Experiments in Unconstrained Offline Handwritten Text Recognition
نویسندگان
چکیده
A system for off-line handwritten text recognition is presented. It is characterized by a segmentation-free approach, i.e. whole lines of text are processed by the recognition module. The methods used for pre-processing, feature extraction, and statistical modelling are described, and several experiments on writer-independent, multiple writer, and single writer handwriting recognition tasks are conducted. Particularly, the incorporation of linear discriminant analysis, allograph character models, and statistical language knowledge is investigated. The evaluation results for lexicon-free handwriting recognition demonstrate the effectiveness of the proposed methods.
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