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金属矿山 ›› 2017, Vol. 46 ›› Issue (10): 67-71.

• 国际矿山测量学术论坛专栏 • 上一篇    下一篇

三维激光扫描点云边界提取研究

杜秋,郭广礼   

  1. 中国矿业大学环境与测绘学院,江苏 徐州 221116
  • 出版日期:2017-10-15 发布日期:2017-10-15
  • 基金资助:

    国家自然科学基金面上项目(编号:51674249),国家自然科学基金应急管理项目(编号:41641036)。

Research on Boundary Extraction of 3D Laser Scanning Point Cloud

Du Qiu,Guo Guangli   

  1. School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China
  • Online:2017-10-15 Published:2017-10-15

摘要: 在数字矿山建设过程中,三维激光扫描仪可快速获得地表或建筑物的点云数据。点云边界不仅作为曲面表达的重要几何特征,而且作为模型求解曲面的定义域,对重建曲面模型的品质和精度起着重要作用。利用激光点云数据进行建模首先需从海量数据当中提取边界区域的采样点。本文提出了一种通过局部型面参考点集拟合微切平面,讨论参考点在对应微切平面上投影点的几何分布来自动提取边界特征的算法。该算法运行速度快,提取结果准确,可适用于各种复杂型面的点云数据。

关键词: 数字矿山, 三维激光扫描, 点云边界, 特征提取, K近邻

Abstract: In the process of digital mine construction,3D laser scanning is used to obtain point cloud data of surface or buildings quickly.The point cloud boundary is not only an important geometric feature to represent surface,but also serves as a model to solve the domain of the surface,which plays an important role in reconstructing the quality and precision of the surface model.It is necessary to extract the boundary points from the mass data in order to model the laser point cloud data.In this paper,a method is proposed to automatically extract the boundary features of the point cloud by discussing the geometric distribution of the local point set projection onto the micro-tangent plane fitted by them.This algorithm could be applied to various point cloud data in complicated surface with its rapid processing speed and accurate extraction result.

Key words: Digital mine, 3D laser scanning, Boundary point, Feature extraction, K-nearest neighbor