Chaotic MultiAgent system approach for MRF-based image segmentation

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 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.

Original languageEnglish (US)
Title of host publicationISPA 2005 - Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis
PublisherIEEE Computer Society
Pages268-273
Number of pages6
ISBN (Print)953184089X, 9789531840897
DOIs
StatePublished - 2005
EventISPA 2005 - 4th International Symposium on Image and Signal Processing and Analysis - Zagreb, Croatia
Duration: Sep 15 2005Sep 17 2005

Publication series

NameImage and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium
Volume2005

Other

OtherISPA 2005 - 4th International Symposium on Image and Signal Processing and Analysis
CountryCroatia
CityZagreb
Period9/15/059/17/05

Keywords

  • Chaotic system
  • Genetic Algorithms
  • Image Segmentation
  • MRF
  • MultiAgent Systems

ASJC Scopus subject areas

  • Engineering(all)

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