A Pixel Labeling Framework for Comparing Texture Features: Application to Digitized Ancient Books

Abstract : In this article, a complete framework for the comparative analysis of texture features is presented and evaluated for the segmentation and characterization of ancient book pages. Firstly, the content of an entire book is characterized by extracting the texture attributes of each page. The extraction of the texture features is based on a multiresolution analysis. Secondly, a clustering approach is performed in order to classify automatically the homogeneous regions of book pages. Namely, two approaches are compared based on two different statistical categories of texture features, autocorrelation and co-occurrence, in order to segment the content of ancient book pages and find homogeneous regions with little a priori knowledge. By computing several clustering and classification accuracy measures, the results of the comparison show the effectiveness of the proposed framework. Tests on different book contents (text vs. graphics, manuscript vs. printed) show that those texture features are more suitable to distinguish textual regions from graphical ones, than to distinguish text fonts.
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Communication dans un congrès
International Conference on Pattern Recognition Applications and Methods, Mar 2014, Angers, France. Proceedings of the International Conference on Pattern Recognition Applications and Methods, pp.553-560, 2014, 〈10.5220/0004804705530560〉
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Maroua Mehri, Petra Gomez-Krämer, Pierre Héroux, Alain Boucher, Rémy Mullot. A Pixel Labeling Framework for Comparing Texture Features: Application to Digitized Ancient Books. International Conference on Pattern Recognition Applications and Methods, Mar 2014, Angers, France. Proceedings of the International Conference on Pattern Recognition Applications and Methods, pp.553-560, 2014, 〈10.5220/0004804705530560〉. 〈hal-01119154〉

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