广东工业大学学报2017，Vol.34Issue(6)：37-42,6.DOI:10.12052/gdutxb.170034
一种改进的FREAK算法的图像特征点匹配
An Improved FREAK Algorithm for Image Feature Point Matching
摘要
Abstract
FREAK algorithm has the defects of not having scale invariance and single feature point matching strategy,and being prone to unsatisfactory results.Based on SIFT and RANSAC algorithm,an improved FREAK algorithm is proposed:SFREAK (SIFT and FREAK).First of all,in the generation of Gauss differential Pyramid image,the feature points are detected with scale invariance;then the feature points are described with FREAK descriptor,obtaining binary descriptor;finally,in the process of feature points matching using Hamming distance matching for coarse matching,the matching points are purified with RANSAC algorithm,and the feature points of two images are matched.The experimental results show that the proposed algorithm can effectively solve the FREAK not having scale invariance in image scaling,and SFREAK algorithm for feature point matching accuracy rate reached 95.7％,increased by 61.9％ compared with FREAK.Therefore,compared with the traditional SIFT algorithm and FREAK algorithm,the improved algorithm shows better robustness.关键词
改进FREAK/SIFT/RANSAC/特征点匹配Key words
improved FREAK/SIFT/RANSAC/feature points matching分类
信息技术与安全科学引用本文复制引用
叶志坚,王福龙..一种改进的FREAK算法的图像特征点匹配[J].广东工业大学学报,2017,34(6):37-42,6.基金项目
广州市科学研究专项基金资助项目(201510010059) （201510010059）
