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The Visual Computer

, Volume 34, Issue 5, pp 659–673 | Cite as

A self-adaptive segmentation method for a point cloud

  • Yuling Fan
  • Meili Wang
  • Nan Geng
  • Dongjian He
  • Jian Chang
  • Jian J. Zhang
Original Article

Abstract

The segmentation of a point cloud is one of the key technologies for three-dimensional reconstruction, and the segmentation from three-dimensional views can facilitate reverse engineering. In this paper, we propose a self-adaptive segmentation algorithm, which can address challenges related to the region-growing algorithm, such as inconsistent or excessive segmentation. Our algorithm consists of two main steps: automatic selection of seed points according to extracted features and segmentation of the points using an improved region-growing algorithm. The benefits of our approach are the ability to select seed points without user intervention and the reduction of the influence of noise. We demonstrate the robustness and effectiveness of our algorithm on different point cloud models and the results show that the segmentation accuracy rate achieves 96%.

Keywords

Point cloud Segmentation Seed point Region growing 

Notes

Acknowledgements

This work was partially funded by the National High-tech research and Development Program (863 Program: 2013AA10230402), National Natural Science Foundation of China (61402374), and the China Postdoctoral Science Foundation (2014M562457). The authors acknowledge the authors of [26], Shenzhen Key Lab of Visual Computing and Visual Analytics for the source data and the models.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Yuling Fan
    • 1
  • Meili Wang
    • 1
  • Nan Geng
    • 1
  • Dongjian He
    • 2
  • Jian Chang
    • 3
  • Jian J. Zhang
    • 3
  1. 1.College of Information EngineeringNorthwest A&F UniversityXianyangChina
  2. 2.College of Mechanical and Electronic EngineeringNorthwest A&F UniversityXianyangChina
  3. 3.National Centre for Computer Animation, Media SchoolBournemouth UniversityBournemouthUK

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