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Using Layered Color Precision for a Self-Calibrating Vision System

  • Matthias Jüngel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

This paper presents a vision system for robotic soccer which was tested on Sony’s four legged robot Aibo. The input for the vision system are images of the camera and the sensor readings of the robot’s head joints, the output are the positions of all recognized objects in relation to the robot. The object recognition is based on the colors of the objects and uses a color look-up table. The vision system creates the color look-up table on its own during a soccer game. Thus no pre-run calibration is needed and the robot can cope with inhomogeneous or changing light on the soccer field. It is shown, how different layers of color representation can be used to refine the results of color classification. However, the self-calibrated color look-up table is not as accurate as a hand-made. Together with the introduced object recognition which is very robust relating to the quality of the color table, the self-calibrating vision works very well. This robustness is achieved using the detection of edges on scan lines.

Keywords

Vision System Object Recognition Color Space Color Channel Average Color 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Matthias Jüngel
    • 1
  1. 1.Institut für Informatik, LFG Künstliche IntelligenzHumboldt-Universität zu BerlinBerlinGermany

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