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A Fuzzy Cooperative Approach to Resolve the Image Segmentation Problem

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  • Hamza Abdellahoum

    (LSI Laboratory, Department of Computer Science, University of Science and Technology Houari Boumediene, Algeria)

  • Abdelmajid Boukra

    (LSI Laboratory, Department of Computer Science, University of Science and Technology Houari Boumediene, Algeria)

Abstract

The image segmentation problem is one of the most studied problems because it helps in several areas. In this paper, the authors propose new algorithms to resolve two problems, namely cluster detection and centers initialization. The authors opt to use statistical methods to automatically determine the number of clusters and the fuzzy sets theory to start the algorithm with a near optimal configuration. They use the image histogram information to determine the number of clusters and a cooperative approach involving three metaheuristics, genetic algorithm (GA), firefly algorithm (FA). and biogeography-based optimization algorithm (BBO), to detect the clusters centers in the initialization step. The experimental study shows that, first, the proposed solution determines a near optimal initial clusters centers set leading to good image segmentation compared to well-known methods; second, the number of clusters determined automatically by the proposed approach contributes to improve the image segmentation quality.

Suggested Citation

  • Hamza Abdellahoum & Abdelmajid Boukra, 2021. "A Fuzzy Cooperative Approach to Resolve the Image Segmentation Problem," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 12(3), pages 188-214, July.
  • Handle: RePEc:igg:jsir00:v:12:y:2021:i:3:p:188-214
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