基于Pal算法改进的边缘模糊检测算法比较分析

A Comparative Analysis of the Improved Fuzzy Edge Detection Algorithm

边缘检测是图像分析和计算机视觉中最重要的内容之一。80年代中期,从图像所具有的不确定性是由模糊性引起的观点出发,首次将模糊集理论引入图像的边缘检测中,提出了图像边缘检测模糊算法(简称Pal算法)。与传统的空间域微分算法相比,该算法具有较好的抑噪、边缘检测效果,但是此算法仍然存在不少缺陷。就三种改进的模糊算法从算法原理和检测效果上与传统的Pal算法进行比较分析,用以说明改进算法能取得更好的检测效果。

Edge detection is one of the most important contents of the image analysis and computer vision.In the mid-80 s,on the basis of the view that the uncertainty of image is resulted from fuzziness,we introduced the fuzzy set theory into the image edge detection,and proposed fuzzy edge detection algorithm（Referred to as Pal algorithm）.Compared with the traditional differential algorithm,this method has better noise suppression,edge detection results.However,it still has a lot of defects.This paper makes a comparative analysis of the algorithm and the tested effect to illustrate the better effect of the improved algorithm,