Improved moving object detection method based on Gaussian mixture mode

Gaussian mixture model (GMM) is widely used in moving objects detection in image sequences; however, the existing moving objects detection methods which are based on Gaussian mixture model are not so efficient especially when dealing with noise or illumination mutation. In order to solve the problems above, a new method is proposed. Edge images are not sensitive to noise or illumination mutation, so that the edge Gaussian mixture model (EGMM) which is constructed with edge images can be used to improve the moving objects detection. And neighborhood-based difference method is improved to restrain noise effectively. The proposed method combines the edge Gaussian mixture model with the improved neighborhood-based difference method. Experimental results prove that the proposed method can increase detection rate while reducing false alarm rate and has stronger capacity of restraining noise and dealing with illumination mutation.