An Automatic Extraction Method of Road from Vehicle-Borne Laser Scanning Point Clouds
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摘要: 针对车载移动测量系统数据采集特点，构建车载激光点云扫描线索引，提出了一种基于扫描线索引的道路路面与路边点云稳健分类法。首先通过分析扫描线上不同地物剖面的空间分布特征，进行剖面激光点生长聚类，形成完整的地物剖面目标点集；然后根据点集的几何特征因子判断点集类型；最后利用相邻多条扫描线上路边点分布规律进行去噪。对车载移动测量系统获取的两份点云数据进行实验，路面与路边提取的平均完整率分别为94.4%、86%，平均准确率分别为98.9%、99.1%。实验分析表明，该方法能有效减少粗糙路面点的错误分类，适应不同的道路路边条件，降低独立地物对路边提取的干扰。Abstract: Laser scanning lines index are built from original vehicle-borne laser scanning data. An classification method for automatic extraction of road pavement and side is proposed. Firstly, through the analysis of the spatial distribution characteristics of different objects in scanning lines, a clustering of objects profile points are applied. Then, according to the geometric features of the point set, the type of point set is determined. Finally, the distribution of the edge points of the adjacent multiple scanning lines is used to de-noise. Two point cloud data provided by Vehicle Survey System are used in the experiment. The average integrity rate of road pavement and side extraction are 94.4%, 86%, the average accuracy rate are 98.9%, 99.1%.The experiment shows that this method can effectively decrease the error classification of pavement points, reduce the objects interference to the roadside extraction, and adapt to different road conditions of urban street.
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Keywords:
- vehicle-borne laser /
- road extraction /
- scanning line index /
- moving dynamic window
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图 4 扫描线不同地物剖面点高程分布
Figure 4. Elevation Distribution of Different Object Profile Points
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图 5 扫描线不同地物剖面点水平投影距离分布
Figure 5. Horizontal Distance Distribution of Different Object Profile Points
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图 9 路段1结果与高差斜率法对比显示
Figure 9. Result Display and Comparison with the Elevation and Slope Method of Road One
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图 10 路段2结果与高差斜率法对比显示
Figure 10. Result Display and Comparison with the Elevation and Slope Method of Road Two
表 1 路面与路边完整率分析
Table 1 Integrity Rate Analysis of Pavement and Side
路段 路面 路边 RP/m2 CP/m2 PIR/% RS/m CS/m SIR/% 路段1 17 555.9 16 007.6 91.2 2 499.1 2 032.2 81.3 路段2 20 015.3 19 507.4 97.5 4 009.4 3 632.6 90.6 
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表 2 路面与路边准确率分析与对比
Table 2 Accuracy Analysis and Comparison of Pavement and Side
处理算法 路面 路边 TP/m2 FP/m2 PAR/% PER/% TS/m FS/m SAR/% SER/% 高差斜率法 路段1 16 039.3 186.6 98.8 1.2 2 057.7 186.9 91.7 8.3 路段2 17 554.3 362.5 98.0 2.0 3 045.5 256.3 92.2 7.8 本文方法 路段1 16 007.6 81.6 99.5 0.5 2 032.2 5.6 99.7 0.3 路段2 19 507.4 340.5 98.3 1.7 3 632.6 54.6 98.5 1.5
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[1] Pu S, Rutzinger M, Vosselman G,et al. Recognizing Basic Structures from Mobile Laser Scanning Data for Road Inventory Studies[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011,66(6):S28-S39 doi: 10.1016/j.isprsjprs.2011.08.006
[2] Li J. Automated Extraction of Street-scene Objects from Mobile Lidar Point Clouds[J].International Journal of Remote Sensing,2012,33(18):5839-5861 doi: 10.1080/01431161.2012.674229
[3] Boyko A, Funkhouser T. Extracting Roads from Dense Point Clouds in Large Scale Urban Environment[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2011,66(6):S2-S12 doi: 10.1016/j.isprsjprs.2011.09.009
[4] Chen Y Z, Zhao H J, Shibasaki R. A Mobile System Combining Laser Scanners and Cameras for Urban Spatial Objects Extraction[C]. Proceedings of the Sixth International Conference on Machine Learning and Cybernetics,Hong Kong, China,2007
[5] Barber D, Mills J, Smith-Voysey S. Geometric Validation of a Ground-based Mobile Laser Scanning System[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2008,63(1):128-141 doi: 10.1016/j.isprsjprs.2007.07.005
[6] 史文中,李必军,李清泉.基于投影点密度的车载激光扫描距离图像分割方法[J].测绘学报,2005,34(2):95-100 http://www.cnki.com.cn/Article/CJFDTOTAL-CHXB200502001.htm Shi Wenzhong, Li Bijun, Li Qingquan. A Method for Segmentation of Range Image Captured by Vehicle-borne Laserscanning Based on the Density of Projected Points[J]. Acta Geodaetica et Cartographica Sinica, 2005, 34(2):95-100 http://www.cnki.com.cn/Article/CJFDTOTAL-CHXB200502001.htm
[7] Jaakkola A, Hyyppä J, Hyyppä H, et al. Retrieval Algorithms for Road Surface Modelling Using Laser-based Mobile Mapping[J]. Sensors,2008, 8(9):5238-5249 doi: 10.3390/s8095238
[8] El-Halawany S, Moussa A, Lichti D D, et al. Detection of Road Curb from Mobile Terrestrial Laser Scanner Point Cloud[C]. ISPRS Calgary 2011 Workshop, Calgary, Canada, 2011
[9] Zhou L, Vosselman G.Mapping Curbstones in Airborne and Mobile Laser Scanning Data[J]. International Journal of Applied Earth Observation and Geoinformation, 2012,18(1):293-304 http://cn.bing.com/academic/profile?id=8728a4c8e2078be918a5eb3c003b32e9&encoded=0&v=paper_preview&mkt=zh-cn
[10] Dinesh M, Ryosuke S. Auto-extraction of Urban Features from Vehicle-Borne Laser Data. Symposium on Geospatial Theory[C]. Processing and Applications, Ottawa, Canada,2002
[11] Yuan X,Zhao C X,Cai Y F,et al. Road-Surface Abstraction Using Ladar Sensing[C].200810th International Conference on Control, Automation, Robotics and Vision, Vietnam, 2008
[12] 刘如飞,田茂义,许君一. 车载激光扫描数据中高速公路路面点滤波[J]. 武汉大学学报·信息科学版,2015,40(6):751-755 http://ch.whu.edu.cn/CN/abstract/abstract3271.shtml Liu Rufei, Tian Maoyi,Xu Junyi. Expressway Road surface Point filtering of Mobile Laser Scanning Data[J].Geomatics and Information Science of Wuhan University,2015,40(6):751-755 http://ch.whu.edu.cn/CN/abstract/abstract3271.shtml
[13] 方莉娜,杨必胜.车载激光扫描数据的结构化道路自动提取方法[J]. 测绘学报,2013,42(2):260-267 http://www.cnki.com.cn/Article/CJFDTOTAL-CHXB201302017.htm Fang Lina, Yang Bisheng. Automated Extracting Structural Roads from Mobile Laser Scanning Point Clouds[J]. Acta Geodaetica et Cartographica Sinica,2013,42(2):260-267 http://www.cnki.com.cn/Article/CJFDTOTAL-CHXB201302017.htm
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