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Virtual restoration of the Ghent altarpiece using crack detection and inpainting

Publication ,  Journal Article
Ružić, T; Cornelis, B; Platiša, L; Pižurica, A; Dooms, A; Philips, W; Martens, M; De Mey, M; Daubechies, I
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
September 2, 2011

In this paper, we present a new method for virtual restoration of digitized paintings, with the special focus on the Ghent Altarpiece (1432), one of Belgium's greatest masterpieces. The goal of the work is to remove cracks from the digitized painting thereby approximating how the painting looked like before ageing for nearly 600 years and aiding art historical and palaeographical analysis. For crack detection, we employ a multiscale morphological approach, which can cope with greatly varying thickness of the cracks as well as with their varying intensities (from dark to the light ones). Due to the content of the painting (with extremely many fine details) and complex type of cracks (including inconsistent whitish clouds around them), the available inpainting methods do not provide satisfactory results on many parts of the painting. We show that patch-based methods outperform pixel-based ones, but leaving still much room for improvements in this application. We propose a new method for candidate patch selection, which can be combined with different patch-based inpainting methods to improve their performance in crack removal. The results demonstrate improved performance, with less artefacts and better preserved fine details. © 2011 Springer-Verlag.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

September 2, 2011

Volume

6915 LNCS

Start / End Page

417 / 428

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Ružić, T., Cornelis, B., Platiša, L., Pižurica, A., Dooms, A., Philips, W., … Daubechies, I. (2011). Virtual restoration of the Ghent altarpiece using crack detection and inpainting. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6915 LNCS, 417–428. https://doi.org/10.1007/978-3-642-23687-7_38
Ružić, T., B. Cornelis, L. Platiša, A. Pižurica, A. Dooms, W. Philips, M. Martens, M. De Mey, and I. Daubechies. “Virtual restoration of the Ghent altarpiece using crack detection and inpainting.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6915 LNCS (September 2, 2011): 417–28. https://doi.org/10.1007/978-3-642-23687-7_38.
Ružić T, Cornelis B, Platiša L, Pižurica A, Dooms A, Philips W, et al. Virtual restoration of the Ghent altarpiece using crack detection and inpainting. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011 Sep 2;6915 LNCS:417–28.
Ružić, T., et al. “Virtual restoration of the Ghent altarpiece using crack detection and inpainting.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6915 LNCS, Sept. 2011, pp. 417–28. Scopus, doi:10.1007/978-3-642-23687-7_38.
Ružić T, Cornelis B, Platiša L, Pižurica A, Dooms A, Philips W, Martens M, De Mey M, Daubechies I. Virtual restoration of the Ghent altarpiece using crack detection and inpainting. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011 Sep 2;6915 LNCS:417–428.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

September 2, 2011

Volume

6915 LNCS

Start / End Page

417 / 428

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences