X-ray fluorescence (XRF) and reflectance spectroscopy (RS) are commonly used for the characterization of painting materials. It is well known that the former provides the chemical fingerprint of the pictorial layers, while the latter returns the molecular description of the pigments constituting the uppermost layers. Even if these two techniques cannot unveil the stratigraphy, their synergetic application well describes the materials employed for realizing the panels and represents a key turn for non-invasive scientific analysis of works of art. However, the potential of the cross-comparison between XRF and RS is not fully exploited yet. The measurement points often barely match, and they are usually few isolated spots spread over the whole surface of the painting; these facts limit the mutual exchange of information between the data sets and can lead to losing details. In this scenario, XRF mapping (MA-XRF) and hyperspectral reflectance imaging (HRI) provide a connection channel that promises to be a decisive tool to strengthen the relationship between X-ray fluorescence and reflectance spectroscopy and, therefore, to deepen the knowledge about the case studies. Due to the spatial localization of the information they contain, the maps provide not only a straightforward reference for comparing the data but also a three-dimensional collection of elemental and molecular images. By applying computer vision and statistical methods such as spectral angle mapper (SAM), it is possible to implement an innovative approach that exploits the elemental features, obtained from XRF spectra, to improve the comprehension of the molecular aspects given by RS, and vice versa. Once we discussed the main issues behind our approach, we applied it to analyze the painting Chariot Race by Giorgio De Chirico (1928–1929, oil on canvas, Pinacoteca di Brera, Milan, Italy). The results reflect the complexity of the painting, and even if only some of the spectra identified by the method as peculiar are ascribable to recognizable pigments, the mutual correspondence between elemental distributions and SAM maps defines a mixture of materials that matches the description given by the artist in his “Small Treatise on Pictorial Technique” (De Chirico in Abscondita, 2019).

An innovative protocol for the study of painting materials involving the combined use of MA-XRF maps and hyperspectral images / A. Galli, M. Caccia, S. Caglio, L. Bonizzoni, I. Castiglioni, M. Gironda, R. Alberti, M. Martini. - In: THE EUROPEAN PHYSICAL JOURNAL PLUS. - ISSN 2190-5444. - 137:1(2022), pp. 22.1-22.16. [10.1140/epjp/s13360-021-02183-4]

An innovative protocol for the study of painting materials involving the combined use of MA-XRF maps and hyperspectral images

L. Bonizzoni;
2022

Abstract

X-ray fluorescence (XRF) and reflectance spectroscopy (RS) are commonly used for the characterization of painting materials. It is well known that the former provides the chemical fingerprint of the pictorial layers, while the latter returns the molecular description of the pigments constituting the uppermost layers. Even if these two techniques cannot unveil the stratigraphy, their synergetic application well describes the materials employed for realizing the panels and represents a key turn for non-invasive scientific analysis of works of art. However, the potential of the cross-comparison between XRF and RS is not fully exploited yet. The measurement points often barely match, and they are usually few isolated spots spread over the whole surface of the painting; these facts limit the mutual exchange of information between the data sets and can lead to losing details. In this scenario, XRF mapping (MA-XRF) and hyperspectral reflectance imaging (HRI) provide a connection channel that promises to be a decisive tool to strengthen the relationship between X-ray fluorescence and reflectance spectroscopy and, therefore, to deepen the knowledge about the case studies. Due to the spatial localization of the information they contain, the maps provide not only a straightforward reference for comparing the data but also a three-dimensional collection of elemental and molecular images. By applying computer vision and statistical methods such as spectral angle mapper (SAM), it is possible to implement an innovative approach that exploits the elemental features, obtained from XRF spectra, to improve the comprehension of the molecular aspects given by RS, and vice versa. Once we discussed the main issues behind our approach, we applied it to analyze the painting Chariot Race by Giorgio De Chirico (1928–1929, oil on canvas, Pinacoteca di Brera, Milan, Italy). The results reflect the complexity of the painting, and even if only some of the spectra identified by the method as peculiar are ascribable to recognizable pigments, the mutual correspondence between elemental distributions and SAM maps defines a mixture of materials that matches the description given by the artist in his “Small Treatise on Pictorial Technique” (De Chirico in Abscondita, 2019).
Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/899593
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