Content-based image retrieval has shown to be more and more useful for several application domains, from audiovisual media to security. As content-based retrieval became mature, different scientific applications were revealed client for such methods. More recently, botanical applications generated very large image collections and then became very demanding content-based visual similarity computation. In this paper, we describe low-level feature extraction for visual appearance comparison between genetically modified plants for gene expression studies.


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    Titel :

    Content-based image retrieval in botanical collections for gene expression studies


    Beteiligte:
    Yahiaoui, I. (Autor:in) / Boujemaa, N. (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    495195 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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