Recognition of Japanese connected cursive characters using multiple candidate regions

Kazuya Ueki; Kohei Yamada; Ryou Mutou; Rostam Sayyed Nezhad; Tomoka Kojima; Yasuaki Hagiwara; Takuya Taketomi

doi:10.1117/12.2566328

1 June 2020 Recognition of Japanese connected cursive characters using multiple candidate regions

Kazuya Ueki, Kohei Yamada, Ryou Mutou, Rostam Sayyed Nezhad, Tomoka Kojima, Yasuaki Hagiwara, Takuya Taketomi

Proceedings Volume 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020; 115152U (2020) https://doi.org/10.1117/12.2566328
Event: International Workshop on Advanced Imaging Technologies 2020 (IWAIT 2020), 2020, Yogyakarta, Indonesia

Abstract

It is very difficult to recognize cursive characters (kuzushiji) in classic Japanese literature. One of the difficulties is that multiple characters are connected. In this study, we propose a method for correctly recognizing consecutive kuzushiji characters by using multiple candidate regions as input to a neural network. An evaluation using an image database of three consecutive kuzushiji characters demonstrated that the proposed method had a higher accuracy rate than a method in which character detection preceded character recognition.

Citation Download Citation

Kazuya Ueki, Kohei Yamada, Ryou Mutou, Rostam Sayyed Nezhad, Tomoka Kojima, Yasuaki Hagiwara, and Takuya Taketomi "Recognition of Japanese connected cursive characters using multiple candidate regions", Proc. SPIE 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020, 115152U (1 June 2020); https://doi.org/10.1117/12.2566328

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