图像局部方向均值边缘检测算法

Novel Image Edge Detection Algorithm Based on Local Orientation Average

根据图像边缘形成的光学原理,将图像边缘分为斜坡形边缘和三角形边缘,提出了一种新的基于方向均值的图像边缘检测方法。该方法以图像像素点为中心,沿不同方向将邻域内的像素分割成两个半圆,分别计算出半圆内像素的样本均值及其差值,再根据均值差值最大值和最小值的方向与两种不同边缘之间的关系,设计边缘幅度响应函数,判断边缘类型,计算边缘幅度响应值和方向,结合漏检概率设计了边缘检测评价函数,并利用评价函数分析平滑尺寸与邻域半径之间的关系。实验结果表明,本文算法具有较好的检测精度,在一定程度上抑制了噪声对边缘检测的影响。

According to the principle of the image edge formation, the image edges consist of the triangle edge and the ramp edge. Based on orientation average, this paper proposes a new image edge detection algorithm which segments the neighborhood of the center pixel into two semicircles along different direction and then calculates the difference of the mean values of the two semicircles. With the directions of maximum difference and the minimum difference, an edge magnitude response function is designed to judge the edge type of the pixel, the triangle edge or the ramp edge. For inhibiting the effects of the noise, this method adopts Gauss-smooth pre-filter which inhibits the noise in images effectively. The edge-detection fitness function combining omission ratio is designed. By utilizing the fitness function, the algorithm analyzes the relationship of the size of the smoothing filter and the radius of the neighborhood of the center pixel. Experimental results show that the algorithm has good precision, and to a certain extent, inhibits the effects of noise on edge detection.