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<datestamp>2018-01-11</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Automatic name extraction from degraded document images</title>
<creator>Likforman-Sulem, Laurence</creator>
<creator>Vaillant, Pascal</creator>
<creator>De Bodard De La Jacopière, Aliette</creator>
<contributor>Laboratoire Traitement et Communication de l'Information (LTCI) ; Télécom ParisTech - Institut Mines-Télécom [Paris] - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Groupe de Recherche en Informatique et Mathématiques Appliquées Antilles-Guyane (GRIMAAG) ; Université des Antilles et de la Guyane (UAG)</contributor>
<description>17 pages, 11 figures.</description>
<description>International audience</description>
<source>ISSN: 1433-7541</source>
<source>EISSN: 1433-755X</source>
<source>Pattern Analysis and Applications</source>
<publisher>Springer Verlag</publisher>
<identifier>hal-00329459</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00329459</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00329459</source>
<source>Pattern Analysis and Applications, Springer Verlag, 2006, 9 (2-3), pp.211-227. 〈10.1007/s10044-006-0038-6〉</source>
<identifier>DOI : 10.1007/s10044-006-0038-6</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1007/s10044-006-0038-6</relation>
<language>en</language>
<subject lang=en>Document image analysis</subject>
<subject lang=en>Name extraction</subject>
<subject lang=en>Neural Networks</subject>
<subject lang=en>Facsimile processing</subject>
<subject lang=en>Journal title pages</subject>
<subject lang=en>Document understanding</subject>
<subject lang=en>Visual clues</subject>
<subject>ACM H.3.1; I.5.4</subject>
<subject>[INFO.INFO-TT] Computer Science [cs]/Document and Text Processing</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>The problem addressed in this paper is the automatic extraction of names from a document image. Our approach relies on the combination of two complementary analyses. First, the image-based analysis exploits visual clues to select the regions of interest in the document. Second, the textual-based analysis searches for name patterns and low-level word textual features. Both analyses are then combined at the word level through a neural network fusion scheme. Reported results on degraded documents such as facsimile and photocopied technical journals demonstrate the interest of the combined approach.</description>
<date>2006-10</date>
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