This paper describes an off-line system which recognizes unconstrained handwritten month words extracted from Canadian bank cheques. A segmentation based grapheme level HMM (hidden Markov model) classifier and two multilayer perceptron classifiers with different architectures and different features have been developed in CENPARMI for the recognition of month words. In this paper, a combination method with an effective conditional topology is presented, and the most widely used combination rules including Vote, Sum and Product, are experimented. A new modified Product rule is also proposed, which has produced the best recognition rate of 85.36% when tested on a real-life standard Canadian bank cheque database.


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    Titel :

    Recognition of handwritten month words on bank cheques


    Beteiligte:
    Qizhi Xu, (Autor:in) / Jin Ho Kim, (Autor:in) / Lam, L. (Autor:in) / Suen, C.Y. (Autor:in)


    Erscheinungsdatum :

    2002-01-01


    Format / Umfang :

    286410 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    Cursive Script Recognition Applied to the Processing of Bank Cheques

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