文献类型：期刊文献

英文题名：Oil Spill Detection Using LBP Feature and K-Means Clustering in Shipborne Radar Image

作者：Xu, Jin[1];Pan, Xinxiang[1];Jia, Baozhu[1];Wu, Xuerui[2,3,4];Liu, Peng[5];Li, Bo[6]

机构：[1]Guangdong Ocean Univ, Maritime Coll, Zhanjiang 524088, Peoples R China;[2]Chifeng Univ, Sch Resources Environm & Architectural Engn, Chifeng 024000, Inner Mongolia, Peoples R China;[3]Suzhou Univ Sci & Technol, Res Ctr BeiDou Nav & Environm Remote Sensing, Suzhou 215009, Peoples R China;[4]Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China;[5]Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China;[6]Guangdong Ocean Univ, Continuing Educ Coll, Zhanjiang 524088, Peoples R China

年份：2021

卷号：9

期号：1

起止页码：1

外文期刊名：JOURNAL OF MARINE SCIENCE AND ENGINEERING

收录：SCI-EXPANDED(收录号：WOS:000610353200001)、、Scopus(收录号：2-s2.0-85099604598)、WOS

基金：This research was funded by the National Natural Science Foundation of China [grant numbers 51709031, 51979045], the Fundamental Research Funds for the Central Universities [grant number 3132019138], the Innovation Support Project of Dalian [grant number 2018RQ22], the Enterprise-university-research Cooperation Project of the Ministry of Education of China [grant number 201702043016], the Special projects in key fields (Artificial Intelligence) of Universities in Guangdong Province [grant number 2019KZDZX1035] and program for scientific research start-up funds of Guangdong Ocean University.

语种：英文

外文关键词：oil spill; LBP; K-means; shipborne radar; remote sensing; oil pollution; image analysis; machine learning; radar detection

外文摘要：Oil spill accidents have seriously harmed the marine environment. Effective oil spill monitoring can provide strong scientific and technological support for emergency response of law enforcement departments. Shipborne radar can be used to monitor oil spills immediately after the accident. In this paper, the original shipborne radar image collected by the teaching-practice ship Yukun of Dalian Maritime University during the oil spill accident of Dalian on 16 July 2010 was taken as the research data, and an oil spill detection method was proposed by using LBP texture feature and K-means algorithm. First, Laplacian operator, Otsu algorithm, and mean filter were used to suppress the co-frequency interference noises and high brightness pixels. Then the gray intensity correction matrix was used to reduce image nonuniformity. Next, using LBP texture feature and K-means clustering algorithm, the effective oil spill regions were extracted. Finally, the adaptive threshold was applied to identify the oil films. This method can automatically detect oil spills in shipborne radar image. It can provide a guarantee for real-time monitoring of oil spill accidents.