Study on moving-objects detection technique in video surveillance system

A new method of moving-objects detection based on fusion of background subtraction and temporal differencing is proposed in this paper. The method constructs the adaptive background model by Gaussian model for each pixel in the image sequences, combined with temporal difference to update the background selectively, and simultaneous used background subtraction method extract movement areas from the background model. Then integration the two foreground regions segmented for object recognition, together with utilization of the median filter and mathematical morphology operation to eliminate noise and the small area of non-human movement parts. Finally obtain the complete reliable moving-objects. Experimental results show that the approach identifies targets accuracy, and can satisfy the needs of real-time in visual surveillance system.