| Issue |
J. Eur. Opt. Soc.-Rapid Publ.
Volume 13, Number 1, 2017
|
|
|---|---|---|
| Article Number | 40 | |
| Number of page(s) | 12 | |
| DOI | https://doi.org/10.1186/s41476-017-0068-2 | |
| Published online | 20 December 2017 | |
Research
Quantitative coating thickness determination using a coefficient-independent hyperspectral scattering model
1
Aerospace Non-Destructive Testing Laboratory, Delft University of Technology, Kluyverweg 1, 2600 GB, Delft, The Netherlands
2
Department of Imaging Physics, Delft University of Technology, Lorentzweg 1, 2628 CJ, Delft, The Netherlands
Received:
31
August
2017
Accepted:
28
November
2017
Background: Hyperspectral imaging is a technique that enables the mapping of spectral signatures across a surface. It is most commonly used for surface chemical mapping in fields as diverse as satellite remote sensing, biomedical imaging and heritage science. Existing models, such as the Kubelka-Munk theory and the Lambert-Beer law also relate layer thickness with absorption, and in the case of the Kubelka-Munk theory scattering, however they are not able to fully describe the complex behavior of the light-layer interaction.
Methods: This paper describes a new approach for hyperspectral imaging, the mapping of coating surface thickness using a coefficient-independent scattering model. The approach taken in this paper is to model the absorption and scattering behavior using a developed coefficient-independent model, calibrated using reference sample thickness measurements performed with optical coherence tomography.
Results: The results show that this new model, by considering the spectral variation that can be recorded by the hyperspectral imaging camera, is able to measure coatings of 250 μm thickness with an accuracy of 11 μm in a fast and repeatable way.
Conclusions: The new coefficient-independent scattering model presented can successfully measure the thickness of coatings from hyperspectral imaging data.
Key words: Absorption / Scattering / Coating thickness measurement / Hyperspectral imaging / Quantitative imaging
© The Author(s) 2017
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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