2014
DOI: 10.1007/s11263-014-0773-x
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Shape Description and Matching Using Integral Invariants on Eccentricity Transformed Images

Abstract: Matching occluded and noisy shapes is a prob- inside the shape; but they ignore the boundary information. 15We describe a method that combines the boundary signature 16 of a shape obtained from II and structural information from 17 the Ecc to yield results that improve on them separately.

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Cited by 16 publications
(5 citation statements)
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“…There are many effective objective methods that have been proposed for shape description in the field of pattern recognition and computer vision (Latecki & Lakämper, 1999; Direkolu & Nixon, 2011). Current methods for shape description can be classified into two categories: contour based and region based (Janan & Brady, 2015). These methods may provide many objective measures for design research.…”
Section: Methodsmentioning
confidence: 99%
“…There are many effective objective methods that have been proposed for shape description in the field of pattern recognition and computer vision (Latecki & Lakämper, 1999; Direkolu & Nixon, 2011). Current methods for shape description can be classified into two categories: contour based and region based (Janan & Brady, 2015). These methods may provide many objective measures for design research.…”
Section: Methodsmentioning
confidence: 99%
“…Above all, the DFCC sequence is treated as a positive integer with n digits. The sequence is then searched corresponding to the minimum positive integer [25].…”
Section: ) Difference Freeman Chain Code (Dfcc) For the Contour Reprmentioning
confidence: 99%
“…These region-based approaches are computationally intense and most of them need to normalize the image to achieve common geometrical invariance. The representative approaches in the literature for contour based include Contour Flexibility [10], Curvature Scale Space [11], Fourier Descriptors [12], Shape Contexts (SC) [13], Inner-Distance Shape Contexts [14], Distance Sets [15], Aligning Curves [16], Height Functions [17], Shape Signature [18] and integral invariants [19]. These contour descriptors are based on the boundary of a shape; they do not capture the internal structure of the shape, and so they are unsuitable for disjoint shapes or shapes with holes because internal boundary and topological information is used by these descriptors.…”
Section: Introductionmentioning
confidence: 99%