文献类型：期刊文献

英文题名：Oil Spill Monitoring of Shipborne Radar Image Features Using SVM and Local Adaptive Threshold

作者：Xu, Jin[1,2];Wang, Haixia[1];Cui, Can[3];Zhao, Baigang[1];Li, Bo[2,4]

机构：[1]Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China;[2]Guangdong Ocean Univ, Maritime Coll, Zhanjiang 524088, Peoples R China;[3]Shenyang Aerosp Univ, Civil Aviat Coll, Shenyang 110000, Peoples R China;[4]Liaoning Hydrogeol & Engn Geol Reconnaissance Ins, Lab Dept, Dalian 116000, Peoples R China

年份：2020

卷号：13

期号：3

外文期刊名：ALGORITHMS

收录：ESCI(收录号：WOS:000525030200008)、EI(收录号：20201708513300)、Scopus(收录号：2-s2.0-85083493848)、WOS

基金：This research was funded by the National Natural Science Foundation of China [grant number 51709031], the Fundamental Research Funds for the Central Universities [grant number 3132019138] and the Innovation Support Project of Dalian [grant number 2018RQ22].

语种：英文

外文关键词：oil spill; SVM; real-time monitoring; shipborne radar; remote sensing; image processing; GIS

外文摘要：In the case of marine accidents, monitoring marine oil spills can provide an important basis for identifying liabilities and assessing the damage. Shipborne radar can ensure large-scale, real-time monitoring, in all weather, with high-resolution. It therefore has the potential for broad applications in oil spill monitoring. Considering the original gray-scale image from the shipborne radar acquired in the case of the Dalian 7.16 oil spill accident, a complete oil spill detection method is proposed. Firstly, the co-frequency interferences and speckles in the original image are eliminated by preprocessing. Secondly, the wave information is classified using a support vector machine (SVM), and the effective wave monitoring area is generated according to the gray distribution matrix. Finally, oil spills are detected by a local adaptive threshold and displayed on an electronic chart based on geographic information system (GIS). The results show that the SVM can extract the effective wave information from the original shipborne radar image, and the local adaptive threshold method has strong applicability for oil film segmentation. This method can provide a technical basis for real-time cleaning and liability determination in oil spill accidents.