Learning-Based Authentication of Jackson Pollock's Paintings
10.1117/2.1200905.1643 Learning-based authentication of Jackson Pollock’s paintings David G. Stork Even apparently ‘useless’ visual features can improve computer- assisted authentication of artwork as long as multiple features are used to train machine classifiers. The abstract expressionist Jackson Pollock (1912–1956), nick- named ‘Jack the Dripper,’ is one of America’s most important artists. He is best known for his ‘action’ paintings, executed by dripping, pouring, and splashing liquid paint onto horizontal canvases on the floor (see Figure 1). Many artworks of doubt- ful authorship (and some deliberate fakes) have been generated using this drip technique, however, such as the large, unsigned Figure 1. Jackson Pollock’s ‘Convergence’ (1952), 237.5cm 393.7cm, × work Teri Horton purchased for $5.00 in a thrift shop in San oil on canvas. c 2009 The Pollock-Krasner Foundation/Artists Rights ! Bernadino (CA) in the early 1990s. Although some art scholars Society (ARS), New York. have attributed this painting to Pollock, others have contested or rejected this notion. The feature documentary ‘Who the #$&% is Jackson Pollock?’ focuses on this nearly two-decades-old two-legged shape in this particular 2D space, while fakes debate, which—once resolved—will determine the work’s value do not. at either $5 or $50,000,000. In 2008, physicists Jones-Smith, Mathur, and Krauss criticized 2, 3 Art authentication based on signatures, provenance (the Taylor’s fractal and box-counting approach. They suggested documentary record of ownership), chemical studies of media that highly artificial images can match the fractal properties of (e.g., oil or acrylic), material studies of support (e.g., paper or genuine ‘Pollocks’ and asserted that the range of spatial scales canvas), preparation (e.g., sizing), fingerprints, and traditional the Taylor team used was too small to estimate a true fractal di- connoisseurship is not always definitive.
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