• DocumentCode
    2463189
  • Title

    Discrete models for energy-minimizing segmentation

  • Author

    Ackah-Miezan, A. ; Gagalowicz, A.

  • Author_Institution
    INRIA-Rocquencourt, Le Chesnay, France
  • fYear
    1993
  • fDate
    11-14 May 1993
  • Firstpage
    200
  • Lastpage
    207
  • Abstract
    The image segmentation problem may be considered as the search for a way to subdivide an image domain into regions which represent the projection of visible parts of objects in a real scene. The authors analyze the problem of image segmentation in the framework of the approximation theory as defined by D. Mumford and J. Shah (1988). They show that for real images the problem of the choice of the energy functional is dictated by the model of the world, and they propose a method to optimize it based on a deterministic algorithm processed at multiple levels of resolution. Problems encountered in dealing with real scenes lead to several modifications of the algorithm and the energy functional. Images are shown on which the algorithm was tested
  • Keywords
    approximation theory; deterministic algorithms; image segmentation; approximation theory; deterministic algorithm; discrete models; energy functional; energy-minimizing segmentation; image domain; image segmentation problem; regions; Approximation methods; Energy measurement; Image analysis; Image processing; Image reconstruction; Image segmentation; Layout; Light sources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1993. Proceedings., Fourth International Conference on
  • Conference_Location
    Berlin
  • Print_ISBN
    0-8186-3870-2
  • Type

    conf

  • DOI
    10.1109/ICCV.1993.378219
  • Filename
    378219