Abstract

The article presents the first results of our system applied to the automatic recognition of handwritten dates on Brazilian bank checks. Considering the omni-writer context, we detail our recognition module dedicated to processing the month field. This module is based on the combination of holistic and analytical approaches with a fixed lexicon. Both approaches operate with a single explicit segmentation technique to provide a grapheme sequence for the purposed hidden Markov models of each recognizer. We show significant improvements when combining both modules to get a satisfactory recognition rate considering the small database images we work with. Finally, we present various perspectives for future work.

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