• DocumentCode
    2642330
  • Title

    Unsupervised perceptual model for color image´s segmentation

  • Author

    Sobrevilla, P. ; Gomez, D. ; Montero, J. ; Montseny, E.

  • Author_Institution
    Applied. Math. II Dept., Tech. Univ. of Catalonia, Barcelona, Spain
  • fYear
    2005
  • fDate
    26-28 June 2005
  • Firstpage
    349
  • Lastpage
    354
  • Abstract
    Color segmentation is a fundamental step in image understanding. Moreover, for getting accurate color image´s segmentation algorithms human being´s perception of color should be considered. In this line we propose an unsupervised segmentation algorithm that is based on a fuzzy graph coloring process for representing the fuzzy color similarity degrees among neighboring pixels from a perceptual point of view. As main goal is to detect and extract the regions explaining the image, we stress the role of coloring procedures for unsupervised segmentation and fuzzy classification by means of useful, comprehensive and simple enough fuzzy graphical representations.
  • Keywords
    fuzzy set theory; graph colouring; image classification; image colour analysis; image segmentation; color image segmentation; color perception; fuzzy classification; fuzzy color similarity degree; fuzzy graph coloring process; fuzzy graphical representation; image detection; image extraction; perceptual vision; unsupervised perceptual model; unsupervised segmentation; Application software; Classification algorithms; Color; Computer vision; Fuzzy sets; Humans; Image segmentation; Pixel; Statistics; Stress; Segmentation algorithms; coloring problem; fuzzy sets; image classification; perceptual vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
  • Print_ISBN
    0-7803-9187-X
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2005.1548560
  • Filename
    1548560