Paper
15 October 2012 Reflectance variability of surface coatings reveals characteristic eigenvalue spectra
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Abstract
We have examined the trial-to-trial variability of the reflectance spectra of surface coatings containing effect pigments. Principal component analysis of reflectances was done at each detection angle separately. A method for classification of principal components is applied based on the eigenvalue spectra. It was found that the eigenvalue spectra follow characteristic power laws and depend on the detection angle. Three different subsets of principal components were examined to separate the relevant spectral features related to the pigments from other noise sources. Reconstruction of the reflectance spectra by taking only the first subset indicated that reflectance variability was higher at near-specular reflection, suggesting a correlation with the trial-to-trial deposition of effect pigments. Reconstruction by using the second subset indicates that variability was higher at short wavelengths. Finally, reconstruction by using only the third subset indicates that reflectance variability was not totally random as a function of the wavelength. The methods employed can be useful in the evaluation of color variability in industrial paint application processes.
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José M. Medina, José A. Díaz, and Rui Barros "Reflectance variability of surface coatings reveals characteristic eigenvalue spectra", Proc. SPIE 8495, Reflection, Scattering, and Diffraction from Surfaces III, 849514 (15 October 2012); https://doi.org/10.1117/12.929926
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Cited by 4 scholarly publications.
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KEYWORDS
Principal component analysis

Metallic coatings

Aluminum

Reflectivity

Metals

Standards development

Absorption

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