CAJ | 학술논문

实时交通信息检测在智能交通系统中起着重要的作用，视频车辆检测是交通信息检测的一种重要手段。背景差分算法因其灵活性和准确性，成为基于视频的运动目标实时检测的一种常用方法，传统背景差分算法仅仅强调对二维图像的处理，尤其强调对图像分割和目标跟踪。该文对传统背景差分算法进行了改进，提出一种基于虚拟线框的车辆视频检测算法。该算法核心思想通过在每个车道设置两个虚拟线框来检测交通流参数，虚拟线框的输出信号源于背景差分。该方法只需对虚拟线框内的图像区域进行处理，从而并且避开了在视频图像中进行复杂的车辆特征提取与跟踪，减少了运算量，降低了运算负荷。经测试算法的处理速度为25帧/秒，车辆识别精度约为88%。
실시교통신식검측재지능교통계통중기착중요적작용，시빈차량검측시교통신식검측적일충중요수단。배경차분산법인기령활성화준학성，성위기우시빈적운동목표실시검측적일충상용방법，전통배경차분산법부부강조대이유도상적처리，우기강조대도상분할화목표근종。해문대전통배경차분산법진행료개진，제출일충기우허의선광적차량시빈검측산법。해산법핵심사상통과재매개차도설치량개허의선광래검측교통류삼수，허의선광적수출신호원우배경차분。해방법지수대허의선광내적도상구역진행처리，종이병차피개료재시빈도상중진행복잡적차량특정제취여근종，감소료운산량，강저료운산부하。경측시산법적처리속도위25정/초，차량식별정도약위88%。
The collection of real-time traffic data plays a critical role in the intelligent transport system, and video-based detection is an important part in traveler information systems. Background difference method has become common means in real-time mo?tion detection because of its flexibility and veracity. Traditional background difference method is mainly based on 2-dimensional image processing, especially on image division and vehicle tracking. Improved the traditional background difference method, an al?gorithm of vehicle detection which is based on virtual frame is proposed in the paper. The main idea of this algorithm is based on the lane, each lane can have two virtual-frame to detect its traffic parameters. Each virtual-frame ’s output signals mainly derive from the background difference. This method is only processing small area within virtual-frame and avoiding vehicle tracking in 2-dimensional image, hence the time cost of calculation and the computation burthen is reduced. The experiment tells us that the speed of the algorithm is 25 fps, the precision is about 88%.