Abstract
There are vast amount of historical documents written in cursive writing style in Japan. However, characters written by the style cannot be read by modern people, because the style was taught no longer. Therefore, an efficient method to convert historical characters into modern characters automatically is required. Especially, since every page in a Japanese historical document is stored by a photo image, it is necessary to automatically recognize all characters in a photo image. However, it is difficult to recognize each historical characters separately, because they are written connected and because there are many types of shape of characters. In this paper, we propose a method combining a method using deep learning to detect characters in a photo image and a method separating a block into characters. The remained parts that cannot be recognized by the former method are separated into characters by the latter method. Thus, it is expected that the recognition ratio is improved. We evaluate the performance of the proposed algorithm by using photo images of actual documents.
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Sichao, L., Miwa, H. (2020). Recognition of Historical Characters by Combination of Method Detecting Character in Photo Image of Document and Method Separating Block to Characters. In: Barolli, L., Okada, Y., Amato, F. (eds) Advances in Internet, Data and Web Technologies. EIDWT 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-030-39746-3_48
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DOI: https://doi.org/10.1007/978-3-030-39746-3_48
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