The paper describes a method of classifying natural textures based on maximum likelihood parameter estimation technique. The wavelet transform (WT) is used to represent the textural images in multiresolution. Co-occurrence matrices are then computed for the different scales of the wavelet transform and textural features are obtained from the co-occurrence matrices. Then a maximum likelihood classifier is designed using a set of training texture samples. Ten different Brodot textures have been classified using this procedure with an average classification accuracy of 99.7.<>


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    Titel :

    A maximum likelihood approach to texture classification using wavelet transform


    Beteiligte:
    Thyagarajan, K.S. (Autor:in) / Nguyen, T. (Autor:in) / Persons, C.E. (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    420444 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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