摘要
提出了一种新方法用于提取用于匹配计算的可靠特征点——凹凸(ridges/troughs)边界上的特征点沿凹凸边界上的高曲率点,凹凸边界线的交叉点以及图像表面上的最小值点.实验表明,与传统的沿阶跃边界提取特征点的方法相比,该算法提取出的特征点可靠性更高,大大减少了误匹配率.在凹凸边界点检测阶段,只需要对图像扫描一遍即可,而凹凸边界交叉点和高曲率点的提取要消耗更多的时间.因此本方法可用于对特征点可靠性要求很高但数量需求不大的情况.
An approach of extracting reliable feature points alone ridges/troughs is presented. The feature points including high curvature points along ridge/trough, cross points of ridges/troughs and minimum points in image surface. Experimental result shows that the approach is more robust as compare with the traditional approach of extracting feature points along step edges and reduce the possibility of the appearance of outliers. Scanning the image for just one time will get the points along ridges/troughs, but computing the cross points of ridges/troughs and the high curvature points along ridge/trough will cost more time. So this approach is available for applications that require only a small set of highly reliable feature points.
出处
《光子学报》
EI
CAS
CSCD
北大核心
2006年第2期312-315,共4页
Acta Photonica Sinica
关键词
特征点
图像匹配
凹凸边界
Feature point
Image matching
Ridges/troughs edge
