Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Comparison of Traditional Approach for Edge Detection with Soft Computing Approach

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 11
Year of Publication: 2014
Neha S. Joshi
Nitin S. Choubey

Neha S Joshi and Nitin S Choubey. Article: Comparison of Traditional Approach for Edge Detection with Soft Computing Approach. International Journal of Computer Applications 96(11):17-23, June 2014. Full text available. BibTeX

	author = {Neha S. Joshi and Nitin S. Choubey},
	title = {Article: Comparison of Traditional Approach for Edge Detection with Soft Computing Approach},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {11},
	pages = {17-23},
	month = {June},
	note = {Full text available}


Image processing supports applications in different fields such as medicine, astronomy, product quality, industrial applications. Edge detection plays important role in segmentation and object identification process. Soft computing approach represents a good mathematical framework to deal with uncertainty of information. The performance of the well-known edge detectors, like Canny, Sobel, etc, depends critically on the choice of the input parameters. Threshold decision is the key uncertainty in the edge detection algorithms. In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical morphology and multiscale wavelet transform is proposed. The proposed method overcomes the limitation of wavelet based edge detection and mathematical morphology based edge detection in noisy images. Method present will give best results for noisy images.


  • Rafael C. Gonzalez, Richard E. Woodes, and Steven L. Eddins, DIGITAL IMAGE PROCESSING, published by Pearson Education (Singapore) Pvt. Ltd
  • Dr. H. B. Kekre and Ms. Saylee M. Gharge, "Image Segmentation using Extended Edge Operator for Mammography Images", International Journal on Computer Science and Engineering, Vol. 02, No. 04, 2010, 1086-1091.
  • Y. Becerikli and H. EnginDemiray, Alternative Neural Network Based Edge Detection, Neural Information Processing, Vol. 10, Nos. 8-9, Sept. 2006.
  • M. Egmont-Petersen, D. de Ridder, H. Handels, Image processing with neural networks – a review, Vol. 35, No. 10, pp. 2279-2301,2002.
  • J. Canny, "A Computational Approach to Edge Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence. 8 (6), pp- 679-687, 1986.
  • M. Zhao, A. M . N . Fu, H. Yan, "a technique of three Level Thresholding Based on Probablity Partition an Fuzzy 3-Partition", IEEE Trans on Fuzzy System,vol. 9, no. 3, pp. 469-479, June 2001
  • S. Wang, F. Ge, T. Liu, "Evaluating Edge Detection through Boundary Detection", Department of Computer Science and Engineering, Univercity of south Carolina,Columbia, Usa, 2006.
  • W. zhang, J, Kang, "Edge detection based on fusion of wavelet transform and mathematical morphology", IEEE, 2009.
  • Serra, J. : 'Image analysis and mathematical morphology' (Academic, New York, 1982)
  • Samet, H. , and Webber, R. E. : 'Hierarchical data structures and algorithms for computer graphics. I. Fundamentals', IEEE Trans. Comput. Graph. Appl. , 1988, 8, (3), pp. 48–68)
  • Yang Yong, Huang Shuying, Modified Pal and King algorithm for fuzzy edge detection, Chinese Journal of Scientific Instrument, Vol. 29, No. 9, 2008, pp. 1918-1922.
  • Zhang Jinping, Lian Yongxiang, Dong Linfu, A new method of fuzzy edge detection based on Gauss function, International Conference on Computer and Automation Engineering (ICC AE), Vol. 4, 2010, pp. 559-562.
  • Fabrizio Russo "Edge Detection in Noisy ImagesUsing Fuzzy Reasoning" IEEE Instrumentation and Measurement Technology Conference St. Paul, Minnesota, USA, May 18-21, 1998 Edge Detection in Noisy ImagesUsing Fuzzy Reasoning.
  • Yan Ha "Method of edge detection based on Non-linear cellular Automata" 978-1-4244-2114-5/08/$25. 00 © 2008 IEEE
  • Gao Qinqing ,Chen Dexi ,ZengGuangping and He Ketai* "Image Enhancement Technique Based On Improved PSO Algorithm" 978-1-4244-8756-1/11/$26. 00_c 2011 IEEE
  • Mrs. Abhradita Deepak Borkar and Mr. MithileshAtulkar "Detection of Edges Using Fuzzy Inference System" International Journal of Innovative Research in Computer and Communication Engineering Vol. 1, Issue 1, March 2013
  • S. Mallat, W. L. Hwang, "Singularity detection and processing with wavelet," IEEE Tran. Inform. Theory, Vol. 38, No. 2, March, 1992.
  • S. Wenchang, S. Jianshe, Z. Lin, "Wavelet Multi-scale Edge Detection Using Adaptive threshold," IEEE, 2009.
  • L. Zhang, P. Bao, "Edge detection by scale multiplication in wavelet domain," Elsevier Science B. V. Pattern Recognition letters 23, pp. 1771-1784, 2002.
  • C. Q. Zhan, L. J. Karam, "Wavelet-based adaptive image denoising with edge preservation," IEEE, 2003.
  • E. Brannock, M. Weeks, "Edge detection using wavelets," ACM SE, March, 2006.
  • Masrour Dowlatabadi and Jalil Shirazi," Improvements in Edge Detection Based on Mathematical Morphology and Wavelet Transform using Fuzzy Rules" World Academy of Science, Engineering and Technology Vol:5 2011-10-22
  • ArpitSinghal, Mandeep Singh "Speckle Noise Removal and Edge Detection Using Mathematical Morphology" International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-1, Issue- 5, November 2011
  • Mehul Thakkar and Prof. Hitesh Shah "Edge Detection Techniques Using Fuzzy Thresholding" 978-1-4673-0126-8/11/$26. 00c 2011 IEEE
  • Zhao Yuqian, Gui Wei-hua, Chen Zhencheng, Tang Jing-tian, and Li Ling-yun. , "Medical Images Edge Detection Based on Mathematical Morphology", ", Proceedings of the IEEE Engineering in Medicine and Biology 27th Annual International Conference Shanghai, China, PP: 6492– 6495, 2005.
  • J Patel and et al. , "Fuzzy Inference based Edge Detection System using Sobel and Laplacian of Gaussian Operators" ICWET'11, ACM 978-1-4503-0449-8, pp 694-697, February 25–26, 2011
  • Abdallah A. Alshennawy, and Ayman A. Aly, "Edge Detection in Digital Images Using Fuzzy Logic Technique", World Academy of Science, Engineering and Technology, 2009, pp-178-186.
  • Pushpajit A. Khaire and Nileshsingh V. Thakur. "Image Edge Detection based on Soft Computing Approach" International Journal of Computer Applications (0975 – 8887) Volume 51– No. 8, August 2012
  • Pushpajit A. Khaire and Nileshsingh V. Thakur, "A Fuzzy Set Approach for Edge Detection" International Journal of Image Processing (IJIP), Volume (6): Issue (6), 2012.
  • L. R. Liang, C. G. Looney," Competitive fuzzy edge detection", Applied Soft Computing, Vol. 3, No. 2, 2003, pp. 123-137.
  • RajasekaranS and G A VijayalakshmiPai, Neural Networks, Fuzzy Logic and Genetic Algorithms-Synthesis and Applications, Prentice-Hall of India, 2003
  • SamanSinaie, AfshinGhanizadeh, and SitiMariyam Shamsuddin and EmadaldinMozafariMajd "A Hybrid Edge Detection Method Based on Fuzzy Set Theory and CellularLearning Automata" 2009 International Conference on Computational Science and Its Applications 978-0-7695-3701-6/09 $25. 00 © 2009 IEEE DOI 10. 1109/ICCSA. 2009. 19
  • Dhirajkumar Patel and S A More "Edge Detection Technique by Fuzzy Logic and Cellular Learning Automata using Fuzzy Image Processing" 978-1-4673-2907-1/13/$31. 00 ©2013 IEEE
  • Dhirajkumar Patel and S A More "An enhanced approach for EDGE image enhancement using fuzzy set theory and cellular learning automata (CLA)" World Journal of Science and Technology 2012, 2(4):158-162
  • Hamid R. Ezhyosh, "Fast Fuzzy Edge Detection" 0-7803-7461˜/02 pp. 239-242 IEEE 2002
  • Raman Maini and HimanshuAggarwal, "Study and Comparison of Various Image Edge Detection Techniques", International Journal of Image Processing (IJIP), Volume (3), 2010, pp-1-12.
  • Li Fang, Weiren Shi, Shuhan Chen," Fuzzy reasoning-based edge detection method using multiple features" WSEAS TRANSACTIONS on COMPUTERS E-ISSN: 2224-2872 Issue 11, Volume 11, November 2012
  • Y. Xu et al, " Wavelet transform domain filter: a spatially selective noise filtration technique", IEEE Trans on image processing, vol. . 3, pp. 747- 758, 1994.
  • Chaganti, Venkata Ravikiran, "Edge Detection of Noisy Images using 2-d Discrete Wavelet Transform" (2005). Electronic Theses, Treatises and Dissertations. Paper 3948.