Offline handwritten text recognition using support vector machines

Comenia script is a novel handwritten text introduced at primary schools in the Czech Republic. This paper describes a method for handwritten text recognition (HWR) of this font. In particular it proposes a method for preprocessing and normalization of data and optical character recognition based on SVM classifier. We have trained and statistically evaluated several models, where we have focused on recognition of different styles of writing of the same characters - for the forensic purposes and identification of the author of a document. The best model has achieved 92.86 % accuracy without any further postprocessing, e.g. a spellchecker. We also proposed using more than one classification model for character recognition that has shown to increase accuracy when compared to a single model approach.