Abstract
The paper introduces a methodology for the automatic classification of ancient Greek inscriptions to cutters by exploiting the three dimensional digital representation of each inscription. In particular, the authors employed surface information features extracted from 3D datasets of the letters depicted on each inscription. Therefore, implementations of various alphabet symbols are used to extract a three dimensional “ideal” prototype of the symbol for each inscription separately. Next, statistical criteria are introduced so as to reject the hypothesis that two inscriptions have been carved by the same writer, determining thus the distinct number of cutters who carved a given set of inscriptions. The remaining inscriptions are then classified to the (be) determined by the previous step cutters by maximizing resemblance likelihood of their underlined alphabet symbols “ideal” prototypes. The methodology has been applied to twenty eight Ancient Athenian inscriptions and classified them to eight different cutters. The classification results have been fully confirmed by expert epigraphists.
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Galanopoulos, G., Papaodysseus, C., Arabadjis, D., Exarhos, M. (2012). Exploiting 3D Digital Representations of Ancient Inscriptions to Identify Their Writer. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33191-6_19
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DOI: https://doi.org/10.1007/978-3-642-33191-6_19
Publisher Name: Springer, Berlin, Heidelberg
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