Content-based image retrieval is generally about understanding of information in the images concerned. The more the system is able to understand the content of images the more effective it will be in retrieving desired images. In this paper, we have developed a method that combines a clustering technique with the color correlation histogram. According to this method, an image is divided into several blocks using a xed partitioning scheme. Then, selected lower-level MPEG-7 features are used to represent the partitions and a clustering technique is applied to group similar patterns into a cluster. The cluster indices will then be used to construct a corellogram which is not based on the lower-level primitives, but on regions consisting of a distribution of primitives. The result shows that the proposed method signi cantly outperforms other methods on image retrieval and categorization.


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    Title :

    CIREC : Cluster Correlogram Image Retrieval and Categorization using MPEG-7 Descriptors


    Contributors:


    Publication date :

    2007-04-01


    Size :

    474214 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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