A Fringe Phase Extraction Method Based on Neural Network

Wenxin Hu, Hong Miao, Keyu Yan, Yu Fu
2021 Sensors  
In optical metrology, the output is usually in the form of a fringe pattern, from which a phase map can be generated and phase information can be converted into the desired parameters. This paper proposes an end-to-end method of fringe phase extraction based on the neural network. This method uses the U-net neural network to directly learn the correspondence between the gray level of a fringe pattern and the wrapped phase map, which is simpler than the exist deep learning methods. The results
more » ... simulation and experimental fringe patterns verify the accuracy and the robustness of this method. While it yields the same accuracy, the proposed method features easier operation and a simpler principle than the traditional phase-shifting method and has a faster speed than wavelet transform method.
doi:10.3390/s21051664 pmid:33670957 pmcid:PMC7957713 fatcat:npptgoqdvrhs5cfog5qv5njbh4