1 Service Expérimentation et Développement [Paris Rocquencourt]
2 École nationale des chartes
3 Laboratoire d'Informatique Gaspard-Monge
4 Models of visual object recognition and scene understanding
5 Centre Jean Mabillon
6 Archives nationales
7 Institut de recherche et d'histoire des textes
8 Comité des travaux historiques et scientifiques
The study of watermarks is a key step for archivists and historians as it enables them to reveal the origin of paper. Although highly practical, automatic watermark recognition comes with many difficulties and is still considered an unsolved challenge. Nonetheless, Shen et al. [2019] recently introduced a new approach for this specific task which showed promising results. Building upon this approach, this work proposes a new public web application dedicated to automatic watermark recognition entitled Filigranes pour tous. The application not only hosts a detailed catalog of more than 17k watermarks manually collected from the French National Archives (Minutier central) or extracted from existing online resources (Briquet database), but it also enables non-specialists to identify a watermark from a simple photograph in a few seconds. Moreover, additional watermarks can easily be added by the users making the enrichment of the existing catalog possible through crowdsourcing. Our Web application is available at https://filigranes.inria.fr/.
Keywords: [SHS.MUSEO]Humanities and Social Sciences/Cultural heritage and museology
Funding:
Source : OpenAIRE Graph
Exploitation des bases d'images patrimoniales; Funder: French National Research Agency (ANR); Code: ANR-17-CE23-0008
References
1 Document citing this article
Xi Shen;Robin Champenois;Shiry Ginosar;Ilaria Pastrolin;Morgane Rousselot;et al., 2022, Spatially-Consistent Feature Matching and Learning for Heritage Image Analysis, HAL (Le Centre pour la Communication Scientifique Directe), 130, 5, pp. 1325-1339, omid:br/062502792895 doi:10.1007/s11263-022-01576-x, https://hal.science/hal-03620996.