A character degradation model for grayscale ancient document images

Abstract : Kanungo noise model is widely used to test the robustness of different binary document image analysis methods towards noise. This model only works with binary images while most document images are in grayscale. Because binarizing a document image might degrade its contents and lead to a loss of information, more and more researchers are currently focusing on segmentation-free methods (Angelika et al [2]). Thus, we propose a local noise model for grayscale images. Its main principle is to locally degrade the image in the neighbourhoods of "seed-points" selected close to the character boundary. These points define the center of "noise regions". The pixel values inside the noise region are modified by a Gaussian random distribution to make the final result more realistic. While Kanungo noise models scanning artifacts, our model simulates degradations due to the age of the document itself and printing/writing process such as ink splotches, white specks or streaks. It is very easy for users to parameterize and create a set of benchmark databases with an increasing level of noise. These databases will further be used to test the robustness of different grayscale document image analysis methods (i.e. text line segmentation, OCR, handwriting recognition).
Type de document :
Communication dans un congrès
International Conference on Pattern Recognition (ICPR 2012), Nov 2012, Tsukuba, Japan. pp.685-688, 2012
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https://hal.archives-ouvertes.fr/hal-00860693
Contributeur : Muriel Visani <>
Soumis le : mardi 10 septembre 2013 - 21:19:00
Dernière modification le : jeudi 9 février 2017 - 16:58:40

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  • HAL Id : hal-00860693, version 1

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Van Cuong Kieu, Muriel Visani, Nicholas Journet, Jean-Philippe Domenger, Rémy Mullot. A character degradation model for grayscale ancient document images. International Conference on Pattern Recognition (ICPR 2012), Nov 2012, Tsukuba, Japan. pp.685-688, 2012. <hal-00860693>

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