Near infrared spectroscopic reflectance imaging : supervised versus unsupervised analysis using an art conservation application

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DOIResolve DOI: http://doi.org/10.1016/S0924-2031(99)00004-1
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TypeArticle
Journal titleVibrational Spectroscopy
ISSN0924-2031
Volume19
Issue1
Pages3345; # of pages: 13
SubjectNear-infrared imaging; Spectroscopic imaging; Image analysis; Fuzzy C-means clustering; Linear discriminant analysis; Art conservation
AbstractNear-IR spectroscopic imaging was used to analyze the remnants of a work of art, a 16th century drawing, attributed to the School of Pieter Bruegel the Elder, which had been significantly altered during a cleaning attempt. Using a combination of a CCD camera and a liquid crystal tunable filter (LCTF), near-IR spectroscopic images (650-1050 nm) were collected from the drawing and from a test sample composed of four substances with differing near-IR spectra deposited on a whiteboard surface. Both supervised and unsupervised classification methodologies (linear discriminant analysis (LDA) and fuzzy C-means (FCM) clustering, respectively) were used to analyze the data. FCM clustering, in combination with several spectral normalization routines, proved an excellent data exploration method for the test sample. LDA gave consistently clearer results than the FCM methods, but required a priori knowledge of the spectral properties of the sample, provided, in this case, by the FCM analysis. LDA of the spectroscopic image of the work of art revealed clearly and for the first time the location of regions of the drawing where faint traces of ink residue remained.
Publication date
PublisherElsevier Science B.V.
LanguageEnglish
AffiliationNational Research Council Canada; NRC Institute for Biodiagnostics
Peer reviewedYes
NRC number924
NPARC number9147701
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Record identifier1c9c4fb0-2c66-48d2-8708-d16a632fb3e9
Record created2009-06-25
Record modified2016-10-12
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