基于图像点云的道路缺陷检测  

Road Defect Detection Based on Image Point Cloud

作　　者：李威祥 李武劲 陈思源 LI Wei-Xiang;LI Wu-Jin;CHEN Si-Yuan(School of Information Science and Engineering,Hunan Institute of Science and Technology,Yueyang 414006,China;Hunan Provincial 3D Reconstruction and Intelligent Application Engineering Research Center,Yueyang 414006,China)

机构地区：[1]湖南理工学院信息科学与工程学院,岳阳414006 [2]“三维重建与智能应用技术”湖南省工程研究中心,岳阳414006

出　　处：《计算机系统应用》2024年第3期220-225,共6页Computer Systems & Applications

基　　金：湖南省水利厅项目(XSKJ2021000-13);湖南省教育厅优秀青年项目(20B266)。

摘　　要：本文针对无人机图像点云道路缺陷检测问题,提出了一种基于点云切片平面拟合与聚类的道路缺陷检测方法.首先,采集无人机图像进行三维重建生成图像点云,对点云进行坡度滤波与统计离群点滤波,消除噪声和异常点的干扰.然后,对点云进行切片并利用随机采样一致性平面拟合算法估计道路的平面模型.随后,运用点云DBSCAN聚类算法分类出边缘噪声与道路损伤点云.最后,采用点云切片法估计损伤程度.在实验中,我们使用真实无人机采集的点云数据,并与基于点云垂直度特征检测方法进行了对比.实验结果表明,本文方法表现出较高的准确性和鲁棒性,体积估计的误差为1 307 cm^(3).相较于传统方法,本文方法能够更精确地检测出道路损伤,并能适应复杂的道路形状变化.To address the challenge of detecting road defects in drone-captured image point clouds,this study introduces a road defect detection method based on point cloud slicing,plane fitting,and clustering.Firstly,drone images are captured to facilitate 3D reconstruction and the generation of image point clouds.Subsequently,point cloud data undergoes slope filtering and statistical outlier filtering to eliminate noise and anomalous data points.Next,the point clouds are sliced,and a random sample consensus(RANSAC) plane fitting algorithm is applied to estimate the road's plane model.Then,the point cloud DBSCAN clustering algorithm is employed to differentiate between edge noise and road damage point clouds.Finally,the point cloud slicing technique is utilized to assess the extent of the damage.In the experiments,the study employs actual drone-collected point cloud data and compares the proposed method with an approach relying on point cloud verticality features.The experimental results demonstrate that the proposed method exhibits a high level of accuracy and robustness,with a volume estimation error of only 1 307 cm^(3).Compared to traditional methods,the proposed method excels in precisely detecting road damage and adapting to intricate road shape variations.

关 键 词：无人机 图像三维重建 道路检测 点云拟合 点云聚类 

分 类 号：U418[交通运输工程—道路与铁道工程] TP391.41[自动化与计算机技术—计算机应用技术]