Chaotic multiagent system approach for MRF-based image segmentation

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.