A newalgorithmhas been used to help visualizehidden drawingss under the ‘Virgin of the Rocks’ ofLeonardo da Vinci.
Professor Pier Luigi Dragotti of Imperial College London and Dr. Catherine Higgitt of the National Gallery used the new algorithm combined with a technique calledX-ray fluorescence macro scan(MA-XRF), which maps chemical elements inside the paints.
In doing so, they revealed, more clearly than ever, the hidden figures that Leonardo first drew before changing his design to the one he finally painted. These includedabandoned images of an angel and the Christ Child.
Professor Dragotti, from Imperial’s Department of Electrical and Electronic Engineering, said: “It was like looking for a needle in a haystack, but it was a great feeling to see the wings and head finally discovered.”
Researchers at the National Gallery had already discovered, using infrared images, parts of Leonardo’s initial drawings below the surface of the painting, which included the Virgin in a different pose placed higher on the panel. More recently, the team used MA-XRF toscan non-invasivelyeach pixel of the paint to detect different chemical elements within the materials that Leonardo used in the paint.
They discovered that the drawing of the first hidden composition contained zinc, which makes it possible to reveal more forgotten figures, iincluding the Infant Jesus and a winged angel on the right,where now only the landscape is seen. At Imperial, Professor Dragotti developed the algorithm to automatically process the large amount of data from the MA-XRF scans, improving existing more manual methods and producing better and more reliable images to help them visualize the data.
Pixel by pixel
“Each pixel contained different amounts of each element, within several layers. We analyzed each pixel individually before combining them to see all the drawings in the painting. This revealeda much sharper picture of the angel and the baby“, said.
Dr. Higgitt added: “Before, we received very weak signals of zinc inside the paint due to its overlap with other elements, but the algorithm has given us more confidence in the signals related to the undercut.”
Researchers say their custom techniquecould be applied to the data of other paintings, making the analysis of works of art easier to use and allowing art students and galleries to access data more easily.