基于最小生成树的点云数据去噪方法

A Method to Remove Outliers of Point Cloud with the Minimum Spanning Tree Clustering Algorithm

为了保证重建的模型质量或模型配准的精度,提出采用基于最小生成树的聚类算法将点云数据中的噪点去除,并在尸体股骨上对这种骨表面点云数据的获取方法的可行性和噪点去除方法的有效性进行了验证。实验证明,这种数据获取方法是可行的,所采用的噪点去除方法也是有效的。

In order to improve the quality of the minimum spanning tree clustering algorithm. The data are tested in body experiments. Experiments method to remove outliers is effective. reconstructed model, outliers are removed with the acquisition and pretreatment methods for point cloud show that this acquisition method is feasible and the