Contribution to the Automatic Recognition of Business Documents
Identifieur interne : 000190 ( France/Analysis ); précédent : 000189; suivant : 000191Contribution to the Automatic Recognition of Business Documents
Auteurs : Djamel Gaceb [France] ; Frank Lebourgeois [France] ; Véronique Eglin [France] ; Hubert Emptoz [France]Source :
English descriptors
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Abstract
The automatic processing of paper documents and mails is a major challenge for all companies. Current recognition systems use modular architectures in which each stage of the process is independent. To improve the performances, it is necessary to reintroduce a cooperation between the different modules, for example by coupling the segmentation / recognition or zones of interests location / segmentation steps. In this context we propose a mixed approach for text localization and image segmentation which respects real time constraints. In the first part, we are going to present the state of the art in text location and thresholding in the images of postal addresses. In the second part, we will describe our method which simultaneously localize and segment text zones. The Location of text blocks obtained from a multiresolution approach on cumulated gradients computed directly from grey level images. The coupling of the two processes (text zones location and thresholding) allows to reduce simultaneously the computing time by processing only necessary parts of the image and by obtaining a better character segmentation for the OCR (Optical Character Recognition). We will present the results obtained from the implementation of our approach on an industrial line which daily processes several tons of documents from large companies.
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Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 000036
- to stream Hal, to step Curation: 000036
- to stream Hal, to step Checkpoint: 000127
- to stream Main, to step Merge: 000F68
- to stream Main, to step Curation: 000F53
- to stream Main, to step Exploration: 000F53
- to stream France, to step Extraction: 000190
Links to Exploration step
Hal:inria-00104169Le document en format XML
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69134 Ecully cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.ec-lyon.fr</ref></desc></org></tutelle><tutelle active="#struct-194495" type="direct"><org type="institution" xml:id="struct-194495" status="VALID"><orgName>Université Claude Bernard Lyon 1</orgName><orgName type="acronym">UCBL</orgName><desc><address><addrLine>43, boulevard du 11 novembre 1918, 69622 Villeurbanne cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lyon1.fr/</ref></desc></org></tutelle><tutelle name="- LYON" active="#struct-301232" type="direct"><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><tutelle name="UMR5205" active="#struct-441569" type="direct"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="IdRef">02636817X</idno><idno type="ISNI">0000000122597504</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">Lyon</settlement><region type="region" nuts="2">Auvergne-Rhône-Alpes</region><region type="old region" nuts="2">Rhône-Alpes</region></placeName><orgName type="university">Université Claude Bernard Lyon 1</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lyon</orgName></affiliation></author><author><name sortKey="Emptoz, Hubert" sort="Emptoz, Hubert" uniqKey="Emptoz H" first="Hubert" last="Emptoz">Hubert Emptoz</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-2003" status="VALID"><orgName>Laboratoire d'InfoRmatique en Image et Systèmes d'information</orgName><orgName type="acronym">LIRIS</orgName><desc><address><addrLine>Bâtiment Blaise Pascal - 20, avenue Albert Einstein - 69621 Villeurbanne cedex</addrLine><country key="FR"></country></address><ref type="url">http://liris.cnrs.fr/</ref></desc><listRelation><relation active="#struct-33804" type="direct"></relation><relation active="#struct-126765" type="direct"></relation><relation active="#struct-194495" type="direct"></relation><relation name="- LYON" active="#struct-301232" type="direct"></relation><relation name="UMR5205" active="#struct-441569" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-33804" type="direct"><org type="institution" xml:id="struct-33804" status="VALID"><orgName>Université Lumière - Lyon 2</orgName><orgName type="acronym">UL2</orgName><desc><address><addrLine>86, rue Pasteur - 69007 Lyon</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lyon2.fr</ref></desc></org></tutelle><tutelle active="#struct-126765" type="direct"><org type="institution" xml:id="struct-126765" status="VALID"><orgName>École Centrale de Lyon</orgName><orgName type="acronym">ECL</orgName><desc><address><addrLine>36 avenue Guy de Collongue - 69134 Ecully cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.ec-lyon.fr</ref></desc></org></tutelle><tutelle active="#struct-194495" type="direct"><org type="institution" xml:id="struct-194495" status="VALID"><orgName>Université Claude Bernard Lyon 1</orgName><orgName type="acronym">UCBL</orgName><desc><address><addrLine>43, boulevard du 11 novembre 1918, 69622 Villeurbanne cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lyon1.fr/</ref></desc></org></tutelle><tutelle name="- LYON" active="#struct-301232" type="direct"><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><tutelle name="UMR5205" active="#struct-441569" type="direct"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="IdRef">02636817X</idno><idno type="ISNI">0000000122597504</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">Lyon</settlement><region type="region" nuts="2">Auvergne-Rhône-Alpes</region><region type="old region" nuts="2">Rhône-Alpes</region></placeName><orgName type="university">Université Claude Bernard Lyon 1</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lyon</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Text location</term><term>business documents processing</term><term>business documents processing.</term><term>image segmentation</term><term>real time processing</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The automatic processing of paper documents and mails is a major challenge for all companies. Current recognition systems use modular architectures in which each stage of the process is independent. To improve the performances, it is necessary to reintroduce a cooperation between the different modules, for example by coupling the segmentation / recognition or zones of interests location / segmentation steps. In this context we propose a mixed approach for text localization and image segmentation which respects real time constraints. In the first part, we are going to present the state of the art in text location and thresholding in the images of postal addresses. In the second part, we will describe our method which simultaneously localize and segment text zones. The Location of text blocks obtained from a multiresolution approach on cumulated gradients computed directly from grey level images. The coupling of the two processes (text zones location and thresholding) allows to reduce simultaneously the computing time by processing only necessary parts of the image and by obtaining a better character segmentation for the OCR (Optical Character Recognition). We will present the results obtained from the implementation of our approach on an industrial line which daily processes several tons of documents from large companies.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Auvergne-Rhône-Alpes</li><li>Rhône-Alpes</li></region><settlement><li>Lyon</li></settlement><orgName><li>Université Claude Bernard Lyon 1</li><li>Université de Lyon</li></orgName></list><tree><country name="France"><region name="Auvergne-Rhône-Alpes"><name sortKey="Gaceb, Djamel" sort="Gaceb, Djamel" uniqKey="Gaceb D" first="Djamel" last="Gaceb">Djamel Gaceb</name></region><name sortKey="Eglin, Veronique" sort="Eglin, Veronique" uniqKey="Eglin V" first="Véronique" last="Eglin">Véronique Eglin</name><name sortKey="Emptoz, Hubert" sort="Emptoz, Hubert" uniqKey="Emptoz H" first="Hubert" last="Emptoz">Hubert Emptoz</name><name sortKey="Lebourgeois, Frank" sort="Lebourgeois, Frank" uniqKey="Lebourgeois F" first="Frank" last="Lebourgeois">Frank Lebourgeois</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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|area= OcrV1
|flux= France
|étape= Analysis
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|texte= Contribution to the Automatic Recognition of Business Documents
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