| 基于成像模型的车道线检测与跟踪方法 |
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| 引用本文： | 陈龙,李清泉,毛庆洲. 基于成像模型的车道线检测与跟踪方法[J]. 中国公路学报, 2011, 0(6) |
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| 作者姓名： | 陈龙 李清泉 毛庆洲 |
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| 作者单位： | 武汉大学时空数据智能获取技术与应用教育部工程研究中心;武汉大学电子信息学院;武汉大学测绘遥感信息工程国家重点实验室; |
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| 基金项目： | 国家自然科学基金创新研究群体基金项目(40721001); 教育部高等学校博士学科点专项科研基金项目(20070486001) |
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| 摘 要： | 针对结构化道路上存在非车道线标记干扰的情况,提出一种基于成像模型的线扫描车道线检测及跟踪方法。检测算法中首先对路面图像进行形态学高帽变换预处理,然后建立前方道路图像的成像模型,将图像坐标系中车道参数和世界坐标系中实际车道参数对应,对图像进行初扫描,利用边缘贡献函数及RANSAC算法选取最确定线后,以此线为标准进行二次扫描,得到边缘点后统计边缘贡献函数局部最大值并拟合成直线车道线。跟踪算法中运用Kalman滤波器预测车道线区域,并提取符合标准的控制点拟合成模型为B样条的车道线。试验结果表明:该方法能够快速准确地在复杂环境中提取多个车道线,尤其对存在非车道线道路标记干扰的情况有显著效果。
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| 关 键 词： | 交通工程 车道线检测与跟踪 成像模型 梯度贡献函数 Kalman滤波 |
Lane Detection and Following Algorithm Based on Imaging Model |
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| CHEN Long,,LI Qing-quan,,MAO Qing-zhou. Lane Detection and Following Algorithm Based on Imaging Model[J]. China Journal of Highway and Transport, 2011, 0(6) |
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| Authors: | CHEN Long LI Qing-quan MAO Qing-zhou |
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| Affiliation: | CHEN Long1,2,LI Qing-quan1,3,MAO Qing-zhou1,3(1.Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application of Ministry of Education,Wuhan University,Wuhan 430079,Hubei,China,2.School of Electronic Information,3.State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,China) |
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| Abstract: | Considering the interruption of non-lane road markings,authors presented a lane detection and following algorithm on the basis of imaging model.In detection stage,lane image was firstly preprocessed by a morphological top-hat transform,imaging model was created for building relationship of lane parameters of the image coordinate and the world geodesic system(WGS) coordinate.Then the image was scanned for the first time on the basis of imaging model,after that,the edge distribution function(EDF) and RANSAC a... |
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| Keywords: | traffic engineering lane detection and following imaging model edge distribution function Kalman filter |
| 本文献已被 CNKI 等数据库收录！ |
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