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Cornell ECE Professor C. Richard Johnson, Jr. combines ECE and fine art to develop new digital signal processing applications

Wednesday, June 25, 2014


Cornell ECE’s C. Richard Johnson, Jr. was honored as the opening plenary speaker at the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing on May 6, in Florence, Italy.

He delivered the talk, Signal Processing in Computational Art History to over 2,000 researchers, describing emerging applications of digital signal processing to art historical issues of dating and attribution.

These emerging applications include:

  • Thread counting for weave matching of Old Master paintings on canvas from x-radiographs, which has proved helpful in studies of paintings of van Gogh, Vermeer, and Poussin;
  • Texture similarity assessment for metadata (manufacturer, surface finish, brand, and date of manufacture) classification of historic photographic papers, in particular silver gelatin and inkjet papers, from raking light images; and
  • Chain line pattern matching for mold-mate identification of laid papers from beta- radiographs, initially for the prints of Rembrandt

According to the talk’s abstract, a key component of the scholarly analysis of fine art utilizes the extraction features from revealing images of the artwork, a technique that has expanded significantly under the label of technical art history. Within the past seven years, painstaking manual methods of feature extraction from images of an artwork’s support materials, in particular canvas and paper, have been enhanced with the application of signal processing in projects spearheaded by Professor Johnson. When combined with big data handling capabilities, significant advances have been achieved, creating an approach called computational art history.

This emerging topic and the basic image processing tools underpinning it will be taught in ECE 4210/5953 "Art Support Analysis Algorithms" in fall 2014.  As Professor Johnson notes: "This course offers a rare opportunity for undergraduates and M.Eng ECE students to experience the thrill of basic research on a very young emerging topic by addressing questions of significant impact to art historians which no one has previously answered and that can be resolved using technical skills in the undergraduate ECE toolkit."

Professor Johnson is the Geoffrey S. M. Hedrick Senior Professor of Engineering and a Stephen H. Weiss Presidential Fellow at Cornell University. He received a Ph.D. in Electrical Engineering from Stanford University, along with the first Ph.D. minor in Art History granted by Stanford, in 1977. At the start of 2007, after 30 years of research on adaptive feedback systems theory and blind equalization in communication receivers, Professor Johnson accepted a 5-year appointment as an Adjunct Research Fellow of the Van Gogh Museum (Amsterdam, the Netherlands) to facilitate the interaction of art historians and conservation specialists with algorithm-building signal processors. In 2013, Professor Johnson was appointed a Scientific Researcher of the Rijksmuseum (Amsterdam, the Netherlands) and Computational Art History Advisor to the RKD - Netherlands Institute for Art History (the Hague, the Netherlands).

Professor Johnson founded the Thread Count Automation Project (TCAP) in collaboration with the Van Gogh Museum in 2007, initiated the Historic Photographic Paper Classification (HPPC) Challenge in cooperation with the Museum of Modern Art in 2010, and launched the Chain Line Pattern (CLiP) Matching Project with the Morgan Library & Museum in 2012, which was joined by the Rijskmuseum and the Metropolitan Museum of Art in 2013 and the Dutch University Institute for Art History in Florence in 2014.


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