摘要
SUSAN角点检测算法以抗噪声性能强,运算速度快而被广泛运用于特征点的提取。传统的SUSAN算法的灰度差阈值固定,不能有效去除伪角点,并且在大尺寸模板检测下耗时多。针对这些问题,从模板尺寸对检测结果的影响出发,讨论不同尺寸模板的检测效果,从而提出一种变换模板提取特征点的方法。采用一种自动选取阈值的方法实现了阈值的自动选取,使用能量分布法和像素投影法去除了伪角点。结果显示,该方法缩短了检测时间,并且提高了检测准确度。
SUSAN corner detection algorithm is widely used in feature extraction for its good performance in noise resistance and fast calculation. The traditional SUSAN algorithm has a fixed brightness difference threshold and can＇t eliminate the fake corner well. The traditional algorithm is time - consuming when large - size mask is used. Aiming at those problems, the relationship between mask size and detection results is discussed, and an algorithm using alternate mask is proposed. A method that can select the threshold automatically is adopted. The energy distribution and pixel projection methods are used to eliminate the fake corners. The experimental results show that this improved algorithm reduces the detection time and improves the detection accuracy.
出处
《现代电子技术》
2009年第20期42-44,共3页
Modern Electronics Technique
基金
国家高技术研究发展专项经费资助项目(2007AA01Z301)
关键词
特征提取
SUSAN算法
能量分布
像素投影
feature extraction
SUSAN algorithm
energy distribution
pixel projection
