CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Combining Cellular Automata and Particle Swarm Optimization for Edge Detection

by Safia Djemame, Mohamed Batouche
journal cover thumbnail

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.

References
  1. Rosin P. L. "Training Cellular Automata for Image Processing," IEEE Transactions on Image Processing, Vol. 15, No. 7 (2006) 2076-2087.
  2. Hernandez G. , Hermann J. J. , "Cellular Automata for Elementary Image Enhancement" Graphical Models and Image Processing (GMIP) , vol. 4, N° 58, (1996) 82-89.
  3. Wongthanavazu S. , Lursinsap C. , "A 3-D CA Based Edge Operator for 3-D Images" , The proceedings of the 11th IEEE int. Conference on Image Processing (IEEE-ICIP 2004), IEEE press, (2004) 235-238.
  4. Rosin P. L, Image Processing Using 3-state Cellular Automata, Computer Vision and Image Understanding , Elsevier vol. 114, (2010), 790-802.
  5. Slatnia S. , Batouche M. , Melkemi K. E, Evolutionary Cellular Automata Based-Approach for Edge-Detection , International workshop on Fuzzy Logic and Applications WILF 2007, vol LNAI 4578, (2007) 404-411.
  6. Kazar O. , Slatnia S. , Evolutionary Cellular Automata forIimage Segmentation and Noise Filtering Using Genetic Algorithms, Journal of Applied Computer Science and Mathematics, n° 10 (5), (2011) 33-40
  7. Batouche M. , Meshoul S. , Abbassene A. , On Solving Edge Detection by Emergence, International Conference on Industrial , Engineering and other Applications of Applied Intelligent Systems, vol. LNAI 4031, (2006) 800-808.
  8. Bull L. , A. Adamatzky, A learning classifier system approach to the identification of cellular automata, J. Cellular Automata 2 (1) (2007) 21–38.
  9. Terrazas G. , Siepmann P. , Kendall G. , Krasnogor K. O, An Evolutionary Methodology for the Automated Design of Cellular Automaton-based Complex Systems, J. Cellular Automata 2 (1) (2007) 77–102.
  10. Djemame S. , Djidel O. , Batouche M. , Image Segmentation Using Continuous Cellular Automata, IEEE catalog, ISBN 978-1-4577-0905-0, (2011) 94-97.
  11. Shan Y. , Yang A. , "Applications of Complex Adaptive Systems" IGI publishing, Hershey, NewYork, ISBN-13:978-1-59904-962-5, 2008
  12. Shan Y. , Yang A. , « Intelligent Complex Adaptive Systems », IGI publishing, Hershey, NewYork, ISBN-13: 978-1-59904-719-5, 2008
  13. Wolfram S. , "A New Kind of Science", Wolfram media. ISBN 1-57955-008-8, 2002
  14. Kennedy J. , Eberhart R. C, A Discrete Binary Version of the Particle Swarm Algorithm, In: Proceedings of IEEE Conference on Systems, Man, and Cybernetics, (1997) 4104-4109.
  15. Shi Y. , Eberhart R. , A Modified Particle Swarm Optimizer, In: Proceedings of IEEE International Conference on Evolutionary Computation, Anchorage, Alaska,1998, pp. 66–73.
  16. Wang Z. , Bovik A. C. , Sheikh H. R. , Simoncelli E. P. , Image Quality Assessment: from Error Visibility to Structural Similarity, IEEE Trans. Image Process. 13 (4) (2004) 600–612.
Index Terms

Computer Science
Information Sciences

Keywords

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

Powered by PhDFocusTM