage
label(im, high_connectivity = FALSE, tolerance = 0)
94 liply

Arguments
im an image
high_connectivity
4(false)- or 8(true)-connectivity in 2d case, and between 6(false)- or 26(true)-
connectivity in 3d case. Default FALSE
tolerance Tolerance used to determine if two neighboring pixels belong to the same region.

Examples
imname <- system.file('extdata/parrots.png',package='imager')
im <- load.image(imname) %>% grayscale
#Thresholding yields different discrete regions of high intensity
regions <- isoblur(im,10) %>% threshold("97%")
labels <- label(regions)
layout(t(1:2))
plot(regions,"Regions")
plot(labels,"Labels")

liply Apply function to each element of a list, then combine the result as an
image by appending along specified axis

Description
This is just a shortcut for purrr::map followed by imappend

Usage
liply(lst, fun, axis, ...)

Arguments
lst a list
fun function to apply
axis which axis to append along (e.g. "c" for colour)
... further arguments to be passed to fun

Examples
build.im <- function(size) as.cimg(function(x,y) (x+y)/size,size,size)
liply(c(10,50,100),build.im,"y") %>% plot
load.dir 95

load.dir Load all images in a directory

Description
Load all images in a directory and return them as an image list.

Usage
load.dir(path, pattern = NULL, quiet = FALSE)

Arguments
path directory to load from
pattern optional: file pattern (ex. *jpg). Default NULL, in which case we look for file
extensions png,jpeg,jpg,tif,bmp.
quiet if TRUE, loading errors are quiet. If FALSE, they are displayed. Default FALSE

Value
an image list

Author(s)
Simon Barthelme

Examples
path <- system.file(package="imager") %>% paste0("/extdata")
load.dir(path)

load.example Load example image

Description
Imager ships with five test pictures and a video. Two (parrots and boats) come from the [Kodak
set](http://r0k.us/graphics/kodak/). Another (birds) is a sketch of birds by Leonardo, from Wiki-
media. The "coins" image comes from scikit-image. The Hubble Deep field (hubble) is from
Wikimedia. The test video ("tennis") comes from [xiph.org](https://media.xiph.org/video/derf/)’s
collection.

Usage
load.example(name)
96 load.image

Arguments
name name of the example

Value
an image

Author(s)
Simon Barthelme

Examples
load.example("hubble") %>% plot
load.example("birds") %>% plot
load.example("parrots") %>% plot

load.image Load image from file or URL

Description
PNG, JPEG and BMP are supported via the readbitmap package. You’ll need to install ImageMag-
ick for other formats. If the path is actually a URL, it should start with http(s) or ftp(s).

Usage
load.image(file)

Arguments
file path to file or URL

Value
an object of class ’cimg’

Examples
#Find path to example file from package
fpath <- system.file('extdata/Leonardo_Birds.jpg',package='imager')
im <- load.image(fpath)
plot(im)
#Load the R logo directly from the CRAN webpage
#load.image("https://cran.r-project.org/Rlogo.jpg") %>% plot
load.video 97

load.video Load a video using ffmpeg

Description
You need to have ffmpeg on your path for this to work. This function uses ffmpeg to split the video
into individual frames, which are then loaded as images and recombined. Videos are memory-
intensive, and load.video performs a safety check before loading a video that would be larger than
maxSize in memory (default 1GB)

Usage
load.video(
fname,
maxSize = 1,
skip.to = 0,
frames = NULL,
fps = NULL,
extra.args = "",
verbose = FALSE
)

Arguments
fname file to load
maxSize max. allowed size in memory, in GB (default max 1GB).
skip.to skip to a certain point in time (in sec., or "hh:mm::ss" format)
frames number of frames to load (default NULL, all)
fps frames per second (default NULL, determined automatically)
extra.args extra arguments to be passed to ffmpeg (default "", none)
verbose if TRUE, show ffmpeg output (default FALSE)

Value
an image with the extracted frames along the "z" coordinates

Author(s)
Simon Barthelme

See Also
save.video, make.video
98 magick

Examples

fname <- system.file('extdata/tennis_sif.mpeg',package='imager')

##Not run
## load.video(fname) %>% play
## load.video(fname,fps=10) %>% play
## load.video(fname,skip=2) %>% play

magick Convert a magick image to a cimg image or image list and vice versa

Description
The magick library package stores its data as "magick-image" object, which may in fact contain
several images or an animation. These functions convert magick objects into imager objects or
imager objects into magick objects. Note that cimg2magick function requires magick package.

Usage
magick2imlist(obj, alpha = "rm", ...)

magick2cimg(obj, alpha = "rm", ...)

cimg2magick(im, rotate = TRUE)

Arguments
obj an object of class "magick-image"
alpha what do to with the alpha channel ("rm": remove and store as attribute, "flatten":
flatten, "keep": keep). Default: "rm"
... ignored
im an image of class cimg
rotate determine if rotate image to adjust orientation of image

Value
an object of class cimg or imlist
an object of class "magick-image"

Author(s)
Jan Wijffels, Simon Barthelme
Shota Ochi

See Also
flatten.alpha, rm.alpha
make.video 99

make.video Make/save a video using ffmpeg

Description
You need to have ffmpeg on your path for this to work. This function uses ffmpeg to combine
individual frames into a video. save.video can be called directly with an image or image list as
input. make.video takes as argument a directory that contains a sequence of images representing
individual frames to be combined into a video.

Usage
make.video(
dname,
fname,
pattern = "image-%d.png",
fps = 25,
extra.args = "",
verbose = FALSE
)

save.video(im, fname, ...)

Arguments
dname name of a directory containing individual files
fname name of the output file. The format is determined automatically from the name
(example "a.mpeg" will have MPEG format)
pattern pattern of filename for frames (the default matches "image-1.png", "image-
2.png", etc.. See ffmpeg documentation for more).
fps frames per second (default 25)
extra.args extra arguments to be passed to ffmpeg (default "", none)
verbose if TRUE, show ffmpeg output (default FALSE)
im an image or image list
... extra arguments to save.video, passed on to make.video

Functions
• save.video: Save a video using ffmpeg

Author(s)
Simon Barthelme
100 map_il

See Also
load.video

Examples
## Not run
## iml <- map_il(seq(0,20,l=60),~ isoblur(boats,.))
## f <- tempfile(fileext=".avi")
## save.video(iml,f)
## load.video(f) %>% play
## #Making a video from a directory
## dd <- tempdir()
## for (i in 1:length(iml)) {
## png(sprintf("%s/image-%i.png",dd,i));
## plot(iml[[i]]); dev.off() }
## make.video(dd,f)
## load.video(f) %>% play

map_il Type-stable map for use with the purrr package

Description
Works like purrr::map, purrr::map_dbl and the like but ensures that the output is an image list.

Usage
map_il(...)

map2_il(...)

pmap_il(...)

Arguments
... passed to map

Value
an image list

Functions
• map2_il: Parallel map (two values)
• pmap_il: Parallel map (multiple values)

Author(s)
Simon Barthelme
medianblur 101

Examples
#Returns a list
imsplit(boats,"x",2) %>% purrr::map(~ isoblur(.,3))
#Returns an "imlist" object
imsplit(boats,"x",2) %>% map_il(~ isoblur(.,3))
#Fails if function returns an object that's not an image
try(imsplit(boats,"x",2) %>% map_il(~ . > 2))
#Parallel maps
map2_il(1:3,101:103,~ imshift(boats,.x,.y))
pmap_il(list(x=1:3,y=4:6,z=7:9),function(x,y,z) imfill(x,y,z))

medianblur Blur image with the median filter. In a window of size n x n centered at
pixel (x,y), compute median pixel value over the window. Optionally,
ignore values that are too far from the value at current pixel.

Description
Blur image with the median filter.
In a window of size n x n centered at pixel (x,y), compute median pixel value over the window.
Optionally, ignore values that are too far from the value at current pixel.

Usage
medianblur(im, n, threshold = 0)

Arguments
im an image
n Size of the median filter.
threshold Threshold used to discard pixels too far from the current pixel value in the me-
dian computation. Can be used for edge-preserving smoothing. Default 0 (in-
clude all pixels in window).

See Also
isoblur, boxblur

Examples
medianblur(boats,5) %>% plot(main="Median blur, 5 pixels")
medianblur(boats,10) %>% plot(main="Median blur, 10 pixels")
medianblur(boats,10,8) %>% plot(main="Median blur, 10 pixels, threshold = 8")
102 mutate_plyr

mirror Mirror image content along specified axis

Description
Mirror image content along specified axis

Usage
mirror(im, axis)

Arguments
im an image
axis Mirror axis ("x","y","z","c")

Examples
mirror(boats,"x") %>% plot
mirror(boats,"y") %>% plot

mutate_plyr Mutate a data frame by adding new or replacing existing columns.

Description
This function copied directly from plyr, and modified to use a different name to avoid namespace
collisions with dplyr/tidyverse functions.

Usage
mutate_plyr(.data, ...)

Arguments
.data the data frame to transform
... named parameters giving definitions of new columns.

Details
This function is very similar to transform but it executes the transformations iteratively so that later
transformations can use the columns created by earlier transformations. Like transform, unnamed
components are silently dropped.
Mutate seems to be considerably faster than transform for large data frames.
nfline 103

nfline Plot a line, Hesse normal form parameterisation

Description
This is a simple interface over abline meant to be used along with the Hough transform. In the
Hesse normal form (theta,rho), a line is represented as the set of values (x,y) such that cos(theta)*x
+ sin(theta)*y = rho. Here theta is an angle and rho is a distance. See the documentation for
hough_lines.

Usage
nfline(theta, rho, col, ...)

Arguments
theta angle (radians)
rho distance
col colour
... other graphical parameters, passed along to abline

Value
nothing

Author(s)
Simon Barthelme

Examples
#Boring example, see ?hough_lines
plot(boats)
nfline(theta=0,rho=10,col="red")

pad Pad image with n pixels along specified axis

Description
Pad image with n pixels along specified axis

Usage
pad(im, nPix, axes, pos = 0, val)
104 patchstat

Arguments
im the input image
nPix how many pixels to pad with
axes which axes to pad along
pos -1: prepend 0: center 1: append
val colour of the padded pixels (default 0 in all channels). Can be a string for colour
images, e.g. "red", or "black".

Value
a padded image

Author(s)
Simon Barthelme

Examples
pad(boats,20,"xy") %>% plot
pad(boats,20,pos=-1,"xy") %>% plot
pad(boats,20,pos=1,"xy") %>% plot
pad(boats,20,pos=1,"xy",val="red") %>% plot

patchstat Return image patch summary

Description
Patches are rectangular image regions centered at cx,cy with width wx and height wy. This function
provides a fast way of extracting a statistic over image patches (for example, their mean). Supported
functions: sum,mean,min,max,median,var,sd, or any valid CImg expression. WARNINGS: - values
outside of the image region are considered to be 0. - widths and heights should be odd integers
(they’re rounded up otherwise).

Usage
patchstat(im, expr, cx, cy, wx, wy)

Arguments
im an image
expr statistic to extract. a string, either one of the usual statistics like "mean","median",
or a CImg expression.
cx vector of x coordinates for patch centers
cy vector of y coordinates for patch centers
wx vector of patch widths (or single value)
wy vector of patch heights (or single value)
patch_summary_cimg 105

Value

a numeric vector

See Also

extract_patches

Examples
im <- grayscale(boats)
#Mean of an image patch centered at (10,10) of size 3x3
patchstat(im,'mean',10,10,3,3)
#Mean of image patches centered at (10,10) and (20,4) of size 2x2
patchstat(im,'mean',c(10,20),c(10,4),5,5)
#Sample 10 random positions
ptch <- pixel.grid(im) %>% dplyr::sample_n(10)
#Compute median patch value
with(ptch,patchstat(im,'median',x,y,3,3))

patch_summary_cimg Extract a numerical summary from image patches, using CImg’s mini-
language Experimental feature.

Description

Extract a numerical summary from image patches, using CImg’s mini-language Experimental fea-
ture.

Usage

patch_summary_cimg(im, expr, cx, cy, wx, wy)

Arguments

im an image
expr a CImg expression (as a string)
cx vector of x coordinates for patch centers
cy vector of y coordinates for patch centers
wx vector of coordinates for patch width
wy vector of coordinates for patch height
106 periodic.part

Examples
#Example: median filtering using patch_summary_cimg
#Center a patch at each pixel
im <- grayscale(boats)
patches <- pixel.grid(im) %>% dplyr::mutate(w=3,h=3)
#Extract patch summary
out <- dplyr::mutate(patches,med=patch_summary_cimg(im,"ic",x,y,w,h))
as.cimg(out,v.name="med") %>% plot

periodic.part Compute the periodic part of an image, using the periodic/smooth de-
composition of Moisan (2011)

Description
Moisan (2011) defines an additive image decomposition im = periodic + smooth where the periodic
part shouldn’t be too far from the original image. The periodic part can be used in frequency-domain
analyses, to reduce the artifacts induced by non-periodicity.

Usage
periodic.part(im)

Arguments
im an image

Value
an image

Author(s)
Simon Barthelme

References
L. Moisan, Periodic plus Smooth Image Decomposition,J. Math. Imaging Vision, vol. 39:2, pp.
161-179, 2011

Examples
im <- load.example("parrots") %>% subim(x <= 512)
layout(t(1:3))
plot(im,main="Original image")
periodic.part(im) %>% plot(main="Periodic part")
#The smooth error is the difference between
#the original image and its periodic part
(im-periodic.part(im)) %>% plot(main="Smooth part")
permute_axes 107

permute_axes Permute image axes

Description
By default images are stored in xyzc order. Use permute_axes to change that order.

Usage
permute_axes(im, perm)

Arguments
im an image
perm a character string, e.g., "zxyc" to have the z-axis come first

Examples
im <- array(0,c(10,30,40,3)) %>% as.cimg
permute_axes(im,"zxyc")

pixel.grid Return the pixel grid for an image

Description
The pixel grid for image im gives the (x,y,z,c) coordinates of each successive pixel as a data.frame.
The c coordinate has been renamed ’cc’ to avoid conflicts with R’s c function. NB: coordinates
start at (x=1,y=1), corresponding to the top left corner of the image, unless standardise == TRUE,
in which case we use the usual Cartesian coordinates with origin at the center of the image and
scaled such that x varies between -.5 and .5, and a y arrow pointing up

Usage
pixel.grid(im, standardise = FALSE, drop.unused = TRUE, dim = NULL)

Arguments
im an image
standardise If TRUE use a centered, scaled coordinate system. If FALSE use standard image
coordinates (default FALSE)
drop.unused if TRUE ignore empty dimensions, if FALSE include them anyway (default
TRUE)
dim a vector of image dimensions (optional, may be used instead of "im")
108 pixset

Value

a data.frame

Examples
im <- as.cimg(array(0,c(10,10))) #A 10x10 image
pixel.grid(im) %>% head
pixel.grid(dim=dim(im)) %>% head #Same as above
pixel.grid(dim=c(10,10,3,2)) %>% head
pixel.grid(im,standardise=TRUE) %>% head
pixel.grid(im,drop.unused=FALSE) %>% head

pixset Pixel sets (pixsets)

Description

Pixel sets represent sets of pixels in images (ROIs, foreground, etc.). From an implementation point
of view, they’re just a thin layer over arrays of logical values, just like the cimg class is a layer
over arrays of numeric values. Pixsets can be turned back into logical arrays, but they come with
a number of generic functions that should make your life easier. They are created automatically
whenever you run a test on an image (for example im > 0 returns a pixset).

Usage

pixset(x)

Arguments

x an array of logical values

Examples
#A test on an image returns a pixset
boats > 250
#Pixsets can be combined using the usual Boolean operators
(boats > 230) & (Xc(boats) < width(boats)/2)
#Subset an image using a pixset
boats[boats > 250]
#Turn a pixset into an image
as.cimg(boats > 250)
#Equivalently:
(boats > 250) + 0
play 109

play Play a video

Description
A very basic video player. Press the space bar to pause and ESC to close.

Usage
play(vid, loop = FALSE, delay = 30L, normalise = TRUE)

Arguments
vid A cimg object, to be played as video
loop loop the video (default false)
delay delay between frames, in ms. Default 30.
normalise if true pixel values are rescaled to 0...255 (default TRUE). The normalisation
is based on the *first frame*. If you don’t want the default behaviour you can
normalise by hand. Default TRUE.

plot.cimg Display an image using base graphics

Description
If you want to control precisely how numerical values are turned into colours for plotting, you need
to specify a colour scale using the colourscale argument (see examples). Otherwise the default is
"gray" for grayscale images, "rgb" for colour. These expect values in [0..1], so the default is to
rescale the data to [0..1]. If you wish to over-ride that behaviour, set rescale=FALSE. See examples
for an explanation. If the image is one dimensional (i.e., a simple row or column image), then pixel
values will be plotted as a line.

Usage
## S3 method for class 'cimg'
plot(
x,
frame,
xlim = c(1, width(x)),
ylim = c(height(x), 1),
xlab = "x",
ylab = "y",
rescale = TRUE,
colourscale = NULL,
110 plot.cimg

colorscale = NULL,
interpolate = TRUE,
axes = TRUE,
main = "",
xaxs = "i",
yaxs = "i",
asp = 1,
col.na = rgb(0, 0, 0, 0),
...
)

Arguments

x the image
frame which frame to display, if the image has depth > 1
xlim x plot limits (default: 1 to width)
ylim y plot limits (default: 1 to height)
xlab x axis label
ylab y axis label
rescale rescale pixel values so that their range is [0,1]
colourscale, colorscale
an optional colour scale (default is gray or rgb)
interpolate should the image be plotted with antialiasing (default TRUE)
axes Whether to draw axes (default TRUE)
main Main title
xaxs The style of axis interval calculation to be used for the x-axis. See ?par
yaxs The style of axis interval calculation to be used for the y-axis. See ?par
asp aspect ratio. The default value (1) means that the aspect ratio of the image will
be kept regardless of the dimensions of the plot. A numeric value other than one
changes the aspect ratio, but it will be kept the same regardless of dimensions.
Setting asp="varying" means the aspect ratio will depend on plot dimensions
(this used to be the default in versions of imager < 0.40)
col.na which colour to use for NA values, as R rgb code. The default is "rgb(0,0,0,0)",
which corresponds to a fully transparent colour.
... other parameters to be passed to plot.default (eg "main")

See Also

display, which is much faster, as.raster, which converts images to R raster objects
plot.imlist 111

Examples
plot(boats,main="Boats")
plot(boats,axes=FALSE,xlab="",ylab="")

#Pixel values are rescaled to 0-1 by default, so that the following two plots are identical
plot(boats)
plot(boats/2,main="Rescaled")
#If you don't want that behaviour, you can set rescale to FALSE, but
#then you need to make sure values are in [0,1]
try(plot(boats,rescale=FALSE)) #Error!
try(plot(boats/255,rescale=FALSE)) #Works
#You can specify a colour scale if you don't want the default one.
#A colour scale is a function that takes pixels values and return an RGB code,
#like R's rgb function,e.g.
rgb(0,1,0)
#Let's switch colour channels
cscale <- function(r,g,b) rgb(b,g,r)
plot(boats/255,rescale=FALSE,colourscale=cscale)
#Display slice of HSV colour space
im <- imfill(255,255,val=1)
im <- list(Xc(im)/255,Yc(im)/255,im) %>% imappend("c")
plot(im,colourscale=hsv,rescale=FALSE,
xlab="Hue",ylab="Saturation")
#In grayscale images, the colourscale function should take in a single value
#and return an RGB code
boats.gs <- grayscale(boats)
#We use an interpolation function from package scales
cscale <- scales::gradient_n_pal(c("red","purple","lightblue"),c(0,.5,1))
plot(boats.gs,rescale=FALSE,colourscale=cscale)
#Plot a one-dimensional image
imsub(boats,x==1) %>% plot(main="Image values along first column")
#Plotting with and without anti-aliasing:
boats.small <- imresize(boats,.3)
plot(boats.small,interp=TRUE)
plot(boats.small,interp=FALSE)

plot.imlist Plot an image list

Description
Each image in the list will be plotted separately. The layout argument controls the overall layout of
the plot window. The default layout is "rect", which will fit all of your images into a rectangle that’s
as close to a square as possible.

Usage
## S3 method for class 'imlist'
plot(x, layout = "rect", ...)
112 px.flood

Arguments
x an image list (of type imlist)
layout either a matrix (in the format defined by the layout command) or one of "row","col"
or "rect". Default: "rect"
... other parameters, to be passed to the plot command

Author(s)
Simon Barthelme

Examples
imsplit(boats,"c") #Returns an image list
imsplit(boats,"c") %>% plot
imsplit(boats,"c") %>% plot(layout="row")
imsplit(boats,"c") %>% plot(layout="col")
imsplit(boats,"x",5) %>% plot(layout="rect")

px.flood Select a region of homogeneous colour

Description
Select pixels that are similar to a seed pixel. The underlying algorithm is the same as the bucket fill
(AKA flood fill). Unlike with the bucket fill, the image isn’t changed, the function simply returns a
pixel set containing the selected pixels.

Usage
px.flood(im, x, y, z = 1, sigma = 0, high_connexity = FALSE)

Arguments
im an image
x X-coordinate of the starting point of the region to flood
y Y-coordinate of the starting point of the region to flood
z Z-coordinate of the starting point of the region to flood
sigma Tolerance concerning neighborhood values.
high_connexity Use 8-connexity (only for 2d images, default FALSE).

Details
Old name: selectSimilar (deprecated)
px.na 113

See Also

bucketfill

Examples

#Select part of a sail

px <- px.flood(boats,x=169,y=179,sigma=.2)
plot(boats)
highlight(px)

px.na A pixset for NA values

Description

A pixset containing all NA pixels

Usage

px.na(im)

Arguments

im an image

Value

a pixset

Examples

im <- boats
im[1] <- NA
px.na(im)
114 RasterPackage

px.remove_outer Remove all connected regions that touch image boundaries

Description
All pixels that belong to a connected region in contact with image boundaries are set to FALSE.

Usage
px.remove_outer(px)

Arguments
px a pixset

Value
a pixset

Author(s)
Simon Barthelme

Examples
im <- draw_circle(imfill(100,100),c(0,50,100),c(50,50,50),radius=10,color=1)
plot(im)
as.pixset(im) %>% px.remove_outer %>% plot

RasterPackage Convert a RasterLayer/RasterBrick to a cimg image/image list

Description
The raster library stores its data as "RasterLayer" and "RasterBrick" objects. The raster package
can store its data out-of-RAM, so in order not to load too much data the "maxpixels" argument sets
a limit on how many pixels are loaded.

Usage
## S3 method for class 'RasterLayer'
as.cimg(obj, maxpixels = 1e+07, ...)

## S3 method for class 'RasterStackBrick'

as.imlist(obj, maxpixels = 1e+07, ...)
renorm 115

Arguments

obj an object of class "RasterLayer"

maxpixels max. number of pixels to load (default 1e7)
... ignored

Author(s)

Simon Barthelme, adapted from the image method for RasterLayer by Robert J Hijmans

renorm Renormalise image

Description

Pixel data is usually expressed on a 0...255 scale for displaying. This function performs a linear
renormalisation to range min...max

Usage

renorm(x, min = 0, max = 255)

Arguments

x numeric data
min min of the range
max max of the range

Author(s)

Simon Barthelme

Examples

renorm(0:10)
renorm(-5:5) #Same as above
116 resize

resize Resize image

Description
If the dimension arguments are negative, they are interpreted as a proportion of the original image.

Usage
resize(
im,
size_x = -100L,
size_y = -100L,
size_z = -100L,
size_c = -100L,
interpolation_type = 1L,
boundary_conditions = 0L,
centering_x = 0,
centering_y = 0,
centering_z = 0,
centering_c = 0
)

Arguments
im an image
size_x Number of columns (new size along the X-axis).
size_y Number of rows (new size along the Y-axis).
size_z Number of slices (new size along the Z-axis).
size_c Number of vector-channels (new size along the C-axis).
interpolation_type
Method of interpolation: -1 = no interpolation: raw memory resizing. 0 = no
interpolation: additional space is filled according to boundary_conditions. 1 =
nearest-neighbor interpolation. 2 = moving average interpolation. 3 = linear
interpolation. 4 = grid interpolation. 5 = cubic interpolation. 6 = lanczos inter-
polation.
boundary_conditions
Border condition type.
centering_x Set centering type (only if interpolation_type=0).
centering_y Set centering type (only if interpolation_type=0).
centering_z Set centering type (only if interpolation_type=0).
centering_c Set centering type (only if interpolation_type=0).

See Also
See imresize for an easier interface.
resize_doubleXY 117

resize_doubleXY Resize image uniformly

Description
Resize image by a single scale factor. For non-uniform scaling and a wider range of options, see
resize.

Usage
resize_doubleXY(im)

resize_halfXY(im)

resize_tripleXY(im)

imresize(im, scale = 1, interpolation = 3)

Arguments
im an image
scale a scale factor
interpolation interpolation method to use (see doc for resize). Default 3, linear. Set to 5 for
cubic, 6 for Lanczos (higher quality).

Value
an image

Functions
• resize_doubleXY: Double size
• resize_halfXY: Half size
• resize_tripleXY: Triple size
• imresize: resize by scale factor

Author(s)
Simon Barthelme

References
For double-scale, triple-scale, etc. uses an anisotropic scaling algorithm described in: http://
scale2x.sourceforge.net/algorithm.html. For half-scaling uses what the CImg doc describes
as an "optimised filter", see resize_halfXY in CImg.h.
118 RGBtoHSL

See Also
resize

Examples
im <- load.example("parrots")
imresize(im,1/4) #Quarter size
map_il(2:4,~ imresize(im,1/.)) %>% imappend("x") %>% plot

RGBtoHSL Colour space conversions in imager

Description
All functions listed here assume the input image has three colour channels (spectrum(im) == 3)

Usage
RGBtoHSL(im)

RGBtoXYZ(im)

XYZtoRGB(im)

HSLtoRGB(im)

RGBtoHSV(im)

HSVtoRGB(im)

RGBtoHSI(im)

HSItoRGB(im)

RGBtosRGB(im)

sRGBtoRGB(im)

RGBtoYCbCr(im)

YCbCrtoRGB(im)

RGBtoYUV(im)

YUVtoRGB(im)

LabtoRGB(im)
RGBtoHSL 119

RGBtoLab(im)

LabtoXYZ(im)

XYZtoLab(im)

LabtosRGB(im)

sRGBtoLab(im)

Arguments

im an image

Functions

• RGBtoHSL: RGB to HSL conversion

• RGBtoXYZ: CIE RGB to CIE XYZ (1931) conversion, D65 white point
• XYZtoRGB: CIE XYZ to CIE RGB (1931) conversion, D65 white point
• HSLtoRGB: HSL to RGB conversion
• RGBtoHSV: RGB to HSV conversion
• HSVtoRGB: HSV to RGB conversion
• RGBtoHSI: RGB to HSI conversion
• HSItoRGB: HSI to RGB conversion
• RGBtosRGB: RGB to sRGB conversion
• sRGBtoRGB: sRGB to RGB conversion
• RGBtoYCbCr: RGB to YCbCr conversion
• YCbCrtoRGB: YCbCr to RGB conversion
• RGBtoYUV: RGB to YUV conversion
• YUVtoRGB: YUV to RGB conversion
• LabtoRGB: Lab to RGB (linear)
• RGBtoLab: RGB (linear) to Lab
• LabtoXYZ: Lab to XYZ
• XYZtoLab: XYZ to Lab
• LabtosRGB: Lab to sRGB
• sRGBtoLab: sRGB to Lab
120 rotate_xy

rm.alpha Remove alpha channel and store as attribute

Description
Remove alpha channel and store as attribute

Usage
rm.alpha(im)

Arguments
im an image with 4 RGBA colour channels

Value
an image with only three RGB channels and the alpha channel as attribute

Author(s)
Simon Barthelme

See Also
flatten.alpha

Examples
#An image with 4 colour channels (RGBA)
im <- imfill(2,2,val=c(0,0,0,0))
#Remove fourth channel
rm.alpha(im)
attr(rm.alpha(im),"alpha")

rotate_xy Rotate image by an arbitrary angle, around a center point.

Description
Rotate image by an arbitrary angle, around a center point.

Usage
rotate_xy(im, angle, cx, cy, interpolation = 1L, boundary_conditions = 0L)
save.image 121

Arguments
im an image
angle Rotation angle, in degrees.
cx X-coordinate of the rotation center.
cy Y-coordinate of the rotation center.
interpolation Interpolation type. 0=nearest | 1=linear | 2=cubic
boundary_conditions
Boundary conditions. 0=dirichlet | 1=neumann | 2=periodic

Examples
rotate_xy(boats,30,200,400) %>% plot
rotate_xy(boats,30,200,400,boundary=2) %>% plot

save.image Save image

Description
You’ll need ImageMagick for formats other than PNG and JPEG.

Usage
save.image(im, file, quality = 0.7)

Arguments
im an image (of class cimg)
file path to file. The format is determined by the file’s name
quality (JPEG only) default 0.7. Higher quality means less compression.

Value
nothing

See Also
save.video

Examples
#Create temporary file
tmpF <- tempfile(fileext=".png")
#Save boats image
save.image(boats,tmpF)
#Read back and display
load.image(tmpF) %>% plot
122 split_connected

split_connected Split pixset into connected components

Description

Compute connected components (using "label"), then split into as many sets as there are compo-
nents. Useful for segmentation

Usage

split_connected(px, ...)

Arguments

px a pixset
... further arguments passed to label

Value

a list of pixsets

Author(s)

Simon Barthelme

See Also

label

Examples

px <- isoblur(grayscale(boats),5) > .75

plot(px)
spl <- split_connected(px)
plot(spl[[1]])
px <- isoblur(grayscale(boats),5) > .75
plot(px)
spl <- split_connected(px)
plot(spl[[1]])
squeeze 123

squeeze Remove empty dimensions from an array

Description
Works just like Matlab’s squeeze function: if anything in dim(x) equals one the corresponding
dimension is removed

Usage
squeeze(x)

Arguments
x an array

Examples
A <- array(1:9,c(3,1,3)) #3D array with one flat dimension
A %>% squeeze #flat dimension removed

stencil.cross A cross-shaped stencil

Description
Returns a stencil corresponding to all nearest-neighbours of a pixel

Usage
stencil.cross(z = FALSE, cc = FALSE, origin = FALSE)

Arguments
z include neighbours along the z axis
cc include neighbours along the cc axis
origin include center pixel (default false)

Value
a data.frame defining a stencil

Author(s)
Simon Barthelme
124 threshold

See Also
get.stencil

threshold Threshold grayscale image

Description
Thresholding corresponding to setting all values below a threshold to 0, all above to 1. If you call
threshold with thr="auto" a threshold will be computed automatically using kmeans (ie., using a
variant of Otsu’s method). This works well if the pixel values have a clear bimodal distribution.
If you call threshold with a string argument of the form "XX%" (e.g., "98%"), the threshold will
be set at percentile XX. Computing quantiles or running kmeans is expensive for large images, so
if approx == TRUE threshold will skip pixels if the total number of pixels is above 10,000. Note
that thresholding a colour image will threshold all the colour channels jointly, which may not be the
desired behaviour! Use iiply(im,"c",threshold) to find optimal values for each channel separately.

Usage
threshold(im, thr = "auto", approx = TRUE, adjust = 1)

Arguments
im the image
thr a threshold, either numeric, or "auto", or a string for quantiles
approx Skip pixels when computing quantiles in large images (default TRUE)
adjust use to adjust the automatic threshold: if the auto-threshold is at k, effective
threshold will be at adjust*k (default 1)

Value
a pixset with the selected pixels

Author(s)
Simon Barthelme

Examples
im <- load.example("birds")
im.g <- grayscale(im)
threshold(im.g,"15%") %>% plot
threshold(im.g,"auto") %>% plot
threshold(im.g,.1) %>% plot
#If auto-threshold is too high, adjust downwards or upwards
#using "adjust"
threshold(im,adjust=.5) %>% plot
threshold(im,adjust=1.3) %>% plot
vanvliet 125

vanvliet Young-Van Vliet recursive Gaussian filter.

Description
The Young-van Vliet filter is a fast approximation to a Gaussian filter (order = 0), or Gaussian
derivatives (order = 1 or 2).

Usage
vanvliet(im, sigma, order = 0L, axis = "x", neumann = FALSE)

Arguments
im an image
sigma standard deviation of the Gaussian filter
order the order of the filter 0,1,2,3
axis Axis along which the filter is computed. One of ’x’, ’y’, ’z’, ’c’
neumann If true, use Neumann boundary conditions (default false, Dirichlet)

References
From: I.T. Young, L.J. van Vliet, M. van Ginkel, Recursive Gabor filtering. IEEE Trans. Sig. Proc.,
vol. 50, pp. 2799-2805, 2002. (this is an improvement over Young-Van Vliet, Sig. Proc. 44, 1995)
Boundary conditions (only for order 0) using Triggs matrix, from B. Triggs and M. Sdika. Boundary
conditions for Young-van Vliet recursive filtering. IEEE Trans. Signal Processing, vol. 54, pp.
2365-2367, 2006.

Examples
vanvliet(boats,sigma=2,order=0) %>% plot("Zeroth-order Young-van Vliet along x")
vanvliet(boats,sigma=2,order=1) %>% plot("First-order Young-van Vliet along x")
vanvliet(boats,sigma=2,order=1) %>% plot("Second-order Young-van Vliet along x")
vanvliet(boats,sigma=2,order=1,axis="y") %>% plot("Second-order Young-van Vliet along y")

warp Warp image

Description
Warp image

Usage
warp(im, warpfield, mode = 0L, interpolation = 1L, boundary_conditions = 0L)
126 watershed

Arguments

im an image
warpfield Warping field. The (x,y,z) fields should be stacked along the colour coordinate.
mode Can be 0=backward-absolute | 1=backward-relative | 2=forward-absolute | 3=forward-
relative
interpolation Can be <tt> 0=nearest | 1=linear | 2=cubic </tt>.
boundary_conditions
Boundary conditions. Can be <tt> 0=dirichlet | 1=neumann | 2=periodic </tt>.

See Also

imwarp for a user-friendly interface

Examples
#Shift image via warp
warp.x <- imfill(width(boats),height(boats),val=5)
warp.y <- imfill(width(boats),height(boats),val=20)
warpfield <- list(warp.x,warp.y) %>% imappend("c")
warp(boats,warpfield,mode=1) %>% plot

watershed Compute watershed transform.

Description

The watershed transform is a label propagation algorithm. The value of non-zero pixels will get
propagated to their zero-value neighbours. The propagation is controlled by a priority map. See
examples.

Usage

watershed(im, priority, fill_lines = TRUE)

Arguments

im an image
priority Priority map.
fill_lines Sets if watershed lines must be filled or not.
where 127

Examples
#In our initial image we'll place three seeds
#(non-zero pixels) at various locations, with values 1, 2 and 3.
#We'll use the watershed algorithm to propagate these values
imd <- function(x,y) imdirac(c(100,100,1,1),x,y)
im <- imd(20,20)+2*imd(40,40)+3*imd(80,80)
layout(t(1:3))
plot(im,main="Seed image")
#Now we build an priority map: neighbours of our seeds
#should get high priority.
#We'll use a distance map for that
p <- 1-distance_transform(sign(im),1)
plot(p,main="Priority map")
watershed(im,p) %>% plot(main="Watershed transform")

where Return locations in pixel set

Description
Return locations in pixel set

Usage
where(x)

Arguments
x a pixset

Examples
#All pixel locations with value greater than .99
where(boats > .99)

%inr% Check that value is in a range

Description
A shortcut for x >= a | x <= b.

Usage
x %inr% range
128 %inr%

Arguments
x numeric values
range a vector of length two, of the form c(a,b)

Value
a vector of logicals 1:10

Author(s)
Simon Barthelme
Index

∗Topic datasets cannyEdges, 26

boats, 22 capture.plot, 27
%inr%, 127 Cc (imcoord), 71
center.stencil, 27
add (imager.combine), 65 channel (cimg.extract), 31
add.color (add.colour), 5 channel<- (imager.replace), 67
add.colour, 5 channels, 28
as.cimg, 6 ci, 28
as.cimg.array, 7 cimg, 29
as.cimg.data.frame, 8 cimg.dimensions, 30
as.cimg.function, 9 cimg.extract, 31
as.cimg.pixset (as.pixset), 16 cimg.use.openmp, 32
as.cimg.raster, 10 cimg2im, 33
as.cimg.RasterLayer (RasterPackage), 114 cimg2magick (magick), 98
as.data.frame.cimg, 11 circles, 33
as.data.frame.imlist, 12 clean, 34
as.data.frame.pixset, 12 color.at (at), 18
as.igraph.cimg, 13 color.at<- (at), 18
colorise, 35
as.igraph.pixset, 14
common_pixsets, 36
as.imlist (as.imlist.list), 15
contours, 38
as.imlist.list, 15
convert_pixset (as.data.frame.pixset),
as.imlist.RasterStackBrick
12
(RasterPackage), 114
convolve (correlate), 39
as.pixset, 16
coord.index, 39
as.raster.cimg, 17
correlate, 39
at, 18
crop.bbox (bbox), 20
at<- (at), 18
crop.borders, 40
autocrop, 19
average (imager.combine), 65 depth (cimg.dimensions), 30
deriche, 41
B (cimg.extract), 31 diffusion_tensors, 42
B<- (imager.replace), 67 dilate (erode), 48
bbox, 20 dilate_rect (erode), 48
blur_anisotropic, 21 dilate_square (erode), 48
boats, 22 displacement, 42
boundary, 23 display, 43
boxblur, 23 display.cimg, 43
boxblur_xy, 24 display.list, 44
bucketfill, 25 distance_transform, 45

129
130 INDEX

draw_circle, 45 imager.combine, 65
draw_rect, 46 imager.replace, 67
draw_text, 47 imager.subset, 68
imappend, 69
enorm (imager.combine), 65 imchange, 70
equal (imager.combine), 65 imcol (cimg.extract), 31
erode, 48 imcoord, 71
erode_rect (erode), 48 imdirac, 72
erode_square (erode), 48 imdo (imeval), 74
extract_patches, 50 imdraw, 73
extract_patches3D (extract_patches), 50 imeval, 74
imfill, 76
FFT, 51 imgradient, 77
fill (clean), 34 imhessian, 77
flatten.alpha, 52 iminfo, 78
frame (cimg.extract), 31 imlap, 79
frame<- (imager.replace), 67 imlist, 79
frames, 53 imnoise, 80
implot, 81
G (cimg.extract), 31 imrep, 82
G<- (imager.replace), 67 imresize (resize_doubleXY), 117
get.locations, 53 imrotate, 82
get.stencil, 54 imrow (cimg.extract), 31
get_gradient, 55 imsharpen, 83
get_hessian, 55 imshift, 84
grab, 56 imsplit, 84
grabLine (grab), 56 imsub, 85
grabPoint (grab), 56 imwarp, 86
grabRect (grab), 56 index.coord, 88
grayscale, 57 inpaint, 89
grow, 57 interact, 90
gsdim, 58 interp, 91
is.cimg, 91
haar, 59 is.imlist, 92
height (cimg.dimensions), 30 is.pixset, 92
highlight, 60 isoblur, 93
hough_circle, 60
hough_line, 61 label, 93
HSItoRGB (RGBtoHSL), 118 LabtoRGB (RGBtoHSL), 118
HSLtoRGB (RGBtoHSL), 118 LabtosRGB (RGBtoHSL), 118
HSVtoRGB (RGBtoHSL), 118 LabtoXYZ (RGBtoHSL), 118
liply, 94
idply, 62 load.dir, 95
iiply, 63 load.example, 95
ilply, 63 load.image, 96
im2cimg, 64 load.video, 97
im_split, 88
imager, 64 magick, 98
imager.colourspaces (RGBtoHSL), 118 magick2cimg (magick), 98
INDEX 131

magick2imlist (magick), 98 px.top (common_pixsets), 36

make.video, 99
map2_il (map_il), 100 R (cimg.extract), 31
map_il, 100 R<- (imager.replace), 67
mclosing (erode), 48 RasterPackage, 114
mclosing_square (erode), 48 renorm, 115
medianblur, 101 resize, 116
mirror, 102 resize_doubleXY, 117
mopening (erode), 48 resize_halfXY (resize_doubleXY), 117
mopening_square (erode), 48 resize_tripleXY (resize_doubleXY), 117
mult (imager.combine), 65 resize_uniform (resize_doubleXY), 117
mutate_plyr, 102 RGBtoHSI (RGBtoHSL), 118
RGBtoHSL, 118
nfline, 103 RGBtoHSV (RGBtoHSL), 118
nPix (cimg.dimensions), 30 RGBtoLab (RGBtoHSL), 118
RGBtosRGB (RGBtoHSL), 118
pad, 103 RGBtoXYZ (RGBtoHSL), 118
parall (imager.combine), 65 RGBtoYCbCr (RGBtoHSL), 118
parany (imager.combine), 65 RGBtoYUV (RGBtoHSL), 118
parmax (imager.combine), 65 rm.alpha, 120
parmed (imager.combine), 65 rotate_xy, 120
parmin (imager.combine), 65
parorder (imager.combine), 65 save.image, 121
parrank (imager.combine), 65 save.video (make.video), 99
parsd (imager.combine), 65 shrink (grow), 57
parsort (imager.combine), 65 spectrum (cimg.dimensions), 30
parvar (imager.combine), 65 split_connected, 122
patch_summary_cimg, 105 squeeze, 123
patchstat, 104 sRGBtoLab (RGBtoHSL), 118
periodic.part, 106 sRGBtoRGB (RGBtoHSL), 118
permute_axes, 107 stencil.cross, 123
pixel.grid, 107 subim (imsub), 85
pixset, 108
play, 109 threshold, 124
plot.cimg, 109 transform, 102
plot.imlist, 111
pmap_il (map_il), 100 vanvliet, 125
px.all (common_pixsets), 36
px.borders (common_pixsets), 36 warp, 125
px.bottom (common_pixsets), 36 watershed, 126
px.circle (common_pixsets), 36 where, 127
px.diamond (common_pixsets), 36 which.parmax (imager.combine), 65
px.flood, 112 which.parmin (imager.combine), 65
px.left (common_pixsets), 36 width (cimg.dimensions), 30
px.na, 113 wsum (imager.combine), 65
px.none (common_pixsets), 36
px.remove_outer, 114 Xc (imcoord), 71
px.right (common_pixsets), 36 XYZtoLab (RGBtoHSL), 118
px.square (common_pixsets), 36 XYZtoRGB (RGBtoHSL), 118
132 INDEX

Yc (imcoord), 71
YCbCrtoRGB (RGBtoHSL), 118
YUVtoRGB (RGBtoHSL), 118

Zc (imcoord), 71