D 2021

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

BANKOVIČ, Mikuláš, Vít NOVOTNÝ and Petr SOJKA

Basic information

Original name

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

Authors

BANKOVIČ, Mikuláš (703 Slovakia, guarantor, belonging to the institution), Vít NOVOTNÝ (203 Czech Republic, belonging to the institution) and Petr SOJKA (203 Czech Republic, belonging to the institution)

Edition

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

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/00216224:14330/21:00119900

Organization unit

Faculty of Informatics

ISBN

978-80-263-1670-1

ISSN

Keywords in English

Super-resolution; Optical character recognition; Medieval texts
Změněno: 15/5/2024 10:24, RNDr. Pavel Šmerk, Ph.D.

Abstract

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.