A fast matching method for large viewpoint changes images based on ORB algorithm

被引：0

作者：

Zeng Q.-H. ^{[1
,2
]}

Chen Y. ^{[1
]}

Wang Y.-S. ^{[1
,2
]}

Liu J.-Y. ^{[1
,2
]}

Liu S. ^{[3
]}

机构：

[1] College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing

[2] Collaborative Innovation Center for Satellite Communication and Navigation, Nanjing

[3] AVIC Luoyang Electro-Optical Equipment Research Institute, Luoyang

来源：

Kongzhi yu Juece/Control and Decision | 2017年 / 32卷 / 12期

关键词：

Affine transformation; Large viewing; ORB; Perspective transformation;

D O I：

10.13195/j.kzyjc.2016.1521

中图分类号：

学科分类号：

摘要：

For the problem that the affine scale invariant feature transform(ASIFT) algorithm does well in large viewing image matching but has low computing efficiency, a fast large viewing image matching method based on the oriented FAST and rotated BRIEF(ORB) algorithm is proposed. The improved algorithm combines the perspective transformation model and ORB algorithm to optimize the affine transformation model and SIFT algorithm in the ASIFT algorithm. The refined matching is performed with the homography matrix based on coarse matching, which can reduce the number of simulation and improve the efficiency of the algorithm. The experimental results show that the proposed algorithm has the ability to resist the angle of view, and is 10 times faster than the ASIFT algorithm. Also, it has strong real-time performance and high engineering application value. © 2017, Editorial Office of Control and Decision. All right reserved.

引用

页码：2233 / 2239

页数：6

共 16 条

[11]

Su K.X., Han G.L., Sun H.J., Anti-viewpoint changing image matching algorithm based on SURF, Chinese J of Liquid Crystals and Displays, 28, 4, pp. 626-632, (2013)

[12]

Hou Y., Zhou S.L., Lei L., Et al., Fast fully affine invariant image matching based on ORB, Computer Engineering and Science, 36, 2, pp. 303-310, (2014)

[13]

Fu C., Deng L., Lu G., Et al., Improved image matching based on fast retina keypoint algorithm, Computer Engineering and Applications, 52, 19, pp. 208-212, (2016)

[14]

Rosten E., Drummond T., Machine learning for high-speed corner detection, Computer Vision-ECCV 2006, pp. 430-443, (2006)

[15]

Calonder M., Lepetit V., Strecha C., Et al., BRIEF: Binary robust independent elementary features, Computer Vision-ECCV 2010 European Conf on Computer Vision, pp. 778-792, (2010)

[16]

Wang S.X., Zhou B., A homography matrix estimation method based on RANSAC, Scientific Chinese, 23, (2015)

← 1 2 →