Can mathematics help deciding which paintings are authentic and which ones are forgeries? The mathematical analysis of visual stylometry is a relatively new area in mathematics. In this talk we present some recent work in this direction. In particular we show that a technique known as the empirical mode decomposition (EMD), combined with techniques from machine learning, can be an effective tool for the authentication of visual arts. We apply our techniques to drawings by Pieter Bruegel the Elder and Rembrandt.
Yang Wang received his PhD in mathematics from Harvard University in 1990 under the supervision David Mumford. Before joining MSU as the chair of the department of Mathematics he was a faculty member at Georgia Tech from 1989 to 2006 and a program officer at NSF 2006-2007. Wang's research interests span a broad range of pure and applied mathematics, including tiling, fractal geometry, wavelets, signal processing, blind source separations, among others.