Deep learning-based single-shot absolute phase retrieval using a triangular-wave embedded fringe coding strategy

Yile Xiao; Yixuan Li; Jiaming Qian

doi:10.1117/12.2667475

27 January 2023 Deep learning-based single-shot absolute phase retrieval using a triangular-wave embedded fringe coding strategy

Yile Xiao, Yixuan Li, Jiaming Qian

Author Affiliations +

Proceedings Volume 12550, International Conference on Optical and Photonic Engineering (icOPEN 2022); 125500A (2023) https://doi.org/10.1117/12.2667475
Event: International Conference on Optical and Photonic Engineering (icOPEN 2022), 2022, ONLINE, China

Abstract

In the field of 3D measurement, fringe projection profilometry attracts the most interest due to its high precision and convenience. However, it is still challenging to retrieve the unambiguous absolute phase from a single fringe image. In this paper, we propose a deep learning-based method for retrieving the absolute phase of triangular-wave embedded fringe images. Through the learning of a large amount of data, we use two neural networks to obtain high-precision wrapped phase and coarse absolute phase from the triangular-wave embedded fringe images respectively so as to obtain accurate fringe order. Combining the wrapped phase and fringe order, we can obtain high-precision absolute phases. The experimental results demonstrate that compared with our previous proposed composite dual-frequency fringe coding strategy, the fringe image of the new triangular-wave embedded fringe coding strategy as the input of the network can obtain the absolute phase with higher accuracy.

Citation Download Citation

Yile Xiao, Yixuan Li, and Jiaming Qian "Deep learning-based single-shot absolute phase retrieval using a triangular-wave embedded fringe coding strategy", Proc. SPIE 12550, International Conference on Optical and Photonic Engineering (icOPEN 2022), 125500A (27 January 2023); https://doi.org/10.1117/12.2667475

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