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A New Method for Line Matching

  • Yanxia Wang
  • Ma Yan
  • Qixin Chen
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 154)

Abstract

To exploit the existing mature technology of points matching and combine the concept of edge potential functions (EPF), proposing a new method to match curve segments. The method makes full of feature points, the relation between feature points and curves, and gray space, has matching accuracy, and narrows down the searching space and improves the speed of matching.

Keywords

Feature Point Curve Segment Normalize Cross Correlation Curve Match Left View 
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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Notes

Acknowledgements

This work is sponsored by Project No10XLB19 supported by Dr. Research Funds of Chongqing Normal University, Chongqing Education Committee (KJ090809) and Chongqing Higher Education Educational Reform (NO:102118).

References

  1. Cordelia Schmid, Andrew Zisserman. Automatic Line Matching across Views. International Conference on Computer Vision & Pattern Recognition (1997) 666–671.Google Scholar
  2. C. Schmid, A. Zisserman, Automatic line matching across views. IEEE International Conference on Computer Vision and Pattern Recognition (1997).Google Scholar
  3. C. Schmid, A. Zisserman, The geometry and matching of lines and curves over multiple views, Int. J. Comput. Vision 40 (3) (2000) 199–233.Google Scholar
  4. Y. Deng, X.Y. Lin, A fast line segment based dense stereo algorithm using tree dynamic programming, in: European Conference on Computer Vision (2006).Google Scholar
  5. Herbert Bay, Vittorio Ferrari, Luc Van Gool. Wide-Baseline Stereo Matching with Line Segments. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Diego, June (2005).Google Scholar
  6. Zhiheng Wang, Fuchao Wu, Zhanyi Hu. A robust descriptor for line matching Pattern. nt. J. Comput. Vision, (2002) 42 (3): 189–204.Google Scholar
  7. Minh-Son Dao, Francesco G. B., De Natale, Andrea Massa. Edge Potential Functions (EPF) and Genetic Algorithms (GA) for Edge-Based Matching of Visual Objects. IEEE Transactions on Multimedia, Vol.9, No. 1, January (2007).Google Scholar

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  1. 1.College of Computer and Information ScienceChongqing Normal UniversityChongqingChina
  2. 2.Department education administrationGuizhou University of Finance and EconomicsGuiyangChina

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