A new approach of vehicle detection in complex environments
Vehicle detection is a major way of subtracting moving vehicles from traffic flow images in ITS. In order to acquire an accurate background from the constantly changing traffic environment, we design and realize a robust background updating model based on single Gaussian distribution. Then, we use the method of local normalization to subtract the texture image, and carry out texture segmentation to acquire the moving vehicles by virtue of the Laws texture energy method. The experiment shows that this method can efficiently eliminate the effect of the vehicle shadows and bright pavements and it is especially suitable for the nighttime vehicle detection in complex traffic environments with streetlights.
vehicle detection single Gaussian method local normalization texture segmentation
Chen Di Liu Bing-han
College of Mathematics and Computer Science Fuzhou University Fuzhou, China
国际会议
厦门
英文
455-459
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）