SUSAN角点检测算法稳定性改进研究  

Research on Improving Stability of SUSAN Corner Detection Algorithm

作　　者：侯明亮[1] 

机构地区：[1]淮海工学院计算机工程学院,江苏连云港222005

出　　处：《计算机与现代化》2010年第10期75-77,80,共4页Computer and Modernization

基　　金：江苏省自然科学基金资助项目(08KJD520013)

摘　　要：SUSAN算法在图像旋转和有噪声的情况下是比较稳定的角点检测方法,但也有漏检和误检的问题。针对其缺陷,提出改进的角点检测方法。改进的办法是将原方法的SUSAN核同值吸收区,替换为在响应圆域内与核像素点灰度值相同,且与核像素点邻接连通的区域。通过改进,避免了原方法漏检和误检的问题,仿真试验结果证明改进方法的正确性和有效性。Smallest univalue segment assimilating nucleus（SUSAN） is one of the most excellent methods which are robust to noise and less affected by rotation.However,it could not detect all the true corners and generate some false corners in some special case.To solve these problems,an improved SUSAN corner detector is proposed and its performance is compared with SUSAN corner detection.With the improved SUSAN,a corner point is judged based on gray level values of the pixels in a circular neighborhood of the nucleus which is the same as the conventional SUSAN,however,the improved SUSAN calculates the number of the pixels in the univalue adjoining nucleus and connected segment rather than calculate the number of the pixels of univalue nucleus in the neighborhood.Due to this improvement,the improved SUSAN can not only inherit the main merits but also avoid the fatal fault of conventional SUSAN.Experimental results demonstrate that the improved SUSAN corner detection is accurate and efficient.

关 键 词：角点检测 SUSAN 核 

分 类 号：TN911.73[电子电信—通信与信息系统]