Learning to Detect Tables in Scanned Document Images using Line Information
Identifieur interne : 000077 ( Hal/Corpus ); précédent : 000076; suivant : 000078Learning to Detect Tables in Scanned Document Images using Line Information
Auteurs : Thotreingam Kasar ; Philippine Barlas ; Adam Sébastien ; Clément Chatelain ; Thierry PaquetSource :
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Abstract
This paper presents a method to detect table regions in document images by identifying the column and row line-separators and their properties. The method employs a run-length approach to identify the horizontal and vertical lines present in the input image. From each group of intersecting horizontal and vertical lines, a set of 26 low-level features are extracted and an SVM classifier is used to test if it belongs to a table or not. The performance of the method is evaluated on a heterogeneous corpus of French, English and Arabic documents that contain various types of table structures and compared with that of the Tesseract OCR system.
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DOI: 10.1109/ICDAR.2013.240
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Hal:hal-00934902Le document en format XML
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76821 Mont-Saint-Aignan</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-rouen.fr/</ref></desc></org></tutelle><tutelle active="#struct-301288" type="indirect"><org type="department" xml:id="struct-301288" status="VALID"><orgName>Institut National des Sciences Appliquées - Rouen</orgName><orgName type="acronym">INSA Rouen</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-301232" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-301232" type="indirect"><org type="institution" xml:id="struct-301232" status="VALID"><orgName>Institut National des Sciences Appliquées</orgName><orgName type="acronym">INSA</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation></affiliation></author><author><name sortKey="Paquet, Thierry" sort="Paquet, Thierry" uniqKey="Paquet T" first="Thierry" last="Paquet">Thierry Paquet</name><affiliation><hal:affiliation type="researchteam" xml:id="struct-389520" status="INCOMING"><orgName>DOCAPP</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-23832" type="direct"></relation><relation active="#struct-300317" type="indirect"></relation><relation name="EA4108" active="#struct-300318" type="indirect"></relation><relation active="#struct-301288" type="indirect"></relation><relation active="#struct-301232" type="indirect"></relation></listRelation><tutelles><tutelle active="#struct-23832" type="direct"><org type="laboratory" xml:id="struct-23832" status="VALID"><orgName>Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes</orgName><orgName type="acronym">LITIS</orgName><desc><address><addrLine>Avenue de l'Université UFR des Sciences et Techniques 76800 Saint-Etienne du Rouvray</addrLine><country key="FR"></country></address><ref type="url">http://www.litislab.eu</ref></desc><listRelation><relation active="#struct-300317" type="direct"></relation><relation name="EA4108" active="#struct-300318" type="direct"></relation><relation active="#struct-301288" type="direct"></relation><relation active="#struct-301232" type="indirect"></relation></listRelation></org></tutelle><tutelle active="#struct-300317" type="indirect"><org type="institution" xml:id="struct-300317" status="VALID"><orgName>Université du Havre</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle name="EA4108" active="#struct-300318" type="indirect"><org type="institution" xml:id="struct-300318" status="VALID"><orgName>Université de Rouen</orgName><desc><address><addrLine> 1 rue Thomas Becket - 76821 Mont-Saint-Aignan</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-rouen.fr/</ref></desc></org></tutelle><tutelle active="#struct-301288" type="indirect"><org type="department" xml:id="struct-301288" status="VALID"><orgName>Institut National des Sciences Appliquées - Rouen</orgName><orgName type="acronym">INSA Rouen</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-301232" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-301232" type="indirect"><org type="institution" xml:id="struct-301232" status="VALID"><orgName>Institut National des Sciences Appliquées</orgName><orgName type="acronym">INSA</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation></affiliation></author></analytic><idno type="DOI">10.1109/ICDAR.2013.240</idno></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="fr"><term>Table detection</term><term>line detection</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper presents a method to detect table regions in document images by identifying the column and row line-separators and their properties. The method employs a run-length approach to identify the horizontal and vertical lines present in the input image. From each group of intersecting horizontal and vertical lines, a set of 26 low-level features are extracted and an SVM classifier is used to test if it belongs to a table or not. The performance of the method is evaluated on a heterogeneous corpus of French, English and Arabic documents that contain various types of table structures and compared with that of the Tesseract OCR system.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Learning to Detect Tables in Scanned Document Images using Line Information</title><author role="aut"><persName><forename type="first">Thotreingam</forename><surname>Kasar</surname></persName><email></email><idno type="halauthor">944933</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Philippine</forename><surname>Barlas</surname></persName><email></email><idno type="halauthor">944934</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Adam</forename><surname>Sébastien</surname></persName><email></email><idno type="halauthor">974130</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Clément</forename><surname>Chatelain</surname></persName><email>clement.chatelain@univ-rouen.fr</email><idno type="idhal">clement-chatelain</idno><idno type="halauthor">134991</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Thierry</forename><surname>Paquet</surname></persName><email></email><idno type="halauthor">86898</idno><affiliation ref="#struct-389520"></affiliation></author><editor role="depositor"><persName><forename>Sébastien</forename><surname>Adam</surname></persName><email>Sebastien.Adam@univ-rouen.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2014-01-22 17:16:18</date><date type="whenWritten">2013-02-04</date><date type="whenModified">2014-10-28 17:58:39</date><date type="whenReleased">2014-01-30 08:36:13</date><date type="whenProduced">2013-08-25</date><date type="whenEndEmbargoed">2014-01-22</date><ref type="file" target="https://hal.archives-ouvertes.fr/hal-00934902/document"><date notBefore="2014-01-22"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.archives-ouvertes.fr/hal-00934902/file/ICDAR_table_detection.pdf"><date notBefore="2014-01-22"></date></ref></edition><respStmt><resp>contributor</resp><name key="131493"><persName><forename>Sébastien</forename><surname>Adam</surname></persName><email>Sebastien.Adam@univ-rouen.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00934902</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00934902</idno><idno type="halBibtex">kasar:hal-00934902</idno><idno type="halRefHtml">Internation conférence on document analysis and recognition, Aug 2013, Washington, United States. pp.1185 - 1189, 2014, <10.1109/ICDAR.2013.240></idno><idno type="halRef">Internation conférence on document analysis and recognition, Aug 2013, Washington, United States. pp.1185 - 1189, 2014, <10.1109/ICDAR.2013.240></idno></publicationStmt><seriesStmt><idno type="stamp" n="UNIV-LEHAVRE">Université du Havre</idno><idno type="stamp" n="UNIV-ROUEN">Université de Rouen</idno><idno type="stamp" n="LITIS">Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes</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">Learning to Detect Tables in Scanned Document Images using Line Information</title><author role="aut"><persName><forename type="first">Thotreingam</forename><surname>Kasar</surname></persName><idno type="halAuthorId">944933</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Philippine</forename><surname>Barlas</surname></persName><idno type="halAuthorId">944934</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Adam</forename><surname>Sébastien</surname></persName><idno type="halAuthorId">974130</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Clément</forename><surname>Chatelain</surname></persName><email>clement.chatelain@univ-rouen.fr</email><idno type="idHal">clement-chatelain</idno><idno type="halAuthorId">134991</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Thierry</forename><surname>Paquet</surname></persName><idno type="halAuthorId">86898</idno><affiliation ref="#struct-389520"></affiliation></author></analytic><monogr><title level="m">Proceedings of ICDAR'13</title><meeting><title>Internation conférence on document analysis and recognition</title><date type="start">2013-08-25</date><date type="end">2013-08-28</date><settlement>Washington</settlement><country key="US">United States</country></meeting><imprint><biblScope unit="pp">1185 - 1189</biblScope><date type="datePub">2014-08-16</date></imprint></monogr><idno type="doi">10.1109/ICDAR.2013.240</idno></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="fr">Table detection</term><term xml:lang="fr">line detection</term></keywords><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">This paper presents a method to detect table regions in document images by identifying the column and row line-separators and their properties. The method employs a run-length approach to identify the horizontal and vertical lines present in the input image. From each group of intersecting horizontal and vertical lines, a set of 26 low-level features are extracted and an SVM classifier is used to test if it belongs to a table or not. The performance of the method is evaluated on a heterogeneous corpus of French, English and Arabic documents that contain various types of table structures and compared with that of the Tesseract OCR system.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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