• DocumentCode
    3059816
  • Title

    Colour segmentation with polynomial classification

  • Author

    Bartneck, N. ; Ritter, W.

  • Author_Institution
    Res. Inst. for Inf. Technol., Daimler-Benz AG, Ulm, Germany
  • fYear
    1992
  • fDate
    30 Aug-3 Sep 1992
  • Firstpage
    635
  • Lastpage
    638
  • Abstract
    An important step for image analysis is the reduction of colour levels to a small number of significant levels. This can be considered as a classification task. In this paper questions of suitable colour spaces are discussed, which have a strong correlation to the feature space used for classification. Furthermore polynomial classification as a method for colour segmentation with supervised learning is introduced. Finally results are shown coming from the application fields of traffic sign recognition and postal automation
  • Keywords
    feature extraction; image segmentation; learning (artificial intelligence); colour levels; feature space; image analysis; polynomial classification; postal automation; supervised learning; traffic sign recognition; Automation; Image analysis; Image color analysis; Image recognition; Image segmentation; Information analysis; Polynomials; Postal services; Space technology; Supervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
  • Conference_Location
    The Hague
  • Print_ISBN
    0-8186-2915-0
  • Type

    conf

  • DOI
    10.1109/ICPR.1992.201857
  • Filename
    201857