When Tesseract Does It Alone: Optical Character Recognition of Medieval Texts
|Druh||Článek ve sborníku|
|Konference||Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020|
|Fakulta / Pracoviště MU|
|Klíčová slova||Optical character recognition; OCR; Historical texts|
Optical character recognition of scanned images for contemporary printed texts is widely considered a solved problem. However, the optical character recognition of early printed books and reprints of Medieval texts remains an open challenge.
In our work, we present a dataset of 19th and 20th century letterpress reprints of documents from the Hussite era (1419–1436) and perform a quantitative and qualitative evaluation of speed and accuracy on six existing OCR algorithms.
We conclude that the Tesseract family of OCR algoritms is the fastest and the most accurate on our dataset, and we suggest improvements to our dataset.