Congrès DH2022 – Tokyo- Juillet 2022

Le projet ROIi a participé au congrès mondial Digital Humanities de Tokyo qui s’est déroulé en visioconférence du fait de la pandémie de covid-19. Christelle Bahier-Porte et Thierry Fournel ont présenté, au nom de l’équipe, les principes, enjeux et premiers résultats du projet au sein d’un panel organisé par Hazel Wilkinson (University of Birmingham).

Le panel s’intitule Computer Vision for the Study of Printers’ Ornaments and Illustrations in European Hand-Press Books. Le programme est le suivant :

Giles Bergel, Abhishek Dutta (University of Oxford, Department of Engineering Science), “Visual Analysis of Chapbooks Printed in Scotland”

Christelle Bahier-Porte (UJM, IHRIM), Thierry Fournel (UJM, Laboratoire Hubert Curien),”Region of interest to investigate after learning the use of ornaments by Rey”

Hazel Wilkinson (University of Birmingham, Alan Turing Insitute) “Compositor, Visual AI, and Quantitative Network Analysis: Opportunities and Obstacles”

Drew Thomas (University of St Andrews), “Using Artificial Intelligence to Identify the Counterfeit Printers of the Protestant Reformation”

Panel Abstract:

Printers’ ornaments are the decorative images that appear in printed books to embellish title pages, headings, chapter endings, and any otherwise blank spaces. They were common throughout the hand press period in Europe (c.1470-1830), when they were printed from designs cut into wood or metal blocks, or cast in type-metal (Wilkinson, 2019). They are closely related to woodcut chapbook illustrations, which provided contextual visual stimuli to readers, and, like ornaments, were often designed in such a way that they could be reused in different contexts. Both cuts and type ornaments are like bibliographical fingerprints: their unique features can allow us to identify the printer of a book, even if the printer did not sign their name, or used a pseudonym (Maslen, 2001; Blayney 2021). Identifying a book’s printer can help us to date printed material, and better understand the workings of the book trade, and the circulation of texts and ideas. In literary studies, printers’ ornaments assist in our enquiries into the original circumstances of a book’s production, guiding the decisions of scholarly editors by increasing our understanding of the relationships between authors and the craftspeople who gave their texts material form. Ornaments are also of intrinsic interest as examples of graphic design.

Computer vision and machine learning can help us to build databases of ornaments and cuts, and to derive useful information from them. The four papers in this panel will present different problems and solutions arising from the use of visual AI to investigate ornaments and illustrations. Four projects are represented here, each of which has made some use of the open source VGG Image Search Engine (VISE) , and a key aspect of the panel will be discussion of the strengths and limitations of VISE for different kinds of research into ornament and illustration. The papers argue that different approaches are necessary when dealing with large, catch-all databases, compared to smaller, curated datasets that concentrate on a single printer or document type, with two examples of each kind. Paying attention to recent scholarship, several of the papers advance the established potential of ornaments to solve problems of printer identification and fraud detection (May, 2019). These papers will discuss the strengths and limitations of visual AI versus the human expert when it comes to making fine distinctions between images. It is possible to use data visualisation to draw wider conclusions from ornament usage about the activities and habits of printers, which could shape our understanding of the circulation of ideas in early modern Europe. Some of the papers will present arguments for the best use of the data these projects are producing, but the panel will also reflect on the inherent biases and flaws in digitization projects, which can skew our conclusions (Orr, 2021). The panel itself consists of both senior and early career researchers of different nationalities, and includes both men and women.

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