@inproceedings{scholars9687,
       publisher = {American Institute of Physics Inc.},
         journal = {AIP Conference Proceedings},
           title = {Color-based oil spill image segmentation},
            note = {cited By 0; Conference of 6th International Conference on Production, Energy and Reliability, ICPER 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:141991},
          volume = {2035},
            year = {2018},
             doi = {10.1063/1.5075603},
          author = {Osman, A. B. and Ovinis, M. and Ismael, M. A. and Fakhruldin, M. H. and Faye, I.},
            issn = {0094243X},
            isbn = {9780735417618},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057345191&doi=10.1063\%2f1.5075603&partnerID=40&md5=f01a91553b34b759009f69a801844474},
        abstract = {Oil spill image segmentation is an important task for quantifying the total amount of spilled oil. However, segmentation of oil region from images is a challenging problem. This is due to un-defined edge between oil and sea water. This paper proposes a novel approach based on oil color. The proposed color-based method segments the oil spill region based on clustering the colors of oil and water within the image into various groups, from which the oiled region can be segmented and defined. A k-mean cluster was applied to differentiate between the various colors. As a result, the color-based method able to determine the oiled region. A comparison to classical Otsu thresholding method showed that the color-based method had a better oil segmentation. {\^A}{\copyright} 2018 Author(s).}
}