A new algorithm for the recognition of the numerical amount on bankchecks is presented. Mainly, it results from the modification of the well known Baptista-Kulkarni algorithm (1988). The improvements proposed are based on the recognition by parts approach, which promises a better than human character recognition ability in a context free situation. It is shown that with this algorithm a misrecognition rate of lower than 1% can be reached with a reasonably high rejection rate, using numerals extracted from a common database. Better performances could be obtained using numerals extracted from Italian bankchecks, due to the greater attention that people pay to writing amounts on them.


    Access

    Check access

    Check availability in my library


    Export, share and cite



    Title :

    A structural method with local refining for handwritten character recognition


    Author / Creator :

    Type of media :

    Conference paper


    Type of material :

    Electronic Resource



    A Structural Method with Local Refining for Handwritten Character Recognition

    Congedo, G. / Dimauro, G. / Impedovo, S. et al. | British Library Conference Proceedings | 1995


    Local minimum squared error for face and handwritten character recognition

    Fan, Z. / Wang, J. / Zhu, Q. et al. | British Library Online Contents | 2013



    Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation

    Kang, K. / Kim, J. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2003


    Fuzzy Logic in Handwritten Character Recognition

    Kiselev, V. V. | British Library Online Contents | 2003