Document Image Quality: Making Fine Discriminations
نویسنده
چکیده
We estimate, using synthetically generated images, the smallest changes in document image quality that can be distinguished reliably and fully automatically by Kanungo's bootstrapping test Kan96]. Six parameters of a physics{based document{image degradation model Bai92] are varied, one at a time: for each, over a range of parameter-value diierences, two sets of synthetic images are generated pseudorandomly and the two sets tested for statistical equivalence using Kanungo's method. The rate at which Kanungo's method rejects the hypothesis that the two sets are drawn from the same distribution is analyzed as a function of parameter diierence (a specialized \power function"). The nest discriminations aaorded by the method are given by the width of the power function at a low xed reject threshold. The data show that remarkably ne discriminations are possible { often subtler than are evident to visual inspection { for all six parameters. As few as 25 reference images are suucient. These results suggest that Kanungo's method is suuciently sensitive to a wide range of physics{based image degradations to serve as an engineering foundation for many image{quality estimation and OCR engineering purposes.
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