Underwater Pipeline Oil Spill Detection Based on Structure of Root and Branch Cells

Abstract

The existing oil spill detection methods mainly rely on physical sensors or numerical models cannot locate the spill position accurately and in time. To solve this problem, combining with underwater image processing technology, an unsupervised detection algorithm for oil spill in underwater pipelines is proposed for the first time. First, the oil spill region to be detected is regarded as the moving target, and the foreground detection algorithm is applied to the processed images. Then, the HSV (Hue, Saturation, Value) color space of the image is used to screen the oil spill region meeting the threshold requirements. Next, the bitwise of foreground mask and HSV mask into cells are divided. Finally, according to the characteristics of the oil spill image, false detection is eliminated by classifying cells three times. After qualitative and quantitative analysis, it is proved that the proposed algorithm can detect oil spill region accurately.