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A geometric reasoning based algorithm for point pattern matching

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Abstract

Point pattern matching (PPM) is an important topic in computer vision and pattern recognition. It can be widely used in many areas such as image registration, object recognition, motion detection, target tracking, autonomous navigation, and pose estimation. This paper discusses the incomplete matching problem of two point sets under Euclidean transformation. According to geometric reasoning, some definitions for matching clique, support point pair, support index set, and support index matrix, etc. are given. Based on the properties and theorems of them, a novel reasoning algorithm is presented, which searches for the optimal solution from top to bottom and could find out as many consistent corresponding point pairs as possible. Theoretical analysis and experimental results show that the new algorithm is very effective, and could be, under some conditions, applied to the PPM problem under other kind of transformations.

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References

  1. Vindo, V. V., Ghose, S., Point matching using asymmetric neural networks, Pattern Recognition, 1993, 26(8): 1207–1214.

    Article  Google Scholar 

  2. Morgera, S. D., Cheong, P. L. C., Rigid body constrained noisy point pattern matching, IEEE Trans. on Image Processing, 1995, 4(5): 630–641.

    Article  Google Scholar 

  3. Edward, J. G., A pattern matching algorithm for two-dimensional coordinate lists, The Astronomical Journal, 1986, 91(5): 1244–1248.

    Google Scholar 

  4. Skea, D., Kuwahara, R., Poeckert, R., A control matching algorithm, Pattern Recognition, 1993, 26(2): 269–276.

    Article  Google Scholar 

  5. Stockman, G., Kopstein, S., Benett, S., Matching images to models for registration and object detection via clustering, IEEE Trans. on Pattern Analysis and Machine Intelligence, 1992, PAMI-4(3): 229–241.

    Article  Google Scholar 

  6. Chang, S. H., Cheng, F. H., Hsu, W. H. et al., Fast algorithm for point pattern matching: Invariant to translations, rotations and scale changes, Pattern Recognition, 1997, 30(2): 311–320.

    Article  Google Scholar 

  7. Mundy, J. L., Zisserman, A., Introduction-towards a new framework for vision, in Geometric Invariance in Computer Vision, Cambridge: The MIT Press, 1992, 1–39.

    Google Scholar 

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Authors and Affiliations

  1. Department of Automation, Tsinghua University, 100084, Beijing, China

    Xu Wenli & Zhang Lihua

Authors
  1. Xu Wenli
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  2. Zhang Lihua
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Correspondence to Xu Wenli.

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Xu, W., Zhang, L. A geometric reasoning based algorithm for point pattern matching. Sci China Ser F 44, 445–452 (2001). https://doi.org/10.1007/BF02713948

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  • DOI: https://doi.org/10.1007/BF02713948

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