Instead of obsessing over materials, the new technique takes a hard look at the picture itself – specifically, the thousands of tiny individual strokes that compose it.
The paper Elgammal and his colleagues published last November examined 300 authentic drawings by Picasso, Matisse, Egon Schiele, and a number of other artists and broke them down into more than 80,000 strokes. Machine-learning techniques refined the data set for each artist; forgers were then commissioned to produce a batch of fakes. To put the algorithm though its paces, the forgeries were fed into the system. When analyzing individual strokes, it was over 70% accurate; when whole drawings were examined, the success rate increased to over 80% . (The researchers claim 100% accuracy “in most settings.”).