Oil Spill Image Segmentation Based on Fuzzy C-means Algorithm

被引:0
|
作者
Sun Guangmin [1 ,2 ]
Ma Haocong [1 ]
Zhao Dequn [1 ]
Zhang Fan [1 ]
Jia Linan [1 ]
Sun Junling [1 ]
机构
[1] Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
[2] Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
来源
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INTELLIGENT COMMUNICATION | 2015年 / 16卷
关键词
Oil aerial image; color model; YCbCr color space; fuzzy C-means Algorithm;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Oil spill may cause serious pollution of the marine environment. Unmanned aerial vehicles remote sensing system can be used to monitor oil spill conditions. In order to identify the oil spill area on aerial image accurately, the first step is oil spill region segmentation. The paper presents an image segmentation method of oil spill area based on fuzzy C-means Algorithm. Firstly, according to the color characteristics of the oil, the paper selects YCbCr color space as the feature space. Then, the paper uses fuzzy clustering algorithm to divide the color feature space. Finally, according to oil color model, the paper selects clustering result as the segmentation results of oil spill area. Experiment show that the proposed algorithm's accuracy for oil region segmentation of calibration attain to 95 percent.
引用
收藏
页码:406 / 409
页数:4
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