| 基于张量投票的道路表面裂缝检测 |
| |
| 引用本文： | 李爱霞,管海燕,钟良,于永涛.基于张量投票的道路表面裂缝检测[J].应用科学学报,2015,33(5):541-549. |
| |
| 作者姓名： | 李爱霞 管海燕 钟良 于永涛 |
| |
| 作者单位： | 1. 浙江水利水电学院测绘与市政工程学院, 杭州 310018;
2. 南京信息工程大学地理与遥感学院, 南京 210044;
3. 长江委长江空间信息技术工程有限公司, 武汉 430079;
4. 淮阴工学院计算机工程学院, 江苏淮安 223003 |
| |
| 基金项目： | 浙江省自然科学基金(No.LQ15D010001);浙江省教育厅项目基金(No.Y201432349)资助 |
| |
| 摘 要： | 以车载LiDAR数据为对象,提出一种基于多尺度张量投票技术的道路表面裂缝提取方法. 首先沿行车路线从剖面图中提取道路路坎,通过行车轨迹线约束提取道路数据. 再根据强度和距离信息将道路数据转换成二维特征图像,采用多尺度张量投票法增强特征图像的裂缝信息提取道路表面裂缝. 利用点云数据和道路影像数据进行实验验证,结果表明该方法抗噪能力强,裂缝检测质量高.
|
| 关 键 词： | 张量投票 车载LiDAR数据 裂缝 道路特征图像 |
| 收稿时间： | 2015-04-09 |
| 修稿时间： | 2015-08-27 |
Tensor Voting Based Pavement Crack Extraction |
| |
| LI Ai-xia,GUAN Hai-yan,ZHONG Liang,YU Yong-tao.Tensor Voting Based Pavement Crack Extraction[J].Journal of Applied Sciences,2015,33(5):541-549. |
| |
| Authors: | LI Ai-xia GUAN Hai-yan ZHONG Liang YU Yong-tao |
| |
| Institution: | 1. Department of Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China;
2. College of Geography & Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
3. Changjiang Spatial Information Technology Engineering Company, Wuhan 430079, China;
4. College of Computer Engineering, Huaiyin Institute of Technology, Huai'an 223003, Jiangsu Province, China |
| |
| Abstract: | This paper proposes a multi-scale tensor voting framework that applies tensor voting to mobile laser scanning data to extract pavement cracks. Trajectory data are used to extract road curbs from profiles along the travelling line to separate road points from non-road points. The extracted road points are interpolated into road feature images. Thus curvilinear cracks are enhanced and extracted with a multi-scale tensor voting framework. Experiments on mobile laser scanning data and road image data were carried out. The results show that the method is robust to noise in both road images and feature images, and can achieve good performance in pavement crack extraction. |
| |
| Keywords: | tensor voting mobile LiDAR data pavement cracks road feature image |
|
| 点击此处可从《应用科学学报》浏览原始摘要信息 |
| 点击此处可从《应用科学学报》下载免费的PDF全文 |
|
