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Robust contour matching via the order-preserving assignment problem.

Clayton Scott1, Robert Nowak

  • 1Department of Statistics, Rice University, Houston, TX 77005, USA. cscott@rice.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|July 13, 2006
PubMed
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This study introduces an improved shape matching method by preserving point order along contours, enhancing correspondence accuracy. The novel approach offers robustness against outliers and shape irregularities for better point matching.

Area of Science:

  • Computer Vision
  • Computational Geometry
  • Pattern Recognition

Background:

  • Shape matching is crucial in computer vision and pattern recognition.
  • Traditional methods like the assignment problem (weighted bipartite matching) are common for determining point correspondences.
  • Existing methods can be sensitive to outliers and shape irregularities.

Purpose of the Study:

  • To develop a more robust and accurate method for establishing point correspondences between shapes defined by closed contours.
  • To improve upon the standard assignment problem by incorporating contour ordering constraints.
  • To enhance robustness against noise and irregularities in shape data.

Main Methods:

  • A modified assignment problem is proposed, enforcing the preservation of point order induced by shape contours.

Related Experiment Videos

  • Dynamic programming algorithms are developed for efficient optimization.
  • The method allows for matching only a fraction of feature points, enhancing robustness.
  • A minimum matching size can be specified in advance.

    • Main Results:

    • The proposed method significantly improves the quality of point correspondences compared to the standard assignment problem.
    • Experimental results on the Brown and MPEG-7 shape databases validate the effectiveness of the approach.
    • The method demonstrates robustness with respect to outliers and shape irregularities.

    Conclusions:

    • Preserving contour point ordering is a key factor in achieving accurate shape correspondences.
    • The developed dynamic programming approach provides an efficient and effective solution for ordered shape matching.
    • This method offers a significant advancement for shape analysis and recognition tasks.