International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 8, No. 6, 8 Nov. 2016
Cover page and Table of Contents: PDF (size: 1146KB)
An Analysis of Fuzzy and Spatial Methods for Edge Detection
Full Text (PDF, 1146KB), PP.62-68
Views: 0 Downloads: 0
Author(s)
Pushpa Mamoria
1,*
Deepa Raj
1
Index Terms
Image segmentation, Edge, Threshold, Fuzzy method
Abstract
An image segmentation is an area in which image is subdivided into sub-regions for extracting characteristics of images which will help to analysis in various applications. For getting accuracy sharp changes of intensity is an important issue which is known as edge detection. In this paper various spatial edge detection methods and fuzzy based edge detection method has described and spatial edge detection methods and fuzzy if-then-else are compared to know which method will be more suitable to find edges for the enhancement of images.
Cite This Paper
Pushpa Mamoria, Deepa Raj, "An Analysis of Fuzzy and Spatial Methods for Edge Detection", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.8, No.6, pp.62-68, 2016. DOI:10.5815/ijieeb.2016.06.08
Reference
[1]R. C. Gonzalez and R. E. Woods. “Digital Image Processing,” 3rd ed. Prentice Hall, 2009.
[2]Jang, J.-S. R., C. T. Sun, and E. Mizutani, “Neuro-fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence,” Prentice-Hall, Upper Saddle River, NJ, 1997.
[3]J. F. Canny,“A computational approach to edge detection,” IEEE Trans. On Pattern Analysis and Machine Intelligence. 8(6), 679/698, 1986.
[4]V. K. Madasu, S.Vasikarla, “Fuzzy edge detection in biometric systems,” 36th Applied Imagery Pattern Recognition Workshop, IEEE, 2007.
[5]D. Marr, and E.C. Hildreth, “Theory of edge detection,” Proc. Of the Royal Society of London, 187/217, 1980.
[6]M.Hanmandlu, J.See, and S.Vasikarla, “Fuzzy edge detector using entropy optimization”,Proc. ITCC, 665/670, 2004.
[7]Y.-S. Chen, Y.-M. Chang, J.-C. Lin, “Comparing Intuitionistic Fuzzy Set Theory Method and Canny Algorithm for Edge Detection to Tongue Diagnosis in Traditional Chinese Medicine”, Proc. Of the International conference of Information Application (ICCIA 2012), 2012.
[8]T. Chaira, and A.K. Ray, “A new measure using intuitionistic fuzzy set theory and its Application to edge detection,” Applied Soft Computing, vol. 8-2, March, 2008, pp. 919- 927,doi:10.1016/j.asoc.2007.07.004, 2008.
[9]T. Chaira, “A novel Intuitionistic fuzzy-C means clustering algorithm and its application to medical images,” Applied Soft Computing, vol.11-2, Mar. 2011, pp. 1711-1717, doi:10.1016/j.asoc.2010.05.005, 2011.
[10]P. R. Possa, S. A. Mahmoudi, NaimHarb, C. Valderrama, “A Multi-Resolution FPGA- Based Architecture for Real-Time Edge and Corner Detection”, IEEE Transactions on Computers, January 2013.
[11]S. E. El-Khamy, I. Ghaleb, N. A. El-Yamany, “Fuzzy edge detection using minimum entropy”, in Proceedings of 11th Mediterranean Electrotechnical Conference MELECON, Cairo, Egypt, 2002.
[12]Ho Kenneth, H.L., and Ohnishi, N., FEDGE—fuzzy edge detection by fuzzy categorization and classification of edges, in Fuzzy Logic in Artificial Intelligence, JCAI’95 Workshop, Selected Papers, pp. 182–196, 1995.
[13]Khamy, E.L. et al., Modified Sobel fuzzy edge detector, in Proceedings of 17th National Radio Science Conference (NRSC 2000), C32-1-9, Minui a, Egypt, 2000.
[14]L. A. ZADEH, “Fuzzy sets”, Information and control 8, 338-353, 1965.
[15]K. Pal and R. A. King, “Image Enhancement using Fuzzy Set”, Electronics Letters, Vol. 16, No. 10, May 1980.
[16]P. Mamoria, D. Raj, “An Analysis of Images Using Fuzzy Contrast Enhancement Techniques”, 3rd 2016 International Conference on Computing for Sustainable Global Development, INDIACom-2016(IEEE Conference ID: 37465), BVICAM, New Delhi, India.
[17]S. K. Dubey, S. Panday, “Measurement of Usability of Office Application Using a Fuzzy Multi-Criteria Technique”, IJITCS, MECS Publisher, Vol. 7, No 4, march 2015.