A Novel Correspondence section Technique Affine Rigid Image Registration

被引:11
作者
Lv, Guohua [1 ]
机构
[1] Qilu Univ Technol, Shandong Acad Sci, Coll Informat, Jinan 250353, Shandong, Peoples R China
来源
IEEE ACCESS | 2018年 / 6卷
基金
中国国家自然科学基金;
关键词
Correspondence selection; discriminative power; distance ratio; geometric similarity; image registration; keypoint triplets; RANDOMIZED RANSAC; PERFORMANCE;
D O I
10.1109/ACCESS.2018.2847399
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a novel technique called correspondence selection for rigid transformations in order to effectively refine keypoint matches in rigid image registration. The proposed technique mainly lies in the following two components. First, keypoint matches are ranked and selected by the distance ratio between the best match and the second best match. Second, keypoint matches are further selected by ranking the geometric similarity between corresponding keypoint triplets. These two components enhance the discriminative power of potential keypoint matches in a progressive way. The proposed technique is generally applicable to affine rigid image registration. Experiments have been conducted using a set of benchmark datasets in the field of image registration, indicating that the proposed technique is very effective and achieves the state-of-the-art performance in refining keypoint matches for affine rigid image registration.
引用
收藏
页码:32023 / 32034
页数:12
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