果冻影院

The article, entitled 'The hidden images found in masterpieces' discusses how artificial intelligence techniques are being employed by researchers around the world to resurrect cultural artefacts, such as a painting.

ARTICT, or Art Through the ICT Lens, a research partnership between 果冻影院, Imperial College London, and the National Gallery is one of the focal points of the article. Prof Miguel Rodrigues, leading the researchers at 果冻影院, is also the Principal Investigator of the EPSRC-funded project. 聽

On their work being featured in BBC Culture, Prof Miguel Rodrigues comments:

鈥�鈥淩ecent advances in artificial intelligence technology offer an opportunity to address outstanding challenges in various domains. 果冻影院 EEE is working closely with museums to help reveal and reconstruct hidden or lost features in artwork.鈥�

Their latest research output, 鈥楳ixed X-Ray Image Separation for Artworks With Concealed Designs鈥�, published in the journal IEEE Transactions on Image Processing, reports on the use of a self-supervised deep learning-based image separation approach applied to X-ray images of Francisco de Goya's Do帽a Isabel de Porcel (circa 1805).

While X-ray radiographs have been a turning point in the field of art investigation, X-ray images of paintings with hidden sub-surface features are notoriously difficult for experts to interpret. This is because they include contributions from both the surface painting and the hidden designs. To help interpret mixed X-ray images better, the researchers have proposed a set of artificially intelligent algorithms, powered by deep learning, that would separate the mixed X-ray image into two hypothetical X-ray images. One of these reconstructed images is related to the X-ray image of the concealed painting, while the second image contains information only related to the X-ray image of the visible painting.

This new deep learning approach also enables art historians, conservators, and heritage scientists to better understand other images of paintings with mixed compositions such as infrared reflectograms, X-ray fluorescence scanning element distributions maps or outputs from reflectance imaging spectroscopy.

The restorative project on Van Eyck鈥檚 Ghent Altarpiece (1432) led by Dr Rodrigues at 果冻影院, in collaboration with researchers from Duke University and the National Gallery, was also reported on in the article. The double-sided panels of the painting produce layered X-rays that are difficult for conservators studying each layer to interpret. Their paper, 鈥楢rtificial Intelligence for Art Investigation: Meeting the Challenge of Separating X-ray Images of the Ghent Altarpiece鈥�, demonstrated the use of artificially intelligent algorithms that separated the X-ray images into two distinct images. This helped experts study features from the front and back of the painting鈥檚 double-sided panels.

Deep learning approaches are now widely used to address challenges across most sectors, and the research led by Prof Rodrigues and his team is a crucial example of this.

The combination of traditional X-ray images with deep neural network algorithms can be used to solve critical problems present in art investigation today, one of them being conservation of irreplaceable works of art.

Links

• Research paper '' in Science Advances
• Research paper 鈥樷�� in IEEE Transactions on Image Processing
• Prof Miguel Rodrigues鈥� profile

Image Credit

Francisco de Goya, Do na Isabel de Porcel (NG1473), before 1805. Oil on canvas. 漏 The National Gallery, London. (a). RGB image. (b). X-ray image