A NEW FAST FUZZY EDGE DETECTOR

Abstract

Edge Detection is an important step in many of the image processing techniques. A wide variety of operators have been proposed for edge detection in past. But Most of the edge detection methods available in the literature are gradient based which further apply thresholding to find the final edge map in an image. In this paper, a novel method based on fuzzy logic is proposed for edge detection in gray images without using the gradient and thresholding techniques. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The technique begins by fuzzifying the gray values of pixel into two fuzzy variables namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map obtained so far may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, edge map is improved by finding some left out edge pixels by defining new membership function for the pixels which have their entire 8-neighbourhood pixel classified as white. The proposed method is compared with some of the existing standard edge detector operators available in the literature. The quantitative analysis of the proposed method is given in term of entropy value. Entropy value signifies the information content in image.