A smartphone image-based method for the colorimetric characterization of historical pigments in mural paintings.

Autor:	Sáez-Hernández R; Department of Analytical Chemistry, Faculty of Chemistry, University of Valencia. C/Dr. Moliner, 50, Burjassot, 46100, Spain., Luque MJ; Department of Optics and Optometry and Vision Sciences, Faculty of Chemistry, University of Valencia. C/Dr. Moliner, 50, Burjassot, 46100, Spain., Morales-Rubio Á; Department of Analytical Chemistry, Faculty of Chemistry, University of Valencia. C/Dr. Moliner, 50, Burjassot, 46100, Spain., Cervera ML; Department of Analytical Chemistry, Faculty of Chemistry, University of Valencia. C/Dr. Moliner, 50, Burjassot, 46100, Spain., Mauri-Aucejo AR; Department of Analytical Chemistry, Faculty of Chemistry, University of Valencia. C/Dr. Moliner, 50, Burjassot, 46100, Spain.
Jazyk:	angličtina
Zdroj:	MethodsX [MethodsX] 2024 May 17; Vol. 12, pp. 102746. Date of Electronic Publication: 2024 May 17 (Print Publication: 2024).
DOI:	10.1016/j.mex.2024.102746
Abstrakt:	In this article, the detailed description of a smartphone-based analytical method to turn a smartphone into a colorimeter is described and applied to mural painting replicas. The method consists of a camera characterization process, to estimate CIELAB values from RGB camera responses, correcting for potential experimental interferences, like the effect of the lighting/capture geometry or software for color modification and enhancement. Next, the estimated CIELAB descriptors were used to build a chemometric Support Vector Classifier to objectively distinguish among the colors of the different pigments. The method was validated in terms of color reproduction and classification performance.•A smartphone-based method is described to capture mural painting color.•A color gamut-specific camera characterization procedure is developed and the performance of the smartphone-based colorimeter is compared with a spectrophotometer.•A classification method based on the estimated CIELAB descriptors is validated in terms of classification performance. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2024 The Authors.)
Databáze:	MEDLINE
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