An unsupervised algorithm for arranging an image database as a binary tree is described. Tree nodes are associated with image subsets, maintaining the property that the similarity among the images associated with the children of a node is higher than the similarity among the images associated with the parent node. Experiments with datasets of hundreds and thousands of images show that shallow trees can produce clustering into "meaningful" classes. Visual-content search trees can be used to automate image retrieval by content, or help a human to interactively search for images.


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    Titel :

    Indexing images by trees of visual content


    Beteiligte:
    Schweitzer, H. (Autor:in)


    Erscheinungsdatum :

    01.01.1998


    Format / Umfang :

    842272 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Indexing Images by Trees of Visual Content

    Schweitzer, H. / IEEE; Computer Society | British Library Conference Proceedings | 1998


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    Organizing image databases as visual-content search trees

    Schweitzer, H. | British Library Online Contents | 1999


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    Qian, X. / Tagare, H. D. | British Library Online Contents | 2010