摘要
车辆所处车道线的识别是高级辅助驾驶系统(ADAS)的基础,在此基础上可以开发出车道偏离预警系统和车道保持等系统.然而实际路面情况复杂多变,运用传统的图像灰度化方法难以准确地提取到车道信息.以一段在复杂工况下车载相机捕捉到的视频为例,提出了一种改进的图像灰度化方法用于车道线识别中图像的前处理.基于此方法,可在复杂路面上准确提取出车道线信息.
Lane detection is the basis of Advanced Driving Assistant System(ADAS).On this basis,lane departure warning system and lane keeping system can be developed.However,the actual road conditions are complex and changeable.Therefore,it is difficult to extract lane information accurately using traditional image graying method.In this paper,taking the video captured by a car camera in complex working conditions as an example,an improved image graying method is proposed for image pre-processing in lane detection.Based on this method,lane information can be extracted accurately on complex road surface.
作者
钟泽滨
ZHONG Zebin(School of Automotive Studies,Tongji University,Shanghai 201804,China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2019年第S01期178-182,共5页
Journal of Tongji University:Natural Science
关键词
灰度化
车道线识别
图像处理
graying method
lane detection
image processing
