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

Authors:
Kamal E. Melkemi;Mohamed Batouche;Sebti Foufou
Affiliations:
Computer Science Department, University of Biskra, Biskra, Algeria;LIRE laboratory, University of Constantine, Constantine, Algeria;LE2I laboratory, UFR sciences, University of Burgundy, Dijon, France
Venue:
WILF'05 Proceedings of the 6th international conference on Fuzzy Logic and Applications
Year:
2005

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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.