An Accurate and Robust Region-Growing Algorithm for Plane Segmentation of TLS Point Clouds Using a Multiscale Tensor Voting Method

Hao Wu, Xiang Zhang, Wenzhong Shi, Shaoxian Song, Abraham Cardenas-Tristan, Kui Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


The accuracy and robustness of plane segmentation using a region-growing algorithm remains an important and challenging topic for terrestrial laser scanning point clouds. The plane segmentation of a region-growing algorithm depends heavily on the seed point, as there are currently no universally valid criteria. This article proposes a multiscale tensor voting method (MSTVM) to determine the appropriate seed point for the region-growing algorithm. A comprehensive plane strength indicator calculated by the semivariogram model has been established to assess whether a certain point is suitably considered as a seed point or not. A point cloud containing 17, 881 points in a 400-m2 area was selected to validate the proposed algorithm. The results suggest that the scale range calculated by the semivariogram model can effectively mitigate the scale effect of the tensor voting method (TVM). The comprehensive plane strength of our proposed algorithm in seed point determination is shown to be more salient than the principal component analysis and the TVM. The findings further reveal that the utility of the MSTVM-based region-growing algorithm can achieve more accurate plane segmentation results and perform with better robustness in noisy point clouds. This allows our proposed method to be more widely applied to complex real situations.

Original languageEnglish
Article number8827933
Pages (from-to)4160-4168
Number of pages9
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Issue number10
Publication statusPublished - Oct 2019


  • Multiscale tensor voting method (MSTVM)
  • plane segmentation
  • region-growing algorithm
  • seed point determination
  • semivariogram
  • terrestrial laser scanning (TLS)

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science

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