Detailed Information on Publication Record
2022
When Tesseract Meets PERO : Open-Source Optical Character Recognition of Medieval Texts
NOVOTNÝ, Vít and Aleš HORÁKBasic information
Original name
When Tesseract Meets PERO : Open-Source Optical Character Recognition of Medieval Texts
Authors
NOVOTNÝ, Vít (203 Czech Republic, guarantor, belonging to the institution) and Aleš HORÁK (203 Czech Republic, belonging to the institution)
Edition
Brno, Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022. p. 157-161, 5 pp. 2022
Publisher
Tribun EU
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10200 1.2 Computer and information sciences
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
printed version "print"
References:
RIV identification code
RIV/00216224:14330/22:00127481
Organization unit
Faculty of Informatics
ISBN
978-80-263-1752-4
ISSN
Keywords in English
optical character recognition; OCR; medieval texts; AHISTO project
Změněno: 15/5/2024 09:24, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
Conversion of scanned images to the text form, denoted as optical character recognition or OCR, for contemporary printed texts is widely considered a solved problem. However, the optical character recognition of early printed books and reprints of medieval texts remains an open challenge. In our previous work, we developed an end-to-end image-to-text pipeline (via optical character recognition) for medieval texts, named AHISTO OCR, and we released it together with our test dataset under open licenses. However, the published system relied on the closed-source Google Vision AI service as one component, which made the experiments less reproducible. In this work, we replace Google Vision AI with an open-source OCR algorithm named PERO and we show that this not only makes the AHISTO OCR pipeline open, but also improves the performance of the system. We release the updated AHISTO OCR system and its test results again under open licenses.
Links
LM2018101, research and development project |
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