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

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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