Recognizing Characters of Ancient Manuscripts
Identifieur interne : 000769 ( Main/Exploration ); précédent : 000768; suivant : 000770Recognizing Characters of Ancient Manuscripts
Auteurs : Markus Diem [Autriche] ; Robert Sablatnig [Autriche]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2010.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.
Affiliations:
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Le document en format XML
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SPIE Int. Soc. Opt. Eng.</title><idno type="ISSN">0277-786X</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><title level="j" type="abbreviated">Proc. SPIE Int. Soc. Opt. Eng.</title><idno type="ISSN">0277-786X</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Image analysis</term><term>Imagery</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Analyse image</term><term>Imagerie</term><term>Algorithme</term><term>0130C</term><term>4230</term><term>Méthode</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.</div></front></TEI><affiliations><list><country><li>Autriche</li></country><region><li>Vienne (Autriche)</li></region><settlement><li>Vienne (Autriche)</li></settlement></list><tree><country name="Autriche"><region name="Vienne (Autriche)"><name sortKey="Diem, Markus" sort="Diem, Markus" uniqKey="Diem M" first="Markus" last="Diem">Markus Diem</name></region><name sortKey="Sablatnig, Robert" sort="Sablatnig, Robert" uniqKey="Sablatnig R" first="Robert" last="Sablatnig">Robert Sablatnig</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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