• DocumentCode
    409455
  • Title

    Toward automatic colour calibration using machine learning

  • Author

    Zrimec, Tatjana

  • Author_Institution
    Sch. of Comput. Sci. & Eng., New South Wales Univ., Sydney, NSW, Australia
  • Volume
    1
  • fYear
    2003
  • fDate
    10-12 Dec. 2003
  • Firstpage
    227
  • Abstract
    Robot vision can be seriously affected by variations in lighting conditions in the environment. Therefore, vision systems need to be recalibrated whenever lighting conditions change, otherwise they fail to recognize objects or classify them incorrectly. This paper describes experiments aimed at overcoming the problem of vision recalibration. We use Sony ERS210A robots, which are used in RoboCup, the international robot soccer competition. These robots are equipped with colour cameras. The robots are trained to recognize colours under different lightning conditions using machine learning. Learned knowledge is then used for object recognition. In addition, the robots are trained to recognize objects using colour and other object attributes. Incorporating leaning into the vision system facilitates object recognition and provides the ability to automatically adapt vision to new environments.
  • Keywords
    calibration; image colour analysis; learning (artificial intelligence); lighting; mobile robots; object recognition; robot vision; Sony ERS210A robots; automatic colour calibration; colour cameras; lighting conditions; machine learning; object recognition; robot vision; vision recalibration; Calibration; Cameras; Lightning; Machine learning; Machine vision; Object recognition; Robot sensing systems; Robot vision systems; Robotics and automation; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2003 IEEE International Conference on
  • Print_ISBN
    0-7803-7852-0
  • Type

    conf

  • DOI
    10.1109/ICIT.2003.1290275
  • Filename
    1290275