  Tree skeleton plays an important role in tree structure analysis, forest
inventory and ecosystem monitoring. However, it is a challenge to extract a
skeleton from a tree point cloud with complex branches. In this paper, an
automatic and fast tree skeleton extraction method (FTSEM) based on voxel
thinning is proposed. In this method, a wood-leaf classification algorithm was
introduced to filter leaf points for the reduction of the leaf interference on
tree skeleton generation, tree voxel thinning was adopted to extract raw tree
skeleton quickly, and a breakpoint connection algorithm was used to improve the
skeleton connectivity and completeness. Experiments were carried out in Haidian
Park, Beijing, in which 24 trees were scanned and processed to obtain tree
skeletons. The graph search algorithm (GSA) is used to extract tree skeletons
based on the same datasets. Compared with GSA method, the FTSEM method obtained
more complete tree skeletons. And the time cost of the FTSEM method is
evaluated using the runtime and time per million points (TPMP). The runtime of
FTSEM is from 1.0 s to 13.0 s, and the runtime of GSA is from 6.4 s to 309.3 s.
The average value of TPMP is 1.8 s for FTSEM, and 22.3 s for GSA respectively.
The experimental results demonstrate that the proposed method is feasible,
robust, and fast with a good potential on tree skeleton extraction.
