• DocumentCode
    3127878
  • Title

    Cluster-based segmentation of natural scenes

  • Author

    Pauwels, Eric J. ; Frederix, Greet

  • Author_Institution
    ESAT-PSI, Katholieke Univ., Leuven, Belgium
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    997
  • Abstract
    In cluster-based segmentation pixels are mapped into various feature spaces whereupon they are subjected to a grouping algorithm. In this paper we develop a robust and versatile non-parametric clustering algorithm that is able to handle the unbalanced and irregular clusters encountered in such segmentation applications. The strength of our approach lies in the definition and use of two cluster validity indices that are independent of the cluster topology. By combining them, an excellent clustering can be identified, and experiments confirm that the associated clusters do indeed correspond to perceptually salient image regions
  • Keywords
    computer vision; content-based retrieval; image segmentation; pattern clustering; cluster topology; cluster validity indices; cluster-based segmentation; feature spaces; grouping algorithm; irregular clusters; natural scenes; nonparametric clustering algorithm; perceptually salient image regions; pixel mapping; unbalanced clusters; Clustering algorithms; Computer vision; Content based retrieval; Gaussian processes; Image retrieval; Image segmentation; Layout; Libraries; Mathematics; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on
  • Conference_Location
    Kerkyra
  • Print_ISBN
    0-7695-0164-8
  • Type

    conf

  • DOI
    10.1109/ICCV.1999.790377
  • Filename
    790377