Digital reproductions of historical documents from Late Antiquity to early medieval Europe contain annotations in handwritten graphic symbols or signs. The study of such symbols may potentially reveal essential insights into the social and historical context. However, finding such symbols in handwritten documents is not an easy task, requiring the knowledge and skills of expert users, i.e., paleographers. An AI-based system can be designed, highlighting potential symbols to be validated and enriched by the experts, whose decisions are used to improve the detection performance. This paper shows how this task can benefit from feature auto-encoding, showing how detection performance improves with respect to trivial template matching.
2021, ICDAR 2021: Document Analysis and Recognition – ICDAR 2021 Workshops, Pages 147-162 (volume: 12916)
Accurate Graphic Symbol Detection in Ancient Document Digital Reproductions (04b Atto di convegno in volume)
Ziran Zahra, Bernasconi Eleonora, Ghignoli Antonella, Leotta Francesco, Mecella Massimo
ISBN: 978-3-030-86197-1; 978-3-030-86198-8