Abstract

Recent interdisciplinary research in visual stylometry employs digital image analysis algorithms to study the image features and statistics that underwrite our experience of artworks. This research brings psychologists, computer scientists, and art historians together to explore the formal image qualities that define artistic style. We introduce the field of visual stylometry, discuss it's implications for our understanding of both the nature of categories of art and the role artistic style plays in our engagement with artworks. We then discuss the results of our research employing entropy analyses and discrete tonal analyses to classify paintings by school (Impressionism/Hudson River School) and medium/technique (Wyeth/egg-tempura/watercolor).