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Authors: Sayaka Mori and Tetsuya Suzuki

Affiliation: Department of Electronic Information Systems, College of Systems Engineering and Science, Shibaura Institute of Technology, Saitama, Japan

Keyword(s): Text Line Segmentation, Historical Document, Deep Learning, Semantic Segmentation, Data Synthesis.

Abstract: Because it is difficult even for Japanese to read handwritten Japanese historical documents, computer-assisted transcription of such documents is helpful. We plan to apply semantic segmentation to text line segmentation for handwritten Japanese historical documents. We use both synthesized document images resembling a Japanese historical document and annotations for them because it is time-consuming to manually annotate a large set of document images for training data. The purpose of this research is to evaluate the effect of fine-tuning semantic segmentation models with synthesized Japanese historical document images in text line segmentation. The experimental results show that the segmentation results produced by our method are generally satisfactory for test data consisting of synthesized document images and are also satisfactory for Japanese historical document images with straightforward formats.

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Paper citation in several formats:
Mori, S. and Suzuki, T. (2024). Experimental Application of Semantic Segmentation Models Fine-Tuned with Synthesized Document Images to Text Line Segmentation in a Handwritten Japanese Historical Document. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-684-2; ISSN 2184-4313, SciTePress, pages 826-832. DOI: 10.5220/0012433100003654

@conference{icpram24,
author={Sayaka Mori and Tetsuya Suzuki},
title={Experimental Application of Semantic Segmentation Models Fine-Tuned with Synthesized Document Images to Text Line Segmentation in a Handwritten Japanese Historical Document},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2024},
pages={826-832},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012433100003654},
isbn={978-989-758-684-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Experimental Application of Semantic Segmentation Models Fine-Tuned with Synthesized Document Images to Text Line Segmentation in a Handwritten Japanese Historical Document
SN - 978-989-758-684-2
IS - 2184-4313
AU - Mori, S.
AU - Suzuki, T.
PY - 2024
SP - 826
EP - 832
DO - 10.5220/0012433100003654
PB - SciTePress

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