CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Soft Computing Techniques for Edge Detection Problem: A state-of-the-art Review

by Naveen Singh Dagar, Pawan Kumar Dahiya
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 12
Year of Publication: 2016
Authors: Naveen Singh Dagar, Pawan Kumar Dahiya
10.5120/ijca2016908615

Naveen Singh Dagar, Pawan Kumar Dahiya . Soft Computing Techniques for Edge Detection Problem: A state-of-the-art Review. International Journal of Computer Applications. 136, 12 ( February 2016), 28-34. DOI=10.5120/ijca2016908615

@article{ 10.5120/ijca2016908615,
author = { Naveen Singh Dagar, Pawan Kumar Dahiya },
title = { Soft Computing Techniques for Edge Detection Problem: A state-of-the-art Review },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 12 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 28-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number12/24207-2016908615/ },
doi = { 10.5120/ijca2016908615 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:55.975139+05:30
%A Naveen Singh Dagar
%A Pawan Kumar Dahiya
%T Soft Computing Techniques for Edge Detection Problem: A state-of-the-art Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 12
%P 28-34
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Edge is an abrupt change that occurs in an image. Edge detection is one of the most prevalent problems in image processing. Edge Detection is the approach used most frequently for segmenting images based on abrupt changes in intensity. It is a concept that covers a number of fields in today’s environment. In this paper, a state-of-the-art review of the conventional Edge Detection Techniques is presented. The paper also presents a state-of-the-art review of Soft Computing Techniques such as Fuzzy Logic, Genetic Algorithm, Neural Networks, Evolutionary Computation, Swarm Intelligence etc. for Edge Detection Problem. Further, an analysis of the review is also presented.

References
  1. Akanksha Bali, Shailendra Narayan Singh, “A Review on the Strategies & Techniques of Image Segmentation”, International Conf. on Intelligent Computing Applications, 2015, IEEE. DOI 10.1109/ICICA.2014.53,113-120.
  2. N. Anandakrihnan, S. Santhosh Baboo, “An Evaluation of Popular Edge Detection Techniques in Digital Image Processing”, International Conference on Intelligent Computing Applications (ICICA), 2014 IEEE DOI 10.1109/ICICA.2014.53,213-217.
  3. P. Thakur, N. Madaan, “A Survey of Image Segmentation Techniques,” International Journal of Research in Computer Application and Robotics, ISSN: 2320-7345, Vol. 2, Issue 4, pp.158-165, April 2014.
  4. G.K. Seerha, R. Kaur, “A Study of Automatic Image Segmentation Techniques,” ISSN: 2277 128X, 0018- , Vol. 3, Issue 2, pp. 435-437, Feb 2013.
  5. M. Weingart, O. Vascan, “Image Segmentation Processing-some Techniques and Experimental Results,” 978-1-4799-2442-4/13 ©2013 IEEE.
  6. Prakash B Metre, K. R. Radhika, Gowrishankar, “Survey of Soft Computing Techniques for Joint Radio Resource Management,” 978-1-4799-0356-6/13 ©2013 IEEE, pp. 1109-1112.
  7. H. P. Narkhede, "Review of Image Segmentation Techniques”, International Journal of Science and Modern Technology, ISSN: 2319-6386, Vol.1, Issue 8, pp. 54-61, 2013.
  8. W. Khan, “Survey of Image Segmentation Techniques,” Journal of Image and Graphics, Vol. 1, No. 4, pp. 166-170, Dec 2013.
  9. Jamil A. M. Saif, Ali Abdo Mohammed Al-Kubati, Abdultawab Saif Hazaa, and Mohammed Al-Moraish, “Image Segmentation Using Edge Detection and Thresholding,” The 13th International Arab Conference on Information Technology, ACIT'2012 Dec.10-13 ISSN: 1812-0857.
  10. Kritika Sharma, Chandrashekhar Kamargaonkar, and Monisha Sharma, PhD “An Improved Image Segmentation Algorithm Based on Otsu Method,” International Journal of Engineering Research & Technology (IJERT), Vol. 1 Issue 6, August - 2012 ISSN: 2278-0181.
  11. A. Khanna, Dr. M. Shrivastava, “Unsupervised Techniques of Segmentation on Texture Images: A Comparison,” 978-1-4673-1318-6/12 ©2012 IEEE.
  12. Naveen Dagar, Rakhi Antil, Pawan Kumar Dahiya, “Improvised Canny Edge Detector & Performance Metric of Edge Detector Using WPR (White Pixel Ratio),” IOSR Journal of Engineering, Vol. 3, No. 7, July 2013.
  13. Shivani Rathi, Pawan Kumar Dahiya, Pardeep Kumar, “Edge Detection using Memetic Algorithm,” International Journal for Research in Applied Science and Engineering Technology, Vol. 1, No.3, pp. 42-52, October 2013.
  14. Pawan Kumar Dahiya, “Recent Trends in Evolutionary Computation,” Ph.D. dissertation, ECE Dept., M. D. Univ., Rohtak, Haryana, India, 2011.
  15. N. Sharma, M. Mishra, M. Shrivastava, “Colour Image Segmentation,” International Journal of Scientific and Technology, ISSN: 2277-8616, Vol.1, Issue 4, pp. 9-12, May 2012.
  16. Fahd Mohsen, Mohiy hadhoud, Kamel Mostafa, Khalid Amin, “A New Image Segmentation method based on new Particle Swarm Optimization,” International Arab Journal of Information Technology, Vol. 9, No. 5, September 2012.
  17. Anand Gupta, Ravi Kumar Dalal, Rahul Gupta, Pulkit Wadhwa, “DGW-Canny: An Improvised Version of Canny Edge Detector,” International Symposium on Intelligent signal Processing & Communication System (ISPACS), Dec.7-9, 2011.
  18. Mr. Salem Saleh Al-Amri, Dr. N.V. Kalyankar and Dr. Khamitkar S.D, “Image Segmentation by using Edge Detection,” International Journal on Computer Science and Engineering, Vol. 02, No. 03, 2010, 804-807.
  19. Shriram K Vasudevan, “Automotive Image Processing Technique,” International Journal of Engineering Science and Technology, Vol. 2 (7), 2010, 2632-2644, ISSN 0975-5462.
  20. K. Padma Vasavi, N. Udaya Kumar, E. V. Krishna Rao and M. Madhavi Latha “A Novel Statistical Thresholding in Edge Detection Using Laplacian Pyramid and Directional Filter Banks” Proceedings of the World Congress on Engineering and Computer Science, October 2010 Vol. I ISSN: 2078-0966.
  21. K. K. Singh, A. Singh, “A Study of Image Segmentation Algorithms for Different Types of Images,” International Journal of Computer Science Issues, ISSN: 1694-0784, Vol.7, Issue 5, 2010.
  22. B.C. Wei, R. Mandava, "Multi objective Optimization Approaches in Image Segmentation- the Direction and Challenges", ICSRS Publication, Vol.2, pp. 41-65, 2010.
  23. R. Szeliski, Computer Vision: Algorithms and Applications, 1st edition, Springer, pp. 265-303, 2010.
  24. S.S Varshney, N.Rajpal, R. Purwar, “Comparative study of Image Segmentation Techniques and Object Matching using Segmentation,” International Conference on Methods and Models in Computer Science, 2009.
  25. N. Senthilkumaran and R. Rajesh, “Edge Detection Techniques for Image Segmentation - A Survey of Soft Computing Approaches”, International Journal of Recent Trends in Engineering, Vol.1, No.2, May 2009, pp.250-254.
  26. N. Senthilkumaran and R. Rajesh, “A Study on Edge Detection Techniques for Image Segmentation”, International Conference on Mathematics and Computer Science, (ICMCS-2009), January 2009, pp. 255-259.
  27. Amir Atapour Abarghouei, Afshin Ghanizadeh and Siti Mariyam Shamsuddin, “Advances of Soft Computing Methods in Edge Detection,” IJASCA, vol 1, No 2, Nov. 2009.
  28. Susmita Ghosh, Swarnajyoti Patra, and Ashish Ghosh, “An unsupervised context-sensitive change detection technique based on modified self-organizing feature map neural network,” International Journal of Approximate Reasoning 50 (2009) 37–50 January 2008.
  29. H. Zhang, J. E. Fritts, S. A. Goldman, “Image Segmentation Evaluation: A Survey of unsupervised methods,” Computer Vision and Image Understanding, pp. 260-280, 2008.
  30. D. Kelkar, S. Gupta, "Improved Quadtree Method for Split Merge Image Segmentation", Emerging Trends in Engineering and Technology, 978-0-7695-3267-7/08 ©2008 IEEE, pp. 44-47, 2008.
  31. Jing Tian, Weiyu Yu, and Shengli Xie, “An Ant Colony Optimization Algorithm for Image Edge Detection”, IEEE, 78-1-4244-1823-7/08/$25.00, 2008.
  32. N. Senthilkumaran and R. Rajesh, “Edge Detection Techniques for Image Segmentation - A Survey,” Proceedings of Intl. Conf. on Managing Next Generation Software Applications, (MNGSA-08), Dec. 2008, pp.749-760.
  33. Mantas Paulinas and Andrius Usinskas, “A Survey of Genetic Algorithms Applicatons for Image Enhancement and Segmentation,” Information Technology and Control, Vol.36, No.3, 2007, pp.278-284.
  34. Mantas Paulinas and Andrius Usinskas, “A Survey of Genetic Algorithms Applicatons for Image Enhancement and Segmentation,” Information Technology and Control, Vol.36, No.3, 2007, pp.278-284.
  35. Kanchan Deshmukh and G. N. Shinde, “An adaptive neuro-fuzzy system for color image segmentation,” J. Indian Inst. Sci., vol. 86, Sept.-Oct.2006, pp.493-506.
  36. M. Gandomkar, M. Vakilian and M. Ehsan, "A Combination of Genetic Algorithm and Simulated Annealing for Optimal Distributed DG Allocation in Distributed Networks," Proceedings of the IEEE Electrical and Computer Engineering Canadian Conference, 2005.
  37. M. Abdulghafour, “Image segmentation using Fuzzy logic and genetic algorithms,” Journal of WSCG, vol.11, no. 1, 2003.
  38. H.D Chung, Y. Sun, “A Hierarchial Approach to Color Image Segmentation, "1057-7149/00 © 2000 IEEE, Vol. 9, No. 12, pp. 2071-2083.
  39. J. Shi and J. Malik, "Normalized Cuts and Image Segmentation”, IEEE.
  40. Raj Kumar Mohanta, Binapani Sethi, “A Review of Genetic Algorithm application for Image Segmentation,” Raj Kumar Mohanta et al, Int. J. Computer Technology & Applications, Vol 3 (2), 720-723, 2000.
  41. Jander Moreira and Luciano Da Fontoura Costa, “Neural-based color image segmentation and classification using self-organizing maps”,Anais do IX SIBGRAPI, 1996, pp.47-54.
  42. Andreas Koschan, “A Comparative Study On Color Edge Detection”, Reprint from Proceedings 2nd Asian Conference on Computer Vision ACCV´95, Singapore, 5-8 December 1995, Vol. III, pp. 574-578.
  43. Suchendra M. Bhandarkar, Yiqing Zhang and Walter D. Potter “An Edge Detection technique using genetic algorithm-based optimization” Vol. 27, no. 9, pp. 1159-1180, March 1994.
Index Terms

Computer Science
Information Sciences

Keywords

Edge Hysteresis Threshold Methods Image Segmentation Otsu Fuzzy Logic Soft Computing Genetic Algorithm Swarm Intelligence Evolutionary Computation Neural Network.

Powered by PhDFocusTM