Hybrid object detection using improved Gaussian mixture model

In this paper, we propose a novel approach to detect moving objects in a complex background. The 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 Experimental results show that the proposed model performs well even in the presence of higher levels of noise.