摘要
随着自动驾驶的火热发展,车道线的实时准确检测变得格外重要。本文采用是基于OpenCV车道线检测算法,首先对路面进行高斯滤波处理,去除周围环境的影响,然后使用Canny算子进行自适应性边缘检测,最后再进行图像的二值化处理、划分感兴趣区域、概率Hough直线变换及图像拟合得到车道线检测图。实验表明:本文能够实时高精度和高效率得检测车道线本,适用于户外交通道路的行驶车道线检测。
With the rapid development of autonomous driving, real-time and accurate detection of lane lines has become particularly important. This paper is based on the OpenCV lane detection algorithm. Firstly, Gaussian filtering is applied to the road surface to remove the influence of the surrounding environment. Then the Canny operator is used for adaptive edge detection. Finally, the image is binarized and the region of interest is divided., probability Hough line transformation and image fitting to obtain the lane line detection map. Experiments show that this paper can detect the lane linebook with high precision and high efficiency in real time, and is suitable for driving lane detection of outdoor traffic roads.
作者
张路遥
梁毓明
张天露
ZHANG Lu-yao;LIANG Yu-ming;ZHANG Tian-lu
出处
《信息技术与信息化》
2019年第12期108-111,共4页
Information Technology and Informatization
基金
江西省教育厅科学技术研究项目(GJJ180445)
关键词
自动驾驶
车道线检测
自适应性
边缘检测
图像拟合
Automatic driving
Lane line detection
Adaptive
Edge detection
Image fitting
