Quality evaluation of degraded document images for binarization result prediction
Résumé
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 In- deed, historical documents suffer from different types of degradation which result in binarization errors.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]
Origine : Fichiers produits par l'(les) auteur(s)