摘要
为保证交通安全,设计了一种基于单目视觉的车道偏离检测系统,利用车载前视摄像头获取图像,实时对动态图像进行处理,在驾驶员非主观偏离车道时进行报警。首先研究了图像预处理技术,包括灰度化、截取有效区域、滤波去噪、图像灰度增强、边缘检测和边缘修复功能。其次对预处理后的图像进行车道线检测,为有效识别具有车道线特征的图像,提出了一种改进的Hough变换算法;对没有车道线特征或车道线特征不明显的图像,采用了动态检测方法。在此基础上,提出了一种车道线纠正算法,即四点标定逆透视变换,将车道图像转化为俯视图,建立图像坐标系与实际俯视坐标系之间的关系,得到实际车辆的位置和偏移角度,判断该车辆的情况并作出指示。最后,在实际道路中对设计中关键技术以及整个系统进行了实验,大量实验结果表明,本文系统能在多种环境的道路中实现车道线的准确识别和偏移判断,具有良好的实时性和鲁棒性。
With the rapid growth of the number of cars,traffic safety has become a hot issue of global concern.According to statistics,the accident caused by lane departure i s increasing year by year.This paper designs a new lane departure warning system based on monocu lar vision.The system processes dynamic image in real time,and alarms when the vehicle deviat es from the lane. Firstly,the paper studies image preprocessing technology,including gray proces sing, intercepting effective region,denoising,image gray enhancement,edge detection and edge repairing.Then,in order to detect the lane whose characteristics are not ap parent or with no lane characteristics,an improved Hough transform and a dynamic detection method are put forward.Next, the paper proposes another algorithm for lane line correction,which is inverse p erspective transformation by four point calibration,turning the lane image into a top view.The system establishes the relation between different coordinate systems,works out the off set of the vehicle, judges the situation and gives directions to the driver.Finaly,a lot of experime nts about the key technology and the whole system are conducted in the real-roa ds.The experimental results show that this design can work well in all kinds of environment and has strong real- time capability and robustness.
作者
李福俊
顾敏明
LI Fu-jun, GU Min-ming(Faculty of Mechanical Engineering and Automation, Zhejiang Science and Technology University, Hangzhou 310018 ,Chin)
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2018年第3期298-304,共7页
Journal of Optoelectronics·Laser
基金
国家自然科学基金(61374022)
浙江省自然科学基金(LQ14F030013)
浙江省科技计划(2015C33084)资助项目
关键词
图像处理
车道偏离预警
车道线检测
HOUGH变换
逆透视变换
image processing
lane departure warning
lane detection
Hough transform
inverse perspective transformation
