Decoding Raphael

This is the first project to investigate the use of computational techniques for the study of artistic practice, taking as point of departure the paintings of Raphael (Raffaello Sanzio, 1483-1520). Dozens of faithful reproductions survive of Raphael's paintings, attesting to the lucrative practice of serial production of paintings within the artist's workshop and to the lasting demand for the master's designs. This project will apply computer vision techniques to the study of these reproductions, providing new insights into Raphael's working methods while, more widely, pioneering new digital approaches for the study of artistic practice in art history.

We develop Unraphael; a digital workflow tool providing a flexible and easy-to-use GUI to inspect and assess the structural similarity of figure-outlines in images/ photographs from paintings. With features such as image preprocessing, background removal, image alignment, close visual inspection, and image clustering based on structural similarity, an image-processing pipeline is created which enables to answer research questions on copying techniques and genealogical relationships between the original paintings and its variants.

While Unraphael is made for art historians and researchers in the humanities to study the artistic practices of and the process of making copies of paintings, the functionality of Unraphael extends well beyond the study of Raphael's paintings and can be used for a wide range of applications in the digital humanities and beyond.