Bayesian crack detection in ultra high resolution multimodal images of paintings

Bruno Cornelis, Yun Yang, Joshua Vogelstein, Ann Dooms, Ingrid Daubechies, David Dunson

Onderzoeksoutput: Conference paper

19 Citaten (Scopus)

Samenvatting

The preservation of our cultural heritage is of paramount importance. Thanks to recent developments in digital acquisition techniques, powerful image analysis algorithms are developed which can be useful non-invasive tools to assist in the restoration and preservation of art. In this paper we propose a semi-supervised crack detection method that can be used for high-dimensional acquisitions of paintings coming from different modalities. Our dataset consists of a recently acquired collection of images of the Ghent Altarpiece (1432), one of Northern Europe's most important art masterpieces. Our goal is to build a classifier that is able to discern crack pixels from the background consisting of non-crack pixels, making optimal use of the information that is provided by each modality. To accomplish this we employ a recently developed non-parametric Bayesian classifier, that uses tensor factorisations to characterise any conditional probability. A prior is placed on the parameters of the factorisation such that every possible interaction between predictors is allowed while still identifying a sparse subset among these predictors. The proposed Bayesian classifier, which we will refer to as conditional Bayesian tensor factorisation or CBTF, is assessed by visually comparing classification results with the Random Forest (RF) algorithm.
Originele taal-2English
Titel18th International Conference on Digital Signal Processing (DSP 2013) Proceedings
UitgeverijIEEE
Aantal pagina's8
ISBN van geprinte versie978-1-4673-5805-7
StatusPublished - 2013
Evenement18th International Conference on Digital Signal Processing (DSP 2013) - Santorini, Greece
Duur: 1 jul 20133 jul 2013
http://dsp2013.dspconferences.org/

Publicatie series

NaamInternational Conference on Digital Signal Processing Proceedings
UitgeverijIEEE
ISSN van geprinte versie1546-1874

Conference

Conference18th International Conference on Digital Signal Processing (DSP 2013)
Land/RegioGreece
StadSantorini
Periode1/07/133/07/13
Internet adres

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