• DocumentCode
    2232390
  • Title

    Chaotic multiagent system approach for MRF-based image segmentation

  • Author

    Melkemi, Kamal E. ; Batouche, Mohamed ; Foufou, Sebti

  • Author_Institution
    Dept. of Comput. Sci., Biskra Univ., Algeria
  • fYear
    2005
  • fDate
    15-17 Sept. 2005
  • Firstpage
    268
  • Lastpage
    273
  • Abstract
    In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.
  • Keywords
    chaos; image segmentation; iterative methods; multi-agent systems; MRF-based image segmentation; chaotic mapping; chaotic multiagent system approach; coordinator agent; iterated conditional modes; Chaos; Chaotic communication; Computational modeling; Computer science; Genetic mutations; Image generation; Image segmentation; Laboratories; Multiagent systems; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on
  • ISSN
    1845-5921
  • Print_ISBN
    953-184-089-X
  • Type

    conf

  • DOI
    10.1109/ISPA.2005.195421
  • Filename
    1521300