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ICDAR
2009
IEEE

Spatial and Spectral Based Segmentation of Text in Multispectral Images of Ancient Documents

10 years 2 months ago
Spatial and Spectral Based Segmentation of Text in Multispectral Images of Ancient Documents
In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images.
Martin Lettner, Robert Sablatnig
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICDAR
Authors Martin Lettner, Robert Sablatnig
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