Ant Colonies For MRF-Based Image Segmentation
نویسندگان
چکیده
Résumé: This paper presents HACSEG, a new ant algorithm for the image segmentation based on the Markov Random Field (MRF) and a modified version of the Ant Colony System algorithm coupled with a local search. HACSEG algorithm differs from other ant algorithms proposed for image segmentation, in the way that each artificial ant is associated with a particular partition that is modified using pheromone trails and heuristic information unlike to build a completely new partition using a iterative constructive process. The new partitions found by ants are then optimized using a local search algorithm. Pheromone trails are updated according to the quality of the partitions found by the best ant. A diversification phase is also used to diversify the search. The experimental results presented outperforms those obtained with other methods. . Mots clés: Image segmentation, Clustering, Markov Random Field, Ant Colony System., local search.
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