摘要
简要分析了交通流检测技术的发展现状,结合当前智能交通系统的应用需求,利用连续三帧差分的运动估计方法来构建初始背景,并采用统计打分的策略实时地对背景进行更新;同时提出了一种简单而有效的阴影消除算法以提高交通流参数检测的准确度。另外,针对现有交通流检测系统无车辆跟踪这一环节,可能导致流量多计数的问题,本文提出同时利用车辆的位置信息、颜色信息和分形维信息对车辆进行匹配跟踪的策略。大量实验证明该检测算法能快速、有效地检测出各种交通流参数,为实现交通管理的自动化奠定基础。
This paper analyzes the development status of the techniques to acquire traffic information.According to the application requirements on current traffic systems,a motion estimation method adopting three-frame-differencing is used to construct initial background,and the background is updated in real time with the strategy of statistical scoring.A simple and effective method of shadow removal is put forward to increase the accuracy of traffic flow parameters detection.In addition,aiming at Flow Rate Calculation error caused by existing traffic flow detection system having no vehicle tracking system,a matching pursuit algorithm of the vehicle based on the location information,the color information and the fractal dimension information of the vehicle is proposed.A great deal of experiments demonstrate the system can detect various traffic flow parameters quickly and effectively.
出处
《信息与电子工程》
2011年第2期258-263,共6页
information and electronic engineering
基金
河南省科技攻关项目(102102310361)
关键词
智能交通系统
背景差分法
目标检测
车辆定位
运动目标定位
intelligent transportation system
background subtraction
target detection
vehicle location
motion object positioning
