基于空间网格划分的点云质量检测算法

A Point Cloud Quality Detection Algorithm Based on Spatial Meshing

随着三维激光扫描技术的快速发展,它以非接触性、高密度、高精度、数字化、自动化等特点,被广泛用于多个邻域,其中在建筑物变形监测领域的应用也越来越广泛。针对扫描设备获取的大量变形监测数据,快速地统计出前后两期数据变化差异值,提出了一种基于空间网格划分的点云质量检测算法,算法通过对不同期点云模型进行空间网格划分,依据网格进行点云邻域搜索,并根据点云变化差异值给点云赋予不同色谱颜色值,最后进行直观的两期点云变化差异可视化,并绘制出统计信息图。研究表明,该算法能够快速地分析对比两期点云数据,输出变化差异统计信息,能够为工程的运营提供快速的安全指导参考。

With the rapid development of 3D laser scanning technology,it has been used widely in many areas because its characteristics of non-contact,high-density,high-accuracy,digitization. In addition,it is being more and more widely used in the area of deformation monitoring of buildings. For the large amount of deformation monitoring data obtained by scanning equipments and how to quickly and statistically figure out the difference in data before and after,the paper presents a point cloud quality detection algorithm based on spatial meshing. This algorithm does spatial meshing on point cloud models in different periods,searches point cloud areas according to the grid,and endows the point cloud with different color values based on the difference of point cloud change. Subsequently,the difference between point clouds in two periods can be visualized and the statistical information figure can be drawn. The experimental results have showed that,this algorithm can quickly compare the data of point clouds in two periods,and output statistical information of difference. It is able to offer fast security guidance to project operation.