A new method for analysing image histograms is introduced. The technique decomposes a histogram into probability level sets. The relationships between these level sets are encoded using a tree. The tree has fewer nodes than the histogram and so is a compressed feature. When used in image retrieval experiments the tree is shown to have a performance that is superior to many methods and no worse than the best alternatives. The tree is efficient because it can be built using a computationally efficient algorithm known as a sieve.


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    Title :

    Analysing and simplifying histograms using scale-trees


    Contributors:
    Gibson, S. (author) / Harvey, R. (author)


    Publication date :

    2001-01-01


    Size :

    778679 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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