摘要
台阶线是露天矿测量的主要对象之一,传统的全站仪、GPS点式测量方法耗时长、劳动强度大、效率低,而基于无人机点云的现代测量方法为台阶线高效提取提供了可能。基于无人机影像构建的密集匹配点云数据,提出了一种自适应高程阈值的台阶线提取方法。该方法首先通过邻域点云的协方差矩阵对地形条件进行判断,依据不同的地形自适应地选用不同的高程差阈值进行台阶线特征点提取,极大限度地减少误提取数量;然后,基于点云聚类分割后各点云簇中点的数量与高程特征对误提取的点云进行剔除,并采用三次B样条曲线对特征点进行拟合,较好完成了露天矿台阶线提取。试验表明:该方法可以高效地完成露天矿台阶线特征点提取,有效区分台阶线和道路边线特征点;同时依据特征点拟合出的曲线效果良好,真实反映了台阶线的实际位置。上述分析为露天矿台阶线高效测量提供了新的解决方法。
Step line is one of the main objects of open-pit mine survey.The traditional point measurement method of total station and GPS is time-consuming,labor-intensive and inefficient,while the modern measurement method based on UAV point cloud provides the possibility for efficient extraction of step lines.Based on the dense matching point cloud data constructed from UAV images,a step line extraction method with adaptive elevation threshold was proposed.Firstly,the terrain condition was judged by the covariance matrix of the neighborhood point cloud,and different elevation difference thresholds were adaptively selected according to different terrain to extract the step line feature points,which greatly reduced the number of false extraction.Then,based on the number of points in each point cloud cluster and elevation characteristics after point cloud clustering segmentation,the misextracted point clouds were removed,and the cubic B-spline curve was used to fit the feature points.Finally,the step line extraction of open-pit mine was completed.The test results showed that the method can efficiently extract the feature points of the step line in open-pit mine,and effectively distinguish the step line and the road edge line feature points.At the same time,the curve fitted according to the feature points has a good effect and truly reflects the actual position of the step line.The above analysis provides a new solution for the efficient measurement of step lines in open-pit mines.
作者
王继野
WANG Jiye(China Railway 19th Bureau Group Mining Investment Co.,Ltd.,Beijing 100161,China)
出处
《金属矿山》
CAS
北大核心
2022年第9期155-160,共6页
Metal Mine
关键词
露天矿山测量
台阶线
特征点
自适应
高程特征
三次
B
样条曲线
open-pie mine survey
step line
feature point
self-adaptation
elevation feature
cubic B-spline curve
