| Title |
Comparative Performance Analysis of Feature Detection and Matching Methods for Lunar Terrain Images |
| Authors |
홍성철(Hong, Sungchul) ; 신휴성(Shin, Hyu-Soung) |
| DOI |
https://doi.org/10.12652/Ksce.2020.40.4.0437 |
| Keywords |
달 탐사 로버;달 지형 영상;영상 특징점 검출 및 정합 기법;영상 정합점 Lunar rover;Lunar terrain image;Feature detection and matching method;Image matching point |
| Abstract |
A lunar rover's optical camera is used to provide navigation and terrain information in an exploration zone. However, due to the scant presence of atmosphere, the Moon has homogeneous terrain with dark soil. Also, in extreme environments, the rover has limited data storage with low computation capability. Thus, for successful exploration, it is required to examine feature detection and matching methods which are robust to lunar terrain and environmental characteristics. In this research, SIFT, SURF, BRISK, ORB, and AKAZE are comparatively analyzed with lunar terrain images from a lunar rover. Experimental results show that SIFT and AKAZE are most robust for lunar terrain characteristics. AKAZE detects less quantity of feature points than SIFT, but feature points are detected and matched with high precision and the least computational cost. AKAZE is adequate for fast and accurate navigation information. Although SIFT has the highest computational cost, the largest quantity of feature points are stably detected and matched. The rover periodically sends terrain images to Earth. Thus, SIFT is suitable for global 3D terrain map construction in that a large amount of terrain images can be processed on Earth. Study results are expected to provide a guideline to utilize feature detection and matching methods for future lunar exploration rovers. |