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Authors: Kazuya Ueki and Tomoka Kojima

Affiliation: School of Information Science, Meisei University, Tokyo, Japan

Keyword(s): Character Recognition, Japanese Cursive Character, Kuzushiji, Convolutional Neural Network.

Abstract: We conducted detailed experiments of Japanese cursive character recognition to promote Japanese historical document transcription and digitization by using a publicly available kuzushiji dataset released by the Center for Open Data in the Humanities (CODH). Using deep learning, we analyzed the causes of recognition difficulties through a recognition experiment of over 1,500-class of kuzushiji characters. Furthermore, assuming actual transcription conditions, we introduced a method to automatically determine which characters should be held for judgment by identifying difficult-to-recognize characters or characters that were not used during training. As a result, we confirmed that a classification rate of more than 90% could be achieved by narrowing down the characters to be classified even when a recognition model with a classification rate of 73.10% was used. This function could improve transcribers’ ability to judge correctness from context in the post-process—namely, the previous a nd subsequent characters. (More)

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Paper citation in several formats:
Ueki, K. and Kojima, T. (2020). Japanese Cursive Character Recognition for Efficient Transcription. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 402-406. DOI: 10.5220/0008913204020406

@conference{icpram20,
author={Kazuya Ueki. and Tomoka Kojima.},
title={Japanese Cursive Character Recognition for Efficient Transcription},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={402-406},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008913204020406},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Japanese Cursive Character Recognition for Efficient Transcription
SN - 978-989-758-397-1
IS - 2184-4313
AU - Ueki, K.
AU - Kojima, T.
PY - 2020
SP - 402
EP - 406
DO - 10.5220/0008913204020406
PB - SciTePress

- Science and Technology Publications, Lda.
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