Automatic Egyptian hieroglyph recognition by retrieving images as texts

In this paper we propose an approach for automatically recognizing ancient Egyptian hieroglyph from photographs. To this end we first manually annotated and segmented a large collection of nearly 4,000 hieroglyphs. In our automatic approach we localize and segment each individual hieroglyph, determine the reading order and subsequently evaluate 5 visual descriptors in 3 different matching schemes to evaluate visual hieroglyph recognition. In addition to visual-only cues, we use a corpus of Egyptian texts to learn language models that help re-rank the visual output.

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