Scribe attribution for early medieval handwriting by means of letter extraction and classification and a voting procedure for larger pieces
2014 (English)In: 22nd International Conference on Pattern Recognition (ICPR), 2014, 1910-1915 p.Conference paper (Refereed)
The present study investigates a method for the attribution of scribal hands, inspired by traditional palaeography in being based on comparison of letter shapes. The system was developed for and evaluated on early medieval Caroline minuscule manuscripts. The generation of a prediction for a page image involves writing identification, letter segmentation, and letter classification. The system then uses the letter proposals to predict the scribal hand behind a page. Letters and sequences of connected letters are identified by means of connected component labeling and split into letter-size pieces. The hand (and character) prediction makes use of a dataset containing instances of the letters b, d, p, and q, cut out from manuscript pages whose scribal origin is known. Letters are represented by features capturing the distribution of foreground. Cosine similarity is used for nearest neighbor classification. The hand behind a page is finally predicted by means of a voting procedure taking the highest scoring letter-level hits as its input. This hand prediction method was evaluated on pages from five different hands and reached an accuracy above 99% for four of them and 87% for a fifth significantly more difficult one. The hand behind single toplisted letters was correctly predicted in 83% of the cases.
Place, publisher, year, edition, pages
2014. 1910-1915 p.
, International Conference on Pattern Recognition, ISSN 1051-4651
Language Technology (Computational Linguistics)
IdentifiersURN: urn:nbn:se:uu:diva-241360DOI: 10.1109/ICPR.2014.334ISI: 000359818002005ISBN: 978-1-4799-5208-3OAI: oai:DiVA.org:uu-241360DiVA: diva2:778565
22nd International Conference on Pattern Recognition (ICPR), 24-28 Aug, 2014, Stockholm, Sweden