散乱数据点云边界特征自动提取算法

Automatic extraction of boundary characteristic from scatter data

提出一种散乱数据点云边界特征自动提取算法,该算法采用R*-tree动态空间索引结构组织散乱数据点云的拓扑关系,基于该结构获取采样点的k近邻点作为局部型面参考数据,以最小二乘法拟合该数据的微切平面,并将其向微切平面投影,根据采样点与其k近邻所对应投影点连线的最大夹角识别散乱点云边界特征.实例验证该算法可快速、准确地提取散乱数据点云的边界特征.

A new automatic extraction algorithm of scatter data boundary characteristic was proposed. The topology of scattered points was constructed using R^＊ -tree dynamic spacial index structure. The k neighbors of the sampling point was obtained as local model surface reference data based on the dynamic spacial index structure and the local model surface reference data was projected to the tangency plane fitted by using least squares method. The boundary characteristic of scatter data could be extracted according to the maximum angle between the connections of the projections of the sampling point and its k neighbors. The accurately and availably extraction of scatter data boundary characteristic was proved by the application examples.