To increase the range of sizes of video scene text recognizable by optical character recognition (OCR), we developed a Bayesian super-resolution algorithm that uses a text-specific bimodal prior. We evaluated the effectiveness of the bimodal prior, compared with and in conjunction with a piecewise smoothness prior, visually and by measuring the accuracy of the OCR results on the variously super-resolved images. The bimodal prior improved the readability of 4- to 7-pixel-high scene text significantly better than bicubic interpolation, and increased the accuracy of OCR results better than the piecewise smoothness prior.


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    Title :

    Bayesian super-resolution of text in video with a text-specific bimodal prior


    Contributors:
    Donaldson, K. (author) / Myers, G.K. (author)


    Publication date :

    2005-01-01


    Size :

    274813 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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