Research on Motion Target Detection Algorithm with Adaptive Hybrid Gaussian Model Combined with Four-Frame Difference

Aiming at the problem that motion target detection under complex background is easily affected by illumination change, target transient occlusion, and target edge missing, a motion target detection algorithm based on hybrid Gaussian model with adaptive learning rate and improved four-frame difference is proposed. Firstly, the hybrid Gaussian background modelling based on adaptive learning rate is used to effectively solve the ghosting and false detection phenomenon that occurs due to the constant update rate of the background. Secondly, the improved four-frame difference method is used to overcome the problems of ambient illumination changes and transient occlusion of the moving target, and use the Canny algorithm to extract the edge of the target to solve the problem of target edge loss. lastly, perform or operations to obtain detection results. The experimental results show that the fusion algorithm can completely extract the moving target under the complex environment, with certain anti-interference ability and high detection accuracy.