2025/12/03 by Ahmed R. Nasser, Mimdal Mohamed, Nasser, Ahmed +11
Computer Science · Arts and Humanities · #Image Processing and 3D Reconstruction #Handwritten Text Recognition Techniques #Ancient Egypt and Archaeology
paper · pdf · doi:10.48550/arxiv.2512.03817
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.