An Effective Background Subtraction Method Based on Pixel Change Classification

Background subtraction is an effective way which is commonly used in intelligent monitoring system for extraction of moving objects. However, the key step of background subtraction need for a precise and time-varying background model. In this paper, we describe an improved background model with its updating method, and apply to a computer vision-based motion detection system able to detect moving objects in real-time. Our system first establishes an background based on Gaussian model; second computes the set of statistical parameters of background model according to the way pixel changes; and then extracts moving objects using the updated background model. Finally experimental results and a performance measure establishing the confidence of the method are presented.