Extraction of rod-like objects from vehicle-borne LiDAR data

A rod-like objects extraction method based on clustering is presented. Firstly, project the original point clouds onto the horizontal plane, divide them into grids, and take a single grid as data processing unit to remove the ground points; Secondly, make the grid based on processing data for point clouds detection and numbered, give the same attribute values and cluster the object points using eight neighborhood search method. Then, take the clustered single point clouds as processing units, take advantage of various object features, such as height, density projection, the projection area and shape to exclude the other object points progressively, and achieve the fine extraction of the rod-like objects. The experiment tests the validity of the method described in the text of the extraction of the rod-like objects in road environment.