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CITATION.cff
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: >-
Loghi: An End-to-End Framework for Making Historical
Documents Machine-Readable
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- orcid: "https://orcid.org/0000-0001-6535-2849"
affiliation: Humanities Cluster KNAW
email: [email protected]
given-names: Rutger
name-particle: van
family-names: Koert
- affiliation: Humanities Cluster KNAW
given-names: Stefan
family-names: Klut
email: [email protected]
orcid: "https://orcid.org/0000-0002-1957-2442"
- given-names: Tim
family-names: Koornstra
email: [email protected]
affiliation: Nationaal Archief
orcid: "https://orcid.org/0009-0002-5643-6180"
- given-names: Martijn
family-names: Maas
email: [email protected]
affiliation: Humanities Cluster KNAW
orcid: "https://orcid.org/0009-0000-4850-2614"
- affiliation: Nationaal Archief
orcid: "https://orcid.org/0009-0000-2274-8608"
email: [email protected]
given-names: Luke
family-names: Peters
identifiers:
- type: doi
value: 10.1007/978-3-031-70645-5_6
description: DOI of the Springer publication
- type: url
value: "https://github.com/knaw-huc/loghi"
description: Github repo
repository-code: "https://github.com/knaw-huc/loghi"
abstract: >-
"Loghi is a novel framework and suite of tools for the layout analysis and text recognition of historical documents. Scans are processed in a modular pipeline, with the option to use alternative tools in most stages. Layout analysis and text recognition can be trained on example images with PageXML ground truth. The framework is intended to convert scanned documents to machine-readable PageXML. Additional tooling is provided for the creation of synthetic ground truth. A visualiser for troubleshooting the text recognition training is also made available. The result is a framework for end-to-end text recognition, which works from initial layout analysis on the scanned documents, and includes text line detection, text recognition, reading order detection and language detection. The Loghi pipeline has been used successfully in several projects. We achieve good results on the layout analysis and text recognition of both the handwritten and printed archives of the Dutch States General on resolutions spanning the 17th and 18th century. The CER on handwritten 17th century material is below 3 percent. Loghi is open source and free to use."
keywords:
- pagexml
- handwritten text recognition
- layout analysis
license: MIT
preferred-citation:
type: conference-paper
authors:
- orcid: "https://orcid.org/0000-0001-6535-2849"
affiliation: Humanities Cluster KNAW
email: [email protected]
given-names: Rutger
name-particle: van
family-names: Koert
- affiliation: Humanities Cluster KNAW
given-names: Stefan
family-names: Klut
email: [email protected]
orcid: "https://orcid.org/0000-0002-1957-2442"
- given-names: Tim
family-names: Koornstra
email: [email protected]
affiliation: Nationaal Archief
orcid: "https://orcid.org/0009-0002-5643-6180"
- given-names: Martijn
family-names: Maas
email: [email protected]
affiliation: Humanities Cluster KNAW
orcid: "https://orcid.org/0009-0000-4850-2614"
- affiliation: Nationaal Archief
orcid: "https://orcid.org/0009-0000-2274-8608"
email: [email protected]
given-names: Luke
family-names: Peters
title: >-
Loghi: An End-to-End Framework for Making Historical Documents Machine-Readable
isbn: 978-3-031-70645-5
conference:
name: "Document Analysis and Recognition -- ICDAR 2024 Workshops"
location: "Athens, Greece"
pages: 73-88
publisher: Springer Nature Switzerland
editors:
- name: "Mouchère, Harold"
- name: "Zhu, Anna"
year: 2024
doi: 10.1007/978-3-031-70645-5_6
abstract: >-
"Loghi is a novel framework and suite of tools for the layout analysis and text recognition of historical documents. Scans are processed in a modular pipeline, with the option to use alternative tools in most stages. Layout analysis and text recognition can be trained on example images with PageXML ground truth. The framework is intended to convert scanned documents to machine-readable PageXML. Additional tooling is provided for the creation of synthetic ground truth. A visualiser for troubleshooting the text recognition training is also made available. The result is a framework for end-to-end text recognition, which works from initial layout analysis on the scanned documents, and includes text line detection, text recognition, reading order detection and language detection. The Loghi pipeline has been used successfully in several projects. We achieve good results on the layout analysis and text recognition of both the handwritten and printed archives of the Dutch States General on resolutions spanning the 17th and 18th century. The CER on handwritten 17th century material is below 3 percent. Loghi is open source and free to use."