Abstract
This paper presents advances in zone classification for printed document image analysis. It firstly introduces entropic heuristic for text separation problem. Then a brief recall on existing texture and geometric discriminant parameters proposed in a previous research is done. Several of them are chosen and modified to perform statistical pattern recognition. For each of these two aspects, experiments are done. A document image database with groundtruth is used. Available results are discussed.
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Keywords
- Support Vector Machine
- Linear Discriminant Analysis
- Document Image
- Radial Basis Function Kernel
- Horizontal Projection
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© 2002 Springer-Verlag Berlin Heidelberg
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Duong, J., Côté, M., Emptoz, H. (2002). Feature Approach for Printed Document Image Analysis. In: Caelli, T., Amin, A., Duin, R.P.W., de Ridder, D., Kamel, M. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2002. Lecture Notes in Computer Science, vol 2396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70659-3_16
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DOI: https://doi.org/10.1007/3-540-70659-3_16
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