
This paper presents the results of the ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script (CLaMM), jointly organized by Computer Scientists and Humanists (paleographers). This work aims at providing a rich database of European medieval manuscripts to the community on Handwriting Analysis and Recognition. At this competition, we proposed two independent classification tasks which attracted five participants with seven submitted classifiers. Those classifiers are trained on a set of 2000 images with their ground truths. In the first task of script crisp classification, the classifiers have been evaluated on a test set of 1000 single-type manuscripts. In the second task of "Fuzzy Classification", the classifiers have been carried out on a set of 2000 multi-script-type manuscripts. The results of the participants provide the first baseline evaluation up to the accuracy score of 83.9% for the task 1 and to the fuzzy weighted score of 2.96/4 for the task 2. An analysis based on the intra-class distance and matrix of confusion of each classifier is also given.
Character style recognition, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Image classification, Feature extraction, [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, Historical documents, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], Latin script classification
Character style recognition, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Image classification, Feature extraction, [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, Historical documents, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], Latin script classification
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