ABSTRACT
Reprint of Japanese historical manuscripts is time-consuming and requires training because they are hand-written, and may contain characters different from those currently used. We proposed a framework for assisting the human process for reading Japanese historical manuscripts and implemented a part of a system based on the framework as a Web service. In this paper, we present a graphical user interface (GUI) for the system and reprint process through the GUI. We conducted a user test to evaluate the system with the GUI by a questionnaire. From the results of the experiment, we confirmed that the GUI can be used intuitively but we also found points to be improved in the GUI.
- Yuta Arai, Tetsuya Suzuki, and Akira Aiba. 2013. Recognizing Historical KANA Texts Using Constraints. Springer Japan, Tokyo, 151--164.Google Scholar
- Richard G. Casey and Eric Lecolinet. 1996. A Survey of Methods and Strategies in Character Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 18, 7 (July 1996), 690--706. Google ScholarDigital Library
- Bjarke Frellesvig. 2010. A History of the Japanese Language. Cambridge University Press. Google ScholarDigital Library
- Taichi Hayasaka, Wataru Ohno, Yumie Kato, and Kazuaki Yamamoto. 2017. Recognition of Kuzushiji (Hentaigana and cursive script) by Deep Learning (ver.0.4.1). (2017). http://vpac.toyota-ct.ac.jp/kuzushiji/Google Scholar
- Taichi Hayasaka, Wataru Ohno, Yumie Kato, and Kazuaki Yamamoto. 2017. Trial Production of Application Software for Machine Transcription of Hentaigana by Deep Learning. In Proceedings of the 31st Annual Conference of the Japanese Society for Artificial Intelligence.Google Scholar
- Laurence Likforman-Sulem, Abderrazak Zahour, and Bruno Taconet. 2007. Text line segmentation of historical documents: a survey. International Journal of Document Analysis and Recognition (IJDAR) 9, 2 (01 Apr 2007), 123--138. Google ScholarDigital Library
- Ryuichi Oka. 1998. Spotting Method for Classification of Real World Data. Comput. J. 41, 8 (1998), 559--565.Google ScholarCross Ref
- Tamekazu Reizei. 1994. Tales of Ise (photocopy). Kasama Shoin.Google Scholar
- Kazuki Sando, Tetsuya Suzuki, and Akira Aiba. 2018. A Constraint Solving Web Service for Recognizing Historical Japanese KANA Texts. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,. INSTICC, SciTePress, 257--265.Google ScholarCross Ref
- Kengo Terasawa and Toshio Kawashima. 2011. Word Spotting Online. In Proceedings of the Computers and the Humanities Symposium, Vol. 2011. 329--334.Google Scholar
- Satoru Watanabe, Tetsuya Suzuki, and Akira Aiba. 2015. Reducing of the Number of Solutions Using Adjacency Relation of Words in Recognizing Historical KANA Texts. IPSJ Journal 56, 3 (mar 2015), 951--959. http://ci.nii.ac.jp/naid/110009884088/en/Google Scholar
- Shoji Yamada and Mamoru Shibayama. 2003. An Estimation Method of Unreadable Historical Character for Manuscripts in Fixed Forms using n - gram and OCR. IPSJ SIG Notes 2003, 59 (may 2003), 17--24. http://ci.nii.ac.jp/naid/110002911078/en/Google Scholar
- Sumiko Yamamoto and Tomejiro Osawa. 2016. Labor saving for reprinting Japanese rare classical books. Journal of Information Processing and Management 58, 11 (2016), 819--827.Google Scholar
Index Terms
- A Handwritten Japanese Historical Kana Reprint Support System: Development of a Graphical User Interface
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