Unsupervised Detection and Localization of Egyptian Hieroglyphs

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dc.contributor.authorLion, Paulineen_US
dc.contributor.authorTrunz, Elenaen_US
dc.contributor.authorKlein, Reinharden_US
dc.contributor.editorCorsini, Massimilianoen_US
dc.contributor.editorFerdani, Danieleen_US
dc.contributor.editorKuijper, Arjanen_US
dc.contributor.editorKutlu, Hasanen_US
dc.date.accessioned2024-09-15T09:57:17Z
dc.date.available2024-09-15T09:57:17Z
dc.date.issued2024
dc.description.abstractThe extensive variability in hieroglyph forms, coupled with erosion, fading, damage, and lighting effects, makes hieroglyphic script highly complex and difficult to segment. This complexity, along with the scarcity of labeled data, poses challenges for traditional supervised learning methods. In this paper, we present a novel unsupervised approach for detecting and localizing Egyptian hieroglyphs in images. Our method employs classical computer vision algorithms to generate pseudo-labels, which are then used to train a Faster R-CNN model. Augmented by post-processing techniques, our approach achieves detection results comparable to that of previous supervised methods for hieroglyph segmentation. Evaluated on unseen backgrounds, it demonstrates significant potential for advancing research in Egyptian culture and history.en_US
dc.description.sectionheadersAI-based Wedge and Glyph Detection
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.identifier.doi10.2312/gch.20241259
dc.identifier.isbn978-3-03868-248-6
dc.identifier.issn2312-6124
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/gch.20241259
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/gch20241259
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Object detection; Computer vision; Applied computing → Arts and humanities; Archaeology
dc.subjectComputing methodologies → Object detection
dc.subjectComputer vision
dc.subjectApplied computing → Arts and humanities
dc.subjectArchaeology
dc.titleUnsupervised Detection and Localization of Egyptian Hieroglyphsen_US
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GCH 2024 - Eurographics Workshop on Graphics and Cultural Heritage