This paper introduces a new approach to content based image retrieval by texture. There are three problems to solve: high computational time, handling high dimension data, and comparing images consistent with human perception. To decrease the computational, time, we present a new strategy to extract an image feature with high retrieval accuracy. We also propose how to reduce the image feature dimension using the reward-punishment algorithm, so any robust indexing methods can be used. By weighting the extracted image features, a system may perceive the image consistently with human perception.


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    Titel :

    Fast content-based image retrieval using quasi-Gabor filter and reduction of image feature dimension


    Beteiligte:
    Park, M. (Autor:in) / Jin, J.S. (Autor:in) / Wilson, L.S. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    861021 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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