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Using Computed Weave Maps to Gain Art-Historical Insight from Vermeer's Canvases

May 2, 2017

Dr. C. Richard Johnson, Jr., Cornell University

The Thread Count Automation Project (TCAP), launched by Professor Johnson in 2007, discovered striped patterns in color-coded images of local thread densities obtained from digital image processing of x-radiographs of Old Master paintings on canvas. These striped patterns provide a "fingerprint" for pieces of canvas cut from the same roll. This spurred a four-year effort assisted by Walter Liedtke, one of the world's leading scholars of Dutch and Flemish paintings, to gather x-radiographs of all thirty-four paintings on canvas by the Dutch master Johannes Vermeer (1632–1675). Thus far, six matching pairs of roll-mates have been identified. They provide evidence regarding authentication, dating, and—potentially—artistic intent. In addition to weave density maps, images were created of thread angle from their nominal horizontal and vertical directions. These angle maps provide forensic information regarding warp/weft thread designation and cusping, which offers insight into Vermeer's studio practice and the possible re-sizing of his paintings since their creation. The insights generated by computed weave maps arising from the application of digital image processing are pioneering contributions from engineering to the emerging field of computational art history.

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