Salima Ouadfel

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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 is based on(More)
In this paper, we present a novel method for unsupervised image segmentation. Image segmentation is cast as a clustering problem, which aims to partition a given set of pixels into a number of homogenous clusters, based on a similarity criterion. The clustering problem is a difficult optimization problem for two main reasons: first the search space of the(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)