基于光流的运动车辆检测和跟踪技术的研究

运动车辆的检测和跟踪是智能交通系统的重要研究方向.利用基于微分光流法的Lucas-Kanade算法进行运动车辆检测,通过幅度平方函数进行车辆的阈值分割,并利用形态学进行图像修正.Blob算法对车辆图像特征进行统计和分析,对运动车辆进行标注并跟踪.最后,根据检测结果,计算交通流参数.通过仿真实验,说明算法具有一定的实用性.

Research on Detection and Tracking of Moving Vehicles Based on Optical Flow

The detection and tracking for moving vehicles is an important research direction in the Intelligent Traffic System. Lucas-Kanade algorithm based on the differential optical flow is used for the detection of moving vehicles. Both the magnitude squared function and morphology are employed respectively for the threshold segmentation of the vehicles and for their image correction. By means of the Blob algorithms, the features of the vehicle images are counted and analyzed, labeled and tracked. The parameters of the traffic flow are computed on the basis of The simulation experiments show that these algorithms have certain practicality.