Combining Adaptive Thresholding and Region Filling for Xylene Spills Detection from Ultraviolet Images

Numerous marine chemical spill accidents have caused enormous damage to the marine ecological environment. Multiple researchers are engaged in providing effective method to detect chemical spill detection. In this paper, we compare the properties between ultraviolet (UV) images and visible images. It turns out that the characteristics of UV images help eliminate the background influence. Then, we develop a new algorithm for segmenting chemical spills from UV imagery. This algorithm, combining adaptive thresholding and region filling, can effectively solve the problem of uneven illumination than the Otsu and FCM algorithms. Moreover, this algorithm does well in time consuming. Experimental results on UV imagery demonstrate that our approach can accurately segment chemical spill without producing too much false alarms.