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I 2 ABSTRACT In this paper, we propose a new algorithm for image segtnentation based on the Markov Random Field (MRF) and the Ant Colony Optimization (ACO) metaheuristic. The underlying idea is to take advantage from the ACO nietaheuristic characteristics and the MRF theory to develop a novel ngents-based approach to segment an image. The proposed algorithm(More)
In order to implement clustering under the condition that the number of clusters is not known a priori, we propose in this paper ACPSO a novel automatic image clustering algorithm based on particle swarm optimization algorithm. ACPSO can partition image into compact and well separated clusters without any knowledge on the real number of clusters. ACPSO used(More)
In this paper, we present a new automatic image clustering algorithm based on a modified version of particle swarm optimization algorithm. ACMPSO clustering algorithm can partition image into compact and well separated clusters without any knowledge on the real number of clusters. It uses a swarm of particles with variable number of length, which evolve(More)
Les objets pédagogiques et les métadonnées qui leur sont attachées sont depuis déjà un certain temps au coeur de nombreux travaux tant dans les institutions d'enseignement que dans les organismes de standardisation. Ces travaux étant assez coûteux en temps et ils visent à permettre l'interopérabilité et la réutilisation de ces objets dans différents(More)