Learning to Detect Tables in Scanned Document Images using Line Information
Identifieur interne : 000213 ( Main/Exploration ); précédent : 000212; suivant : 000214Learning to Detect Tables in Scanned Document Images using Line Information
Auteurs : Thotreingam Kasar [France] ; Philippine Barlas [France] ; Sebastien Adam [France] ; Clément Chatelain [France] ; Thierry Paquet [France]Source :
English descriptors
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 runlength 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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Le 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="direct"><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><country>France</country><placeName><settlement type="city">Rouen</settlement><region type="region" nuts="2">Région Bourgogne</region></placeName><orgName type="university">Université de Rouen</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>document image analysis</term><term>runlength</term><term>table 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 runlength 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><affiliations><list><country><li>France</li></country><region><li>Région Bourgogne</li></region><settlement><li>Rouen</li></settlement><orgName><li>Université de Rouen</li></orgName></list><tree><country name="France"><region name="Région Bourgogne"><name sortKey="Kasar, Thotreingam" sort="Kasar, Thotreingam" uniqKey="Kasar T" first="Thotreingam" last="Kasar">Thotreingam Kasar</name></region><name sortKey="Adam, Sebastien" sort="Adam, Sebastien" uniqKey="Adam S" first="Sebastien" last="Adam">Sebastien Adam</name><name sortKey="Barlas, Philippine" sort="Barlas, Philippine" uniqKey="Barlas P" first="Philippine" last="Barlas">Philippine Barlas</name><name sortKey="Chatelain, Clement" sort="Chatelain, Clement" uniqKey="Chatelain C" first="Clément" last="Chatelain">Clément Chatelain</name><name sortKey="Paquet, Thierry" sort="Paquet, Thierry" uniqKey="Paquet T" first="Thierry" last="Paquet">Thierry Paquet</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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