Want to be able to tell a real work of art from a forgery? Do the maths

Scientists have created a computer that can tell the mathematical difference between a genuine work of art and a forgery by analysing features invisible to the human eye, paving the way to a new method of art fraud detection.

Scientists have created a computer that can tell the mathematical difference between a genuine work of art and a forgery by analysing features invisible to the human eye, paving the way to a new method of art fraud detection.

The computer can also distinguish between the different contributions of apprentices who collaborated on a well-known masterpiece officially attributed to a single artist. Scientists said the technique meant academics could have a better understanding of the hidden contributions made by lesser-known artists.

The researchers used a mathematical approach, analysing the statistical likelihood that a particular brush or pen stroke was performed by the artist. A similar mathematical approach powered by computer has been used to analyse the words in famous texts to see whether they were the sole creation of a well-known author.

Henry Farid, associate professor of computer science at Dartmouth College in Hanover, New Hampshire, said the technique could be applied to fine art thanks to the widespread use of high-resolution digital imagery that collects up to 2,400 points of light in a single square inch of canvas.

"We have been able to mathematically capture subtle characteristics of an artist that are not necessarily visible to the human eye," he said. "We expect this technique, in collaboration with existing physical authentication, to play an important role in the field of art authentication. Similar methods have been used to analyse works of literature.

"We can find things in art work that are unique to the artist, such as the subtle choice of words or phrasing and cadence that are characteristic of a certain writer."

Scientists had to program the computer with an artist's personal style of painting or drawing using digital images of masterpieces known to be the work of the same painter. The machine was then able to decide whether a new work it subsequently analysed was likely to be a forgery.

Professor Farid and his colleagues analysed 13 drawings that had been attributed - at least at some time - to the Flemish artist Pieter Bruegel the Elder. The computer successfully distinguished between eight of the paintings known to be by the artist and five famous imitations by contemporary artists, including some by artists who intended to commit a forgery.

A second part of the research, in the journal Proceedings of the National Academy of Sciences, analysed digital images of the Madonna with Child by the great Italian renaissance artist Perugino who became famous for his altar pieces. The way the faces of the six figures in the work were painted were analysed mathematically for similarities. That found the three on the left of the painting appear to have been the work of one artist, and the three on the right were different enough from all other faces to have been the work of different artists, probably Perugino's apprentices, a common practice in Renaissance art.

Analysing brush and pen strokes mathematically will be used with other techniques, such as X-rays to see underneath a coat of paint, in determining a painting's authenticity, the researchers say.