Several content-based image retrieval systems use region-based descriptors of salient regions to represent the image content. In this application domain, no perfect pixel-wise segmentation is required, but instead, a stable and unsupervised extraction of salient region-descriptors is needed which might be generally applicable. Accordingly, in this paper an algorithm is proposed which combines local and area-based information of multidimensional features, such as luminance, color and texture to extract robustly region-descriptors of salient regions. Furthermore, the selection of the corresponding regions is parameter-free thus ensuring its general applicability. The algorithm is easy to extend to other feature types and has been used to extract salient regions from images of a large database consisting of outdoor scenes.


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    Title :

    Unsupervised extraction of salient region-descriptors for content based image retrieval


    Contributors:
    Dimai, A. (author)


    Publication date :

    1999-01-01


    Size :

    103043 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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