Oil spill identification in marine SAR images based on texture feature and fuzzy logic system

Authors:
Peng Liu;Chaofang Zhao
Affiliations:
Ocean Remote Sensing Institute, Ocean University of China, Qingdao, China and Key Laboratory of Ocean Remote Sensing, Ministry of Education of China;Ocean Remote Sensing Institute, Ocean University of China, Qingdao, China and Key Laboratory of Ocean Remote Sensing, Ministry of Education of China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
Year:
2009

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Abstract

A model based on texture feature and fuzzy logic algorithm was constructed to discriminate oil spills from look-alike phenomena in the SAR images. Statistics texture feature of SAR images were extracted and used as the input parameters in the fuzzy logic system. The texture features consisted of entropy second order, angular second moment, contrast and inverse difference moment of dark objects. The system analyzed 38 SAR images with 77 oil spills and 52 lookalikes, and provided the probability of a dark object to be an oil spill. The remaining 26 processed SAR images, which were not included in the training, were used to test the system. The result showed that 80.5% of the oil spills were correctly classified. It seemed that the texture features and fuzzy logic system were effective in identifying oil spills on marine SAR images.