Ancient Egyptian Hieroglyphic Texts Structure Identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00382709" target="_blank" >RIV/68407700:21230/25:00382709 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-78014-1_27" target="_blank" >https://doi.org/10.1007/978-3-031-78014-1_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-78014-1_27" target="_blank" >10.1007/978-3-031-78014-1_27</a>
Alternative languages
Result language
angličtina
Original language name
Ancient Egyptian Hieroglyphic Texts Structure Identification
Original language description
In our project, we deal with translating texts recorded by the ancient Egyptian civilization into contemporary English. In this paper, we focus particularly on identification of text structures consisting of hieroglyphs. The identification is based on classification of segmented image blobs and their spatial relations using graph neural networks. We reached 99.8% accuracy on a dataset of facsimiles created for the shaft tomb of Menekhibnekau. The high accuracy is due to a combination of precise results achieved by the CRAFT method, additional features like the size of the hieroglyphs, including very robust topological properties of blob adjacency weighted by the learned nonlinear graph neural network scheme not relying on simple horizontal or vertical projections as used in standard OCR approaches. The graph of blob spatial relations is built using distance transform. We also propose an algorithm for a separation of hieroglyphs from mostly linear structures delineating the strips of hieroglyphs if they touch. Strips of hieroglyphs identified this way can be used to extract blobs of glyphs into reading sequences before their classification to Gardiner’s codes, transliteration and translation. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA24-11979S" target="_blank" >GA24-11979S: Hieroglyph Recognition and Translation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
26th International Conference on Speech and Computer, SPECOM 2024
ISBN
978-3-031-78014-1
ISSN
1611-3349
e-ISSN
1611-3349
Number of pages
16
Pages from-to
362-377
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
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Event location
Belgrade
Event date
Nov 25, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001415334000027