Fast fuzzy edge detection algorithm based on classifier
基于分类器的图像模糊边缘检测快速算法

A new fast fuzzy edge-detection algorithm was presented by analyzing and improving Pal-King fuzzy edge detection method. Firstly, this algorithm enhanced the original image in fuzzy way and designed one classifier according to its and its 8-neighbor gray levels; secondly, classified each pixel into the proper edge class by computing and comparing its greatest fuzzy truth of membership; lastly, thinned the edge pixels detected and omit the noise edge pixels. This fast algorithm not only abandoned the complex iterative calculation of Pal-King method, but also conquered missing edge information which is low gray level and can detect various details by setting various parameters. Finally experimental results showed that this method improves the Pal-King algorithm efficiently and its calculation speed was about 20 times faster than Pal-King algorithm.