We present a method for automatically selecting the best filter to treat poor quality printed documents using image quality assessment. We introduce five quality measures to obtain information about the quality of the images, and morphological filters to improve their quality. A training set of 370 images was used to develop the system. Experimental results on the test set show a significant improvement in the recognition rate from 73.24% using no filter at all to 93.09% after applying a filter that was automatically selected.


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    Title :

    Automatic filter selection using image quality assessment


    Contributors:
    Souza, A. (author) / Cheriet, M. (author) / Naoi, S. (author) / Suen, C.Y. (author)


    Publication date :

    2003-01-01


    Size :

    232237 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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