A robust hybrid movement detection method in dynamic background

Motion segmentation is a very critical task in video surveillance system. In this paper, we propose a novel approach to detect moving objects in a complex background. Gaussian mixture model (GMM) is an effective way to extract moving objects from a video sequence. However, the conventional mixture Gaussian method suffers from false motion detection in complex backgrounds and slow convergence. This work, in order to achieve robust and accurate extraction of the shapes of moving objects, applies a hybrid method to remove noise from images. The proposed model consists of two stages. The first stage consists of a fourth order PDE and the second stage is a relaxed median filter, which processes the output of fourth order PDE. Experimental results show that the proposed model performs well even in the presence of higher levels of noise.