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首页> 外文会议>2013 Fifth International Conference on Geo-Information Technologies for Natural Disaster Management >Rapid Update of Road Surface Databases Using Mobile LiDAR: Road-Markings
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Rapid Update of Road Surface Databases Using Mobile LiDAR: Road-Markings

机译：使用移动LiDAR快速更新路面数据库：道路标记

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摘要

Road surface markings are used on paved roadways to provide guidance and information to drivers and pedestrians, which are a critical feature in the traffic management systems. This paper presents an automated approach to detection and extraction of road markings from mobile laser scanning (MLS) point clouds by taking advantages of multiple data features. To improve computational efficiency, the raw MLS point cloud data are first converted to geo-referenced images, based on elevation, intensity and point density, using inverse distance weighted interpolation, respectively. Afterwards, three filters are designed to extract road markings step-by-step: (1) the elevation filter is used to generate an elevation mask to remove high objects from the geo-referenced intensity image, (2) the point density filter is implemented to extract road surfaces in the geo-referenced intensity image, (3) the filtered geo-referenced intensity image is processed by thresholding and point density to obtain road markings, followed by a Canny detector and Hough transform used to extract straight-lines of road markings. Two RIEGL VMX-450 datasets demonstrate that the proposed multi-feature road marking extraction method has a good performance of road marking extraction from a large volume of mobile laser scanning data.
机译：铺装道路上使用路面标记为驾驶员和行人提供指导和信息，这是交通管理系统中的关键功能。本文提出了一种自动方法，可以利用多种数据特征从移动激光扫描（MLS）点云中检测和提取道路标记。为了提高计算效率，首先分别使用反距离加权插值，分别基于高程，强度和点密度，将原始MLS点云数据转换为地理参考图像。然后，设计了三个过滤器以逐步提取道路标记：（1）使用高程过滤器生成高程遮罩，以从地理参考强度图像中去除高物体，（2）实施点密度过滤器以提取地理参考强度图像中的路面，（3）通过阈值化和点密度处理滤波后的地理参考强度图像以获得道路标记，然后使用Canny检测器和霍夫变换提取道路的直线标记。两个RIEGL VMX-450数据集表明，所提出的多特征道路标记提取方法具有从大量移动激光扫描数据中提取道路标记的良好性能。

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