基于概率密度梯度的边缘检测  

Edge Detection Based on Density Gradient

作　　者：孙达[1] 刘家锋[1] 唐降龙[1] 

机构地区：[1]哈尔滨工业大学计算机学院,哈尔滨150001

出　　处：《计算机学报》2009年第2期299-307,共9页Chinese Journal of Computers

基　　金：国家自然科学基金(60672090)资助~~

摘　　要：提出了一种新颖的基于概率密度梯度的边缘检测算法.新算法通过估计图像中各像素点的概率密度梯度得到图像的概率密度梯度场,然后根据图像的边缘点在概率密度梯度场中具有两侧梯度方向相反的特性实现边缘检测.与现有的算法相比,新算法检测得到的边缘点具有尺度不变性,并可以直接从图像中检测出具特定尺寸区域的轮廓,完好地保持物体的形状.This paper proposes a new image edge detection algorithm based on the density gradient. The image pixels are taken as some sample points in the image sample space, and the image can be transformed into the density gradient field by density gradient estimation. In the density gradient field, all the density gradients point against the image edge. According this property, the new algorithm selects the points around which all the gradients point against them as the edge points. Comparing with other detectors, the edges detected by the new algorithm are invariant to the detection scales, and the object＇s boundary can be directly selected out by the new detector as their size.

关 键 词：边缘检测 概率密度梯度 图像处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]