Text Degradations and OCR Training
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
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Document image quality is degraded through processes such as scanning, printing, and photocopying. The resulting bilevel image degradations can be categorized based either on observable degradation features or on degradation model parameters. The image degradation features can be related mathematically to model parameters. In this paper we statistically compare pairs of populations of degraded character images created with different model parameters. The probability that the character populations were degraded by the same model parameters correlates with the relationship between observable degradation features and the model parameters. Two metrics of character difference are used: Hamming distance and moment feature distance. Knowledge about the conditions under which characters will be similar and when they will be different can influence the choice of parameters for future experiments.