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Tree skeleton plays an important role in tree structure analysis, forestinventory and ecosystem monitoring. However, it is a challenge to extract askeleton from a tree point cloud with complex branches. In this paper, anautomatic and fast tree skeleton extraction method (FTSEM) based on voxelthinning is proposed. In this method, a wood-leaf classification algorithm wasintroduced to filter leaf points for the reduction of the leaf interference ontree skeleton generation, tree voxel thinning was adopted to extract raw treeskeleton quickly, and a breakpoint connection algorithm was used to improve theskeleton connectivity and completeness. Experiments were carried out in HaidianPark, Beijing, in which 24 trees were scanned and processed to obtain treeskeletons. The graph search algorithm (GSA) is used to extract tree skeletonsbased on the same datasets. Compared with GSA method, the FTSEM method obtainedmore complete tree skeletons. And the time cost of the FTSEM method isevaluated using the runtime and time per million points (TPMP). The runtime ofFTSEM 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.

Fast tree skeleton extraction using voxel thinning based on tree point cloud