MRF model-based approach for image segmentation using a chaotic MultiAgent system

Kamal E. Melkemi, Mohamed Batouche, Sebti Foufou

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is shown through experimental results.

    Original languageEnglish (US)
    Title of host publicationFuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers
    Pages344-353
    Number of pages10
    DOIs
    StatePublished - Jun 23 2006
    Event6th International Workshop - Fuzzy Logic and Applications - Crema, Italy
    Duration: Sep 15 2005Sep 17 2005

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3849 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other6th International Workshop - Fuzzy Logic and Applications
    CountryItaly
    CityCrema
    Period9/15/059/17/05

    Fingerprint

    Multi agent systems
    Image segmentation
    Image Segmentation
    Chaotic System
    Multi-agent Systems
    Model-based
    Segmentation
    Chaotic systems
    Initialization
    Crossover
    Distributed Systems
    Mutation
    Experimental Results

    Keywords

    • Chaotic System
    • Genetic Algorithms
    • Image Segmentation
    • Markov Random Field
    • MultiAgent Systems

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

    Cite this

    Melkemi, K. E., Batouche, M., & Foufou, S. (2006). MRF model-based approach for image segmentation using a chaotic MultiAgent system. In Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers (pp. 344-353). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3849 LNAI). https://doi.org/10.1007/11676935_43

    MRF model-based approach for image segmentation using a chaotic MultiAgent system. / Melkemi, Kamal E.; Batouche, Mohamed; Foufou, Sebti.

    Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. p. 344-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3849 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Melkemi, KE, Batouche, M & Foufou, S 2006, MRF model-based approach for image segmentation using a chaotic MultiAgent system. in Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3849 LNAI, pp. 344-353, 6th International Workshop - Fuzzy Logic and Applications, Crema, Italy, 9/15/05. https://doi.org/10.1007/11676935_43
    Melkemi KE, Batouche M, Foufou S. MRF model-based approach for image segmentation using a chaotic MultiAgent system. In Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. p. 344-353. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11676935_43
    Melkemi, Kamal E. ; Batouche, Mohamed ; Foufou, Sebti. / MRF model-based approach for image segmentation using a chaotic MultiAgent system. Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. pp. 344-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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