Oil Spill Detection using Segmentation based Approaches

This paper presents a description and comparison of two segmentation methods for the oil spill detection in the sea surface. SLAR sensors acquire video sequences from which snapshots are extracted for the detection of oil spills. Both approaches are segmentation based on graph techniques and J-image respectively. Finally, the aim of applying both approaches to SLAR snapshots, as shown, is to detect the largest part of the oil slick and minimize the false detection of the spill.This work was funded by Ministry of Economy and Competitiveness and supported by Spanish project (RTC-2014-1863-8)