Maritime Object Segmentation Using Dynamic Background Modeling and Shadow Suppression

Moving object segmentation in maritime domain is a challenging task due to the various real time practical problems, such as waves on the water surface, boat wakes and weather issues (such as bright sun, fog and heavy rain). These problems contribute to generate a highly dynamic background, gradual and sudden illumination changes, camera jitter, shadows and reflections that can provoke false detections. To deal with above issues, in this paper a fast and robust moving object segmentation method on a water surface for maritime surveillance using dynamic background modeling and shadow suppression (OSDBMSS) in the complex wavelet domain is proposed. For dynamic background modeling, we have used frame difference, background registration, background difference and background difference mask in the complex wavelet domain. For shadow detection and removal, we exploit the high frequency subband in the complex wavelet domain. A comparative analysis of the proposed method is presented both qualitatively and quantitatively with other standard methods available in the literature for publicly available datasets of videos in different maritime scenarios, with varying light and weather conditions. Experimental results indicate that the proposed method is performing better in comparison to other standard methods for all the test cases.