Abstract
Cuneiform writing is one of the earliest methods of writing in human history. It is based on pressing a stylus (reed) on clay tablets, resulting in wedge marks (cuneiforms) which, when combined, provide meaningful symbols. Applying modern machine learning methods to the study of ancient cuneiform tablets is a fascinating task. In the present paper we describe a method for extracting geometrical features of the wedges imprinted by the stylus that is used for writing. We introduce two independent feature extraction methods to describe the wedges. The data for this study come from precise optical scans of three tablets, originating from different historical periods. We use these tablets to demonstrate the validity of our extracted features, and to demonstrate the accuracy of classifying the different tablets.
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