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A Comparison of Evolutionary Algorithms: PSO, DE and GA for Fuzzy C-Partition

by Assas Ouarda, M. Bouamar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 10
Year of Publication: 2014
Authors: Assas Ouarda, M. Bouamar
10.5120/15919-5028

Assas Ouarda, M. Bouamar . A Comparison of Evolutionary Algorithms: PSO, DE and GA for Fuzzy C-Partition. International Journal of Computer Applications. 91, 10 ( April 2014), 32-38. DOI=10.5120/15919-5028

@article{ 10.5120/15919-5028,
author = { Assas Ouarda, M. Bouamar },
title = { A Comparison of Evolutionary Algorithms: PSO, DE and GA for Fuzzy C-Partition },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 10 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 32-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number10/15919-5028/ },
doi = { 10.5120/15919-5028 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:12:24.269295+05:30
%A Assas Ouarda
%A M. Bouamar
%T A Comparison of Evolutionary Algorithms: PSO, DE and GA for Fuzzy C-Partition
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 10
%P 32-38
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The fuzzy c-partition entropy technique for threshold selection is one of the best image thresholding techniques, but its complexity increases with the number of thresholds. In this paper, the selection of thresholds (fuzzy parameters) was seen as an optimization problem and solved using particle swarm optimization (PSO), differential evolution (DE), genetic (GA) algorithms. The proposed fast approaches have been tested on many images. For example, the processing time of four-level thresholding using PSO, DE and GA is reduced to less than 0. 4s. PSO, DE and GA show equal performance when the number of thresholds is small. When the number of thresholds is greater, the PSO algorithm performs better than GA and DE in terms of precision and robustness. But the GA algorithm is the most efficient with respect to the execution time.

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Index Terms

Computer Science
Information Sciences

Keywords

Entropy Histograms Optimization Particle swarm optimization Thresholding Fuzzy c-partition Differential Evolution Algorithm

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