Quality evaluation of ancient digitized documents for binarization prediction
| Autor: | Nicholas Journet, Jean-Philippe Domenger, Vincent Rabeux, 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), Rabeux, Vincent |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
business.industry
Computer science media_common.quotation_subject ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 02 engineering and technology computer.software_genre 030218 nuclear medicine & medical imaging Image (mathematics) 03 medical and health sciences Ancient document 0302 clinical medicine [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV] [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] 0202 electrical engineering electronic engineering information engineering ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 020201 artificial intelligence & image processing Quality (business) Data mining Artificial intelligence State (computer science) business computer media_common |
| Zdroj: | International conference on document image analysis 2013 International conference on document image analysis International conference on document image analysis, Aug 2013, Washington, United States. pp.1023 ICDAR |
| Popis: | International audience; This article proposes an approach to predict the result of binarization algorithms on a given document image according to its state of degradation. Indeed, historical docu- ments 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 intensity, quantity and location of the degradation. These features allow us to build prediction models of binarization 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 document image. Obviously, this image-by-image strategy improves the binarization of the entire dataset. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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