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Reseach Article

Combining Cellular Automata and Particle Swarm Optimization for Edge Detection

by Safia Djemame, Mohamed Batouche
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 57 - Number 14
Year of Publication: 2012
Authors: Safia Djemame, Mohamed Batouche
10.5120/9182-3602

Safia Djemame, Mohamed Batouche . Combining Cellular Automata and Particle Swarm Optimization for Edge Detection. International Journal of Computer Applications. 57, 14 ( November 2012), 16-22. DOI=10.5120/9182-3602

@article{ 10.5120/9182-3602,
author = { Safia Djemame, Mohamed Batouche },
title = { Combining Cellular Automata and Particle Swarm Optimization for Edge Detection },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 14 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 16-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number14/9182-3602/ },
doi = { 10.5120/9182-3602 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:00:26.070013+05:30
%A Safia Djemame
%A Mohamed Batouche
%T Combining Cellular Automata and Particle Swarm Optimization for Edge Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 14
%P 16-22
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cellular Automata can be successfully applied in image processing. In this paper, we propose a new edge detection algorithm, based on cellular automata to extract edges of different types of images, using a totalistic transition rule. The metaheuristic PSO is used to find out the optimal and appropriate transition rules set of cellular automata for edge detection task. This combination increases the efficiency of the algorithm, and ensures its convergence to an optimal edge as shown in various experiments. Comparisons are made with standard methods (Canny) and other algorithms based on Cellular Automata and Genetic Algorithms. Obtained results are promising.

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Index Terms

Computer Science
Information Sciences

Keywords

Cellular automata Edge detection Complex systems Metaheuristics Particle swarm optimization Rule Optimization