Jialuo Chen
Computer Vision Center, Computer Science Department, Universitat Autònoma de Barcelona
Mohamed Ali Souibgui
Computer Vision Center, Computer Science Department, Universitat Autònoma de Barcelona
Alicia Fornés
Computer Vision Center, Computer Science Department, Universitat Autònoma de Barcelona
Beáta Megyesi
Dept. of Linguistics and Philology, Uppsala University, Sweden
Ladda ner artikel
https://doi.org/10.3384/ecp2020171008Ingår i: Proceedings of the 3rd International Conference on Historical Cryptology HistoCrypt 2020
Linköping Electronic Conference Proceedings 171:8, s. 52-59
NEALT Proceedings Series 44:8, p. 52-59
Publicerad: 2020-05-19
ISBN: 978-91-7929-827-2
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
Manual transcription of handwritten text is a time consuming task. In the case of encrypted manuscripts, the recogni-tion is even more complex due to the huge variety of alphabets and symbol sets. To speed up and ease this process, we present a web-based tool aimed to (semi)-automatically transcribe the encrypted sources. The user uploads one or several images of the desired encrypted document(s) as input, and the system returns the transcription(s). This process is carried out in an interactive fashion with the user to obtain more accurate results. For discovering and testing, the developed web tool is freely available.
Historical encoded manuscripts; Web based transcription tool; Semi-automatic transcription; Unsupervised learning
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