Point cloud data reduction methods of octree based coding and neighborhood search
Laser scanning technology makes it easy to obtain high accuracy and speed of the surface of the part model information. The amount of data generated is enormous, and therefore need to be streamlined. Based on the reverse engineering point cloud data pretreatment, analyzes the existing data streamline method, this paper puts forward a kind of insufficient based on spatial octree non uniform grid and combining the neighborhood search algorithm. By octree record division process, thus make neighborhood search method are confined to sampling the bounding box and around where the bounding box. A large number of real data results show that: the algorithm can improve the quality of search neighboring points, and ultimately achieve the good effect of the streamlining.
Proceedings of 2011 International Conference on Electronic Mechanical Engineering and Information Technology