SURF-Based Image Matching Method for Landing on Small Celestial Bodies

DOI

10.2991/masta-19.2019.68How to use a DOI?

Keywords

SURF, FLANN, RANAC, Image matching, Landing on small bodies

Abstract

In deep space exploration missions, one of the main methods used to achieve accurate landing of small celestial body by detectors is the terrain-matching navigation method based on optical images. Image matching technology is the key technology of this method. This paper proposed a small celestial image matching method based on SURF (Speeded Up Robust Features) to improve the adhesion accuracy of small celestial bodies. Firstly, we used the SURF feature detector to perform feature point detection on the surface image of the target celestial body then, the feature points are matched by the fast nearest neighbor search method. And mismatches are eliminated with NNDR and RANSAC. Finally, under the influence of image rotation, Gaussian noise, etc., the matching results of the algorithm were simulated and analyzed. The simulation results demonstrate that the proposed method has good robustness in complex environment of small celestial and high matching accuracy. It can provide effective landmark information and attitude information for subsequent visual navigation.

Copyright

© 2019, 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  - Yu-lang Chen
AU  - Jing-min Gao
PY  - 2019/07
DA  - 2019/07
TI  - SURF-Based Image Matching Method for Landing on Small Celestial Bodies
BT  - Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)
PB  - Atlantis Press
SP  - 401
EP  - 407
SN  - 1951-6851
UR  - https://doi.org/10.2991/masta-19.2019.68
DO  - 10.2991/masta-19.2019.68
ID  - Chen2019/07
ER  -