Magazine article Science News

Con Artist: Scanning Program Can Discern True Art

Magazine article Science News

Con Artist: Scanning Program Can Discern True Art

Article excerpt

Until now, discerning an artist's style has been in the eye of the beholder. However, a new mathematical tool distills style into an array of statistics as a potential means to spot forgeries. In a recent study, the technique distinguished eight drawings by the 16th-century artist Pieter Brueghel the Elder from five imitations attributed to the master until a decade or so ago.

Several digital-imaging researchers, including the study's authors, agree that the work is only a first step toward a reliable fraud-detection technique. However, the preliminary findings are encouraging, comments David Donoho, a statistician at Stanford University.

The technique employs a process called wavelet decomposition to break down a digital image into a collection of more-basic images, called subbands. Just as a musical tone consists of a low fundamental frequency with higher-frequency overtones, an image's low-frequency subbands show the broad strokes, while higher-frequency subbands depict details. Wavelets have been used in a wide range of image-processing applications, such as layering detail onto the animated creatures in the film A Bug's Life.

Wavelet decomposition is good at analyzing textures. For instance, a smooth, untroubled surface such as a blue sky would show up mostly in the low-frequency subbands, while blades of grass would produce activity primarily in higher-frequency subbands.

Now, in an upcoming Proceedings of the National Academy of Sciences, researchers report capturing the texture of an artist's strokes. …

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