ICDAR2017 Competition on the Classification of Medieval Handwritings in Latin Script

• Main Authors: Cloppet, Florence, Eglin, Veronique, Helias-Baron, Marlene, Cuong Kieu, Stutzmann, Dominique, Vincent, Nicole
• Format: Conference Proceeding
• Language: English
• Subjects: Character recognition; Europe; Feature extraction; Historical documents; Image classification; Image color analysis; Image resolution; Libraries; Medieval Latin script classification; Quantitative analysis; Task analysis; Training; Training data
• ISSN: 2379-2140
• DOI: 10.1109/ICDAR.2017.224

This paper presents the results of the ICDAR2017 Competition on the Classification of Medieval Handwritings in Latin Script (CLaMM), jointly organized by Computer Scientists and Humanists (paleographers). This work follows a competition at ICFHR2016 and aims at providing a rich annotated database of European medieval manuscripts to the community on Handwriting Analysis and Recognition. We proposed four independent classification tasks which attracted 10 registered teams, with 6 submitted classifiers from 4 participants. Those classifiers are trained on a set of 3540 images with their ground truths. In task 1 (Script classification) and task 3 (Date classification), the classifiers have been evaluated by a test set of 2000 greyscale, tiff, 300 dpi images. In task 2 (Script classification) and task 4 (Date classification), the test set consists of 1000 images in different formats, resolutions and color representation. The best scores are respectively 85.2% for task 1, 76.5% for task 2, 59% for task 3, and 49.9% for task 4. An analysis based on the matrix of confusion of each classifier is also given.