Title
A Modified Particle Swarm Optimization Algorithm for Automatic Image Clustering
Author
-
s
Salima Ouadfel, Mohamed Batouche, and Abdelmalik Taleb
-
Ahmed
Contact
Info
batouche@ksu.edu.sa
Department
Software
Engineering
Major
Citation
proceedings of the International Symposium on Modelling and Implementation of Complex
Systems, MISC’2010, pp. 49
-
57
Year of
Publication
2010
Publisher
Sponser
Type of
Publication
Conference
ISSN
URL/DOI
http://www.umc.edu.dz/vf/images/misc/session1B/8
-
1B
-
paper3
-
Salima
-
Ouadfel.pdf
Full Text
(Yes, No)
Yes
Key words
image clustering. Particle swarm optimization. Automatic
clustering.
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 resu
lts demonstrate that ACMPSOoutperforms other optimization
algorithms.
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