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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15680

Title: A Modified Particle Swarm Optimization Algorithm for Automatic Image Clustering
Authors: Salima Ouadfel
Mohamed Batouche
Abdelmalik Taleb-Ahmed
Keywords: image clustering. Particle swarm optimization. Automatic
Issue Date: 2010
Abstract: 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 dynamically using mutation operators. Experimental results on real images demonstrate that the proposed algorithm is able to extract the correct number of clusters with denser and more compactness clusters. The results demonstrate that ACMPSOoutperforms other optimization algorithms.
URI: http://hdl.handle.net/123456789/15680
Appears in Collections:College of Computer and Information Sciences

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