TY  - CONF
AU  - Arnau Baro
AU  - Jialuo Chen
AU  - Alicia Fornes
AU  - Beata Megyesi
A2  - DATeCH
PY  - 2019//
TI  - Towards a generic unsupervised method for transcription of encoded manuscripts
BT  - 3rd International Conference on Digital Access to Textual Cultural Heritage
SP  - 73
EP  - 78
KW  - A. Baró
KW  - J. Chen
KW  - A. Fornés
KW  - B. Megyesi.
N2  - Historical ciphers, a special type of manuscripts, contain encrypted information, important for the interpretation of our history. The first step towards decipherment is to transcribe the images, either manually or by automatic image processing techniques. Despite the improvements in handwritten text recognition (HTR) thanks to deep learning methodologies, the need of labelled data to train is an important limitation. Given that ciphers often use symbol sets across various alphabets and unique symbols without any transcription scheme available, these supervised HTR techniques are not suitable to transcribe ciphers. In this paper we propose an un-supervised method for transcribing encrypted manuscripts based on clustering and label propagation, which has been successfully applied to community detection in networks. We analyze the performance on ciphers with various symbol sets, and discuss the advantages and drawbacks compared to supervised HTR methods.
L1  - http://refbase.cvc.uab.es/files/BCF2019.pdf
UR  - http://dx.doi.org/10.1145/3322905.3322920
N1  - DAG; 600.097; 600.140; 600.121
ID  - Arnau Baro2019
ER  -