An Edge Detection Algorithm based on Fuzzy Logic

Edges characterize boundaries and are therefore considered for prime importance in image processing. Edge detection filters out useless data, noise and frequencies while preserving the important structural properties in an image. The proposed method adopts fuzzy reasoning in order to extract edges. Here the scanning of an image using the windowing technique takes place which is subjected to a set of fuzzy conditions. A 2*2 scanning mask is used and the Fuzzy inference system designed has four inputs, which corresponds to four pixels of the scanning matrix, one output that tells whether the pixel under consideration is "edge" or "non- edge" pixel. In this paper, we evaluate the performance of a fuzzy inference system in edge detection. The results for images with high contrast variation are compared to those obtained with the linear Sobel operator.