Artificial intelligence for art investigation: Meeting the challenge of separating x-ray images of the Ghent Altarpiece.

Published

Journal Article

X-ray images of polyptych wings, or other artworks painted on both sides of their support, contain in one image content from both paintings, making them difficult for experts to "read." To improve the utility of these x-ray images in studying these artworks, it is desirable to separate the content into two images, each pertaining to only one side. This is a difficult task for which previous approaches have been only partially successful. Deep neural network algorithms have recently achieved remarkable progress in a wide range of image analysis and other challenging tasks. We, therefore, propose a new self-supervised approach to this x-ray separation, leveraging an available convolutional neural network architecture; results obtained for details from the Adam and Eve panels of the Ghent Altarpiece spectacularly improve on previous attempts.

Full Text

Duke Authors

Cited Authors

  • Sabetsarvestani, Z; Sober, B; Higgitt, C; Daubechies, I; Rodrigues, MRD

Published Date

  • August 30, 2019

Published In

Volume / Issue

  • 5 / 8

Start / End Page

  • eaaw7416 -

PubMed ID

  • 31497645

Pubmed Central ID

  • 31497645

Electronic International Standard Serial Number (EISSN)

  • 2375-2548

International Standard Serial Number (ISSN)

  • 2375-2548

Digital Object Identifier (DOI)

  • 10.1126/sciadv.aaw7416

Language

  • eng