Abstract
This paper presents an affine invariant shape descriptor which could be applied to both binary and gray-level images. The proposed algorithm uses gradient based features which are extracted along the object boundaries. We use two-dimensional steerable G-Filters [1] to obtain gradient information at different orientations. We aggregate the gradients into a shape signature. The signatures derived from rotated objects are shifted versions of the signatures derived from the original object. The shape descriptor is defined as the Fourier transform of the signature. We also provide a distance definition for the proposed descriptor taking shifted property of the signature into account. The performance of the proposed descriptor is evaluated over a database containing license plate characters. The experiments show that the devised method outperforms other well-known Fourier-based shape descriptors such as centroid distance and boundary curvature.
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© 2006 Springer-Verlag Berlin Heidelberg
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Çapar, A., Kurt, B., Gökmen, M. (2006). Affine Invariant Gradient Based Shape Descriptor. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_68
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DOI: https://doi.org/10.1007/11848035_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
Online ISBN: 978-3-540-39393-1
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