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A Edge Feature Matching Algorithm Based on Evolutionary Strategies and Least Trimmed Square Hausdorff Distance

  • Li JunShan
  • Han XianFeng
  • Li Long
  • Li Kun
  • Li JianJun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4221)

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.

Keywords

Evolutionary Strategy Reference Image Hausdorff Distance Evolutionary Strategy Extract Feature Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li JunShan
    • 1
  • Han XianFeng
    • 1
  • Li Long
    • 1
  • Li Kun
    • 2
  • Li JianJun
    • 1
  1. 1.Xi’an Research Inst. Of High-tech Hongqing TownXi’anChina
  2. 2.Institute of Intelligent Information ProcessingXidian UniversityXi’anChina

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