Recognition-based segmentation of Nom characters from body text regions of stele images using area Voronoi diagram
Identifieur interne : 000804 ( Main/Exploration ); précédent : 000803; suivant : 000805Recognition-based segmentation of Nom characters from body text regions of stele images using area Voronoi diagram
Auteurs : Thai V. Hoang [France] ; Salvatore Tabbone [France] ; Ngoc-Yen Pham [France]Source :
Abstract
Segmentation of Nom characters from body text regions of stele images is a challenging problem due to the confusing spatial distribution of the connected components composing these characters. In this paper, for each vertical text line, area Voronoi diagram is employed to represent the neighborhood of the connected components and Voronoi edges are used as nonlinear segmentation hypotheses. Characters are then segmented by selecting appropriate adjacent Voronoi regions. For this purpose, we utilize the information about the horizontal overlap of connected components and the recognition distances of candidate characters provided by an OCR engine. Experimental results show that the proposed method is highly accurate and robust to various types of stele.
Url:
DOI: 10.1007/978-3-642-03767-2
Affiliations:
- France
- Auvergne-Rhône-Alpes, Lorraine, Rhône-Alpes
- Grenoble, Nancy
- Institut national polytechnique de Lorraine, Université Joseph Fourier, Université Nancy 2, Université de Grenoble, Université de Lorraine
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Le document en format XML
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Grenoble 1</orgName><orgName type="acronym">UJF</orgName><date type="end">2015-12-31</date><desc><address><addrLine>BP 53 - 38041 Grenoble Cedex 9</addrLine><country key="FR"></country></address><ref type="url">http://www.ujf-grenoble.fr/</ref></desc></org></tutelle><tutelle active="#struct-300357" type="direct"><org type="institution" xml:id="struct-300357" status="VALID"><orgName>École Nationale Supérieure de Physique de Grenoble (ENSPG)</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300943" type="direct"><org type="institution" xml:id="struct-300943" status="VALID"><orgName>HUT</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle name="UMI2954" 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">Grenoble</settlement><region type="region" nuts="2">Auvergne-Rhône-Alpes</region><region type="old region" nuts="2">Rhône-Alpes</region></placeName><orgName type="university">Université Joseph Fourier</orgName><orgName type="institution" wicri:auto="newGroup">Université de Grenoble</orgName></affiliation></author></analytic><idno type="DOI">10.1007/978-3-642-03767-2</idno></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Segmentation of Nom characters from body text regions of stele images is a challenging problem due to the confusing spatial distribution of the connected components composing these characters. In this paper, for each vertical text line, area Voronoi diagram is employed to represent the neighborhood of the connected components and Voronoi edges are used as nonlinear segmentation hypotheses. Characters are then segmented by selecting appropriate adjacent Voronoi regions. For this purpose, we utilize the information about the horizontal overlap of connected components and the recognition distances of candidate characters provided by an OCR engine. Experimental results show that the proposed method is highly accurate and robust to various types of stele.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Auvergne-Rhône-Alpes</li><li>Lorraine</li><li>Rhône-Alpes</li></region><settlement><li>Grenoble</li><li>Nancy</li></settlement><orgName><li>Institut national polytechnique de Lorraine</li><li>Université Joseph Fourier</li><li>Université Nancy 2</li><li>Université de Grenoble</li><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Lorraine"><name sortKey="Hoang, Thai V" sort="Hoang, Thai V" uniqKey="Hoang T" first="Thai V." last="Hoang">Thai V. Hoang</name></region><name sortKey="Pham, Ngoc Yen" sort="Pham, Ngoc Yen" uniqKey="Pham N" first="Ngoc-Yen" last="Pham">Ngoc-Yen Pham</name><name sortKey="Tabbone, Salvatore" sort="Tabbone, Salvatore" uniqKey="Tabbone S" first="Salvatore" last="Tabbone">Salvatore Tabbone</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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|texte= Recognition-based segmentation of Nom characters from body text regions of stele images using area Voronoi diagram
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