车载LiDAR路面点云的空洞检测与修补方法

doi:10.13474/j.cnki.11-2246.2025.1124

测绘通报 ›› 2025, Vol. 0 ›› Issue (11): 154-158.doi: 10.13474/j.cnki.11-2246.2025.1124

车载LiDAR路面点云的空洞检测与修补方法

陈健平¹, 史剑¹, 戴相喜¹, 张沁宇¹, 韩文泉²

1. 南京市测绘勘察研究院股份有限公司, 江苏南京 210019;
2. 莫干山地信实验室, 浙江湖州 313200

收稿日期:2025-04-24 发布日期:2025-12-04
通讯作者: 韩文泉。E-mail:hanwq@mgslab.ac.cn
作者简介:陈健平(1995—),男,硕士,工程师,主要从事测量数据处理与三维算法研究。E-mail:chenjianping1995@126.com

Hole detection and filling in road surface point clouds from vehicle-mounted LiDAR

CHEN Jianping¹, SHI Jian¹, DAI Xiangxi¹, ZHANG Qinyu¹, HAN Wenquan²

1. Nanjing Institute of Surveying, Mapping & Geotechnical Investigation, Co., Ltd., Nanjing 210019, China;
2. Moganshan Geospital Information Laboratory, Huzhou 313200, China

Received:2025-04-24 Published:2025-12-04

摘要/Abstract

摘要： 为解决车载LiDAR点云中因遮挡产生的路面空洞问题,本文提出一种检测与修补方法。该方法首先通过滤波与聚类提取路面点云;然后采用多尺度Alpha Shape算法提取点云边界并识别遮挡导致的边界断裂,利用NURBS曲线恢复完整二维边界;最后在边界范围内划分网格,结合空网格聚类检测路面空洞,通过拟合二次曲面进行插值修补。在10条典型道路场景中验证表明,常见遮挡物引起的空洞修补成功率达96.5%,修补点云与原始数据衔接自然、过渡平滑,关键几何特征得到良好保留。该方法在小范围遮挡场景中表现稳定,对大多数道路点云空洞修补具有良好适用性。

关键词: 车载LiDAR, 路面点云, 点云空洞修补, Alpha Shape算法, NURBS曲线拟合

Abstract: Vehicle-mounted LiDAR scans of urban roads often contain holes in the road surface point cloud due to occlusions by vehicles,pedestrians,and roadside objects.These gaps degrade the completeness and accuracy of downstream 3D modeling and spatial analysis.We propose an automated pipeline for hole detection and repair in road surface point clouds.Firstly,noise and non-road points are removed via filtering and clustering techniques to isolate the road surface.Next,a multi-scale Alpha Shape algorithm extracts the 2D road boundary and identifies boundary breaks caused by occlusion; NURBS curves then restore a continuous boundary.Finally,the area within the repaired boundary is partitioned into a regular grid,empty cells are clustered to locate holes,and a quadratic surface is fitted to surrounding points to interpolate and fill each hole.Experiments on ten diverse urban road segments demonstrate that our method achieves 96.5% hole-filling success for common occluders,produces smooth,seamless transitions with the original data,and preserves critical geometric features such as curb and corner shapes.The proposed approach reliably repairs small-scale occlusions in road surface point clouds and is broadly applicable to most urban driving scenarios.

Key words: vehicle-mounted LiDAR, road surface point clouds, point cloud hole filling, Alpha Shape algorithm, NURBS curve fitting

中图分类号:

P237

陈健平, 史剑, 戴相喜, 张沁宇, 韩文泉. 车载LiDAR路面点云的空洞检测与修补方法[J]. 测绘通报, 2025, 0(11): 154-158.

CHEN Jianping, SHI Jian, DAI Xiangxi, ZHANG Qinyu, HAN Wenquan. Hole detection and filling in road surface point clouds from vehicle-mounted LiDAR[J]. Bulletin of Surveying and Mapping, 2025, 0(11): 154-158.

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车载LiDAR路面点云的空洞检测与修补方法

Hole detection and filling in road surface point clouds from vehicle-mounted LiDAR

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