DOCUMENT IMAGE AND ZONE CLASSIFICATION THROUGH INCREMENTAL LEARNING
Identifieur interne : 001023 ( Main/Exploration ); précédent : 001022; suivant : 001024DOCUMENT IMAGE AND ZONE CLASSIFICATION THROUGH INCREMENTAL LEARNING
Auteurs : Mohamed-Rafik Bouguelia [France] ; Yolande Belaïd [France] ; Abdel Belaïd [France]Source :
Abstract
We present an incremental learning method for document image and zone classification. We consider an industrial context where the system faces a large variability of digitized administrative documents that become available progressively over time. Each new incoming document is segmented into physical regions (zones) which are classified according to a zone-model. We represent the document by means of its classified zones and we classify the document according to a document-model. The classification relies on a reject utility in order to reject ambiguous zones or documents. Models are updated by incrementally learning each new document and its extracted zones. We validate the method on real administrative document images and we achieve a recognition rate of more than 92%.
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BP 10578153 Le Chesnay Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/en/</ref></desc></org></tutelle><tutelle active="#struct-413289" type="indirect"><org type="institution" xml:id="struct-413289" status="VALID"><idno type="IdRef">157040569</idno><idno type="IdUnivLorraine">[UL]100--</idno><orgName>Université de Lorraine</orgName><orgName type="acronym">UL</orgName><date type="start">2012-01-01</date><desc><address><addrLine>34 cours Léopold - CS 25233 - 54052 Nancy cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lorraine.fr/</ref></desc></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="ISNI">0000000122597504</idno><idno type="IdRef">02636817X</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><settlement type="city">Metz</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="it"><term>Document Classification</term><term>Document Image Analysis</term><term>Incremental Learning</term><term>Zone Classification</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We present an incremental learning method for document image and zone classification. We consider an industrial context where the system faces a large variability of digitized administrative documents that become available progressively over time. Each new incoming document is segmented into physical regions (zones) which are classified according to a zone-model. We represent the document by means of its classified zones and we classify the document according to a document-model. The classification relies on a reject utility in order to reject ambiguous zones or documents. Models are updated by incrementally learning each new document and its extracted zones. We validate the method on real administrative document images and we achieve a recognition rate of more than 92%.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="Bouguelia, Mohamed Rafik" sort="Bouguelia, Mohamed Rafik" uniqKey="Bouguelia M" first="Mohamed-Rafik" last="Bouguelia">Mohamed-Rafik Bouguelia</name></region><name sortKey="Belaid, Abdel" sort="Belaid, Abdel" uniqKey="Belaid A" first="Abdel" last="Belaïd">Abdel Belaïd</name><name sortKey="Belaid, Yolande" sort="Belaid, Yolande" uniqKey="Belaid Y" first="Yolande" last="Belaïd">Yolande Belaïd</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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