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摘要近年来，无人驾驶车技术的发展十分迅速，它是一种集硬件与软件为一体的新一代智能系统的产物，它的关键技术是无人驾驶汽车的路径识别，这是现阶段制约无人驾驶车发展的关键，因为路径识别的关键技术是车辆的道路检测，因此，能够进行高效准确的道路检测是实现无人驾驶车技术的首要任务，也是本课题所研究的主要内容。63865
该论文叙述了无人驾驶汽车的背景和简介，介绍了相关的开发工具和环境配置，阐述了系统的总体设计和具体模块的功能，最后截取了系统运行后的部分截图。
本系统用手机拍的照片对图片中路口进行有效的提取和识别处理。该程序按照软件工程的思想，使用MFC进行框架设计，用VC++6.0作为开发平台，用opencv作为开发工具，使用Matlab处理图片，实现了对图片的读入，路口的分割提取以及路口的轮廓检测和路口的识别等功能。本程序界面较为稳定，能够有效的实现程序的功能。
毕业论文关键词 路口识别 路口提取 轮廓匹配 图像处理
毕业设计说明书（论文）外文摘要
Title The analysis of intersection based on visual sense
Abstract In recent years, unmanned vehicle technology has developed rapidly. It is a new generational product of intelligent system combined with hardware and software, it’s key part of unmanned vehicle technology is the recognition of the route, which is the constraint on its development. Therefore, accurate and efficient road detection is the primary task of the unmanned vehicle technology, and it’s also the main content of this subject.
This paper describes the background and profile of driverless car, introduces the relevant development tools and environment configuration, describes the overall design of the system and the specific module functions. And for the last part, it’s some pictures of the system running result.
The system uses pictures took by cellphone to effectively extract and identify intersections. Based on the thought of software engineering, the program adopts MFC to design its framework and VC++6.0 as its development platform. With opencv as its developing tool, it then employs Matlab to process the pictures. Therefore, the program realizes the function of reading pictures, segmenting and extracting intersection as well as detecting and indentifying it. The interface is stable and the function of the program can be effectively realized.
Keywords Intersection identification Intersection extraction Outline match Picture processing
1 绪论 1
1.1 概述 1
1.2 无人驾驶汽车简介 1
1.4 研究目的及意义 4
2 开发环境及相关技术支持 5
2.1 概述 5
2.2 MFC类框架 5
2.4 opencv简介及配置 7
2.4.1 opencv简介 7
2.4.2 opencv配置 8
2.5 matlab生成exe文件 10
2.6 VC++6.0简介 11
3 系统总体设计 12
3.1 概述 12
3.2 需求分析