An illumination-invariant phase-shifting algorithm for three-dimensional profilometry

Abstract

Uneven illumination is a common problem in real optical systems for machine vision applications, and it contributes significant errors when using phase-shifting algorithms (PSA) to reconstruct the surface of a moving object. Here, we propose an illumination-reflectivity-focus (IRF) model to characterize this uneven illumination effect on phase-measuring profilometry. With this model, we separate the illumination factor effectively, and then formulate the phase reconstruction as an optimization problem. To simplify the optimization process, we calibrate the uneven illumination distribution beforehand, and then use the calibrated illumination information during surface profilometry. After calibration, the degrees of freedom are reduced. Accordingly, we develop a novel illumination-invariant phase-shifting algorithm (II-PSA) to reconstruct the surface of a moving object under an uneven illumination environment. Experimental results show that the proposed algorithm can improve the reconstruction quality both visually and numerically. Therefore, using this IRF model and the corresponding II-PSA, not only can we handle uneven illumination in a real optical system with a large field of view (FOV), but we also develop a robust and efficient method for reconstructing the surface of a moving object.

Optical Inspection Systems for Axisymmetric Parts with Spatial 2D Resolution

“…Notes for algorithm for complex compensation of errors: 1. correction of the horizontal component, takes into account the rotation of the test object relative to the vertical axis by changing the parameter z of expression (7).…”

“…As examples of the use of tools that implement the optical method of control, one can cite the tasks of assessing the cryolite ratio [2], determining the position of the electrodes of ore-thermal furnaces [3] in the metallurgical industry, assessing the efficiency of flotation [4] at obage fabrics, monitoring of self-oscillations in the process of cutting materials based on the registration of the light field [5] and roughness measurement [6,7] in mechanical engineering. Technical vision systems are also used in studies of the mechanical properties of bulk materials [8,9].…”

A three-dimensional imaging system for surface profilometry of moving objects

“…This would cause an inaccurate measurement of its dimension, and introduce errors on the reconstructed surface when the PCB is moving along a conveyor belt [7]. Second, there may be uneven illumination on such a large FOV, which results in erroneous and unstable surface reconstruction results [8], [9]. Third, most of the conventional surface reconstruction algorithms cannot work well, as they normally would not take into account the movement of the object under inspection.…”