A software tool for automated extraction of pavement cracks from mobile LiDAR data

路面破损是路面使用性能的一个指标。路面的广泛损坏或退化是强烈的交通负荷加上极端天气条件或老化效应在加拿大各地造成的后果。表面遇险评估通常是手动进行的。然而，如今有几家机构正在用移动激光雷达扫描仪等自动化遇险数据采集设备来取代人工工作。移动激光扫描(LiDAR)系统采集的高密度、高精度的三维点云数据是记录路面破损的新兴数据源。这项新技术克服了传统手工操作的局限性，这些限制通常与高成本、低生产率和低精度有关。移动激光雷达系统能够在正常速度下以低强度对比度在环境照明下扫描道路表面。现有研究表明，移动LiDAR点云可用于评价路面状况，包括车辙、行驶质量、修复、纹理和

Pavement surface distresses are an indicator of pavement performance. Extensive damage or degradation of pavement surfaces is the consequence of intense traffic loads accompanying with extreme weather conditions or aging effect everywhere in Canada. Surface distress evaluation is commonly performed manually. However, nowadays several agencies are replacing the manual work by automated distress data collection devices, such as mobile LiDAR scanner. Dense and high accuracy 3D point cloud data collected by a mobile laser scanning (or LiDAR) system is an emerging data source for recording pavement distresses. This new technology has overcame the limitations of the traditional manual practices that usually associated with high cost, low productivity and low accuracy. Mobile LiDAR systems is capable of scanning road surfaces at ambient lighting with low intensity contrast under normal speed. Existing studies have demonstrated that mobile LiDAR point cloud is applicable to evaluate pavement condition including rutting, ride quality, rehabilitation, texture, and