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An Eigenvector Approach Based on Shape Context Patterns for Point Matching

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3 Author(s)
Xiabi Liu ; Dept. of Comput. Sci. & Eng., Beijing Inst. of Technol. ; Yunde Jia ; Yanjie Wang

In this paper, the problem of point correspondence across two images is treated in the eigenvector analysis matching framework of Scott and Longuet-Higgins. We develop the concept of shape contexts introduced by S. Belongie et al. to shape context patterns as rich local descriptors of points. We further propose a Gaussian-weighted Hausdorff distance between shape context patterns to measure correspondence strength in Scott and Longuet-Higgins framework. The resultant point matching approach is applied to estimate affine transformation between handwritten Chinese character images, whose effectiveness is confirmed by the experimental results

Published in:

Communications and Information Technologies, 2006. ISCIT '06. International Symposium on

Date of Conference:

Oct. 18 2006-Sept. 20 2006