KEYWORDS: Phase unwrapping, Deep learning, 3D metrology, Shadows, Semantics, Network architectures, Education and training, Visualization, Time metrology, Phase reconstruction
Single-frame high-precision 3D measurement using deep learning has been widely studied for its minimal measurement time. However, the long physical and semantic distances make the end-to-end absolute phase reconstruction of single-frame grating challenging. To tackle this difficulty, we propose the DSAS-S2AP-X (Dual-Stage Auxiliary Supervision Network for Single-Frame to Absolute Phase Prediction with X) strategy, which includes the secondary highest frequency unwrapped phase and the highest frequency wrapped phase supervision branches. It combines a multi-frequency temporal phase unwrapping model with existing regression networks X (meaning arbitrary). Experimental results have shown that the DSAS-S2AP-ResUNet34 strategy can reduce the mean absolute error (MAE) and root mean square error (RMSE) of the absolute phase by 34.3% and 25.9% respectively based on the ResUNet34.
The three-frequency heterodyne phase shift profilometry is widely used in high-precision 3D reconstruction. However, the high accuracy comes at the cost of requiring many projected frames, which increases measurement time and decreases measurement efficiency. To address this challenge, we propose a rapid, high-precision absolute phase acquisition method called X+1+1, which fully integrates the accuracy advantages of the multi-frequency n-step heterodyne phase-shifting method and the speed advantages of the Modified Fourier transform profilometry (MFTP). The highest frequency gratings use the standard X-step phase-shifting method to determine the wrapped phase, ensuring high unwrapping accuracy and obtaining background light intensity. For intermediate and low frequencies, a single-frame grating and the Backgroundgenerated Modified Fourier transform profilometry (BGMFTP) are used to solve each wrapped phase to reduce the measurement time. Finally, the heterodyne method processes these three-frequency wrapped phases to obtain the absolute phase. Experimental results demonstrated the high accuracy and speed of this method in the 3D measurement process. Compared to traditional Fourier transform profilometry, the X+1+1 method has a 53% improvement in accuracy, while maintains the same level of performance as the three-frequency four-step heterodyne method in continuous non-marginal flat areas and the projection time was reduced by approximately 50%. The proposed X+1+1 method provides a new solution for balancing speed and accuracy in the application and promotion of structured-light 3D measurement.
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