Tree Segmentation from Scanned Scene Data

Tree segmentation is an important step in tree reconstruction from scanned data. A new method is presented for automatic extraction of single objects from a complex scene. The proposed method can be used as a solution for tree segmentation from 3D point cloud data with few restrictions, where many complex objects are included in the scene, like trees, building, cars, and so on. The scene data is initially segmented into several small regions according to the distances between points. A weighted combination is constructed on distances and normal angles in each small region for further segmentation. The minimization of the function will be used to determine whether these regions will be merged or not. This method is tested on several data sets. Effective segmental results demonstrated that this approach could be applied to nondestructive measurements in forestry.