• DocumentCode
    1646285
  • Title

    A genetic algorithm for image segmentation

  • Author

    Bosco, Giosuè Lo

  • Author_Institution
    Dipartimento di Matematica e Applicazioni, Palermo Univ., Italy
  • fYear
    2001
  • Firstpage
    262
  • Lastpage
    266
  • Abstract
    The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm
  • Keywords
    genetic algorithms; image matching; image segmentation; fitness function; genetic algorithm; global optimization problem; image segmentation; image similarity; real images; Deformable models; Eigenvalues and eigenfunctions; Genetic algorithms; Humans; Image recognition; Image segmentation; Layout; Shape; Surface fitting; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Processing, 2001. Proceedings. 11th International Conference on
  • Conference_Location
    Palermo
  • Print_ISBN
    0-7695-1183-X
  • Type

    conf

  • DOI
    10.1109/ICIAP.2001.957019
  • Filename
    957019