一种参数自适应的Harris角点检测算法

A parameter adaptive Harris corner detection algorithm

针对用固定高斯函数参数σ值及人为设定阈值时角点检测不准确的问题,提出一种σ自适应的Harris算法。在选定区域内设置多个σ值提取Harris预选角点,对非极大值抑制时,采用自适应阈值获得预选角点;对不同σ值生成的预选角点响应函数R采用约束准则筛选出最大值,从而提取出有效的角点,去除伪角点。实验结果表明,本算法具有较好的图像角点检测性能,能够获得更多有效角点和更少伪角点。

Corner detection is not accurate with a fixed Gaussian function parameterσand artificially set value,so aσparameter adaptive Harris algorithm is put forward.Gaussian function parameterσis set in the selected region to extract preselected Harris corner.and in the process of non maximal suppression,the adaptive threshold is used to obtain the preselected angular point.The constraint criterion is adopted to choice the maximum from eachσparameter generation of the preselected angular point response function R,the effective corners are extracted and the false corners are removed.The experimental results show that this algorithm has better image corner detection performance,and can get more effective corners and less false corners.