曲率统计角点检测方法

Curvature Statistic Corner Detection

角点检测是图像处理领域的一个基础问题。本文提出了一种新的基于曲率的角点检测方法,称为曲率统计方法,该方法检测图像中具有最大曲率的边缘作为角点。首先使用Canny边缘检测得到二值化的图像边缘,然后跟踪边缘,对边缘的每一点在其邻域内采用统计方法得到中心点的大致曲率,由此来判断中心点是否为角点。该方法对噪声有很强的鲁棒性。实验结果表明该方法对角点的检测和定位更加准确。

Corner detection is a basic task in the field of image processing. This paper proposes a new corner detection method based on the curvature computing, called Curvature Statistic (CS) method. The edge points which have the maxima of absolute curvature are defined as corners, so curvature of every edge point is computed in CS. The first step is to use Canny edge detector to extract edges of original image, then compute the curvature of every edge point using a statistic method in the neighborhood. When we get the curvature of the point, we can judge whether it is a corner point or not. This method is very robust to noise. In the section of the experimental comparison we can see that CS performs good, and that most corners are detected and the localization of each corner point is more accuracy.