基于机器视觉的车辆排队长度检测

Vehicle queue length detection based on machine vision

现如今智能交通系统的研究越来越受到国内外学者的关注,而车辆排队长度检测技术是智能交通系统中重要的研究内容。为了获取准确的参数数据,文中突破传统的雷达、微波、红外等检测技术,提出一种基于机器视觉的车辆排队长度检测技术。通过运用强大的机器视觉库,对摄像头采集到的视频流信息进行图像灰度化、直方图均衡化、获取感兴趣区域、Canny算子检测车辆等一系列图像算法处理,最后利用摄像机标定技术得到准确的车辆排队长度。实验表明,此检测方法可以检测到较准确的车辆排队长度,可以为智能交通系统提供重要交通参数依据。

The research of intelligent transportation system has been paid more and more attention by scholars both at home and abroad,and vehicle queue length detection technology is an important research content in intelligent transportation system.In order to obtain accurate parameter data.It breaks through the traditional radar,microwave,infrared and other detection techniques,and proposes a vehicle queue length detection technology based on machine vision.By using apowerful machine vision library,a series of image algorithms such as image gray,histogram equalization,region of interest,Canny operator detection vehicle are processed by the video stream information collected by the camera.Finally,the actual vehicle queuing length is obtained by camera calibration technique.Experiments show that this method can detect more accurate vehicle queue length,and can be used as an important traffic parameter basis for intelligent transportation system.