基于OpenCV的道路视频分析系统

当前投入使用的车辆检测系统普遍采用图像回传至服务器后主机集中处理的方式，存在输出数据大，处理时间长等缺点.本文依据ITS系统的构成提出了嵌入式硬件平台的搭建方案，着重对视频图像进行分析并对跟踪算法进行优化.使用OpenCV为图像基础处理工具，通过对比canny算子和sobel算子的区别，选定更具优越性的边缘算法.针对拖影问题，背景采用改进的均值法（即间隔取帧）来提取.最后选用核跟踪的方式实现动态目标的跟踪，并将其应用在系统中实现对动态目标的稳定跟踪.

Road Video Analysis System Based on OpenCV

The vehicle detection system in current use widely uses host to centrally process images passed back to the server, and it thus has shortcomings, such as large output data, long processing time and so on. This paper proposes a constructing plan using embedded hardware platform according to the composition of ITS system. The video image is emphatically analyzed, and the tracking algorithm is also optimized. The basic image processing tool OpenCV is used to select the preferable edge algorithm by comparing the canny operator and sobel operator. Considering smearing, the background is extracted with the improved averaging method (take interval frames). Finally the nuclear track is chosen for dynamic target tracking, and it is applied in the system for getting the stability of dynamic target tracking.