Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography.

NDT cultural heritage defects hyperspectral imaging image processing independent component analysis information fusion painting on canvas principal component analysis pulse-compression thermography

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
08 Oct 2019
Historique:
received: 04 09 2019
revised: 02 10 2019
accepted: 06 10 2019
entrez: 11 10 2019
pubmed: 11 10 2019
medline: 11 10 2019
Statut: epublish

Résumé

The use of different spectral bands in the inspection of artworks is highly recommended to identify the maximum number of defects/anomalies (i.e., the targets), whose presence ought to be known before any possible restoration action. Although an artwork cannot be considered as a composite material in which the zero-defect theory is usually followed by scientists, it is possible to state that the preservation of a multi-layered structure fabricated by the artist's hands is based on a methodological analysis, where the use of non-destructive testing methods is highly desirable. In this paper, the infrared thermography and hyperspectral imaging methods were applied to identify both fabricated and non-fabricated targets in a canvas painting mocking up the famous character "Venus" by Botticelli. The pulse-compression thermography technique was used to retrieve info about the inner structure of the sample and low power light-emitting diode (LED) chips, whose emission was modulated via a pseudo-noise sequence, were exploited as the heat source for minimizing the heat radiated on the sample surface. Hyper-spectral imaging was employed to detect surface and subsurface features such as pentimenti and facial contours. The results demonstrate how the application of statistical algorithms (i.e., principal component and independent component analyses) maximized the number of targets retrieved during the post-acquisition steps for both the employed techniques. Finally, the best results obtained by both techniques and post-processing methods were fused together, resulting in a clear targets map, in which both the surface, subsurface and deeper information are all shown at a glance.

Identifiants

pubmed: 31597266
pii: s19194335
doi: 10.3390/s19194335
pmc: PMC6806314
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Horizon 2020 Framework Programme
ID : 722134

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Auteurs

Stefano Laureti (S)

Department of Informatics, Modeling, Electronics and Systems Engineering, University of Calabria, Via P.Bucci, Arcavacata, 87036 Rende (CS), Italy. stefano.laureti@unical.it.

Hamed Malekmohammadi (H)

Department of Engineering, Polo Scientifico Didattico di Terni, University of Perugia, 05100 Terni (TR), Italy. hamed.malekmohammadi@unipg.it.

Muhammad Khalid Rizwan (MK)

Department of Engineering, Polo Scientifico Didattico di Terni, University of Perugia, 05100 Terni (TR), Italy. muhammadkhalid.rizwan@unipg.it.

Pietro Burrascano (P)

Department of Engineering, Polo Scientifico Didattico di Terni, University of Perugia, 05100 Terni (TR), Italy. pietro.burrascano@unipg.it.

Stefano Sfarra (S)

Department of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila (AQ), Italy. stefano.sfarra@univaq.it.

Miranda Mostacci (M)

Restorer, Via Muranuove 64, 67043 Celano (AQ), Italy. miranda.mostacci.90@gmail.com.

Marco Ricci (M)

Department of Informatics, Modeling, Electronics and Systems Engineering, University of Calabria, Via P.Bucci, Arcavacata, 87036 Rende (CS), Italy. marco.ricci@unical.it.

Classifications MeSH