Using a digital model for fringe projection profilometry optimisation

Fringe projection profilometry (FPP) is a widely used technique for measuring object surface form and three-dimensional (3D) geometry, capable of delivering high-precision, high-resolution measurements when paired with suitable cameras and projectors. However, in practical deployments, identifying parameter configurations that maximise precision while satisfying real-world constraints remains challenging. To address this, an automated digital model framework was implemented in Blender, an open-source 3D software package enabling provides a ray-traced rendering environment that accurate simulation of physical systems. The physical setup was replicated in the digital model by matching characterisation quality, gamma response, and characterisation images. Accurate system characterisation using Zhang’s method Zhang (2021) [1], to obtain intrinsic and extrinsic parameters, is shown to be critical for achieving high precision. Using this digital model, systematic exploration and optimisation of key parameters were demonstrated, including phase-shift count, camera-projector spacing, and fringe density. These parameters span both system geometry (e.g., camera-projector positioning) and algorithmic choices, such as 2D phase-shifting and unwrapping methods Zuo et al. (2016) [2]. Three measurement artefacts, representative of real-world metrology scenarios, were used to benchmark the system Sims-Waterhouse et al. (2017) [3]. The symmetrical mean Chamfer distance (SMCD), computed between ground-truth and reconstructed meshes, was used to evaluate reconstruction quality. After single-objective optimisation within the digital model, transferring the parameters to the physical system reduced the number of required images per measurement by 41% (from 36 to 21). A reduction of 74.0% mean SMCD was also achieved by altering the fringe pattern stripe count. A 36.9% mean SMCD was obtained by adjusting the camera and projector spacing purely in the digital model. These results demonstrate that optimising an FPP system using a digital model can significantly improve reconstruction quality while reducing measurement effort in real-world metrology applications.