CFP last date
20 January 2025
Reseach Article

Edge Detection in Digital Images Corrupted by Salt and Pepper Noise using Adaptive Neuro-Fuzzy Inference System (ANFIS)

by Karishma Bhardwaj, Palvinder Singh Mann
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 12
Year of Publication: 2013
Authors: Karishma Bhardwaj, Palvinder Singh Mann
10.5120/12548-9130

Karishma Bhardwaj, Palvinder Singh Mann . Edge Detection in Digital Images Corrupted by Salt and Pepper Noise using Adaptive Neuro-Fuzzy Inference System (ANFIS). International Journal of Computer Applications. 72, 12 ( June 2013), 36-41. DOI=10.5120/12548-9130

@article{ 10.5120/12548-9130,
author = { Karishma Bhardwaj, Palvinder Singh Mann },
title = { Edge Detection in Digital Images Corrupted by Salt and Pepper Noise using Adaptive Neuro-Fuzzy Inference System (ANFIS) },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 12 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number12/12548-9130/ },
doi = { 10.5120/12548-9130 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:37:45.792598+05:30
%A Karishma Bhardwaj
%A Palvinder Singh Mann
%T Edge Detection in Digital Images Corrupted by Salt and Pepper Noise using Adaptive Neuro-Fuzzy Inference System (ANFIS)
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 12
%P 36-41
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an Edge Detection technique for images corrupted by salt and pepper noise, which is based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). This proposed technique first of all filters out the noise by Noise Adaptive Fuzzy Switching Median Filter (NAFSMF) and then find the edges using proposed ANFIS based edge detector. The training pattern for edge detection is proposed to optimize the internal parameters of the ANFIS based edge detector. The edges are directly determined by the proposed ANFIS based edge detector. This proposed edge detector is then compared with popular edge detectors Sobel, Roberts, Prewitt on the basis of performance metrics PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error) and No. of Edges detected.

References
  1. Saket Bhardwaj, Ajay Mittal "A Survey on Various Edge Detector Techniques" Procedia Technology Elsevier ,Vol. 4,pp. 220 – 226,2012.
  2. Anubhuti Khare, Manish Saxena , Shweta Tiwari "Edge Detection Method for Image Segmentation – A Survey of Soft Computing Approaches" International Journal of Soft Computing and Engineering, Vol. 1, Issue. 4, pp. 174-178, September 2011.
  3. M. EminYuksel and M. TulinYildirim, "A Simple Neuro-Fuzzy Edge Detector for Digital Images Corrupted by Impulse Noise", Int. J. Electron. Commun. (AEU) Elsevier, Vol. 58, pp. 72–75, 2004
  4. M. EminYuksel, "Edge detection in noisy images by neuro-fuzzy processing", Int. J. Electron. Commun. (AEU) Elsevier, Vol. 61, pp. 82 – 89, 2007
  5. Abdallah A. Alshennawy, And Ayman A. Aly, "Edge Detection In Digital Images Using Fuzzy Logic Technique", In proceedings of World Academy of Science Engineering and Technology, Vol. 51 , pp. 178-186, 2009.
  6. Begol, Moslem and Maghooli,Keivan "Improving Digital Image Edge Detection by Fuzzy Systems", In proceedings of World Academy of Science, Engineering and Technology, Vol. 57, pp. 76-79, 2011.
  7. Lei Zhang, Mei Xiao, Jian Ma and Hongxun Song "Edge Detection by Adaptive Neuro-Fuzzy Inference System" 2nd International Conference on Image and Signal Processing,(IEEE),2009.
  8. Hamed Mehrara, Mohammad Zahedinejad and Ali Pourmohammad "Novel Edge Detection Using BP Neural Network Based on Threshold Binarization", Second International Conference on Computer and Electrical Engineering (IEEE), pp. 408-412, 2009.
  9. Aborisade, D. O "Novel Fuzzy logic Based Edge Detection Technique" International Journal of Advanced Science and Technology, Vol. 29, pp. 75-82, April, 2011.
  10. Shashank Mathur, Anil Ahlawat "Application Of Fuzzy Logic On Image Edge Detection" International Conference "Intelligent Information and Engineering Systems" INFOS, Varna, Bulgaria, 2008.
  11. Constantina Raluca Mihalache and Mitic?a Craus "Neural Network and Fuzzy Membership Functions Based Edge Detection for Digital Images" 16th International Conference on System Theory, Control and Computing,(IEEE),2012.
  12. Jappreet Kaur, Manpreet Kaur, Poonamdeep Kaur, Manpreet Kaur "Comparative Analysis of Image Denoising Techniques" International Journal of Emerging Technology and Advanced Engineering, Vol. 2, Issue 6, pp. 296-298, June 2012
  13. Mohsen Sharifi, Mahmoud Fathy, Maryam Tayefeh Mahmoudi "A Classified and Comparative Study of Edge Detection Algorithms" Proceedings of the International Conference on Information Technology: Coding and Computing, (IEEE) 2002.
  14. Om Prakash Verma ,Madasu Hanmandlu ,Ashish Kumar Sultania ,Anil Singh Parihar "A novel fuzzy system for edge detection in noisy image using bacterial foraging" Multidim Syst Sign Process Springer, Vol. 24. pp. 181–198,2013
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Neuro-Fuzzy Inference System (ANFIS) Edge Detection Salt and Pepper noise Sobel Roberts Prewitt