一种精确的图像边缘检测法

边缘检测是图像处理与识别中最基础的内容之一,一幅图像就是一个信息系统,其大量信息是由它的轮廓边缘提供的。边缘提取与检测在图像处理中占有很重要的地位,其算法的优劣直接影响着所研制系统的性能。现有诸多边缘检测的方法各有其特点,同时也都存在着各自的局限性和不足之处,因此图像的边缘检测这个领域还有待于进一步的改进和发展。提出一种用迭代算法求图像分割最佳阈值和运用数学形态学的腐蚀算法实现轮廓提取相结合的图像边缘精确检测算法,从理论上分析了该方法的精确性和较强抗干扰能力,给出此算法的实例并与传统的边缘检测算子Laplacian-Gauss算子、Prewitt算子和Canny算子的检测结果进行了比较。

An accurate image edge detection method

Edge detection is one of the most basical technology of the domain of image processing and identification.An image is an information system.Edges offer a great deal of information.The technology of edge distilling and detection is more consequent in the domain of image processing,the accuracy of which influences the whole capability of the developed system directing.There are many arithmetic ways of edge detection.Nowadays,all have different features and shortcomings.Therefore,the domain of image processing needs to be improved fatherly.This paper presents a new edge detection method which gives out the best threshold of image segmentation based on iterative arithmetic and distills edge by erode arithmetic ways of math morphologic.This paper analyzes this method having high accuracy and strong capacity of anti-jamming in theory.This paper also gives out the test and compares the edge detection efficiently among Laplacian-Gauss arithmetic operators,Prewitt arithmetic operators and Canny arithmetic operators.