We describe a self-organizing framework for content-based retrieval of images from large image databases at the object recognition level. The system uses the theories of optimal projection for optimal feature selection and a hierarchical image database for rapid retrieval rates. We demonstrate the query technique on a large database of widely varying real-world objects in natural settings, and show the applicability of the approach even for large variability within a particular object class.


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    Title :

    Efficient content-based image retrieval using automatic feature selection


    Contributors:
    Swets, D.L. (author) / Weng, J.J. (author)


    Publication date :

    1995-01-01


    Size :

    633095 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Efficient Content-Based Image Retrieval Using Automatic Feature Selection

    Swets, D. L. / Weng, J. J. / IEEE; Computer Society; Technical Committee for Pattern Analysis and Machine Intelligence | British Library Conference Proceedings | 1995



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