BMVC92 pp 119-128 | Cite as

Contextual Junction Finder

  • J. Matas
  • J. Kittler


A novel approach to junction detection using an explicit line finder model and contextual rules is presented. Contextual rules expressing properties of 3D-edges (surface orientation discontinuities) limit the num- ber of line intersections interpreted as junctions. Probabilistic relaxation labelling scheme is used to combine the a priori world knowledge represented by contextual rules and the information contained in observed lines.

Junctions corresponding to a vertex (V-junctions) and an occlusion (T-junctions) of a 3D object are detected and stored in a junction graph. The information in the junction graph is used to extract higher level features. Results of the most promising method, the polyhedral object face recovery, are briefly discussed. The performance of the junction detection process is demonstrated on images from indoor, outdoor, and industrial environments.


Projected Line Intersection Network Line Detector Endpoint Error Line Finder 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    R. Bergevin and M. D. Levine. Extraction of line drawing features for object recognition. In Proceedings of IEEE International Conference Pattern Recognition ,pages 496–501, 1990.CrossRefGoogle Scholar
  2. [2]
    C. Coelho, M. Straforini, and M. Campani. Using geometrical rules and a priori knowledge for the understanding of indoor scenes. In Proc. British Machine Vision Conference ,pages 229–234, 1990.Google Scholar
  3. [3]
    R. Deriche. Using Canny’s criteria to derive a recursively implemented optimal edge detector. International Journal of Computer Vision, 1(2):167, 1987.CrossRefGoogle Scholar
  4. [4]
    R.N. Haber and M. Hershenson. The Psychology of Visual Perception. Holt, Rinehart and Winston Inc., U.S.A, 1973.Google Scholar
  5. [5]
    R. Horaud, F. Veillon, and T. Skordas. Finding geometric and relational structures in an image. In European Conference on Computer Vision ,pages 373–384, 1990.Google Scholar
  6. [6]
    J. Kittler and E.R. Hancock. Combining evidence in probabilistic relaxation. International Journal of Pattern Recognition and Artificial Intelligence ,3:29–51, 1989.CrossRefGoogle Scholar
  7. [7]
    J. Kittler, J. Illingworth, J. Matas, P. Remagnino, K. C. Wong, H. Christensen, J-O. Eklundh, G. Olofsonn, and M. Li. Symbolic scene interpretation and control of perception. Technical report, ESPRIT BRA Project 3038, March 1992.Google Scholar
  8. [8]
    Du Li, G.D. Sullivan, and K.D. Baker. Edge detection at junctions. In AVC ,pages 121–125, 1989.Google Scholar
  9. [9]
    D. Lowe. Three-dimensional object recognition from single two dimensional images. Artifical Intelligence ,31:355–395, 1987.CrossRefGoogle Scholar
  10. [10]
    R. Mohan and R. Nevatia. Using perceptual organisation to extract 3-d structures. IEEE Transactions on Pattern Analysis and Machine Intelli gence, 11(11):1121–1139, 1989.CrossRefGoogle Scholar
  11. [11]
    J. A. Nobel. Finding corners. In AVC ,pages 267–274, 1988.Google Scholar
  12. [12]
    P. L. Palmer, J. Kittler, and M. Petrou. A Hough transform algorithm with a 2D hypothesis testing kernel. In Proceedings of IEEE International Conference Pattern Recognition ,September 1992.Google Scholar
  13. [13]
    J.R Pomerantz. Perceptual organization and information processing. In Perceptual Organization ,pages 141–180, 365 Broadway, Hillsdale, New Jersey, 1981. Lawrence ERLBRAUM associates.Google Scholar
  14. [14]
    J. Princen. Hough Transform Methods for Curve Detection and Parameter Estimation. PhD thesis, University of Surrey, June 1990.Google Scholar
  15. [15]
    VAP project. Vision as process. Technical annex, EEC, March 1989.Google Scholar
  16. [16]
    R. Sedgewick. Algorithms. Addison-Wesley, Reading, 1983.zbMATHGoogle Scholar

Copyright information

© Springer-Verlag London Limited 1992

Authors and Affiliations

  • J. Matas
    • 1
  • J. Kittler
    • 1
  1. 1.Dept. of Electronic and Electrical EngineeringUniversity of SurreyGuildford, SurreyUK

Personalised recommendations