摘要
针对传统Hough变换算法在无人车结构化道路车道标线识别中出现的中间间断车道标线提取不精准、不完整、有用车道标线信息丢失等问题,提出基于感兴趣附近区域的Hough变换车道标线识别算法.运用传统Hough变换对预处理得到的二值图像进行图像部分分块的车道标线提取,在已提取的车道标线周围划定感兴趣附近区域,找出感兴趣附近区域内的像素与车道标线的辅助度关系,通过辅助度计算累计单元的最大值,得到车道标线的参数.对无人车实时采集的图片进行实验,实验结果表明,该算法在直道、弯道情况下平均处理一帧图片耗时分别为80.42ms、92.22ms,具有很好的实时性,且该算法可以有效提取结构化道路的车道标线.
In order to solve the problems in the traditional Hough transform algorithm for UGV structured road lane marking identification, such as the inaccurate and incomplete extraction of the middle of the lane marking and the loss of useful lane information, a Hough transform lane marking identification algorithm based on nearby region of interest（ROD is proposed. Delimiting RIO nearby the lane marks was extracted by the traditional Hough transform from the part of binary preprocessingimage, finding out the relation of the auxiliary degree between the pixel in the ROI and the lane marking. The maximum of the accumulative unit is calculated through this auxiliary degree, with the parameters of lane marks obtaired. The new algorithm was tested by using the real-time captured images. Experimental result shows that 80. 42 ms and 92. 22 ms on average are requined respectively by the algorithm to process one image in the case of straight road and bending road. The algorithm is of good real time and the algorithm can extract structured road lane marking effectively.
出处
《西安工业大学学报》
CAS
2013年第1期14-18,共5页
Journal of Xi’an Technological University
基金
陕西省教育厅自然科学专项(12JK0502)
教育部留学回国人员科研计划项目(2011CY185)
关键词
车道标线识别
传统Hough变换
感兴趣附近区域
辅助度
lane marking identification
traditional hough transform
nearby region of interest
auxiliary degree relation
