Quality evaluation of degraded document images for binarization result prediction

Vincent Rabeux (1) , Nicholas Journet (1) , Anne Vialard (1) , Jean-Philippe Domenger (1)

1 LaBRI - Laboratoire Bordelais de Recherche en Informatique

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 In- deed, historical documents suffer from different types of degradation which result in binarization errors.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.

Domaines: Traitement des images [eess.IV]

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⟩