“Weave Match Hunting: An Application of Signal Processing to Painting Analysis”

Abstract:
The claim that two paintings are on canvas from the same original roll can support conclusions on dating, authenticity, and other issues of basic importance in art historical painting analysis. Traditionally such claims begin with establishing matching average thread counts for the two paintings. Averages are typically obtained from a few manual spot counts at points scattered across the painting. Manual spot counts are taken from x-rays of paintings mounted on a lightbox and viewed through a magnifying eyepiece. Recognizing thread counting from x-rays as a Fourier spectral analysis problem propelled the founding of the Thread Count Automation Project (TCAP) in 2007. Being able to compute the thread count for every square centimeter across the painting revealed a striped pattern in the local weave densities. Paintings sharing threads from the same roll will possess the same striped pattern, which converts a weave match search into a correlation problem. The weave density and angle maps produced by automated thread counting are becoming new fundamental tools in technical art history. The challenges of initiating such an interdisciplinary effort will be described along with several discovered weave matches with art historical implications.

Biography:
C. Richard Johnson, Jr. was born in Macon, GA in 1950. He received a PhD in Electrical Engineering from Stanford University, along with the first PhD minor in Art History granted by Stanford, in 1977. Following 4 years on the faculty at Virginia Tech, he joined the Cornell University faculty in 1981, where he is the Geoffrey S. M. Hedrick Senior Professor of Engineering and a Stephen H. Weiss Presidential Fellow. At the start of 2007, after 30 years of research on adaptive feedback systems theory and blind equalization in communication receivers, Professor Johnson accepted an 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.