Bi-frequency temporal phase unwrapping using deep learning

Wei Yin; Chao Zuo; Shijie Feng; Tianyang Tao; Qian Chen

doi:10.1117/12.2520201

13 May 2019 Bi-frequency temporal phase unwrapping using deep learning

Wei Yin, Chao Zuo, Shijie Feng, Tianyang Tao, Qian Chen

Proceedings Volume 10991, Dimensional Optical Metrology and Inspection for Practical Applications VIII; 109910D (2019) https://doi.org/10.1117/12.2520201
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

In fringe projection profilometry (FPP), multi-frequency phase unwrapping, as a classical algorithm for temporal phase unwrapping (TPU), can eliminate the phase ambiguities and obtain the unwrapped phase with the aid of additional wrapped phase maps with different fringe periods. However, based on the principle of multi-frequency phase unwrapping, it needs multiple groups of fringe patterns with different fringe periods to eliminate the phase ambiguities of the wrapped phase with high-frequency, which is not suitable for high-speed 3D measurement. If two frequency fringe patterns are only projected, the reliability of multi-frequency phase unwrapping will be decreased significantly. Inspired by deep learning techniques, in this study, we demonstrate that the deep neural networks can learn to perform temporal phase unwrapping after appropriate training, which substantially improves the reliability of phase unwrapping compared with the traditional multi-frequency TPU approach even when high-frequency fringe patterns are used. In our experiment, a challenging problem in TPU is that the unwrapped phase of 64-period fringe patterns cannot be directly unwrapped by only using a single-frequency phase, but it can be easily resolved by our method. Experimental results demonstrate the temporal phase unwrapping method using deep learning provides the best unwrapping reliability to realize the absolute 3D measurement for objects with complex surfaces.

Conference Presentation

Citation Download Citation

Wei Yin, Chao Zuo, Shijie Feng, Tianyang Tao, and Qian Chen "Bi-frequency temporal phase unwrapping using deep learning", Proc. SPIE 10991, Dimensional Optical Metrology and Inspection for Practical Applications VIII, 109910D (13 May 2019); https://doi.org/10.1117/12.2520201

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