New Technique of Edge Detection based on FIS
Er. Shikha Bharti, Lectruer, Department of ECE, Model Institute of Engineering & Technology, Jammu India.
Manuscript received on 12 November 2014 | Revised Manuscript received on 22 November 2014 | Manuscript Published on 30 November 2014 | PP: 51-55 | Volume-4 Issue-6, November 2014 | Retrieval Number: F1864114614/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Edge detection of images is an important aspect in the field of image processing. Edges can be detected from the images by using various derivative edge detection methods, such as Sobel operator, Prewitt operator, Roberts operator, Laplacian operators and Canny operators .With these different approaches the edges are detected but somehow false edges are also detected or some important edges are missed due to the presence of noise. Therefore a new technique of artificial intelligence called fuzzy inference system is used in order to reduce these types of effects.. This paper presents a novel edge detection algorithm based on fuzzy inference system.The proposed approach uses a 3×3 sliding window with eight inputs and the center pixel as the output . ,then the pixel values of window are subjected to various fuzzy rules designed . Based on these set of rules the output of fuzzy is decided whether that particular pixel is an edge or not .Moreover the developed algorithm is compared with sobel ,prewitt etc to find the respective mean square error and peak signal to noise ratio of images containing noise.
Keywords: Image Processing, Fuzzy Logic, Fuzzy Image Processing, MATLAB, Edge Detection, Fuzzy Rules, Noise.
Scope of the Article: Fuzzy Logics