When background subtraction method is used to detect moving objects, illumination changes can easily impact the detection. In order to deal with the problem, a novel algorithm which synthesizes the methods of background subtraction and adjacent-frame difference is proposed. This algorithm adopts Gaussian mixture model to reduce the impact of background disturbance, and uses adjacent-frame difference for reference. It deals with illumination changes by background reconstruction and the function of dynamic learning efficiency. The algorithm is simulated when background is disturbed and illumination changes. The results show that the algorithm is more efficient and more robust than traditional methods, and it can attains background model in complex conditions. The algorithm is very suitable for intelligent video systems with static cameras.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.