Automated thread counting algorithms, in development since 2007 by Professors Rick Johnson (Cornell University) and Don Johnson (Rice University), are poised for a profound impact on the practice of technical art history. This work is a pioneering effort in the emerging application of signal and image processing to the analysis of paintings. The approach is based on the utilization of spectral analysis of x-rays of paintings. X-rays can display the periodic intensity pattern due to the greater thickness of the lead white ground between the canvas threads. With the addition of innovative application-specific signal processing, local peaks in the spectrum of the x-ray data can reveal the numbers of threads per centimeter, i.e. a thread count, separately for (nearly) ver- tically and (nearly) horizontally oriented threads. Such thread counts have been used previously, but their manual acquisition proved too costly to be done thoroughly. The introduction of the capability to assemble previously unthinkable thread density and angle pattern maps of high de- tail across the entire surface of a painting leads to correlation-based identification of canvases sharing the same pattern in thread density variations. Such weave maps and matches can now be assembled across all of the paintings on canvas of a single artist or school, thereby significantly extending the art historian?s capabilities in, for example, dating and attribution. The scale, breadth, and depth of such thread-counting projects represent a bold leap in the capabilities of technical art history. This grant supports the analysis phase of the first projects of such grand scope: the thread counting and subsequent weave matching among (i) all of the paintings by Vincent van Gogh (for which data can be obtained by the end of 2010) and (ii) all of the paintings by the Delft School during the career of Johannes Vermeer (for which data can be obtained by the end of 2010). This grant places Professors Rick and Don Johnson in the center of the data fusion, data analysis and database creation activities that are scheduled to occur in Amsterdam during the spring of 2011. The archives being established of thread count reports, including weave density maps providing fingerprints for weave matching and angle maps for characterizing cusping, form a groundbreaking resource at a time when museums are just beginning to address the technological and cultural barriers to technical data sharing among museums and collaborating researchers outside the museum. This project is part of a long-term effort that aims to expand the utility of thread counting from x-rays to all suitable oil paintings on canvas, and to photos of unlined backs of old master paintings and of the raw canvas, for example, of the modern colorfield painters and of densely-woven, multi-pattern fabrics prominent in the design and decorative arts.
By using image processing and statistical processing techniques, we developed methods of characterizing the canvas supports of master paintings. Specifically, we determine the thread density of the canvas support in both the horizontal and vertical directions by processing radiographs of paintings. Our previous work found that these densities varied from painting to painting if their canvases did not come from the same roll. However, if they did, these variations were nearly identical, meaning we could determine which paintings came from the same roll, which could have strong implications about dating the paintings. Radiographs were obtained as a result of close working relationships with museums. The NSF travel grant enabled us to spend significant time visiting museums, gathering radiographs of paintings and working with art historians and greatly fostered developing these relationships. By concentrating our canvas analysis on the works of two artists, we made several interesting technical insights into the artists' practices. We found over 40 groups of paintings that came from the same original bolts of canvas (100-200m long, 2m wide). Combining these results with datings of paintings obtained from careful examination of his letters by art historians at the Van Gogh Museum, we found that van Gogh was very haphazard in his use of canvas, selecting canvas for a painting from several choices rather than exhausting one bolt before moving on to another. For Vermeer, we worked closely with several museums, and obtained data from half of his output. Our results have corrected errors in manual thread counts found in the literature, sometimes by a significant amount. In searching for paintings that came from the same canvas, we found three pairs of Vermeer's paintings that seemed to come for the same bolt of canvas. Two of these three pairs was not surprising to Vermeer experts (similar composition and dating) but one was not as quickly accepted. It is known that Vermeer kept canvas, which would explain different datings for the two paintings, but how long he kept canvas is not known. In the course of examining Vermeer's paintings, we discovered a previously unrecognized canvas weaving fault. This fault occurs only in the weft direction and occurs only for hand-woven canvases. The fault does not occur in every canvas but when it does, technical art historians now have a better understanding of the artist's process in addition to the thread count information. Because of the substantial difference between seventeenth century (Vermeer) and late nineteenth century (van Gogh) canvases, our research demanded improvements into our thread counting algorithm. These improvements made our algorithms more robust and allowed us to be able to analyze paintings-on-canvas from any period.
