Adapting the RWTH-OCR Handwriting Recognition System to French Handwriting
نویسنده
چکیده
This bachelor thesis investigates the use of the RWTH-OCR system on the French handwriting database RIMES. The RWTH-OCR system is based on the RWTH-ASR speech recognition system. The field of offline handwriting recognition is an open topic in research and in the past the RWTH-OCR system has been adapted to several languages as English or Arabic handwriting. The RWTH-OCR is a hidden Markov model based recognition system. The system deals with writing style variations by using only a few preprocessing steps and simple appearance based features. In addition further methods are applied to improve the results, such as model length estimation and discriminative training. Finally, the results achieved by the RWTH-OCR system are compared to the results of the official RIMES 2 evaluation campaign.
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