6533b85efe1ef96bd12bfc03
RESEARCH PRODUCT
MRF Model-Based Approach for Image Segmentation Using a Chaotic MultiAgent System
Mohamed BatoucheKamal Eddine MelkemiSebti Foufousubject
Markov random fieldbusiness.industryComputer scienceMulti-agent systemCrossoverChaoticInitializationImage segmentationComputingMethodologies_ARTIFICIALINTELLIGENCEComputer Science::Multiagent SystemsNonlinear Sciences::Chaotic DynamicsComputerSystemsOrganization_MISCELLANEOUSIterated conditional modesSegmentationArtificial intelligencebusinessAlgorithmdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2006-01-01 |