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Intensity and edge-based symmetry detection applied to car-following

  • Thomas Zielke
  • Michael Brauckmann
  • Werner von Seelen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

We present two methods for detecting symmetry in images, one based directly on the intensity values and another one based on a discrete representation of local orientation. A symmetry finder has been developed which uses the intensity-based method to search an image for compact regions which display some degree of mirror symmetry due to intensity similarities across a straight axis. In a different approach, we look at symmetry as a bilateral relationship between local orientations. A symmetryenhancing edge detector is presented which indicates edges dependent on the orientations at two different image positions. SEED, as we call it, is a detector element implemented by a feedforward network that holds the symmetry conditions. We use SEED to find the contours of symmetric objects of which we know the axis of symmetry from the intensity-based symmetry finder. The methods presented have been applied to the problem of visually guided car-following. Real-time experiments with a system for automatic headway control on motorways have been successful.

Keywords

Local Orientation Visual Tracking Detector Element Directional Filter Symmetric Object 
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.

References

  1. 1.
    Friedberg, S. A.: Finding Axes of Skewed Symmetry. Computer Vision, Graphics, and Image Processing 34 (1986) 138–155Google Scholar
  2. 2.
    Marola, G.: Using Symmetry for Detecting and Locating Objects in a Picture. Computer Vision, Graphics, and Image Processing 46 (1989) 179–195Google Scholar
  3. 3.
    Saint-Marc, P., Medioni, G.: B-Spline Contour Representation and Symmetry Detection, Proceedings, First European Conf. on Computer Vision, Antibes, France (1990) 604–606Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Thomas Zielke
    • 1
  • Michael Brauckmann
    • 1
  • Werner von Seelen
    • 1
  1. 1.Institut für NeuroinformatikRuhr-UniversitätBochumGermany

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