一种杆状交通设施点云自动提取的方法

An Method of Automatic Extraction of Pole-like Traffic Facilities in Point Clouds

该方法主要分成三个步骤:首先对原始点云进行预处理,将点云分配到二维网格,在每一个二维网格根据局部最低高程滤除地面点,然后再对非地面点进行欧式聚类;对于聚类后的对象,利用迭代最小割算法对混合点云进行分割,分离混合点云中的杆状交通设施;最后,根据杆状交通设施的先验知识和形状知识构建滤波器,从所有的对象点云中检测出杆状交通设施点云。

This method is mainly divided into three steps.First,the original point cloud is preprocessed,and the point cloud is distributed to a two-dimensional grid.In each two-dimensional grid,the ground points are filtered according to the local minimum elevation,and then the non-ground points are Euclidean-distance clustered;then the iterative minimum cut algorithm is used to segment the mixed point cloud,and pole-like traffic facilities are able to be separated from the mixed point cloud;finally,according to prior knowledge and shape knowledge of pole-like traffic facilities,a filter is constructed to detect pole-like traffic facility clouds from all object point clouds.