An HMM-MLP hybrid system to recognize handwritten dates

Presents an HMM-MLP hybrid system to process complex date images written on Brazilian bank cheques. The system first segments implicitly a date image into sub-fields through the recognition process based on an HMM approach. Afterwards, a recognition and verification strategy is proposed to recognize the three obligatory date sub-fields (day, month and year) using different classifiers. Markovian and neural approaches have been adopted to recognize and verify words and strings of digits respectively. We also introduce the concept of meta-classes of digits, which is used to reduce the lexicon size of the day and year and improve the precision of their segmentation and recognition. Experiments show interesting results on date recognition.