A Novel Classification Method for Multispectral Imaging Combined with Portable Raman Spectroscopy for the Analysis of a Painting by Vincent Van Gogh

$29.00 plus tax (Refund Policy)

Buy Article:


In this work, a novel combination of portable micro-Raman spectroscopy and semi-automatic methods of data treatment are proposed for the classification and mapping of visible multispectral imaging data for the analysis of a painting on paper by Vincent Van Gogh. Analysis of multispectral imaging data with the sequential maximum-angle convex cone (SMACC) and spectral angle mapper (SAM) algorithms differentiated the surface into areas on the basis of the presence of pigment mixtures. Complementary analytical information was obtained through portable Raman spectroscopy was performed on a few selected points of the painting, allowing for the determination of Van Gogh's palette and the mapping of pigment mixtures on the painting's surface; the number of mixtures employed is varied and at least two different blues are present. The results obtained were integrated with the information from prior ultraviolet (UV)-induced luminescence analysis performed on the same painting to better understand the materials used by the artist. The mathematical treatment of multispectral data using the proposed methods could be extended to the analysis of other painted surfaces.

Keywords: Conservation science; Mapping and classification methods; Micro-Raman spectroscopy; Pigment identification; Visible multispectral imaging

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/13-07032

Affiliations: Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, Milano 20133 Italy

Publication date: November 1, 2013

More about this publication?



Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more