散乱点云曲面边界的二次提取算法

Secondary Extraction Algorithm for Scattered Point Cloud Surface Boundary

针对点云曲面边界提取算法计算量大、时间耗费多的问题,提出一种点云曲面的二次边界提取算法。采用空间包围盒法将点云曲面均匀地分为若干个小立方体,将每个点都放入一个立方体内,并通过每个立方体周围非空子立方体的个数以及分布情况提取边界子立方体。结合点云曲面数据点的分布特征,在边界子立方体内将目标点的所有K近邻点投影到以目标点为中心的平面上,计算投影点与中心点形成的向量与某条坐标轴的夹角,通过判断其是否满足预先设定的条件来判定目标点是否为边界点。实验结果表明,该方法可有效减少计算量,提高提取精度。

To overcome the defects of large amounts of calculation and long duration time consuming and calculation amount of current point cloud surface boundary extraction algorithms,a point cloud surface secondary boundary extraction algorithm is put forward.First of all,the space bounding box method is used to divide the 3D model into several sub cubes evenly.Every cloud point is put in a small cube.The boundary sub cubes are identified by the number and distribution of the sub cubes which has any cloud point.Then,according to the distribution of the data points,every point that is in a boundary sub cube and its K neighbor points are projected to a flat surface.At last,the boundary point is identified according to the principle that the angle between one axis and the vector formed by projected point and center point meets the preset conditions.Experimental results show that the secondary extraction algorithm for scattered point cloud surface boundary can save time and improve precision.