11 July 2017 Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization
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Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the data.
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Hend Mahgoub, Hend Mahgoub, John R. Gilchrist, John R. Gilchrist, Thomas Fearn, Thomas Fearn, Matija Strlič, Matija Strlič, } "Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization", Proc. SPIE 10331, Optics for Arts, Architecture, and Archaeology VI, 103310P (11 July 2017); doi: 10.1117/12.2271971; https://doi.org/10.1117/12.2271971

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