CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Modified Edge Detection Technique using Fuzzy Inference System

by Shaveta Arora, Amanpreet Kaur
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 22
Year of Publication: 2012
Authors: Shaveta Arora, Amanpreet Kaur
10.5120/6409-8757

Shaveta Arora, Amanpreet Kaur . Modified Edge Detection Technique using Fuzzy Inference System. International Journal of Computer Applications. 44, 22 ( April 2012), 9-12. DOI=10.5120/6409-8757

@article{ 10.5120/6409-8757,
author = { Shaveta Arora, Amanpreet Kaur },
title = { Modified Edge Detection Technique using Fuzzy Inference System },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 22 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number22/6409-8757/ },
doi = { 10.5120/6409-8757 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:36:12.584293+05:30
%A Shaveta Arora
%A Amanpreet Kaur
%T Modified Edge Detection Technique using Fuzzy Inference System
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 22
%P 9-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Edge detection of real world images is a challenging task. To extract the edges from the images, derivative edge detection operators or gradient operator, such as Sobel operator, Prewitt operator, Roberts operator, and Laplacian operators ,Canny operators are commonly used for which 3x3 mask is used. Different approaches have been used earlier for detecting edges that have some advantages and disadvantages like false edges are detected, some important edges are missed noise around the corners etc. So, in order to reduce these types of effects; special fuzzy inference system are used and the output of fuzzy system will decide whether that particular pixel is a part of edge or not. This paper presents a new edge detection algorithm based on fuzzy inference system. Fuzzy Image Processing is applied in combination with traditional operators used so far. Then fuzzy system will decide for each pixel using different sets of fuzzy rules.

References
  1. Russo, F. : Edge detection in noisy images using fuzzy reasoning. IEEE Transactions on Instrumentation and Measurement 47 (1998), 1102–110.
  2. Pratt, W. : Digital image processing. California: John Wiley and Sons, 1991.
  3. El-Kham, S. ; Ghaleb, I. ; El-Yamany, N. : Fuzzy edge detection with minimum fuzzy entropy criterion. IEEE MELECON 2002, Egypt, 2002.
  4. R. Gonzalez and R. Wood, Digital Image Processing, Addison – Wesley, 1992.
  5. Sonka, M. ; Hlavac, V. ; Boyle, R. : Image processing, analysis and machine vision. Paci?c Grove, California: Brooks/Cole Publishing Company, 1998.
  6. Umbaugh, S. : Computer vision and image processing. USA: Prentice Hall, Inc. , 1998.
  7. Schalkof, R. : Digital image processing and computer vision. Canada: John-Wiley and Sons Inc. , 1989.
  8. R. Wang, L. Gao, S. Yang, and Y. Liu, "An Edge detection method by combining fuzzy logic and neural networks", Machine Learning and Cybernetics, 7(2005) 4539-4543, 18-21, Aug 2005
  9. Hamid R. Tizhoosh, Fuzzy ImageProcessing: Introduction in Theory and Practice, Springer-Verlag,1997
  10. T. J. Ross, Fuzzy Logic with Engineering Applications, McGraw-Hill, New York (2008).
  11. Marr D. and Hildreth E. C. Theory of edge detection, Proc. of royal society of London. B207,1980,187-217
  12. Canny, J. F. , "A computational approach to edge detection", IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6), 1986, pp. 679-698.
  13. Shashank Mathur, Anil Ahlawat, "Application Of Fuzzy Logic In Image Detection", International Conference "Intelligent Information and Engineering Systems" INFOS 2008, Varna, Bulgaria, June-July 2008
  14. Yinghua Li, Bingqi Liu, and Bin Zhou, "The Application of Image Edge Detection by using Fuzzy Technique", in Conference " Electronic Imaging and Multimedia Technology", November 2004
  15. Yasar Becerikli1 and Tayfun M. Karan, "A New Fuzzy Approach for Edge Detection", Computational Intelligence and Bio inspired Systems" , June 2005.
  16. Cristiano Jacques Miosso, Adolfo Bauchspiess, "Fuzzy Inference System Applied to Edge Detection in Digital Images", in the proceedings of the V Brazilian Conference.
  17. Yüksel ME, "A hybrid neuro-fuzzy filter for edge preserving restoration of images corrupted by impulse noise," IEEE Trans Image Processing, 2006,15(4):928–36, on Neural Networks pp. 481–486, April , 2001.
  18. S. El-Khamy, N. El-Yamany, and M. Lotfy, "A Modified Fuzzy Sobel Edge Detector," Seventeenth National Radio Science Conference (NRSC'2000), February 22-24, Minufia, Egypt, 2000.
  19. L. Liang and C. Looney, "Competitive Fuzzy Edge Detection," Applied Soft Computing, (3), 2003, pp. 123-137.
  20. Mamta Juneja, Parvider Singh Sandhu, "Performance Evalution of Edge Detection Techniques for Images in Spatial Domain", International Journal of Computer Theory and Engineering, vol. 1,No. 5, 2009.
  21. J. See, M. Hanmandlu, and S. Vasikarla. , "Fuzzy-based parameterized gaussian edge detector using global and local properties", In I. C. Society, editor, Proceedings of the International Conference on Technology: Coding and Computing, 2005, pages 101–106.
  22. Alshennawy Abdallah A. and Ayman A. Aly. , "Edge detection in digital images using fuzzy technique", World Academy of Science, Engineering and Technology. vol. 51, 2009, pp. 78-186.
  23. Hu L. , Cheng H. D. and Zang M. A high performance edge detector based on fuzzy inference rules. An International Journal on Information Sciences, vol. 177,Nov 2007, no. 21, pp. 4768-4784.
  24. Tao, C. W. et al(1993), "A Fuzzy if-then approach to edge detection", Proc. of 2nd IEEE intl. conf. on fuzzy systems, pp. 1356–1361.
  25. Li, W. (1997), Recognizing white line markings for vision-guided vehicle navigation by fuzzy reasoning, Pattern Recognition Letters, 18: 771–780.
  26. M. N. Mahani, M. K. Moqadam, H. N. pour, and A. Bahrololoom, "Dynamic Edge Detector Using Fuzzy Logic," CSISS' 2008, Sharif University of Technology, Kish, 2008, (In Persian).
Index Terms

Computer Science
Information Sciences

Keywords

Edge Detection Fuzzy Logic Fuzzy Inference System

Powered by PhDFocusTM