In this paper we describe a plate-recognition system for access control to restricted areas. The system we propose is based on vision, neural networks and a neuro-fuzzy system. Vision is used to detect the license-plate and to single out the characters it contains, while a neural network-based classifier is used to "read" the plate. The resulting string is then matched to a "white list" of allowed plates, to check the transit authorization. In case matching fails, a neuro-fuzzy agent analyses the features of the mismatch, to filter out possible false alarms and to optimize the workload for the human supervisor that has to validate the alarm.


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    Titel :

    Access control system with neuro-fuzzy supervision


    Beteiligte:
    Adorni, G. (Autor:in) / Cagnoni, S. (Autor:in) / Gori, M. (Autor:in) / Mordonini, M. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    689677 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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