应用特征点的彩色图像边缘检测算法

传统的边缘检测技主要通过全局图像扫描，寻找大于设定阈值的点，然后进行伪边缘点的筛除以及断裂边缘的连接。本文提出了一种基于图像特征点检测与边缘生长相结合的边缘检测算法。该方法将边缘看成一种特殊的区域，使用图像分割中区域生长的原理来生成边缘。首先在图像中寻找特征点作为边缘生长的种子点，然后以边缘梯度响应和区域相似度为生长规则，以层序遍历方式得到图像边缘。仿真结果显示，本文提出的算法可以减少参与比较的像素个数，去孤立的边缘，保证边缘的连续性和单一像素宽度。 

Edge Detection for Color Image Based on Feature Points

Traditional edge detection techniques consist of following steps: searching for the points whose gradient value is larger than the intended threshold by global image scanning, removing pseudo edge points and connecting disconnected edge. To get a more excellent performance of edge detection and expand the adaptability of the basic technology, a novel edged detection algorithm is proposed in this paper, which combines feature point detection and edge growing together to improve the detection of edge in image. In this method, edges itself are treated as a special kind of region, and classical region growing method is employed to generate edges. First, feature point detection is adopted to find out points with outstanding characteristics; these points are then used as seeds in order to trace edges in the similar way as region growing. During region growing, the response of edge gradient and the similarity among regions are used to check growing direction. Simulation results show this method can reduce the number of pixels involved in comparison, remove isolated edges and ensure the detected edge is continuous and with a single pixel width.