EAGER: Automated Watermark and Moldmate Identification

Cornell University, Ithaca NY

Investigators

Abstract

Identification of watermarks in antique (pre-1750) laid paper is a vital forensic in determining the date and origin of its production. For artworks on paper, watermarks are a key element in dating and authentication. Classifying and distinguishing watermarks is a difficult, time-consuming task even for paper analysis experts. Recent research has shown that a computer-based decision tree can reduce dramatically the time expended in the task of watermark identification and the concomitant identification of sheets of paper made on the same mold, while at the same time increasing the confidence in the result. The application of digital image processing to this task is one example of the new field of computational art history, which has exploded over the past decade. Through this project, automation using digital image processing can scale up the task of watermark and moldmate identification to handle the universe of the hundreds of individual watermarks in the papers of prints and drawings of Rembrandt and his pupils and allow expansion of this identification beyond these artworks in major museums to the thousands in smaller museums and private collections. This is expected to energize the expansion of this valuable forensic to the thousands of watermarks in laid paper used in artworks on paper by other pre-1750 artists. Advances in computational art history stemming from this project will offer a path for the general population, which is growing quite comfortable with the expansion of computer usage in everyday life, to engage with art in a new and appealing way. Art history is one subfield within cultural heritage that has delayed the longest in joining the emergence of the digital science and humanities. The success of this project will be a major enabler for further trans-disciplinary activities between the humanities and the sciences, thereby decreasing the separation of their two cultures, which is vital as the digitization of all aspects of daily life gains dominance at a scorching pace. This project continues the pioneering efforts in the new field of computational art history that is broadening acceptance of digital image processing as a vital tool in art history research as it tremendously expands the intellectual reach of art historians. As the first tools are developed in this nascent field and more scientists and engineers are drawn to the challenges of these problems, the specific needs of art historians will undoubtedly reveal new tasks requiring advances in the underlying science of digital image processing. This connection between computation and the visual humanities also offers a powerful link to combat the widening gulf in education at all levels between engineering science and the humanities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.