Combining OCR Models for Reading Early Modern Books
Seuret M, van der Loop J, Weichselbaumer N, Mayr M, Molnar J, Hass T, Christlein V (2023)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2023
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
City/Town: Cham
Book Volume: 14191 LNCS
Pages Range: 342-357
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: San José, CA
ISBN: 9783031417337
DOI: 10.1007/978-3-031-41734-4_21
Open Access Link: https://arxiv.org/abs/2305.07131
Abstract
In this paper, we investigate the usage of fine-grained font recognition on OCR for books printed from the 15th to the 18th century. We used a newly created dataset for OCR of early printed books for which fonts are labeled with bounding boxes. We know not only the font group used for each character, but the locations of font changes as well. In books of this period, we frequently find font group changes mid-line or even mid-word that indicate changes in language. We consider 8 different font groups present in our corpus and investigate 13 different subsets: the whole dataset and text lines with a single font, multiple fonts, Roman fonts, Gothic fonts, and each of the considered fonts, respectively. We show that OCR performance is strongly impacted by font style and that selecting fine-tuned models with font group recognition has a very positive impact on the results. Moreover, we developed a system using local font group recognition in order to combine the output of multiple font recognition models, and show that while slower, this approach performs better not only on text lines composed of multiple fonts but on the ones containing a single font only as well.
Authors with CRIS profile
Mathias Seuret
Lehrstuhl für Informatik 5 (Mustererkennung)
Martin Mayr
Lehrstuhl für Informatik 5 (Mustererkennung)
Vincent Christlein
Lehrstuhl für Informatik 5 (Mustererkennung)
Involved external institutions
Germany (DE)How to cite
APA:
Seuret, M., van der Loop, J., Weichselbaumer, N., Mayr, M., Molnar, J., Hass, T., & Christlein, V. (2023). Combining OCR Models for Reading Early Modern Books. In Gernot A. Fink, Rajiv Jain, Koichi Kise, Richard Zanibbi (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 342-357). San José, CA, US: Cham: Springer Science and Business Media Deutschland GmbH.
MLA:
Seuret, Mathias, et al. "Combining OCR Models for Reading Early Modern Books." Proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2023, San José, CA Ed. Gernot A. Fink, Rajiv Jain, Koichi Kise, Richard Zanibbi, Cham: Springer Science and Business Media Deutschland GmbH, 2023. 342-357.
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