基于机器视觉的车道线检测设计

基于机器视觉的车道线检测设计(任务书,开题报告,外文翻译,论文说明书17000字)
摘要
基于机器视觉的车道线检测利用计算机视觉相关技术从获得的实时视频图片中处理识别出目标车道线，定位出安全正确的行车方向和可行驶区域，规避风险。到目前为止，主要有两大类应用比较广泛的车道线检测方法，一类是基于车道特征检测，另一类是基于车道模型检测方法。
本文针对道路图像中两侧车道线的检测问题，研究一种基于图像处理、结合Hough变换直线检测原理的车道线检测方法。整体设计包含几个主要的部分，首先需要对实时采集到的道路图像进行简单的预处理，主要是图像灰度化和图像滤波；预处理后的图像需要进行感兴趣区域的提取，减少后续处理的数据量；利用边缘检测算法对图像中边缘轮廓、几何形状等进行提取；对标准Hough变换加以改进，对目标车道线进行检测识别。
整个设计的程序实现基于MATLAB仿真软件平台，结合不同的功能函数设计实现车道线检测的功能。观察分析程序运行的最终检测结果图，较准确地检测出了图像中的目标车道线，可以证实整体设计的可行性。
关键词：车道线检测；图像预处理；Hough变换

Abstract
The machine vision-based lanedetection uses computer vision related technology to process and identify the target lane from the obtained real-time video pictures, and locate safe and correct driving directions and travelable areas to avoid risks.So far, the widely used lane detection methods at home and abroad can be divided into two categories: detection methods based on lane features and detection methods based on lane models.
Aiming at the detection problem of lane lines in road images, a lane recognition method based on improved Hough transform and least squares method is studied.The overall design consists of several main parts. Firstly, the road image acquired in real time needs to be simply preprocessed, mainly including image graying and image filtering. It is necessary to extract the region of interest from the preprocessed image to reduce the amount of data processed subsequently; the edge contour, geometry, etc. in the image are extracted by the edge detection algorithm; the final target lanedetection is achieved by using the improved Hough transform or the least squares.
The whole design of the program is based on the MATLAB, combined with different functional functions to realize the lane detection function.Observing the final result, it can be seen that the target lane line in the image is detected accurately, which can confirm the feasibility of the overall design.
Key words: lanedetection; Image preprocessing; Hough transform

 
目录
第1章 绪论    1
1.1研究背景及意义    1
1.2国内外研究现状和方法    1
1.3论文主要内容和组织结构    3
第2章 图像预处理    4
2.1道路图像灰度化    4
2.1.1图像灰度化方法    4
2.1.2图像灰度化结果分析    5
2.2图像增强    5
2.2.1图像增强算法概述    5
2.2.2图像滤波    6
2.3感兴趣区域划分    9
2.4本章小结    11
第3章 图像分割    12
3.1图像分割介绍    12
3.2边缘检测    13
3.3边缘检测算子    13
3.4本章小结    16
第4章 车道线检测    17
4.1 Hough变换介绍    17
4.1.1 Hough变换原理    17
4.1.2 Hough变换的改进    19
4.2最小二乘法    20
4.3 整体流程设计    21
4.3.1检测结果分析    22
4.3.2有效性验证    23
4.4本章小结    24
第5章 总结和展望    25
参考文献    26
致谢    27