摘要
This paper presents a voxel-based region growing method for automatic road surface extraction from mobile laser scanning point clouds in an expressway environment.The proposed method has three major steps:constructing a voxel model;extracting the road surface points by employing the voxel-based segmentation algorithm;refining the road boundary using the curb-based segmentation algorithm.To evaluate the accuracy of the proposed method,the two-point cloud datasets of two typical test sites in an expressway environment consisting of flat and bumpy surfaces with a high slope were used.The proposed algorithm extracted the road surface successfully with high accuracy.There was an average recall of 99.5%,the precision was 96.3%,and the F1 score was 97.9%.From the extracted road surface,a framework for the estimation of road roughness was proposed.Good agreement was achieved when comparing the results of the road roughness map with the visual image,indicating the feasibility and effectiveness of the proposed framework.
提出了一种基于体像的区域生长方法,用于高速公路环境下移动激光扫描点云的路面自动提取。该方法包括三个主要步骤:构造体素模型;采用基于体素的分割算法提取路面点;利用基于边界的分割算法细化道路边界。为了评价该方法的准确性,我们使用了高速公路平坦和颠簸高坡路面环境下的两个典型试验点的两点云数据集。该算法成功地实现了路面的高精度提取。平均召回率为99.5%,精度为96.3%,F1得分为97.9%。根据所提取的路面,提出了一种路面平整度估计框架。当将路面粗糙度图的结果与视觉图像进行比较时,得到了很好的一致性,说明了所提框架的可行性和有效性。
基金
Project(SIIT-AUN/SEED-Net-G-S1 Y16/018)supported by the Doctoral Asean University Network Program
Project supported by the Metropolitan Expressway Co.,Ltd.,Japan
Project supported by Elysium Co.Ltd.
Project supported by Aero Asahi Corporation,Co.,Ltd.
Project supported by the Expressway Authority of Thailand。
作者简介
Corresponding author:TRAN Thanh Ha,PhD Candidate,Tel:+66-953274390,E-mail:thanhhabk2006@gmail.com,ORCID:0000-0001-5175-0547。
