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OPTICAL CHARACTER RECOGNITION
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JOURNAL OF ENGINEERING, COMPUTING & ARCHITECTURE ISSN NO:1934-7197
OPTICAL CHARACTER RECOGNITION
Dr. V. Geetha1, Ch V V Sudheer2, A V Saikumar3
Dr C K Gomathy4
1, 4 Assistant Professor, Dept. of CSE, SCSVMV (Deemed to be University), Kancheepuram, TamilNadu, India
2, 3 Student, Dept. of CSE, SCSVMV (Deemed to be University), Kancheepuram, TamilNadu, India
ABSTRACT:
The project is about OCR. It stands for "Optical Character Recognition." OCR is an input
device used to read a printed text. OCR scans the text optically, character by character,
converts them into a machine readable code and stores the text on the system memory and
convert it into Document. The technology of optical character recognition (OCR) was used to
transform printed text into editable text. In a variety of applications, OCR is a very helpful
and popular approach. Text preparation and segmentation techniques can influence OCR
accuracy. Because of the image's varying size, style, orientation, and intricate backdrop,
retrieving text from it might be challenging at times.It is a technology that recognizes text
within a digital image. It is commonly used to recognize text in scanned documents and
images. OCR can be used to convert a physical paper document, or an image into an
accessible electronic version with text.
Keywords: OCR, Tesseract, OpenCV, python.
I. INTRODUCTION
Text recognition is one of the most image or text given on a board sign or a
prominent applications of computer vision paper. The Live Text feature recognizes
which is being used by several the text present in the image, be it a
multinational Tech companies such as contact number or an email id. These
Apple, Google, etc. Apple recently features work on a service or technology
announced including the "Live Text" called OCR (Optical Character
feature in iOS15.This functionality is Recognition). For decades, OCR was the
similar to how Google Lens works on sole means to transform printouts into
Android phones and the Google Search computer-processable data, and it is still
and Photos apps on iOS. So, the basic the preferred method for turning paper
procedure of how these feature works are, invoices into extractable data that can be
a person has to point the camera at an linked into financial systems, for example.
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JOURNAL OF ENGINEERING, COMPUTING & ARCHITECTURE ISSN NO:1934-7197
However, electronic document submission and symbols. Such machines appeared in
now provides organizations with a the middle of 1960s to early 1970s.For the
significantly improved approach to areas third generation of OCR systems, the
like invoicing and sales processing, challenges were documents of poor quality
lowering costs and allowing employees to and large printed and hand-written
focus on higher-value activities. character sets. Low cost and high
performance were also important
II. PROBLEM STATEMENT objectives. Commercial OCR systems with
such capabilities appeared during the
decade 1975 to 1985.The fourth generation
The problem here is for the software
can be characterized by the OCR of
systems to recognize characters in
complex documents intermixing with text,
computer system when information is
graphics, tables and mathematical
scanned through paper documents as we
symbols, unconstrained handwritten
know that we have number of newspapers
characters, color documents, low-quality
and books which are in printed format
noisy documents, etc. Among the
related to different subjects. Whenever we
commercial products, postal address
scan the documents through the scanner,
readers, and reading aids for the blind are
the documents are stored as images such as
available in the market.
jpeg, gif etc., in the computer system.
These images cannot be read or edited by IV.EXISTING SYSTEM
the user. But to reuse this information it is
very difficult to read the individual In the running world there is a growing
contents and searching the contents form demand for the users to convert the printed
these documents line-by-line and word-by- documents for maintaining the security of
word. These days there is a huge demand their data.Manually,it is time taken process
in "storing the information available in to note text in a image without a
these paper documents in to a computer software.So The basic OCR system was
storage disk and then later editing or invented to convert the data available on
reusing this information by searching papers and images into computer
process. processed documents.
III. LITERATURE SURVEY V. PROPOSED METHOD
The first commercialized OCR of this OCR is able to recognize the text in the
generation was IBM 1418, which was scanned documents and images into an
designed to read a special IBM font407. accessible electronic version with text and
The recognition method was template it will convert into documents and we are
matching, which compares the character doing it with real time example using
image with a library of prototype images webcam.So the characters in the images
for each character of each font. Next can be recognized. The OCR technology
generation machines were able to allows for us to search the text by words
recognize regular machine-printed and found within the document.
hand printed characters. The character set
was limited to numerals and a few letters
Volume 12, Issue 3, MARCH - 2022 http://www.journaleca.com/ Page No: 212
JOURNAL OF ENGINEERING, COMPUTING & ARCHITECTURE ISSN NO:1934-7197
manually rewritten from the form by an
experienced user contains less mistakes
than the data recognized by OCR/system.
VI.ARCHITECTURE
VIII. REFERENCES
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