自适应邻域测试的图像误匹配点剔除算法  

Research on Algorithm of Eliminating Mismatching Points Based on Adaptive Neighborhood Test

作　　者：郭恩会 张小国[2] 陈刚[1] GUO Enhui;ZHANG Xiaoguo;CHEN Gang(School of Mechanical Engineering,Southeast University,Nanjing 210018,China;School of Instrument Science and Engineering,Southeast University,Nanjing 210018,China)

机构地区：[1]东南大学机械工程学院,南京210018 [2]东南大学仪器科学与工程学院,南京210018

出　　处：《计算机工程与应用》2019年第14期198-202,265,共6页Computer Engineering and Applications

基　　金：“十二五”科技支撑计划课题(No.2012BAJ23B02)

摘　　要：针对图像特征点暴力匹配与比率测试得到的匹配点对在数量与正确率不能兼顾的情况,提出了一种基于自适应邻域测试的误匹配点对剔除算法。对特征点进行暴力匹配与高阈值的比率测试得到初始匹配点集,对初始匹配点对中的每个匹配特征点进行自适应邻域测试,测试出初始匹配点集中明显的误匹配点对并将之剔除,达到只剔除误匹配而不会误剔除正确匹配的效果。实验结果表明,在保证正确率不降低的前提下,该算法获取的匹配点对数量比原算法多3成以上,并且该算法对图像旋转、尺度缩放具有较好通用性。Aiming at the situation that the matching pair of image feature point brute-match and ratio test can’t take into account both the quantity and the correct rate, an algorithm based on adaptive neighborhood test is proposed to eliminate the mismatched pair. Firstly, the ratio of violent matching and high threshold of feature points is tested to obtain the initial matching point set, then adaptive neighborhood testing is performed on each matching feature point in the initial matching point pair, it tests out the obvious mismatch points in the initial matching points and removes them, achieves the effect of removing only false matches without mistakenly removing the correct match. The experimental results show that the num- ber of matching pairs obtained by this algorithm is more than 30% higher than the original algorithm, on the premise that the correct rate is not reduced, and the algorithm has good versatility for image rotation and scaling.

关 键 词：图像处理 特征点匹配 误匹配 自适应邻域 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]