Quality evaluation of degraded document images for binarization result prediction

Abstract : This article proposes an approach to predict the result of binarization algorithms on a given docu- ment image according to its state of degradation. In- deed, historical documents suffer from different types of degradation which result in binarization errors. We intend to characterize the degradation of a document image by using different features based on the inten- sity, quantity and location of the degradation. These features allow us to build prediction models of bina- rization algorithms that are very accurate according to R2 values and p-values. The prediction models are used to select the best binarization algorithm for a given doc- ument image. Obviously, this image-by-image strategy improves the binarization of the entire dataset.
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Contributor : Vincent Rabeux <>
Submitted on : Monday, September 16, 2013 - 11:51:39 AM
Last modification on : Thursday, January 11, 2018 - 6:20:17 AM
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Vincent Rabeux, Nicholas Journet, Anne Vialard, Jean-Philippe Domenger. Quality evaluation of degraded document images for binarization result prediction. International Journal on Document Analysis and Recognition (IJDAR), 2013, pp.1--13. ⟨10.1007/s10032-013-0211-6⟩. ⟨hal-00862234⟩



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