应用卷积神经网络的车道线检测系统.docx

应用卷积神经网络的车道线检测系统

目录

1.内容概括................................................2

1.1背景与意义...........................................2

1.2研究内容与方法.......................................3

1.3文档结构.............................................4

2.相关工作................................................5

2.1车道线检测技术概述...................................7

2.2卷积神经网络在图像处理中的应用.......................8

2.3车道线检测的挑战与研究进展..........................10

3.系统需求分析...........................................12

3.1功能需求............................................13

3.2性能需求............................................14

3.3系统集成需求........................................15

4.数据采集与预处理.......................................16

4.1数据来源与采集方法..................................17

4.2数据标注规范........................................18

4.3图像预处理流程......................................19

5.卷积神经网络设计与实现.................................20

5.1网络架构选择........................................21

5.2模型训练策略........................................23

5.3模型评估与优化......................................24

6.车道线检测系统实现.....................................26

6.1系统架构设计........................................27

6.2硬件选型与配置......................................28

6.3软件实现与调试......................................29

7.实验与结果分析.........................................31

7.1实验环境搭建........................................32

7.2实验数据集划分......................................33

7.3实验结果展示........................................34

7.4结果分析与讨论......................................34

8.系统测试与应用案例.....................................35

8.1系统功能测试........................................37

8.2系统性能测试........................................38

8.3应用案例介绍........................................39

9.总结与展望.............................................40

9.1研究成果总结........................................41

9.2存在问题与改进方向..................................42

9.3未来工作展望......................