Sliding Windowed Fuzzy Correlation Analysis-Based Marine Motion Detection

Background subtraction is a widely used technique in motion detection. There are many challenges for motion detection in oceanic video like camera jitter, dynamic background and low visibility. If the background is dynamic or if the background changes overtime, a background update should be done in real time to precisely detect any kind of moving objects. In order to achieve an accurate underwater detection of motion in case of static camera with dynamic background in marine video, a novel detection scheme called sliding windowed fuzzy correlation analysis is proposed. The background modelling is based on sliding window technique, and the detection scheme is based on fuzzy correlation analysis. The window size is fixed to 12 in the algorithm to obtain better results and to reduce the latency in execution. The dataset considered here is ‘dataset on underwater change detection’ (Kaghyan and Sarukhanyan, Int J Inf Model Anal 1:146–156, 2012) that consists of five marine videos along with its ground truth. We qualitatively and quantitatively prove that the proposed method attains better motion detection as compared to other existing methods. The computational complexity involved is Intel Core i5 processor with MATLAB® software for simulation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.