Content based indexing is computed from input that consists of matching values between images and templates. The key idea is to embed both images and templates in a low-dimensional Euclidean space so that matching between embedded images and embedded templates approximates the given input. It is shown that such embedding can be computed by means of a singular value decomposition of the input matrix. Classic principal component analysis is shown to be a special case of the proposed technique, corresponding to the case where the templates and the images are the same.


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    Titel :

    Template matching approach to content based image indexing by low dimensional Euclidean embedding


    Beteiligte:
    Schweitzer, H. (Autor:in)


    Erscheinungsdatum :

    2001-01-01


    Format / Umfang :

    527149 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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