Spectral Imaging and Archival Data in Analysing Madonna of the Rabbit Paintings by Manet and Titian

Year: 2018

Authors: Striova J., Ruberto C., Barucci M., Blažek J., Kunzelman D., Dal Fovo A., Pampaloni E., Fontana R.

Autors Affiliation: Natl Res Council CNR, Natl Inst Opt INO, Largo Enrico Fermi 6, I-50125 Florence, Italy; Univ Florence, Natl Inst Nucl Phys INFN, Dept Phys & Astron, Via Sansone 1, I-50019 Sesto Fiorentino, FI, Italy; Czech Acad Sci, Inst Informat Theory & Automat, Pod Vodarenskou Vezi 4, Prague 18208, Czech Republic; Opificio Pietre Dure Firenze, Florence, Italy.

Abstract: A concise insight into the outputs provided by the latest prototype of visible-near infrared (Vis-NIR) multispectral scanner (National Research Council-National Institute of
Optics, CNR-INO, Italy) is presented. The analytical data acquired on an oil painting Madonna of the Rabbit by E. Manet are described. In this work, the Vis-NIR was complemented with X-ray fluorescence (XRF) mapping for the chemical and spatial characterization of several pigments. The spatially registered Vis-NIR data facilitated their processing by spectral correlation mapping (SCM) and artificial neural network (ANN) algorithm, respectively, for pigment mapping and improved visibility of pentimenti and of underdrawing style. The data provided several key elements for the comparison with a homonymous original work by Titian studied within the ARCHive LABoratory (ARCHLAB) transnational access project.

Journal/Review: ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Volume: 57 (25)      Pages from: 7408  to: 7412

More Information: Financial support by Transnational Access to Research Infrastructures activity EU H2020 Programme (IPERION CH GA 654028) is gratefully acknowledged. XRF scanner was developed with support of FOTONART project funded by Fondazione Cassa di Risparmio di Firenze. Eva Pospisilova (Department of Chemistry, Faculty of Science, Masaryk University, Czech Republic) is acknowledged for her contribution during Erasmus+ traineeship.
KeyWords: Data handling; Infrared devices; Mobile ad hoc networks; Neural networks; Spectroscopy, ARCHLAB; Manet; Multispectral imaging; Spectral mappings; Titian, Photomapping
DOI: 10.1002/anie.201800624

ImpactFactor: 12.257
Citations: 35
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