Uncertainty of digital fringe projection measurement caused by structural parameters

Digital fringe projection (DFP) has been widely applied in three-dimensional (3D) precision measurement owing to its advantages of non-contact, high-precision, and large-field measurement. The DFP measurement system undergoes a calibration process to define the parameters that reconstruct the surface points from the camera images. As the DFP system is nonlinear, evaluating the measurement uncertainty caused by the calibration deviation of the structural parameters is a great challenge. In this study, we performed an uncertainty analysis based on the binocular vision model of a DFP system. A virtual DFP system based on the structural parameters of the actual system was built to remove the influence of other uncertainty factors. The adaptive Monte Carlo method (AMCM) was used to evaluate the uncertainty caused by the deviation of the parameters during calibration. The model and method for calculating the uncertainty of the DFP system proposed in this study are helpful in better understanding the propagation of the uncertainty of structural parameters, determining the critical factors affecting the measurement uncertainty, and providing a theoretical basis for subsequent error compensation and accuracy improvement for DFP measurement systems.