Presents an HMM-MLP hybrid system to recognize 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-based approach. Afterwards, the three obligatory date sub-fields are processed by the system (day, month and year). A neural approach has been adopted to work with strings of digits and a Markovian strategy to recognize and verify words. 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.


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    Title :

    Segmentation and recognition of handwritten dates


    Contributors:
    Morita, M. (author) / Sabourin, R. (author) / Bortolozzi, F. (author) / Suen, C.Y. (author)


    Publication date :

    2002-01-01


    Size :

    319179 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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