Character retrieval of vectorized cuneiform script

Motivated by the increasing demand for computerized analysis of documents within the Digital Humanities we present an approach to automating handwritten cuneiform character recognition on vectorized cuneiform tablets. Cuneiform is one of the oldest handwritten scripts used for more than three millennia. In previous work we have shown how to extract vector drawings from 3D-models of cuneiform tablets similar to those manually drawn over digital photographs. We approach the problem of recognizing these characters by applying pattern matching against the basic structural features of cuneiform, the wedge-shaped impressions. Then, we find an optimal assignment between the wedge configuration of two characters w.r.t. wedge shape and position. The similarity of two characters is measured by the quality of the assignment. We compare our method against well known methods for handwritten character recognition with favorable results for our method.