CAJ | 학술논문

介绍了一种城市交通流量视频检测系统及其车辆识别新算法.通过检测道路上的运动目标并利用目标的运动信息和外形特征进行车辆识别.考虑到目标的阴影会影响目标的形状特征,导致目标识别错误,提出了一种新的阴影检测算法--利用目标的灰度特征对运动目标进行阴影检测和分离.实验结果表明该系统在模拟城市混合交通环境下,能够克服目标阴影的影响,准确检测和识别车辆,同时能够满足实时性的要求.
개소료일충성시교통류량시빈검측계통급기차량식별신산법.통과검측도로상적운동목표병이용목표적운동신식화외형특정진행차량식별.고필도목표적음영회영향목표적형상특정,도치목표식별착오,제출료일충신적음영검측산법--이용목표적회도특정대운동목표진행음영검측화분리.실험결과표명해계통재모의성시혼합교통배경하,능구극복목표음영적영향,준학검측화식별차량,동시능구만족실시성적요구.
This paper presents a video-based urban traffic flow detection system and a novel vehicle recognition algorithm. Firstly, moving objects on the roadway are detected. Then, the vehicles are recognized based on their motion information and shape characteristics. Considering that objects shadows will impact the objects appearance and result in false recognition, a novel shadow detection approach is described: object shadows are detected and separated from the moving objects by using intensity characteristics. The experiment results show that the system can greatly reduce the shadows. impact,and accurately detect and recognize the vehicles on the urban multi-traffic road, while satisfiying the real-time requirement.