Deep learning enabled single-shot absolute phase recovery in high-speed composite fringe pattern profilometry of separated objects

Maciej Trusiak; Malgorzata Kujawinska

doi:10.29026/oea.2023.230172

Journals >Opto-Electronic Advances >Volume 6 >Issue 12 >Page 230172 > Article

Opto-Electronic Advances
Vol. 6, Issue 12, 230172 (2023)

Deep learning enabled single-shot absolute phase recovery in high-speed composite fringe pattern profilometry of separated objects

Maciej Trusiak^* and Malgorzata Kujawinska^**

Author Affiliations

Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli Street, Warsaw 02-525, Poland

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DOI: 10.29026/oea.2023.230172 Cite this Article

Maciej Trusiak, Malgorzata Kujawinska. Deep learning enabled single-shot absolute phase recovery in high-speed composite fringe pattern profilometry of separated objects[J]. Opto-Electronic Advances, 2023, 6(12): 230172 Copy Citation Text

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Fig. 1. Back cover of Volume 5, Issue 5 of OEA in 2022.

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Possible future extension of the proposed DCFPP technique: (a) the example triple-frequency projected vertical and cross fringe patterns and their spectra, (b) the hardware system and (c) the enhanced shape reconstruction using cross fringe pattern and two channel reconstructions for vertical and horizontal composite fringe patterns.

Fig. 2. Possible future extension of the proposed DCFPP technique: (a) the example triple-frequency projected vertical and cross fringe patterns and their spectra, (b) the hardware system and (c) the enhanced shape reconstruction using cross fringe pattern and two channel reconstructions for vertical and horizontal composite fringe patterns.

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