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Real-Time Adaptive Colour Segmentation for the RoboCup Middle Size League

  • Claudia Gönner
  • Martin Rous
  • Karl-Friedrich Kraiss
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

In order to detect objects using colour information, the mapping from points in colour space to the most likely object must be known. This work proposes an adaptive colour calibration based on the Bayes Theorem and chrominance histograms. Furthermore the object’s shape is considered resulting in a more robust classification. A randomised hough transform is employed for the ball. The lines of the goals and flagposts are extracted by an orthogonal regression. Shape detection corrects over- and undersegmentations of the colour segmentation, thus enabling an update of the chrominance histograms. The entire algorithm, including a segmentation and a recalibration step, is robust enough to be used during a RoboCup game and runs in real-time.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Claudia Gönner
    • 1
  • Martin Rous
    • 1
  • Karl-Friedrich Kraiss
    • 1
  1. 1.Chair of Technical Computer ScienceTechnical University of Aachen (RWTH)Aachen

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