基于边缘轮廓的车辆尺寸测量系统的设计
发布时间：2018-10-20 19:54
【摘要】：机器视觉技术具有强大的稳定性、广泛适用的功能、超强的速度和非接触特点。目前该技术在车辆尺寸测量、逆向工程、机械零部件的质量检测和特征形状识别等方面得到了广泛的应用。在这个科技迅猛发展和人工智能日渐进步的新时代,车辆的数量逐年成倍地增加,对交通造成了严重的影响。为了满足当代交通智能化管理的需求、加大改装车辆的法律监管力度和保障社会的道路安全。本文利用机器视觉技术,针对智能交通中车辆超载和超限问题,对车辆尺寸测量进行了针对性的研究,着重对测量系统的结构设计与软件算法进行研究,研究了尺寸参数进行非接触性测量和提取的方法。论文主要内容如下:首先对摄像机标定的方法进行了细致的和深入的研究,在针对一些常用的方法分析和比较后采用了一种基于立体环境视觉下的Open CV摄像机模型的标定方法。通过实验,验证了提出的Open CV摄像机模型标定方法的可行性,并对一些车辆的具体参数进行了标定。其次,采用了背景差分原理以实现对具有复杂背景的汽车图像的准确定位。同时针对机器视觉图像处理中的Canny图像边缘检测算法出现边缘模糊和漏检的问题,所以提出图像分块理论和检测边缘算法,以修正原有的Canny边缘检测算法的不足。论文研究了在车辆的尺寸参数测量系统中使用的特征提取算法,对基于Hough变换的检测直线、圆和Harris算子的角点理论模型进行了详细研究。此外,将特征点匹配技术与区域图像匹配技术结合起来,实现了立体匹配和自动检测;研究了基于车辆测量系统的设计方法,通过分析系统功能开发了一种人机友好的上位机管理界面。
[Abstract]:Machine vision technology has strong stability, widely applicable functions, super speed and non-contact characteristics. At present, this technology has been widely used in vehicle dimension measurement, reverse engineering, quality detection and feature shape recognition of mechanical parts. In this new era with the rapid development of science and technology and the increasing progress of artificial intelligence, the number of vehicles has multiplied year by year, which has caused serious impact on traffic. In order to meet the demand of modern traffic intelligent management, the legal supervision of refitted vehicles should be strengthened and the road safety of the society should be guaranteed. In this paper, aiming at the problem of overloading and overloading of vehicles in intelligent transportation, this paper makes a targeted study on the measurement of vehicle size, focusing on the structure design and software algorithm of the measurement system. The method of non-contact measurement and extraction of dimension parameters was studied. The main contents of this paper are as follows: firstly, the method of camera calibration is studied in detail and deeply. After analyzing and comparing some commonly used methods, a calibration method of Open CV camera model based on stereo vision is proposed. The feasibility of the proposed Open CV camera model calibration method is verified by experiments, and some vehicle parameters are calibrated. Secondly, the background difference principle is adopted to accurately locate the automobile image with complex background. At the same time, aiming at the problem of edge blur and miss detection in Canny image edge detection algorithm in machine vision image processing, the theory of image segmentation and edge detection algorithm are proposed to correct the shortcomings of the original Canny edge detection algorithm. In this paper, the feature extraction algorithm used in vehicle dimension parameter measurement system is studied, and the corner theory model of detecting straight line, circle and Harris operator based on Hough transform is studied in detail. In addition, the feature point matching technology and the region image matching technology are combined to realize stereo matching and automatic detection, and the design method based on vehicle measurement system is studied. By analyzing the functions of the system, a man-machine friendly upper computer management interface is developed.
【学位授予单位】：哈尔滨理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U495;TP391.41
[Abstract]:Machine vision technology has strong stability, widely applicable functions, super speed and non-contact characteristics. At present, this technology has been widely used in vehicle dimension measurement, reverse engineering, quality detection and feature shape recognition of mechanical parts. In this new era with the rapid development of science and technology and the increasing progress of artificial intelligence, the number of vehicles has multiplied year by year, which has caused serious impact on traffic. In order to meet the demand of modern traffic intelligent management, the legal supervision of refitted vehicles should be strengthened and the road safety of the society should be guaranteed. In this paper, aiming at the problem of overloading and overloading of vehicles in intelligent transportation, this paper makes a targeted study on the measurement of vehicle size, focusing on the structure design and software algorithm of the measurement system. The method of non-contact measurement and extraction of dimension parameters was studied. The main contents of this paper are as follows: firstly, the method of camera calibration is studied in detail and deeply. After analyzing and comparing some commonly used methods, a calibration method of Open CV camera model based on stereo vision is proposed. The feasibility of the proposed Open CV camera model calibration method is verified by experiments, and some vehicle parameters are calibrated. Secondly, the background difference principle is adopted to accurately locate the automobile image with complex background. At the same time, aiming at the problem of edge blur and miss detection in Canny image edge detection algorithm in machine vision image processing, the theory of image segmentation and edge detection algorithm are proposed to correct the shortcomings of the original Canny edge detection algorithm. In this paper, the feature extraction algorithm used in vehicle dimension parameter measurement system is studied, and the corner theory model of detecting straight line, circle and Harris operator based on Hough transform is studied in detail. In addition, the feature point matching technology and the region image matching technology are combined to realize stereo matching and automatic detection, and the design method based on vehicle measurement system is studied. By analyzing the functions of the system, a man-machine friendly upper computer management interface is developed.
【学位授予单位】：哈尔滨理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U495;TP391.41
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