Multi-Oriented Text Line Extraction from Handwritten Arabic Documents
Identifieur interne : 003384 ( Hal/Curation ); précédent : 003383; suivant : 003385Multi-Oriented Text Line Extraction from Handwritten Arabic Documents
Auteurs : Nazih Ouwayed [France] ; Abdel Belaïd [France]Source :
Abstract
In this paper, we present a novel approach for the multi-oriented text line extraction from handwritten Arabic documents. After image pre-processing, the local orientations are determined in small windows obtained by image paving. The orientation of the text within each window is estimated using the projection profile technique considering several projection angles. Then, the windows which close angles are gathered into largest zones. We use the Wigner-Ville Distribution (WVD) to estimate the global orientation of each zone. The WVD is more precise than the classical projection profile technique. Afterwards, the text lines are extracted in each zone basing on the follow-up of the baselines and the proximity of connected components. The experimental results prove the efficiency of the proposed scheme. It has been evaluated on 50 documents reaching an accuracy of about 97.6%.
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DOI: 10.1109/DAS.2008.14
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<front><div type="abstract" xml:lang="en">In this paper, we present a novel approach for the multi-oriented text line extraction from handwritten Arabic documents. After image pre-processing, the local orientations are determined in small windows obtained by image paving. The orientation of the text within each window is estimated using the projection profile technique considering several projection angles. Then, the windows which close angles are gathered into largest zones. We use the Wigner-Ville Distribution (WVD) to estimate the global orientation of each zone. The WVD is more precise than the classical projection profile technique. Afterwards, the text lines are extracted in each zone basing on the follow-up of the baselines and the proximity of connected components. The experimental results prove the efficiency of the proposed scheme. It has been evaluated on 50 documents reaching an accuracy of about 97.6%.</div>
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<idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno>
<idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno>
<idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno>
</seriesStmt>
<notesStmt><note type="audience" n="2">International</note>
<note type="invited" n="0">No</note>
<note type="popular" n="0">No</note>
<note type="peer" n="1">Yes</note>
<note type="proceedings" n="1">Yes</note>
</notesStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">Multi-Oriented Text Line Extraction from Handwritten Arabic Documents</title>
<author role="aut"><persName><forename type="first">Nazih</forename>
<surname>Ouwayed</surname>
</persName>
<idno type="halAuthorId">373831</idno>
<affiliation ref="#struct-2362"></affiliation>
</author>
<author role="aut"><persName><forename type="first">Abdel</forename>
<surname>Belaïd</surname>
</persName>
<idno type="halAuthorId">52807</idno>
<affiliation ref="#struct-2362"></affiliation>
</author>
</analytic>
<monogr><meeting><title>8th IAPR International Workshop on Document Analysis Systems - DAS'08</title>
<date type="start">2008-09-16</date>
<settlement>Nara</settlement>
<country key="JP">Japan</country>
</meeting>
<imprint><biblScope unit="pp">339-346</biblScope>
<date type="datePub">2008</date>
</imprint>
</monogr>
<idno type="doi">10.1109/DAS.2008.14</idno>
</biblStruct>
</sourceDesc>
<profileDesc><langUsage><language ident="en">English</language>
</langUsage>
<textClass><classCode scheme="halDomain" n="info.info-tt">Computer Science [cs]/Document and Text Processing</classCode>
<classCode scheme="halTypology" n="COMM">Conference papers</classCode>
</textClass>
<abstract xml:lang="en">In this paper, we present a novel approach for the multi-oriented text line extraction from handwritten Arabic documents. After image pre-processing, the local orientations are determined in small windows obtained by image paving. The orientation of the text within each window is estimated using the projection profile technique considering several projection angles. Then, the windows which close angles are gathered into largest zones. We use the Wigner-Ville Distribution (WVD) to estimate the global orientation of each zone. The WVD is more precise than the classical projection profile technique. Afterwards, the text lines are extracted in each zone basing on the follow-up of the baselines and the proximity of connected components. The experimental results prove the efficiency of the proposed scheme. It has been evaluated on 50 documents reaching an accuracy of about 97.6%.</abstract>
</profileDesc>
</hal>
</record>
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