Matching of stereo curves — A closed form solution

  • Yaonan Zhang
  • Jan J. Gerbrands
Low-level Image Processing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 974)


A method is described in this article to solve the stereo matching problem of general closed planar curves under possible imperfect segmentation and occlusions, provided that camera parameters are known. The method decomposes the parameters related to an object plane, i.e. slant, tilt and scale factor, and uses a histogram technique to estimate these parameters. The parameter estimation is based on the disparity information of the stereo curves. Point correspondence plays an important role in the method. We solve this problem in a dynamic programming style. The final matching is assessed by applying a distance transformation. The method has been applied successfully to several practical examples.


  1. 1.
    B. Bhanu and O. Faugeras, “Shape matching of two-dimensional objects,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, pp. 137–156, 1984.Google Scholar
  2. 2.
    E. Salari and S. Balaji, “Recognition of partially occluded objects using B-spline representation,” Pattern Recognition, vol. 24, pp. 653–660, 1991.Google Scholar
  3. 3.
    D. Sherman and S. Peleg, “Stereo by incremental matching of contours,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, pp. 1102–1106, Nov. 1990.Google Scholar
  4. 4.
    A. Bruckstein, R. Holt, A. Netraval, and T. Richardson, “Invariant signatures for planar shape recognition under partial occlusion,” CVGIP: Image Understanding, vol. 58, pp. 49–65, July 1993.Google Scholar
  5. 5.
    Z. Pizlo, “Recognition of planar shapes from perspective images using contour-based invariants,” CVGIP: Image Understanding, vol. 56, pp. 330–350, 1992.Google Scholar
  6. 6.
    B. Kamgar-Parsi, A. Margalit, and A. Rosenfeld, “Matching general polygonal arcs,” CVGIP: Image Understanding, vol. 53, pp. 227–234, 1991.Google Scholar
  7. 7.
    E. Arkin, L. Chew, D. Huttenlocher, K. Kedem, and J. Mitchell, “A efficiently computable metric for comparing polygonal shapes,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, pp. 209–216, 1991.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Yaonan Zhang
    • 1
  • Jan J. Gerbrands
    • 1
  1. 1.Information Theory Group Department of Electrical EngineeringDelft University of TechnologyGA DelftThe Netherlands

Personalised recommendations