Oil Spill Detection Using LBP Feature and K-Means Clustering in Shipborne Radar Image
نویسندگان
چکیده
Oil spill accidents have seriously harmed the marine environment. Effective oil monitoring can provide strong scientific and technological support for emergency response of law enforcement departments. Shipborne radar be used to monitor spills immediately after accident. In this paper, original shipborne image collected by teaching-practice ship Yukun Dalian Maritime University during accident on 16 July 2010 was taken as research data, an detection method proposed using LBP texture feature K-means algorithm. First, Laplacian operator, Otsu algorithm, mean filter were suppress co-frequency interference noises high brightness pixels. Then gray intensity correction matrix reduce nonuniformity. Next, clustering effective regions extracted. Finally, adaptive threshold applied identify films. This automatically detect in image. It a guarantee real-time accidents.
منابع مشابه
Oil spill detection by means of synthetic aperture radar
Università di Cagliari for the suggestions and the stimulating discussions. SAR data used in the studies. Finally, I have to thank to my family and to Raffaella: without their support all this would have never been possible.
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ژورنال
عنوان ژورنال: Journal of Marine Science and Engineering
سال: 2021
ISSN: ['2077-1312']
DOI: https://doi.org/10.3390/jmse9010065