Deep Learning Approach For Automatic Detection Of Oil Slicks

The aim of this study is to propose a deep learning approach for automatic oil slicks detection over surface of ocean based on Synthetic Aperture Radar (SAR) images. Deep networks such as U-Net is a kind of image-segmentation-based algorithm which is proved to be effective for varies of image segmentation problems. Here we introduce an U-Net framework for our oil slicks segmentation task. Our database comes from SAR images of 5 differents regions over the world and is divided into training set and test set. With this U-Net structure, we have achieved an overall precision of 93% and a recall rate of 71% with our test set. The algorithm is able to distinguish between oil slicks and other object known as “lookalike”.