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

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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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.

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References

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© 2006 Springer-Verlag Berlin Heidelberg

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JunShan, L., XianFeng, H., Long, L., Kun, L., JianJun, L. (2006). A Edge Feature Matching Algorithm Based on Evolutionary Strategies and Least Trimmed Square Hausdorff Distance. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_65

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  • DOI: https://doi.org/10.1007/11881070_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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