An Efficient Method of Edge Detection using Fuzzy Logic

Various Edge detection algorithms have been proposed in the literature for extracting the edges from the image. But after emerging the fuzzy logic concept, a lot of Researcher of image processing has been shifted towards the fuzzy logic and its applicability in the field of image processing. This paper presents a fuzzy rule base algorithm, in MATLAB environment, which is capable of detecting edges of an input image by scanning it throughout using a 2*2 pixel window efficiently from the gray scale images. Fuzzy inference system designed has four inputs, which corresponds to four pixels of instantaneous scanning matrix, one output that tells whether the pixel under consideration is “low”, “medium” or “high” pixel. Rule base comprises of seven rules, which classify the target pixel. Also, a Graphical User Interface (GUI) in MATLAB has been designed to aid the loading of the image, and to display the resultant image at different intermediate levels of processing. Threshold level for the image can be set from the slider control of GUI. Main feature of the algorithm is that it has been designed by the smallest possible mask with less number of rules i.e. 2*2 with seven rules unlike 3*3 or bigger masks found in the literature.