Telugu characters can be visualised as being composed of circular segments of different radii. Recognition consists in segmenting the characters into the component elements and identifying them. We choose a feature set to preserve the canonical shapes while filtering out as noise the shape deviations encountered in real life. Hence, this approach does not require extensive training. Instead, "Feature Vector" parameters for individual "basic" characters are extracted from single specimens written in isolation. These are suitably combined to construct "Feature Vectors" for compound characters for the lexicon. These are compared with similar "Feature Vectors" extracted from the test samples to be recognised. Recognition scores ranged from 78 to 90% across different subjects (when the best match alone is taken) and from 91 to 95% for a single subject.


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    Titel :

    Telugu script recognition-a feature based approach


    Beteiligte:
    Rao, P.V.S. (Autor:in) / Ajitha, T.M. (Autor:in)


    Erscheinungsdatum :

    01.01.1995


    Format / Umfang :

    369626 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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