Eugen Rusakov, Turna Somel, Gernot A. Fink and Gerfrid G. W. Mueller
Proc. Int. Conf. on Frontiers in Handwriting Recognition, 2020.
Dortmund, NRW, Germany
Intermediate representations based on binary at- tributes are widely used for image retrieval tasks. Especially for the task of word spotting, attribute representations continually achieves state-of-the-art results. In contrast to Latin scripts, the cuneiform writing system is still a less well-known domain for the document analysis community. This writing system consists of wedge impressions, with the constellations and relative positions of wedges representing sign classes. While for Latin scripts characters are intuitive modeled as visual attributes, cuneiform signs do not reveal an evident approach to model visual attributes for cuneiform signs. However, in this work we introduce an attribute representation based on the so-called Gottstein-System. The idea is decompose signs according to wedge typology and enable a logical expression for sign classes, while sharing these expressions across visually similar cuneiform signs. We adapt this idea of describing wedge expressions in order to introduce to the Query-by-eXpression (QbX) retrieval scenario. Compared to queries based on sign IDs, our approach is capable of repre- senting queries for an open-set retrieval scenario. Furthermore, we extend the Gottstein-System by expressions representing visual hints like wedge crossings or position relations. This way, promising results are achieved, as shown in our experiments.