Classification of newspaper image blocks using texture analysis
Computer Vision, Graphics, and Image Processing
The nature of statistical learning theory
The nature of statistical learning theory
Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
Characterization and Classification of Printed Text in a Multiscale Context
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Zone Classification Using Texture Features
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
IBM Journal of Research and Development
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In this article we present a study based on the use oftexture features for logical pre-labeling. The aim of ourwork is to calculate a great number of texture featuresover three sets of machine-printed document images andto study their joint discriminant power using SVMclassifiers. The three corpuses we use are: the Archives ofSavoie (AoS), composed of strongly structureddocuments, the second one is a subset of the UW3database, and the last one is not structured at all, since itis composed of web site images. The originality of ourcontribution is to sum up various methods used for manyyears in our domain, and to test them on documentshaving really different specificities.