Application of Super-Resolution Models in Optical Character
Recognition of Czech Medieval Texts

D 2021

Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts

BANKOVIČ, Mikuláš, Vít NOVOTNÝ a Petr SOJKA

Základní údaje

Originální název

Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts

Autoři

BANKOVIČ, Mikuláš (703 Slovensko, garant, domácí), Vít NOVOTNÝ (203 Česká republika, domácí) a Petr SOJKA (203 Česká republika, domácí)

Vydání

Brno, Recent Advances in Slavonic Natural Language Processing (RASLAN 2021), od s. 11-18, 8 s. 2021

Nakladatel

Tribun EU

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

Domovská stránka workshopu Full text PDF

Kód RIV

RIV/00216224:14330/21:00119900

Organizační jednotka

Fakulta informatiky

ISBN

978-80-263-1670-1

ISSN

Klíčová slova anglicky

Super-resolution; Optical character recognition; Medieval texts

Změněno: 15. 5. 2024 10:24, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Optical character recognition (OCR) of scanned images is used in multiple applications in numerous domains and several frameworks and OCR algorithms are publicly available. However, some domains such as medieval texts suffer from low accuracy, mainly due to low resources and poor quality data. For such domains, preprocessing techniques help to increase the accuracy of OCR algorithms. In this paper, we experiment with two super-resolution models: Waifu2x and SRGAN. We use the models to reduce noise and increase the image resolution of scanned medieval texts. We evaluate the models on the AHISTO project dataset and compare them against several baselines. We show that our models produce improvements in OCR accuracy.

Citovat

BANKOVIČ, Mikuláš, Vít NOVOTNÝ a Petr SOJKA. Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts. In Horák, Rychlý, Rambousek. Recent Advances in Slavonic Natural Language Processing (RASLAN 2021). Brno: Tribun EU, 2021, s. 11-18. ISBN 978-80-263-1670-1.

@inproceedings{1809720,
   author = {Bankovič, Mikuláš and Novotný, Vít and Sojka, Petr},
   address = {Brno},
   booktitle = {Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)},
   editor = {Horák, Rychlý, Rambousek},
   keywords = {Super-resolution; Optical character recognition; Medieval texts},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Brno},
   isbn = {978-80-263-1670-1},
   pages = {11-18},
   publisher = {Tribun EU},
   title = {Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts},
   url = {https://raslan2021.nlp-consulting.net/},
   year = {2021}
}

TY  - JOUR
ID  - 1809720
AU  - Bankovič, Mikuláš - Novotný, Vít - Sojka, Petr
PY  - 2021
TI  - Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts
PB  - Tribun EU
CY  - Brno
SN  - 9788026316701
KW  - Super-resolution
KW  - Optical character recognition
KW  - Medieval texts
UR  - https://raslan2021.nlp-consulting.net/
N2  - Optical character recognition (OCR) of scanned images is used in multiple applications in numerous domains and several frameworks and OCR algorithms are publicly available. However, some domains such as medieval texts suffer from low accuracy, mainly due to low resources and poor quality data. For such domains, preprocessing techniques help to increase the accuracy of OCR algorithms. In this paper, we experiment with two super-resolution models: Waifu2x and SRGAN. We use the models to reduce noise and increase the image resolution of scanned medieval texts. We evaluate the models on the AHISTO project dataset and compare them against several baselines. We show that our models produce improvements in OCR accuracy.
ER  -

BANKOVIČ, Mikuláš, Vít NOVOTNÝ a Petr SOJKA. Application of Super-Resolution Models in Optical Character Recognition of Czech Medieval Texts. In Horák, Rychlý, Rambousek. \textit{Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)}. Brno: Tribun EU, 2021, s.~11-18. ISBN~978-80-263-1670-1.

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