A selective background updating method for vehicle detection
Jianguo Jiang · Journal of Hefei University of Technology · 2011
To solve the problems that traditional background updating methods have poor real-time performance and can not timely and correctly handle the local background mutation,this paper presents a selective background updating method for vehicle detection.The methods of improved symmetric difference and background difference are integrated to detect vehicle movement areas,and to make each of moving target become an independent connected domain.The seed filling technology based on twice scanning method is used to solve the problem of hole in moving targets caused by the similar gray scale of vehicle and road surfaces.The traditional selective background updating method is improved,and different updating methods are used to update the moving target area and the non-moving target area.Experimental results show that the improved method has good real-time performance and can effectively solve the problem of local background mutation,thus improving the accuracy of vehicle detection.