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A Survey on Two Dimensional Cellular Automata and Its Application in Image Processing

Published on September 2014 by Deepak Ranjan Nayak, Prashanta Kumar Patra, Amitav Mahapatra
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International Conference on Emergent Trends in Computing and Communication
Foundation of Computer Science USA
ETCC - Number 1
September 2014
Authors: Deepak Ranjan Nayak, Prashanta Kumar Patra, Amitav Mahapatra
e03812ef-34b5-4073-88cf-e41976b7a416

Deepak Ranjan Nayak, Prashanta Kumar Patra, Amitav Mahapatra . A Survey on Two Dimensional Cellular Automata and Its Application in Image Processing. International Conference on Emergent Trends in Computing and Communication. ETCC, 1 (September 2014), 78-87.

@article{
author = { Deepak Ranjan Nayak, Prashanta Kumar Patra, Amitav Mahapatra },
title = { A Survey on Two Dimensional Cellular Automata and Its Application in Image Processing },
journal = { International Conference on Emergent Trends in Computing and Communication },
issue_date = { September 2014 },
volume = { ETCC },
number = { 1 },
month = { September },
year = { 2014 },
issn = 0975-8887,
pages = { 78-87 },
numpages = 10,
url = { /proceedings/etcc/number1/17907-1422/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Emergent Trends in Computing and Communication
%A Deepak Ranjan Nayak
%A Prashanta Kumar Patra
%A Amitav Mahapatra
%T A Survey on Two Dimensional Cellular Automata and Its Application in Image Processing
%J International Conference on Emergent Trends in Computing and Communication
%@ 0975-8887
%V ETCC
%N 1
%P 78-87
%D 2014
%I International Journal of Computer Applications
Abstract

Parallel algorithms for solving any image processing task is a highly demanded approach in the modern world. Cellular Automata (CA) are the most common and simple models of parallel computation. So, CA has been successfully used in the domain of image processing for the last couple of years. This paper provides a survey of available literatures of some methodologies employed by different researchers to utilize the cellular automata for solving some important problems of image processing. The survey includes some important image processing tasks such as rotation, zooming, translation, segmentation, edge detection, compression and noise reduction of images. Finally, the experimental results of some methodologies are presented.

References
  1. Ulam, S. 1963. Some Ideas and Prospects in Biomathematics. Annual Review of Biophysics and Bioengineering. pp. 277-292.
  2. Neumann, J. V. 1966. Theory of Self-Reproducing Automata. University of Illinois Press.
  3. Wolfram, S. 1984. Computation Theory of Cellular Automata. Commun. Math. Phys. pp. 15-57.
  4. Wolfram, S. 2002. A new kind of science. Wolfram Media, Inc.
  5. Gonzalez, R. C. and Woods, R. E. 2002. Digital Image Processing. Second Edition. Prentice-Hall.
  6. Khan, A. R. , Choudhury, P. P. , Dihidar, K. , Mitra, S. , Sarkar, P. 1997. VLSI architecture of cellular automata machine. Computers and Mathematics with Applications. 33(5). pp. 79-94.
  7. Chaudhuri, P. P. , RoyChowdhury, D. , Nandi, S. , Chattopadhyay, S. 1997. Additive Cellular Automata Theory and Applications, vol. 1. IEEE Computer Society Press, USA.
  8. Das, D. 2012. A Survey on Cellular Automata and its Application. Springer (CCIS 269). pp 753-762.
  9. Choudhury, P. P. , Nayak, B. K. , Sahoo, S. , Rath, S. P. 2008. Theory and Applications of Two-dimensional, Null-boundary, Nine-Neighborhood,Cellular Automata Linear rules. arXiv: 0804. 2346. cs. DM;cs. CC; cs. CV.
  10. Wongthanavasu, S. and Sadananda, R. 2003. A CA-based edge operator and its performance evaluation. Journal of Visual Communication and Image Representation. 14:83–96.
  11. Scarioni, A. and Moreno, J. A. 1998. Border detection in digital images with a simple cellular automata rule. In S. Bandini, R. Serra and F. S. Liverani (Eds. ). Cellular Automata: Research towards Industry.
  12. Chang, C. , Zhang, Y. , Gdong, Y. 2004. Cellular Automata for Edge Detection of Images. IEEE proceedings on Machine Learning and Cybernetics. 26-29.
  13. Rosin, P. L. 2006. Training Cellular Automata for Image Processing. IEEE Trans. Image Processing. Vol. 15. No. 7. pp. 2076–2087.
  14. Rosin, P. L. 2010. Image Processing using 3-state Cellular Automata. Computer Vision and Image Understanding. Vol. 114. pp. 790–802.
  15. Chen, ang. andhao, e. G. Z. Wang. Cellular automata modeling in edge recognition.
  16. Lee, M. A. and Bruce, L. M. 2010. Applying Cellular Automata to Hyperspectral Edge Detection. IEEE (IGARSS). 2202-2205.
  17. Kazar, O. and Slatnia, S. 2011. Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms. Journal of Applied Computer Science and Mathematics. 10 (5). 33-40.
  18. Djemame, S. and Batouche, M. 2012. Combining Cellular Automata and Particle Swarm Optimization for Edge Detection, International Journal of Computer Applications. vol. 57. No. 14. 16-22.
  19. Hong, W. , Hong-jie, Z. , Hua, W. 2004. Image Segmentation Arithmetic Based on Fuzzy Cellular Automata. Fuzzy Systems and Mathematics. No. 18. pp. 309-313.
  20. Zhang, K. , Li, Z. , Zhao, X. 2007. Edge Detection of Images based on Fuzzy Cellular Automata, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, IEEE.
  21. Patel, D. K. and More, S. A. 2013. Edge detection technique by fuzzy logic and Cellular Learning Automata using fuzzy image processing. IEEE conf. (ICCCI). pp. 1-6.
  22. Pradipta, M. and Chaudhuri, P. P. 2005. Fuzzy cellular automata for modeling pattern classifier. IEICE Trans Inf Syst. 88:691.
  23. Ziou, D. and Tabbone, S. 1998. Edge detection technique an overview. Pattern Recognition and Image Analysis 8 (4). pp. 537-559.
  24. Paul, K. , Chaudhury, D. R, Chaudhuri, P. P. 1999. Cellular Automata Based Transform Coding for Image Compression. Springer. pp. 269- 273.
  25. Safia, D. , Oussama, D. , Chawki, B. M. 2011. Image segmentation using continuous cellular automata, ISPS, IEEE conf. pp. 94-99.
  26. Nayak, D. R. , Sahu, S. K. , Mohammed, J. 2013. A Cellular Automata Based Optimal Edge Detection Technique using Twenty-Five Neighborhood Model. IJCA. vol. 84. No. 10. pp. 27-33.
  27. Mohammed, J. , Nayak, D. R. 2013. An Efficient Edge Detection Technique by TwoDimensional Rectangular Cellular Automata, arXiv:1312. 6370[cs. CV].
  28. Sadeghi, S. , Rezvanian, A. , Kamrani, E. 2012. An efficient method for impulse noise reduction from images using fuzzy cellular automata, International Journal of Elec. and Comm. pp. 772-779.
  29. Qadir, F. , Peer, A. M. A. , Khan, K. 2012. An Effective Image Noise Filtering Algorithm using Cellular Automata, IEEE conf. (ICCCI).
  30. Selvapeter,P. J. and Hordijk, W. 2009. Cellular automata for image noise filtering, IEEE conf. (NaBIC), 193-197.
  31. Maji, P. , Shaw, C. , Ganguly, N. , Sikhdhar, B. K. , Chaudhuri, P. P. 2003. Theory and Application of Cellular Automata for Pattern ClassificationFundamenta Informaticae, 58, pp. 321-354.
  32. Zhao, C. , Shi, C. , He, P. 2008. A Cellular Automaton for Image Compression, ICNC, IEEE conf. , pp. 397-401.
  33. Nandi, S. , Kar, B. K. , Pal Chaudhuri, P. 1994. Theory and Application of Cellular Automata in Cryptography. IEEE Transaction on Computers 43.
  34. Anghelescu, P. , Ionita, S. , Safron, E. 2008. FPGA Implementation of Hybrid Additive Programmable Cellular Automata. In: Eight International Conference on Hybrid IntelligentSystems. IEEE.
  35. Kundu, A. , Pal, A. R. , Sarkar, T. , Banarjee, M. , Guha, S. K. , Mukhopadhayay, D. 2008. Comparative Study on Null Boundary and Periodic Boundary NeighbourhoodMulriple Attractor Cellular Automata for Classification. IEEE.
  36. Das, S. 2006. Theory and Applications of Nonlinear Cellular Automata in: VLSI Design. Ph. D Thesis, B. E. College.
  37. Seredynski, M. , Bouvry, P. 2005. Block Cipher Based on Reversible Cellular Automata. New Generation Computer.
  38. Ganguly, N. , Maji, P. , Das, A. , Sikdar, B. K. , Pal Chaudhuri, P. 2002. Characterization of Nonlinear Cellular Automata Model for Pattern Recognition. In: Pal, N. R. , Sugeno, M. (eds. ) AFSS 2002. LNCS (LNAI), vol. 2275, pp. 214–220. Springer.
  39. Mraz, M. , Zimic, N. , Lapanja, I. , Bajec, l. 2000. Fuzzy Cellular Automata: From Theory to Applications. IEEE.
  40. Khan, A. R. 1998. Replacement of some Graphics Routines with the help of 2D Cellular Automata Algorithms for Faster Graphics Operations, PhD thesis, University of Kashmir.
  41. Yin, L. , Yang, R. , Gabbouj, M. , Neuvo, Y. 1996. Weighted median filters: a tutorial, IEEE Trans Circuits Syst II: Anal Digit Signal Process, 43, 15792.
  42. Ko, S. J. and Lee, YH. 1991. Center weighted median filters and their applications to image enhancement, IEEE Trans Circuits Syst. , 38, 98493.
  43. Chen, T. and Wu, HR. 2001. Adaptive impulse detection using center-weighted median filters, IEEE Signal Process Lett. , 8, 13.
  44. Wang, Z. and Zhang, D. 1999. Progressive switching median filter for the removal of impulse noise from highly corrupted images, IEEE Trans Circuits Syst II: Anal Dig Signal Process, 46, 7880.
  45. Srivasan,K. S. and Ebenezer,D. 2007. A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises", IEEE SigmalPricessingLetter, Vol. 14, No. 3.
  46. Toh,K. and Isa, N. 2010. Noise adaptive fuzzy switching median filter for salt and pepper noise reduction", Signal Process Lett. IEEE, 17, 2814.
  47. Qadir F. , Shah, J. , Peer, M. A. , Khan, K. A. 2012. Replacement of graphics translations with two dimensional cellular automata, twenty five neighborhood model, International Journal of Computational Engineering and Management, Vol. 15, Issue 4, pp. 33-39.
Index Terms

Computer Science
Information Sciences

Keywords

Cellular Automata Linear Rule Edge Detection Noise Reduction Zooming Rotation Translation