• DocumentCode
    2836258
  • Title

    Unsupervised color texture feature extraction and selection for soccer image segmentation

  • Author

    Vandenbroucke, Nicolas ; Macaire, Ludovic ; Postaire, Jack-Gérard

  • Author_Institution
    Lab. d´´Automatique I3D, Univ. des Sci. et Tech. de Lille Flandres Artois, Villeneuve d´´Ascq, France
  • Volume
    2
  • fYear
    2000
  • fDate
    10-13 Sept. 2000
  • Firstpage
    800
  • Abstract
    We describe a new approach for color texture feature extraction and selection. We define color texture features as texture features which are computed by taking into account the color components of the pixels. We determine the most discriminating color texture features among a multidimensional set of color texture features by means of an iterative feature selection procedure associated to an information criterion. This procedure analyses images which are classified by a competitive learning scheme. Soccer image segmentation is achieved by pixel classification. The classification algorithm takes into account these color texture features which are processed in the neighborhood of the pixels. We apply our new unsupervised approach to soccer images segmentation.
  • Keywords
    feature extraction; image classification; image colour analysis; image segmentation; image texture; iterative methods; unsupervised learning; competitive learning; image classification algorithm; iterative feature selection; multidimensional set; pixel classification; pixel color components; soccer image segmentation; unsupervised color texture feature extraction; unsupervised color texture feature selection; Color; Data mining; Feature extraction; Image analysis; Image segmentation; Iterative algorithms; Pixel; Supervised learning; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2000. Proceedings. 2000 International Conference on
  • Conference_Location
    Vancouver, BC, Canada
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-6297-7
  • Type

    conf

  • DOI
    10.1109/ICIP.2000.899830
  • Filename
    899830