基于视频序列的交通违章监测系统设计

发布时间：2018-04-19 12:54

本文选题：目标检测与跟踪 + 阴影消除　；参考：《郑州大学》2015年硕士论文

【摘要】：智能交通系统(Intelligent Transportation System,简称ITS)是未来交通系统的发展方向,它将先进的信息技术、控制技术及计算机技术等有效地集成运用于整个地面交通管理系统,其中交通违规抓拍、车辆跟踪及车流量统计是ITS的重要组成部分。基于地感线圈的传统交通系统安装工程量大、维修困难,并且功能有限,不能满足现代交通的需求。因此,设计一个基于视频序列的车辆跟踪、违章抓拍与车流量统计一体式系统具有十分重要的意义。本文分析了基于视频序列的交通违章监测系统原理,研究了系统设计中的图像预处理、目标检测与跟踪、阴影消除和车流量统计理论和算法,并进行了仿真和分析。综合该仿真结果和系统实时性要求,采用金字塔特征光流(L-K)算法进行目标检测、并基于HSV颜色空间消除运动目标的阴影,采用基于时空上下文信息(STC)进行目标跟踪,结合背景差分法的虚拟线圈技术实现车流量统计。选择基于RS Components公司的ARM11作为硬件的核心模块,采用Micron公司MT9P031 CMOS传感器设计图像采集端,并提供了系统电源及其保护电路。最后,基于Python接口的Qt和Open Cv在硬件平台上实现具有车辆跟踪、违规抓拍和车流量统计功能的一体式违章监测软件。经现场测试验证表明:系统工作可靠、稳定,具有实用价值。
[Abstract]:Intelligent Transportation system (ITSs) is the development direction of traffic system in the future. It effectively integrates advanced information technology, control technology and computer technology into the whole ground traffic management system, in which traffic violations are captured.Vehicle tracking and traffic flow statistics are important parts of ITS.The traditional traffic system based on the earth sense coil can not meet the needs of modern traffic because of its large amount of installation, difficult maintenance and limited function.Therefore, it is of great significance to design a vehicle tracking system based on video sequence, an integrated system of capture and traffic statistics.In this paper, the principle of traffic violation monitoring system based on video sequence is analyzed, and the theories and algorithms of image preprocessing, target detection and tracking, shadow cancellation and traffic flow statistics are studied.Based on the simulation results and the real-time requirements of the system, the pyramidal feature optical flow (L-K) algorithm is used to detect the target, and the shadow of moving target is eliminated based on the HSV color space, and the target tracking is carried out based on the temporal and spatial context information.The virtual coil technology based on background difference method is used to realize traffic flow statistics.The ARM11 based on RS Components company is selected as the core module of the hardware. The MT9P031 CMOS sensor of Micron company is used to design the image acquisition terminal, and the system power supply and its protection circuit are provided.At last, QT and Open CV based on Python interface are realized on the hardware platform, which has the functions of vehicle tracking, illegal capture and traffic flow statistics.The field test shows that the system is reliable, stable and practical.
【学位授予单位】：郑州大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495;TP391.41

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