A edge feature matching algorithm based on evolutionary strategies and least trimmed square hausdorff distance

Authors:
Li JunShan;Han XianFeng;Li Long;Li Kun;Li JianJun
Affiliations:
Xi'an Research Inst. Of High-tech Hongqing Town, Xi'an, China;Xi'an Research Inst. Of High-tech Hongqing Town, Xi'an, China;Xi'an Research Inst. Of High-tech Hongqing Town, Xi'an, China;Institute of Intelligent Information Processing, Xidian University, Xi'an, China;Xi'an Research Inst. Of High-tech Hongqing Town, Xi'an, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

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Abstract

Aimed at problems of low orientation precision of traditional gray correlation matching and bad real-time feature based on partial hausdorff distance matching, a edge feature matching algorithm based on evolutionary strategies and least trimmed square hausdorff distance is presented. Experiments show that it has good matching effect.