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Extraction and recognition of handwritten alphanumeric characters from application forms

This paper presents a reading system capable of extracting the handwritten text and recognizing the alphanumeric characters from application forms. The system has been designed and implemented in the framework of the LE project ACCESS. The application forms are scanned and the handwritten parts are automatically separated. The character recognition is based on discrete hidden Markov models. In our system the estimation of the HMM parameters has been simplified by using a left-to-right HMM with step one. The system recognizes 60 alphanumeric characters (26 English upper-case letters, 24 Greek upper-case letters and 10 digits). The experiments carried out achieved a recognition rate of 93% in character level and 88% in word level. The latter improved to 97% by lexical confirmation. A novelty of this system is the feature extraction algorithm applied to the characters and the resulting very fast recognition.