摘要
提出一种基于视频的快速的车流量统计算法,采用改进的ViBe算法进行背景建模,然后进行像素值判断,只更新背景像素,以此来提取前景目标。并采用符合人类视觉习惯的YUV彩色空间来消除阴影对车流量统计的干扰,提出一种基于像素级和帧级相结合的动态自适应背景更新算法,以解决光照变化对系统的影响。并使用改进的二轮扫描算法来进行车辆分割。在道路上开辟虚拟检测带,根据ViBe模型及其更新次数来判断是否有车辆进入观测带,从而实现车流量统计。相对于传统算法,本系统的实时性与鲁棒性较高。
A quick statistical algorithm for traffic flow was proposed. The improved ViBe algorithm was used to model the background, then the pixels of video for background was judged, and the background pixels was only updated in order to extract the motion objects from the video. And appropriate human visual habit of YUV color space was adopted to eliminate shadows on the interference of traffic statistics. A pixel level and frame level based on the combination of dynamic adaptive background Updated algorithm was presented to meet illumination change. And the improved second round scanning algorithm was used for vehicle division. Then the test window on the road opened up according to the ViBe model and its updated frequency was used to judge whether a vehicle into the observation window, thereby the traf- fic statistics was realized. Compared with the traditional algorithm, the real-time and robustness of this system is higher.
出处
《电子测量与仪器学报》
CSCD
2012年第6期558-563,共6页
Journal of Electronic Measurement and Instrumentation
基金
中央高校基本科研业务费专项资金(编号:2011HGZL0001)
安徽省自然科学基(编号:090412058)
