Text Degradations and OCR Training

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Text Degradations and OCR Training
Printing and scanning of text documents introduces degradations to the characters which can be modeled. Interestingly, certain combinations of the parameters that govern the degradations introduced by the printing and scanning process affect characters in such a way that the degraded characters have a similar appearance, while other degradations leave the characters with an appearance that is very different. It is well known that (generally speaking) a test set that more closely matches a training set will be recognized with higher accuracy than one that matches the training set less well. Likewise, classifiers tend to perform better on data sets that have lower variance. This paper explores an analytical method that uses a formal printer/scanner degradation model to identify the similarity between groups of degraded characters. This similarity is shown to improve the recognition accuracy of a classifier through model directed choice of training set data.
Elisa H. Barney Smith, Tim L. Andersen
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Authors Elisa H. Barney Smith, Tim L. Andersen
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