Sea bottom line is the echo boundary between the water column and seabed on side-scan sonar waterfall image. Tracking it correctly is the basis for geometric and radiative correction of side-scan sonar image. Because of the interfering echoes under complex water environment, the sea bottom line cannot be tracked through traditional threshold and smoothing algorithms. Therefore, a new method, taking full advantage of the spatial distribution characteristics of the sea bottom line, is proposed, in which points density clustering and chains seeking are the two core processes. The former clustering process can be regarded as a filter to cluster points along a direction that is approximately parallel to the track line,and the points are grouped to chains if they are density reachable in a searching neighborhood. Then, by adopting the five principles and tracking strategy given in this paper, the chains relevant to the sea bottom line are sought and identified to finish the tracking work. The test results show that the proposed method performs well even in a complex water environment and has better stability and anti-interference ability compared with traditional tracking methods. This research improves the side-scan sonar data processing, and makes it more accurate, automatic and intelligent.
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The research is supported by the National Natural Science Foundation of China (Coded by 41606114). The Guangzhou Marine Geological Survey Bureau (GMGSB) provided sufficient sonar data for an actual project for the research. We are greatly thankful for their selfless support in the research.
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Wang, A., Church, I., Gou, J. et al. Sea bottom line tracking in side-scan sonar image through the combination of points density clustering and chains seeking. J Mar Sci Technol 25, 849–865 (2020). https://doi.org/10.1007/s00773-019-00685-6
- Side-scan sonar
- Sea bottom line tracking
- DBSCAN clustering
- Chains distinguishing