Rockmore begins his procedure by analyzing the digital image pixel by pixel and creating statistical summaries of each painting or drawing. These summaries capture what Rockmore calls the artist's mathematical signature, which in theory will be consistent from painting to painting. Just as everyone's handwriting is unique - with characteristic letter spacing, slant, and design - so is everyone's painting style, with characteristic brushstroke direction, thickness, and length.
At least that's what the software showed with the Bruegels. When the mathematical signatures of the 13 drawings were mapped, eight works clustered together - the same eight deemed by experts to be authentic Bruegels. The other five were scattered in space. The clarity of the results startled the art world, and holds out the promise that Rockmore will be able to work backward from his current analysis to figure out exactly what makes a Rembrandt real: perhaps the master had thicker brushstrokes than his pupils, or some characteristic shake in his hand.
The article has an economic angle to it. The process is much like what applied economists do with nonexperimental data--try to achieve identification by examining the patterns in data. The process also reminded me of the part of Freakonomics where Levitt diagnoses teacher cheating based on observed patterns in students' test answers. But here, the stakes are even bigger. Consider that:
"The fact that you can put everything on the computer means that everything is numbers," Rockmore says. "As soon as everything is numbers, it makes perfect sense to ask mathematical questions about what the numbers represent." If he's right - if computers can distinguish between artists more accurately than connoisseurs can - the art world is in for some high-stakes corrections. Rockmore's scientific approach will boost the value of some collections by millions of dollars - while devastating others that are tainted by imitations and fakes.
Simply fascinating. Take a break from budget woes and enjoy the article.