Object matching using weight Hausdorff distance matrix combined with genetic algorithm

Qiuze Yu; Bing Yang; Jian Liu; Jinwen Tian

doi:10.1117/12.750657

15 November 2007 Object matching using weight Hausdorff distance matrix combined with genetic algorithm

Qiuze Yu, Bing Yang, Jian Liu, Jinwen Tian

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678821 (2007) https://doi.org/10.1117/12.750657
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Qiuze Yu, Bing Yang, Jian Liu, and Jinwen Tian "Object matching using weight Hausdorff distance matrix combined with genetic algorithm", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678821 (15 November 2007); https://doi.org/10.1117/12.750657

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