Deteriorated Characters Restoration for Early Japanese Books Using Enhanced CycleGAN

Author:

Kaneko Hayata1,Ishibashi Ryuto1,Meng Lin2ORCID

Affiliation:

1. Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu 525-8577, Shiga, Japan

2. College of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu 525-8577, Shiga, Japan

Abstract

Early Japanese books, classical humanities resources in Japan, have great historical and cultural value. However, Kuzushi-ji, the old character in early Japanese books, is scratched, faded ink, and lost due to weathering and deterioration over the years. The restoration of deteriorated early Japanese books has tremendous significance in cultural revitalization. In this paper, we introduce augmented identity loss and propose enhanced CycleGAN for deteriorated character restoration, which combines domain discriminators and augmented identity loss. This enhanced CycleGAN makes it possible to restore multiple levels of deterioration in the early Japanese books. It obtains the high readability of the actual deteriorated characters, which is proved by higher structural similarity(SSIM) and accuracy of deep learning models than standard CycleGAN and traditional image processing. In particular, SSIM increases by 8.72%, and the accuracy of ResNet50 for damaged characters improves by 1.1% compared with the competitive CycleGAN. Moreover, we realize the automatic restoration of pages of early Japanese books written about 300 years ago.

Publisher

MDPI AG

Subject

Materials Science (miscellaneous),Archeology,Conservation

Reference36 articles.

1. The Early Japanese Books Reorganization by Combining Image processing and Deep Learning;Lyu;CAAI Trans. Intell. Technol.,2022

2. KuroNet: Regularized residual U-Nets for end-to-end Kuzushiji character recognition;Lamb;SN Comput. Sci.,2020

3. A Method of Japanese Ancient Text Recognition by Deep Learning;Chen;Procedia Comput. Sci.,2020

4. (2023, May 10). Available online: http://codh.rois.ac.jp/.

5. (2023, May 10). Available online: https://www.arc.ritsumei.ac.jp/.

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