摘要
基于自适应阈值的改进MIC算法首先根据图像角点的分布特性,引入自适应阈值的FAST检测算子遴选出候选角点,从而有效缩小了角点检测范围;其次,根据自适应灰度阈值大小对候选角点进行分类;最后,根据分类结果,使用不同模板以及阈值的MIC算法对候选角点进行筛选,以获得最佳匹配角点.实验结果验证了该算法的有效性和可行性.
In this paper,an improved MIC algorithm based on adaptive threshold is addressed based on the problems above.To begin with,according to the distribution characteristics of corners,the algorithm Introduced FAST detection operator which based on adaptive threshold and then select the candidate corners,which narrows the scope of corner detection.Besides,candidate corners are classified according to adaptive gray level threshold.Finally,the best match corners are selected by using different templates and threshold MIC algorithm in accordance with the classification results.The experimental results verify the feasibility and effectiveness of the algorithm.
出处
《微电子学与计算机》
CSCD
北大核心
2015年第5期79-83,共5页
Microelectronics & Computer
