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We present a system for reading handwritten sentences and paragraphs. The system's main components are preprocessing, feature extraction and recognition. In contrast to other systems, whole lines of text are the basic units for the recognizer. Thus the difficult problem of segmenting a line of text into individual words can be avoided. Another novel feature of the system is the incorporation of a statistical language model into the recognizer. Experiments on the database described previously by the authors (1999) have shown that a recognition rate on the word level of 79.5% and 60.05% for small (776 words) and larger (7719 words) vocabularies can be reached. These figures increase to 84.3% and 67.32% if the top ten choices are taken into account.
Marti et al. (Mon,) studied this question.