Feature Approach for Printed Document Image Analysis
Identifieur interne : 001979 ( Main/Merge ); précédent : 001978; suivant : 001980Feature Approach for Printed Document Image Analysis
Auteurs : Jean Duong [Canada] ; Myrian Côté [Canada] ; Hubert Emptoz [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2002.
Abstract
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.
Url:
DOI: 10.1007/3-540-70659-3_16
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<front><div type="abstract" xml:lang="en">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.</div>
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