항법 적용을 위한 수중 소나 영상 처리 요소 기법 비교 분석
Comparative Study of Sonar Image Processing for Underwater Navigation
1
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Imaging sonars such as side-scanning sonar or forward-looking sonar are becoming fundamental sensors in the underwater robotics field. However, using sonar images for underwater perception presents many challenges. Sonar images are usually low resolution with inherent speckled noise. To overcome the limited sensor information for underwater perception, we investigated preprocessing methods for sonar images and feature detection methods for a nonlinear scale space. In this paper, we focus on a comparative analysis of (1) preprocessing for sonar images and (2) the feature detection performance in relation to the scale space composition.
Abstract
Imaging sonars such as side-scanning sonar or forward-looking sonar are becoming fundamental sensors in the underwater robotics field. However, using sonar images for underwater perception presents many challenges. Sonar images are usually low resolution with inherent speckled noise. To overcome the limited sensor information for underwater perception, we investigated preprocessing methods for sonar images and feature detection methods for a nonlinear scale space. In this paper, we focus on a comparative analysis of (1) preprocessing for sonar images and (2) the feature detection performance in relation to the scale space composition.
참고문헌 (17)
- Alcantarilla, P.F, "KAZE Features. In Computer Vision–ECCV 2012", pp.214~227 (2012), Springer Berlin Heidelberg
- Alcantarilla, P.F, "Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces", IEEE Transactions on Pattern Analysis Machine Intelligence, 34(7), pp.1281~1298 (2011)
- Aykin, M.D, "On Feature Extraction and Region Matching for Forward Scan Sonar Imaging", 2012. IEEE, pp.1~9 (2012)
- Bay, H, "Computer Vision–ECCV 2006", pp.404~417 (2006), Springer Berlin Heidelberg
- Belcher, E, "Dual-frequency Identification Sonar (DIDSON). In Underwater Technology, 2002", Proceedings of the 2002 International Symposium on. IEEE, pp.187~192 (2002)
- Hover, F. S, "Advanced Perception, Navigation and Planning for Autonomous in-Water Ship Hull Inspection", The International Journal of Robotics Research, 31(12), pp.1445~1464 (2012)
- Hurtós, N, "Fourierbased Registration for Robust Forward‐looking Sonar Mosaicing in Low‐visibility Underwater Environments", Journal of Field Robotics, 32(1), pp.123~151 (2015)
- Johannsson, H, "Imaging Sonar-aided Navigation for Autonomous Underwater Harbor Surveillance", Intelligent Robots and Systems (IROS), 2010 IEEE, 2010, 4396~4403
- Kim, K, "Acoustic Camera Image Mosaicing and Super-resolution", OCEANS'04. MTTS, 2004, 653~658
- Leutenegger, S, "November. BRISK: Binary Robust Invariant Scalable Keypoints", Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, pp.2548~2555 (2011)
- Lowe, D.G, "Distinctive Image Features from Scaleinvariant Keypoints", International journal of computer vision, 60(2), pp.91~110 (2004)
- Negahdaripour, S, "Dynamic Scene Analysis and Mosaicing of Benthic Habitats by fs Sonar Imaging-issues and Complexities", OCEANS 2011. IEEE, pp.1~7 (2011)
- Negahdaripour, S, "On Processing and Registration of Forward-scan Acoustic Video Imagery", Computer and Robot Vision, 2005. Proceedings. The 2nd Canadian Conference on. IEEE, pp.452~459 (2005)
- Ridao, P, "Visual Inspection of Hydroelectric Dams using an Autonomous Underwater Vehicle", Journal of Field Robotics, 27(6), pp.759~778 (2010)
- Rublee, E, "ORB:an Efficient Alternative to SIFT or SURF", Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, pp.2564~2571 (2011)
- Shin, Y. S, "Bundle Adjustment from Sonar Images and SLAM Application for Seafloor Mapping", OCEANS'15 MTS, 2015, 1~6
- Tomasi, C, "Bilateral Filtering for Gray and Color Images", Computer Vision, 1998. Sixth International Conference on. IEEE, pp.839~846 (1998)