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Evaluating parametric uncertainty using non-linear regression in fringe projection

Gayton, George; Isa, Mohammed; Leach, Richard K.


George Gayton


Optical coordinate measurement systems, such as fringe projection systems, offer fast, high-density measurements of arbitrary surface topographies. The versatility, speed and information density of fringe projection measurements make them attractive as in-situ measurement devices and autonomous inspection systems. However, the complex nature of the measurement process makes evaluating uncertainty from a fringe projection measurement complex – even in the hypothetical simple case where the accuracy of a measurement is limited only by the accuracy in the quantities that define a measurement from an indication; named system parameters here. In this paper, by validating a series of assumptions, a method to explore the uncertainty in the system parameters of a fringe projection system is given. The results of this investigation imply the common distortion model (the Brown-Conrady model) is not specific enough to the camera or projector of a fringe projection system to evaluate its uncertainty.


Gayton, G., Isa, M., & Leach, R. K. (2023). Evaluating parametric uncertainty using non-linear regression in fringe projection. Optics and Lasers in Engineering, 162, Article 107377.

Journal Article Type Article
Acceptance Date Nov 6, 2022
Online Publication Date Dec 2, 2022
Publication Date 2023-03
Deposit Date Dec 11, 2022
Publicly Available Date Dec 15, 2022
Journal Optics and Lasers in Engineering
Print ISSN 0143-8166
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 162
Article Number 107377
Keywords Electrical and Electronic Engineering; Mechanical Engineering; Atomic and Molecular Physics, and Optics; Electronic, Optical and Magnetic Materials
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