计算机工程与应用2017，Vol.53Issue(9)：141-145,5.DOI:10.3778/j.issn.1002-8331.1510-0327
序列图像特征提取与匹配算法的改进
Improved feature points matching algorithm on sequence image
摘要
Abstract
Feature point matching is an important subject in computer vision field. For the lack of scale invariance charac-teristics of ORB(ORiented Brief)algorithm, this paper proposes an improved method based on the combination of SURF (Speeded-Up Robust Features)and ORB, whose name is SUORB(Speeded-Up ORiented Brief). Firstly, the scale spaces are built, in which the stable extreme points are detected in order to get the feature points with scale invariance informa-tion. Then, the feature points are described by the ORB descriptors with rotation invariance. Finally, Hamming distance is used to finish the final matching task. The experimental results show that SUORB has solved the deficiencies that ORB has little scale invariance. SUORB improves the matching accuracy, compared to ORB when images have scale changes. At the same time, the matching speeds of SUORB and ORB are almost the same.关键词
特征点匹配/多尺度空间/组合算法/方向描述符(ORB)/快速鲁棒特征(SURF)Key words
feature points matching/multi scale space/combination of algorithms/ORiented Brief(ORB)/Speeded-Up Robust Features(SURF)分类
信息技术与安全科学引用本文复制引用
林汀,娄小平,刘锋,李伟仙..序列图像特征提取与匹配算法的改进[J].计算机工程与应用,2017,53(9):141-145,5.基金项目
国家自然科学基金(No.51475047) （No.51475047）
教育部"长江学者与创新团队"发展计划资助项目(No.IRT1212) （No.IRT1212）
北京市属高等学校创新团队建设提升计划项目资助(No.IDHT20130518). （No.IDHT20130518）
