An original approach to texture-based classification of regions, for image indexing and retrieval, is presented. The system addresses automatic macro-textured ROI detection, and classification: we focus our attention on those objects that can be characterized by a texture as a whole, like trees, flowers, walls, clouds, and so on. The proposed architecture is based on the computation of the /spl lambda/ vector from each selected region, and classification of this feature by means of a pool of suitably trained support vector machines (SVM). This approach is an extension of the one previously developed by some of the authors to classify image regions on the basis of the geometrical shape of the objects they contain. Theoretical remarks, motivation of the approach, experimental setup, and the first satisfactory results on natural scenes are reported.


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    Title :

    Texture classification for content-based image retrieval


    Contributors:
    Pirrone, R. (author) / La Cascia, M. (author)


    Publication date :

    2001-01-01


    Size :

    731628 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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