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An Improved 3D Surface Reconstruction Method Based on Three Wavelength Phase Shift Profilometry

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Artificial Intelligence and Robotics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 752))

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Abstract

In order to reduce the noise points when measure the shape of 3D object using Phase Shift Profilometry (PSP) methods, in this paper we propose a novel Three Wave Length PSP (TWPSP) method. Firstly, the direct problems of equivalent wavelength and unwrapped phase are analyzed. Then, the solution of unwrapping method for TWPSP is derived. Finally, based on the global phase filtering the phase noises are reduced. We simulated and compared the proposed TWPSP and the classical TWPSP. Experiential results shown that the noises are greatly restrained. Since the proposed method does not need to calculate the equivalent phase maps, the implement is improved than the classical TWPSP.

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Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Tianjin Polytechnic University, Tianjin, China

    Mingjun Ding, Jiangtao Xi, Guangxu Li & Philip O. Ogunbona

  2. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, Australia

    Jiangtao Xi & Philip O. Ogunbona

  3. School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin, China

    Limei Song

Authors
  1. Mingjun Ding
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  2. Jiangtao Xi
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  3. Guangxu Li
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  4. Limei Song
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  5. Philip O. Ogunbona
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Corresponding author

Correspondence to Guangxu Li .

Editor information

Editors and Affiliations

  1. Department of Mechanical and Control Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

    Huimin Lu

  2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Xing Xu

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Ding, M., Xi, J., Li, G., Song, L., Ogunbona, P.O. (2018). An Improved 3D Surface Reconstruction Method Based on Three Wavelength Phase Shift Profilometry. In: Lu, H., Xu, X. (eds) Artificial Intelligence and Robotics. Studies in Computational Intelligence, vol 752. Springer, Cham. https://doi.org/10.1007/978-3-319-69877-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-69877-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69876-2

  • Online ISBN: 978-3-319-69877-9

  • eBook Packages: EngineeringEngineering (R0)

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