• DocumentCode
    2284643
  • Title

    Genetic fusion: application to multi-components image segmentation

  • Author

    Rosenberger, C. ; Chehdi, K.

  • Author_Institution
    ENSSAT-LASTI, Lannion, France
  • Volume
    6
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    2223
  • Abstract
    In this communication, we propose a new approach which enables to fusion either the results of several segmentation methods of a same image or the different results in the case of a multi-components image. The developed method is based on a genetic algorithm approach which allows to combine segmentation results by taking into account their quality through an evaluation criterion. This criterion provides to quantify a segmentation result without any a priori knowledge such as the ground truth. This approach is applied to segment multi-components images by combining the segmentation results of each component. We show the efficiency of the method through some experimental results on several images
  • Keywords
    genetic algorithms; image segmentation; evaluation criterion; genetic algorithm approach; genetic fusion; multi-components image segmentation; Councils; Genetic algorithms; Genetic mutations; Image processing; Image segmentation; Merging; Pixel; Stability criteria;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-6293-4
  • Type

    conf

  • DOI
    10.1109/ICASSP.2000.859280
  • Filename
    859280