The aim of this work was to characterize the palette and painting technique used for the realization of three late sixteenth century paintings from “Galleria dell'Accademia Nazionale di San Luca” in Rome attributed to Cavalier d’Arpino (Giuseppe Cesari), namely “Cattura di Cristo” (Inv. 158), “Autoritratto” (Inv. 546) and “Perseo e Andromeda” (Inv. 221). This study presents a diagnostic campaign that was carried out with non-invasive and portable techniques such as Energy Dispersive X-ray Fluorescence (ED-XRF) spectrometry, Fiber Optics Reflectance Spectroscopy (FORS) and Multispectral (MS) Imaging. This work was part of a project founded by Regione Lazio and MUR (“IMAGO - Multispectral Imaging for Art, Gamification and hOlografic reality” project). FORS and ED-XRF analyses allowed the preliminary characterization of the pictorial materials in a reliable non-invasive way. In particular, it was possible to identify most of the pigments used for the production of the paintings attributed to Cavalier d’Arpino. The MS images were acquired between the ultraviolet and the near-infrared regions of the electromagnetic spectrum (UV-Vis-NIR) by using different illumination sources and a cooled CCD camera equipped with interferential filters. It was possible to observe significant differences between the visible and the NIR images with some details of the paintings which resulted transparent in the infrared region. Furthermore, MS images were investigated in-depth by the application of data clustering algorithms to obtain semantic segmentation. This methodology exploits the information reported in MS images to generate a pixel classification based on statistical methods together with image analysis techniques. The result provides both an extrapolation of salient parts of the work as well as a better perception of some details. The combined results of this work allowed to investigate in-depth the production of one of the main painters from Italian mannerism.
Non-invasive investigation of three paintings attributed to Cavalier d’Arpino by means of ED-XRF, FORS and Multispectral Imaging / Bruni, Vittoria; Colonna, Edoardo; Felici, Anna Candida; Mazzei, Gianluca; Moffa, Candida; Pascarella, Annalisa; Pelosi, Francesca; Pitolli, Francesca; Porzio, Fabio; Vitulano, Domenico. - (2023). (Intervento presentato al convegno Technart2023. International conference on analytical techniques in art and cultural heritage tenutosi a Lisbon, Portugal).
Non-invasive investigation of three paintings attributed to Cavalier d’Arpino by means of ED-XRF, FORS and Multispectral Imaging
Vittoria Bruni;Edoardo Colonna;Anna Candida Felici;Gianluca Mazzei;Candida Moffa;Annalisa Pascarella;Francesca Pelosi;Francesca Pitolli;Domenico Vitulano
2023
Abstract
The aim of this work was to characterize the palette and painting technique used for the realization of three late sixteenth century paintings from “Galleria dell'Accademia Nazionale di San Luca” in Rome attributed to Cavalier d’Arpino (Giuseppe Cesari), namely “Cattura di Cristo” (Inv. 158), “Autoritratto” (Inv. 546) and “Perseo e Andromeda” (Inv. 221). This study presents a diagnostic campaign that was carried out with non-invasive and portable techniques such as Energy Dispersive X-ray Fluorescence (ED-XRF) spectrometry, Fiber Optics Reflectance Spectroscopy (FORS) and Multispectral (MS) Imaging. This work was part of a project founded by Regione Lazio and MUR (“IMAGO - Multispectral Imaging for Art, Gamification and hOlografic reality” project). FORS and ED-XRF analyses allowed the preliminary characterization of the pictorial materials in a reliable non-invasive way. In particular, it was possible to identify most of the pigments used for the production of the paintings attributed to Cavalier d’Arpino. The MS images were acquired between the ultraviolet and the near-infrared regions of the electromagnetic spectrum (UV-Vis-NIR) by using different illumination sources and a cooled CCD camera equipped with interferential filters. It was possible to observe significant differences between the visible and the NIR images with some details of the paintings which resulted transparent in the infrared region. Furthermore, MS images were investigated in-depth by the application of data clustering algorithms to obtain semantic segmentation. This methodology exploits the information reported in MS images to generate a pixel classification based on statistical methods together with image analysis techniques. The result provides both an extrapolation of salient parts of the work as well as a better perception of some details. The combined results of this work allowed to investigate in-depth the production of one of the main painters from Italian mannerism.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
