The proposed method breaks the color image into its individual color component and then fuzzy filter based canny Edge detection technique is applied. This technique depends on the fuzzy rule-based system using 2 X 2 window mask which is used to modify membership value of the image in different fuzzy sets (which means it will smoothen the image), and this filtered image is given as input to canny edge detection technique and finally after this morphological processing is used. The Performance Parameter becomes better by combining Fuzzy and Canny Edge Detection and also morphological operations. The results were compared with other edge detection techniques like interactive image segmentation by maximal similarity based region merging (MSRM) and Image segmentation using transition region. Therefore it is evident that the developed Algorithm provides Improved Performance parameters for detecting the edge against the wide range of Applications.

Image Segmentation, Fuzzy-canny Method, Morphological Operation, Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR)

[1] Dingwen Zhang, Junwei Han, Lu Jiang, Senmao Ye, and Xiaojun Chang, “Revealing Event Saliency in Unconstrained Video Collection”, IEEE Transactions on Image Processing, Vol. 26, No. 4, April 2017
[2] A.G. Rudnitskii, M.A. Rudnytska, “Segmentation and Denoising of Phase Contrast MRI Image of the Aortic Lumen Via Fractal and Morphological Processing”, 37th International Conference on Electronics and Nanotechnology (ELNANO), 2017 IEEE.
[3] D. Chudasama, T. Patel, S. Joshi, G. Prajapati “Survey on Various Edge Detection Techniques on Noisy Images” , IJERT International Journal of Engineering Research & Technology ISSN: 2278-0181 Vol. 3 Issue 10, October- 2014.
[4] Maini, Raman, and Himanshu Aggarwal, "Study and comparison of various image edge detection techniques", International Journal of Image Processing (IJIP), Issue 3, no. 1, Pp. 1-11, 2009.
[5] Er. Komal Sharma, Er. Navneet Kaur, “Comparative Analysis of Various Edge Detection Techniques”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 12, December 2013.
[6] Ur Rehman Khan, K. Thakur “An Efficient Fuzzy Logic Based Edge Detection Algorithm for Gray Scale Image”, International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 8, August 2012).
[7] S. Patel, P.Trivedi, V. Gandhi and G. Prajapati, “2D Basic Shape Detection Using Region Properties” IJERT International Journal of Engineering Research & Technology, Vol. 2 Issue 5, May-2013.
[8] Mrs. A. Borkar, Mr. M.Atulkumar “Detection of Edges Using Fuzzy Inference System”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 1, Issue 1, March 2013.
[9] T. Gajpal, Mr. S. Meshram “Edge Detection Technique Using Hybrid Fuzzy logic Method”, IJERT International Journal of Engineering Research & Technology, Vol. 2 Issue 2, Febuary-2013.
[10] M. L Comer, E. J. Delp “Morphological operations for color image processing” electronic imaging spiedigitallibrary.
[11] B. Baets, E. Kerre, M. Gupta “Fundamentals of Fuzzy Mathematical Morphology Part 1 Basic concepts” Overseas Publishers Association.
[12] R. Haralick and L. Shapiro Computer and Robot Vision, Vol. 1, Chap. 5, Addison-Wesley Publishing Company, 1992.