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Proceedings Paper

Object matching using weight Hausdorff distance matrix combined with genetic algorithm
Author(s): Qiuze Yu; Bing Yang; Jian Liu; Jinwen Tian
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Paper Abstract

A new similarity measure based on Hausdorff Distance Matrix Frobenius Norm for object matching is proposed in this paper. This measure is more reliable and can achieve higher location accuracy compared with other measures based on classic and modified Hausdorff Distance under the condition of high level noise and high ratio occlusion of template. The search strategy based on genetic algorithms is employed to make algorithm faster. Experimental results under noise of different level demonstrate high performance of the matching algorithm.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678821 (15 November 2007); doi: 10.1117/12.750657
Show Author Affiliations
Qiuze Yu, Huazhong Univ. of Science and Technology (China)
Bing Yang, Huazhong Univ. of Science and Technology (China)
Jian Liu, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision

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