中国机械工程Issue(12)：1655-1658,4.DOI:10.3969/j.issn.1004-132X.2014.12.018
高精度尺度不变特征点匹配方法及其应用
Precise Scale Invariant Feature Matching and Its Application
摘要
Abstract
In object detection and localization system based on local feature matching ,the number of match and false match effects directly on localization accuracy .An improved SIFT matching algo-rithm was proposed to decrease false match and meanwhile kept the sufficient correct match number . After analyzing different match result with different match threshold in conventional SIFT feature match method ,an iterative strategy for adaptive dual-threshold for image match was presented .Then a geometry constrained model based on sparse but accurate match achieved with high threshold was es-tablish to eliminate false match in dense match set achieved with low threshold .Experimental results show that compared with other methods ,the proposed method has higher match accuracy which im-proves the performance of object detection and localization .关键词
特征匹配/SIFT 特征/目标检测/目标定位Key words
feature match/scale invariant feature transform(SIFT ) feature/object detection/object localization分类
信息技术与安全科学引用本文复制引用
化春键,陈莹..高精度尺度不变特征点匹配方法及其应用[J].中国机械工程,2014,(12):1655-1658,4.基金项目
国家自然科学基金资助项目（61104213）；中央高校基本科研业务费专项资金资助项目 （）
