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HieroGlyphTranslator: Automatic Recognition and Translation of Egyptian Hieroglyphs to English

Published 3 days agoVersion 1arXiv:2512.03817

Authors

Ahmed Nasser, Marwan Mohamed, Alaa Sherif, Basmala Mahmoud, Shereen Yehia, Asmaa Saad, Mariam S. El-Rahmany, Ensaf H. Mohamed

Categories

cs.CVcs.LG

Abstract

Egyptian hieroglyphs, the ancient Egyptian writing system, are composed entirely of drawings. Translating these glyphs into English poses various challenges, including the fact that a single glyph can have multiple meanings. Deep learning translation applications are evolving rapidly, producing remarkable results that significantly impact our lives. In this research, we propose a method for the automatic recognition and translation of ancient Egyptian hieroglyphs from images to English. This study utilized two datasets for classification and translation: the Morris Franken dataset and the EgyptianTranslation dataset. Our approach is divided into three stages: segmentation (using Contour and Detectron2), mapping symbols to Gardiner codes, and translation (using the CNN model). The model achieved a BLEU score of 42.2, a significant result compared to previous research.

HieroGlyphTranslator: Automatic Recognition and Translation of Egyptian Hieroglyphs to English

3 days ago
v1
8 authors

Categories

cs.CVcs.LG

Abstract

Egyptian hieroglyphs, the ancient Egyptian writing system, are composed entirely of drawings. Translating these glyphs into English poses various challenges, including the fact that a single glyph can have multiple meanings. Deep learning translation applications are evolving rapidly, producing remarkable results that significantly impact our lives. In this research, we propose a method for the automatic recognition and translation of ancient Egyptian hieroglyphs from images to English. This study utilized two datasets for classification and translation: the Morris Franken dataset and the EgyptianTranslation dataset. Our approach is divided into three stages: segmentation (using Contour and Detectron2), mapping symbols to Gardiner codes, and translation (using the CNN model). The model achieved a BLEU score of 42.2, a significant result compared to previous research.

Authors

Ahmed Nasser, Marwan Mohamed, Alaa Sherif et al. (+5 more)

arXiv ID: 2512.03817
Published Dec 3, 2025

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