船体
计算机科学
水下
人工智能
水文学
坐标系
计算机视觉
主成分分析
模式识别(心理学)
地质学
海洋工程
工程类
海洋学
作者
Shaobo Li,Yi Zhang,Jianhu Zhao,Yunlong Wu,Shaofeng Bian,Guojun Zhai
标识
DOI:10.1109/joe.2023.3318793
摘要
The detection of shipwrecks plays an important role in hydrographic surveying and underwater archaeology. However, traditional 2-D sub-bottom profiler (SBP) data cannot represent the 3-D shape of the buried shipwreck. An automatic shipwreck detection method based on 3-D SBP data is presented in this article. First, the key hull shape parameters are given and analyzed to describe the 3-D geometric characteristics of the shipwreck. Then, geometric contours of reflections were extracted based on 3-D SBP data by using the Enhancement Filtering Method to remove interferences, followed by applying the Global Energy Optimization Method to obtain contour clusters. After that, we elaborated on the main parameters used in hull shape description and presented the definitions of these parameters under a local coordinate system established using principal component analysis. Then, we define the shape index of the shipwreck (SI). To remove the dependence on a shipwreck attitude, we build the local coordinate system. To achieve unsupervised detection, we utilize prior information about the hull shape and determine the threshold for the SI in shipwreck detection. By applying the proposed method to both the real and simulated data, we demonstrate successful detection performance.
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