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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    Titel :

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


    Beteiligte:
    Dimai, A. (Autor:in)


    Erscheinungsdatum :

    01.01.1999


    Format / Umfang :

    103043 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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