“X-rays are a well-established tool to help analyze and restore valuable paintings because the rays’ higher frequency means they pass right through paintings without harming them. X-ray imaging can reveal anything that has been painted over a canvas or where the artist may have altered his (or her) original vision. But the technique has its limitations, and that’s where machine learning can prove useful. Two papers this fall illustrated the use of AI to solve specific problems in art analysis and conservation: one to reconstruct an underpainting in greater detail, and the other to make it easier to image two-sided painted panels.” – Source: Ars Technica
WHY THIS MATTERS:
Here are two ways that machine learning and artificial intelligence have been used in the world of art history and restoration: to recreate a Picasso underpainting and help restore a famed 15th century double-sided panel.
