This work presents the classification of images collected on the World Wide Web, using a supervised classification method, called IDS (itemized dichotomizer 3). The classification consists in separating the images into two semantic classes: graphics and photographs. Photographs include natural scenes, like people, faces, animals, flowers, landscapes and cities. Graphics are logos, drawings, icons, maps, and backgrounds, usually generated by computer. To validate the classifier we used the k-fold cross-validation method. In the experimental tests 96.1% of the images were correctly classified.


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    Title :

    Separating images collected in the World Wide Web into two semantic classes: photographs and graphics


    Contributors:


    Publication date :

    2003-01-01


    Size :

    366528 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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