research-article

Labelling OCR Ground Truth for Usage in Repositories

Authors:

Matthias Boenig,

Konstantin Baierer,

Volker Hartmann,

Maria Federbusch,

Clemens NeudeckerAuthors Info & Claims

DATeCH2019: Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage

Pages 3 - 8

https://doi.org/10.1145/3322905.3322916

Published: 08 May 2019 Publication History

Abstract

The rapid developments in deep/machine learning algorithms have over the last decade largely replaced traditional pattern/language-based approaches to OCR. Training these new tools requires scanned images alongside their transcriptions (Ground Truth, GT). To OCR historical documents with high accuracy, a wide variety and variability of GT is required to create highly specific models for specific document corpora.

In this paper we present an XML-based format to exhaustively describe the features of GT for OCR relevant to training, storage and retrieval (GT metadata, GTM), as well as the tools for creating GT. We discuss the OCRD-ZIP format for bundling digitized books, including METS, images, transcription, GT metadata and more. We'll show how these data formats are used in different repository solutions within the OCR-D framework.

References

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[n. d.]. Metadata Object Description Schema (MODS). http://www.loc.gov/standards/mods/. Accessed: 2019-01-13.

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[n. d.]. OCRD-ZIP. https://ocr-d.github.io/ocrd_zip. Accessed: 2019-01-13.

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Ajinkya Prabhune, Rainer Stotzka, Vaibhav Sakharkar, Jürgen W. Hesser, and Michael Gertz. 2018. MetaStore: an adaptive metadata management framework for heterogeneous metadata models. Distributed and parallel databases 36, 1 (2018), 153--194. https://doi.org/10.1007/s10619-017-7210-4

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Cited By

Rezanezhad VBaierer KGerber MLabusch KNeudecker C(2023)Document Layout Analysis with Deep Learning and HeuristicsProceedings of the 7th International Workshop on Historical Document Imaging and Processing10.1145/3604951.3605513(73-78)Online publication date: 25-Aug-2023
https://dl.acm.org/doi/10.1145/3604951.3605513
Neudecker CBaierer KGerber MClausner CAntonacopoulos APletschacher S(2021)A survey of OCR evaluation tools and metricsProceedings of the 6th International Workshop on Historical Document Imaging and Processing10.1145/3476887.3476888(13-18)Online publication date: 5-Sep-2021
https://dl.acm.org/doi/10.1145/3476887.3476888
Baierer KDong RNeudecker C(2019)okralact - a multi-engine Open Source OCR training systemProceedings of the 5th International Workshop on Historical Document Imaging and Processing10.1145/3352631.3352638(25-30)Online publication date: 20-Sep-2019
https://dl.acm.org/doi/10.1145/3352631.3352638

Index Terms

Labelling OCR Ground Truth for Usage in Repositories
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Optical character recognition

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cover image ACM Other conferences

DATeCH2019: Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage

May 2019

163 pages

ISBN:9781450371940

DOI:10.1145/3322905

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 08 May 2019

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Deutsche Forschungsgemeinschaft

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DATeCH2019

DATeCH2019: 3rd International Conference on Digital Access to Textual Cultural Heritage

May 8 - 10, 2019

Brussels, Belgium

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Cited By

Rezanezhad VBaierer KGerber MLabusch KNeudecker C(2023)Document Layout Analysis with Deep Learning and HeuristicsProceedings of the 7th International Workshop on Historical Document Imaging and Processing10.1145/3604951.3605513(73-78)Online publication date: 25-Aug-2023
https://dl.acm.org/doi/10.1145/3604951.3605513
Neudecker CBaierer KGerber MClausner CAntonacopoulos APletschacher S(2021)A survey of OCR evaluation tools and metricsProceedings of the 6th International Workshop on Historical Document Imaging and Processing10.1145/3476887.3476888(13-18)Online publication date: 5-Sep-2021
https://dl.acm.org/doi/10.1145/3476887.3476888
Baierer KDong RNeudecker C(2019)okralact - a multi-engine Open Source OCR training systemProceedings of the 5th International Workshop on Historical Document Imaging and Processing10.1145/3352631.3352638(25-30)Online publication date: 20-Sep-2019
https://dl.acm.org/doi/10.1145/3352631.3352638

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