Publication Details

Page Layout Analysis System for Unconstrained Historic Documents

KODYM, O.; HRADIŠ, M. Page Layout Analysis System for Unconstrained Historic Documents. In Lladós J., Lopresti D., Uchida S. (eds) Document Analysis and Recognition - ICDAR 2021. Lecture Notes in Computer Science. Lausanne: Springer Nature Switzerland AG, 2021. p. 492-506. ISBN: 978-3-030-86330-2.
Czech title
Systém pro analýzu stránek libovolných historických dokumentů
Type
conference paper
Language
English
Authors
Kodym Oldřich, Ing., Ph.D.
Hradiš Michal, Ing., Ph.D. (DCGM)
Keywords

Layout analysis, Historic documents analysis, Text line extraction 

Abstract

Extraction of text regions and individual text lines from historic documents is necessary for automatic transcription. We propose extending a CNN-based text baseline detection system by adding line height and text block boundary predictions to the model output, allowing the system to extract more comprehensive layout information. We also show that pixel-wise text orientation prediction can be used for processing documents with multiple text orientations. We demonstrate that the proposed method performs well on the cBAD baseline detection dataset. Additionally, we benchmark the method on newly introduced PERO layout dataset which we also make public.

Published
2021
Pages
492–506
Proceedings
Lladós J., Lopresti D., Uchida S. (eds) Document Analysis and Recognition - ICDAR 2021
Series
Lecture Notes in Computer Science
ISBN
978-3-030-86330-2
Publisher
Springer Nature Switzerland AG
Place
Lausanne
DOI
UT WoS
000770800600032
EID Scopus
BibTeX
@inproceedings{BUT175782,
  author="Oldřich {Kodym} and Michal {Hradiš}",
  title="Page Layout Analysis System for Unconstrained Historic Documents",
  booktitle="Lladós J., Lopresti D., Uchida S. (eds) Document Analysis and Recognition - ICDAR 2021",
  year="2021",
  series="Lecture Notes in Computer Science",
  pages="492--506",
  publisher="Springer Nature Switzerland AG",
  address="Lausanne",
  doi="10.1007/978-3-030-86331-9\{_}32",
  isbn="978-3-030-86330-2"
}
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