Quality evaluation of degraded document images for binarization result prediction
| Autor: | Vincent Rabeux, Nicholas Journet, Jean-Philippe Domenger, Anne Vialard |
|---|---|
| Přispěvatelé: | Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB) |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Computer science
media_common.quotation_subject ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology computer.software_genre 01 natural sciences Image (mathematics) 010104 statistics & probability 0202 electrical engineering electronic engineering information engineering Quality (business) 0101 mathematics media_common business.industry Pattern recognition Computer Science Applications [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] Pattern recognition (psychology) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Data mining Artificial intelligence business computer Software Degradation (telecommunications) |
| Zdroj: | International Journal on Document Analysis and Recognition (IJDAR) International Journal on Document Analysis and Recognition (IJDAR), 2013, pp.1--13. ⟨10.1007/s10032-013-0211-6⟩ |
| DOI: | 10.1007/s10032-013-0211-6⟩ |
| Popis: | International audience; 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 In- deed, historical documents suffer from different types of degradation which result in binarization errors.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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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