"Computer vision and image analysis of master drawings and paintings"

Speaker: David G. Stork


This one-day tutorial will apply methods from image processing, computer vision and image analysis to problems in the history and understanding of master paintings. Some of these analysis techniques are built upon methods used in forensic image analysis of photographs but are tailored to specific contingencies of painting. Questions addressed include: How do we judge the sizes and positions of objects depicted and the geometry of structures such as architecture? Was the image created using a mechanical or optical aid? What were the sources of illumination and their color? What form of perspective was used? What is revealed by shadows and reflections depicted within a painting?
Some of the analysis techniques require nothing more than a tutored and perceptive eye; others merely a ruler and pencil; yet others require advanced statistical estimation procedures and computer analysis.
This course is based almost entirely on the analysis of images, not the physical or chemical analysis of pigments and media, the purview of traditional art conservators.


A large number of rigorous techniques have been developed primarily for the forensic image understanding community that can be applied to outstanding problems in art and art history, such as attribution and authentication, and questions about contemporary artistic praxis. Careful and meaningful application of these techniques requires not only the technical knowledge of the methods and their limitations, but also a background in art and art history. This course will provide an entrée into the methods and literature, ending with a number of outstanding problems amenable to attack by rigorous techniques. After completing the course, students should be able to collaborate with scholars in art history to address a range of problems in art history.
ICIAP is a perfect conference for this topic, since the scientific issues in the course appear elsewhere in the conference. Modena is a perfect venue, since many paintings in the tutorial appear in nearby museums, specifically Firenze, Venezia, and Bologna.

Prerequisites/expected background

Students must have basic background to the level of an introductory course in image processing or computer vision (digital filtering, affine transformations, geometric analysis, etc.). It is highly desirable that students have at least a basic knowledge of periods of representational art: Medieval, Renaissance, Baroque, realism and photorealism and at least a passing acquaintance with representational artists from a wide range of periods, such as Giotto, Masaccio, Piero della Francesca, Jan van Eyck, Leonardo da Vinci, Caravaggio, Hans Memling, Hans Holbein, Jan Vermeer, Canaletto, Claude Lorraine, Georges de la Tour, Jean-Auguste-Dominique Ingres, Georges Seurat, Thomas Eakins and Richard Estes.



Dr. David G. Stork is Chief Scientist of Ricoh Innovations and has also taught in the Department of Art and Art History. He has published in optics and art for over two decades, including Seeing the Light: Optics in nature, photography, color, vision and holography (Wiley) the leading textbook on optics in the arts (now in its 21st printing). A graduate in physics of the Massachusetts Institute of Technology and the University of Maryland at College Park, he also studied art history at Wellesley College and was Artist-in-Residence through the New York State Council of the Arts. His anamorphic photographs and graphics (based on late Renaissance methods) have appeared in small art journals as well as Optics and Photonics News and Scientific American magazine. He has taught courses such as "Light, color and visual phenomena," "The physics of aesthetics and perception," and "Optics, perspective and Renaissance painting" over the last quarter century variously at leading liberal arts and research universities such as Wellesley College, Swarthmore College, Clark University and Stanford University. He has published over a hundred technical papers on human and machine learning and perception of patterns, physiological optics, image understanding, concurrency theory, theoretical mechanics, and five books, including Pattern Classification (2nd ed.), the world's all-time best-selling textbook in the field, widely used in computer vision courses. He sits on the editorial boards of four international journals and has delivered nearly 40 plenary lectures at major international conferences. He created the PBS television documentary "2001: HAL's Legacy," based on his book HAL's Legacy: 2001's computer as dream and reality (MIT). He was one of four scientists invited to comment on David Hockney's theory at the December 2001 "Art and Optics" Symposium at the New York Institute for the Humanities and one of two scientists invited to present a lecture in the symposium exploring the possible use of optics by Renaissance painters at the Optical Society of America's Annual Meeting in Rochester, NY, October 2004