Open AccessSTREET-SCENE TREE SEGMENTATION FROM MOBILE LASER SCANNING DATA
Author(s) -
H. Guan,
S. Cao,
Y. Yu,
J. Li,
N. Liu,
P. Chen,
Yanling Li
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b3-221-2016
Subject(s) - segmentation , artificial intelligence , tree (set theory) , computer science , cluster analysis , computer vision , laser scanning , scale space segmentation , region growing , point cloud , pattern recognition (psychology) , mobile mapping , terrain , euclidean distance , voxel , image segmentation , geography , mathematics , laser , cartography , mathematical analysis , physics , optics
Our work addresses the problem of extracting trees from mobile laser scanning data. The work is a two step-wise strategy, including terrain point removal and tree segmentation. First, a voxel-based upward growing filtering is proposed to remove terrain points from the mobile laser scanning data. Then, a tree segmentation is presented to extract individual trees via a Euclidean distance clustering approach and Voxel-based Normalized Cut (VNCut) segmentation approach. A road section data acquired by a RIEGL VMX-450 system are selected for evaluating the proposed tree segmentation method. Qualitative analysis shows that our algorithm achieves a good performance.