Skip to main content
Springer Nature Link
Log in

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

  • Conference paper
Advances in Natural Computation (ICNC 2006)

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

Included in the following conference series:

  • 1343 Accesses

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Zi-xing, C., Guang-you, X.: Artificial Intelligence And Its Application [M]. TsingHua University Publishing Com., Beijing (2004)

    Google Scholar 

  2. Huttenlocher Daniel, P., Klanderman Gregory, A., Ruck lidge William, J.: Comparing images using the hausdorff distance [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9), 850–863 (1993)

    Article  Google Scholar 

  3. Sim, D.G., Kwon, O.K., Park, R.H.: Object matching algorithms using robust Hausdorff distance measures [J]. IEEE Transactions on Image Processing 8(3), 425–429 (1999)

    Article  Google Scholar 

  4. Sim, D.G., Kwon, O.K., Park, R.H.: Object matching algorithm using robust Hausdorff distance measures[J]. IEEE Trans. Image Process 8(2), 425–429 (1999); Wong, R.Y., Hall, E.L. Scene Matching with Invariant Moments, CGIP (8), 16–24 (1978)

    Google Scholar 

  5. Sardana, H.K., Daemi, M.F., lbrahim, M.K.: Global Description of Edge Patterns using Moments. Pattern Recognition 27(1) (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Xi’an Research Inst. Of High-tech Hongqing Town, 710025, Xi’an, China

    Li JunShan, Han XianFeng, Li Long & Li JianJun

  2. Institute of Intelligent Information Processing, Xidian University, 710000, Xi’an, China

    Li Kun

Authors
  1. Li JunShan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Han XianFeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Li Kun
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Li JianJun
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

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

Download citation

  • 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)

Publish with us

Policies and ethics