Research and implementation of image feature point matching method based on OpenCV

DOI

10.2991/ameii-16.2016.141How to use a DOI?

Keywords

OpenCV, Feature point, SIFT, BRISK, Image matching

Abstract

This paper described the distance metric of the Euclidean distance of SIFT operator and Hamming distance of BRISK operator represented based on OpenCV to extract and descript feature points on the two relatively low altitude remote sensing images , and then chose BruteForceMatch (violent match) and FlannBasedMatch (approximate Closest match) two matching methods to match in the same matching operator. Lastly, the RANSAC algorithm was chose to estimate the fundamental matrix, eliminating the effects of error matching on the fundamental matrix accuracy and stability. By using extreme geometric constraints to reject the mistake matching points in error matching, and improve the robustness and accuracy of the matching.The results show that the performance of FlannBasedMatch method is more advantageous.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rong Liu
AU  - Danmei Peng
AU  - Yang Liu
PY  - 2016/04
DA  - 2016/04
TI  - Research and implementation of image feature point matching method based on OpenCV
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 719
EP  - 722
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.141
DO  - 10.2991/ameii-16.2016.141
ID  - Liu2016/04
ER  -