Oumayma Bounou ; Tom Monnier ; Ilaria Pastrolin ; Xi Shen ; Marie-Françoise Limon-Bonnet et al. - A Web Application for Watermark Recognition

jdmdh:6220 - Journal of Data Mining & Digital Humanities, July 17, 2020, Atelier Digit\_Hum - https://doi.org/10.46298/jdmdh.6220
A Web Application for Watermark RecognitionArticle

Authors: Oumayma Bounou 1,2,3,4,5; Tom Monnier 6,3,4; Ilaria Pastrolin 7; Xi SHEN ; Christine Benevent 8,2; Marie-Françoise Limon-Bonnet 9,7; François Bougard ORCID10; Mathieu Aubry 3; Marc H. Smith 6,7; Olivier Poncet 11,7; Pierre-Guillaume Raverdy 12,5

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 difficultiesand is still considered an unsolved challenge. Nonetheless, Shen et al. [2019] recently introduced a newapproach for this specific task which showed promising results. Building upon this approach, this workproposes a new public web application dedicated to automatic watermark recognition entitled Filigranespour 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 photographin 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 athttp://filigranes.inria.fr/.


Volume: Atelier Digit\_Hum
Section: Data deluge: which skills for wich data?
Published on: July 17, 2020
Accepted on: July 15, 2020
Submitted on: March 26, 2020
Keywords: cross-domain recognition,deep learning,watermark recognition,web application,paper analysis,[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

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