Local Orientation Extraction for Wordspotting in Syriac Manuscripts
Identifieur interne : 002753 ( Istex/Corpus ); précédent : 002752; suivant : 002754Local Orientation Extraction for Wordspotting in Syriac Manuscripts
Auteurs : P. Bilane ; S. Bres ; H. EmptozSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2008.
Abstract
Abstract: This paper presents a contribution to Word Spotting applied for digitized Syriac manuscripts. The Syriac language was wrongfully accused of being a dead language and has been set aside by the domain of handwriting recognition. Yet it is a very fascinating handwriting that combines the word structure and calligraphy of the Arabic handwriting with the particularity of being intentionally written tilted by an angle of approximately 45°. For the spotting process, we developed a method that should find all occurrences of a certain query word image, based on a selective sliding window technique, from which we extract directional features and afterwards perform a matching using Euclidean distance correspondence between features. The proposed method does not require any prior information, and does not depend of a word to character segmentation algorithm which would be extremely complex to realize due to the tilted nature of the handwriting.
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DOI: 10.1007/978-3-540-69905-7_55
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ISTEX:B50DC37D09495918D676EA557C3D6ECC0D4FE376Le document en format XML
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Bilane</name><affiliation><mods:affiliation>LIRIS, INSA-Lyon, F-69621, France</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: petra.bilane@insa-lyon.fr</mods:affiliation></affiliation></author><author><name sortKey="Bres, S" sort="Bres, S" uniqKey="Bres S" first="S." last="Bres">S. Bres</name><affiliation><mods:affiliation>LIRIS, INSA-Lyon, F-69621, France</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: stephane.bres@insa-lyon.fr</mods:affiliation></affiliation></author><author><name sortKey="Emptoz, H" sort="Emptoz, H" uniqKey="Emptoz H" first="H." last="Emptoz">H. 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The Syriac language was wrongfully accused of being a dead language and has been set aside by the domain of handwriting recognition. Yet it is a very fascinating handwriting that combines the word structure and calligraphy of the Arabic handwriting with the particularity of being intentionally written tilted by an angle of approximately 45°. For the spotting process, we developed a method that should find all occurrences of a certain query word image, based on a selective sliding window technique, from which we extract directional features and afterwards perform a matching using Euclidean distance correspondence between features. The proposed method does not require any prior information, and does not depend of a word to character segmentation algorithm which would be extremely complex to realize due to the tilted nature of the handwriting.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>P. 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The Syriac language was wrongfully accused of being a dead language and has been set aside by the domain of handwriting recognition. Yet it is a very fascinating handwriting that combines the word structure and calligraphy of the Arabic handwriting with the particularity of being intentionally written tilted by an angle of approximately 45°. For the spotting process, we developed a method that should find all occurrences of a certain query word image, based on a selective sliding window technique, from which we extract directional features and afterwards perform a matching using Euclidean distance correspondence between features. The proposed method does not require any prior information, and does not depend of a word to character segmentation algorithm which would be extremely complex to realize due to the tilted nature of the handwriting.</p></abstract><textClass><keywords scheme="Book Subject Collection"><list><label>SUCO11645</label><item><term>Computer Science</term></item></list></keywords></textClass><textClass><keywords scheme="Book Subject Group"><list><label>I</label><label>I22005</label><label>I2203X</label><label>I22021</label><label>I22040</label><label>I21017</label><label>I16021</label><item><term>Computer Science</term></item><item><term>Computer Imaging, Vision, Pattern Recognition and Graphics</term></item><item><term>Pattern Recognition</term></item><item><term>Image Processing and Computer Vision</term></item><item><term>Biometrics</term></item><item><term>Artificial Intelligence (incl. 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Bern</OrgName><OrgAddress><City>Bern</City><Country>Switzerland</Country></OrgAddress></Affiliation><Affiliation ID="Aff9"><OrgName>Indian Institute of Technology</OrgName><OrgAddress><City>Madras</City><Country>India</Country></OrgAddress></Affiliation><Affiliation ID="Aff10"><OrgName>University of Dortmund</OrgName><OrgAddress><City>Dortmund</City><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff11"><OrgName>Massachusetts Institute of Technology</OrgName><OrgAddress><State>MA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff12"><OrgName>University of California</OrgName><OrgAddress><City>Los Angeles</City><State>CA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff13"><OrgName>University of California</OrgName><OrgAddress><City>Berkeley</City><State>CA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff14"><OrgName>Rice University</OrgName><OrgAddress><City>Houston</City><State>TX</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff15"><OrgName>Max-Planck Institute of Computer Science</OrgName><OrgAddress><City>Saarbrücken</City><Country>Germany</Country></OrgAddress></Affiliation></EditorGroup></SeriesHeader><Book Language="En"><BookInfo BookProductType="Proceedings" ContainsESM="No" Language="En" MediaType="eBook" NumberingDepth="2" NumberingStyle="ContentOnly" OutputMedium="All" TocLevels="0"><BookID>978-3-540-69905-7</BookID><BookTitle>Image and Signal Processing</BookTitle><BookSubTitle>3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1 - 3, 2008. Proceedings</BookSubTitle><BookVolumeNumber>5099</BookVolumeNumber><BookSequenceNumber>5099</BookSequenceNumber><BookDOI>10.1007/978-3-540-69905-7</BookDOI><BookTitleID>164695</BookTitleID><BookPrintISBN>978-3-540-69904-0</BookPrintISBN><BookElectronicISBN>978-3-540-69905-7</BookElectronicISBN><BookChapterCount>71</BookChapterCount><BookCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2008</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I22005" Priority="1" Type="Secondary">Computer Imaging, Vision, Pattern Recognition and Graphics</BookSubject><BookSubject Code="I2203X" Priority="2" Type="Secondary">Pattern Recognition</BookSubject><BookSubject Code="I22021" Priority="3" Type="Secondary">Image Processing and Computer Vision</BookSubject><BookSubject Code="I22040" Priority="4" Type="Secondary">Biometrics</BookSubject><BookSubject Code="I21017" Priority="5" Type="Secondary">Artificial Intelligence (incl. Robotics)</BookSubject><BookSubject Code="I16021" Priority="6" Type="Secondary">Algorithm Analysis and Problem Complexity</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff16"><EditorName DisplayOrder="Western"><GivenName>Abderrahim</GivenName><FamilyName>Elmoataz</FamilyName></EditorName><Contact><Email>abderrahim.elmoataz-billah@unicaen.fr</Email></Contact></Editor><Editor AffiliationIDS="Aff17"><EditorName DisplayOrder="Western"><GivenName>Olivier</GivenName><FamilyName>Lezoray</FamilyName></EditorName><Contact><Email>olivier.lezoray@unicaen.fr</Email></Contact></Editor><Editor AffiliationIDS="Aff18"><EditorName DisplayOrder="Western"><GivenName>Fathallah</GivenName><FamilyName>Nouboud</FamilyName></EditorName><Contact><Email>fathallah.nouboud@uqtr.ca</Email></Contact></Editor><Editor AffiliationIDS="Aff19"><EditorName DisplayOrder="Western"><GivenName>Driss</GivenName><FamilyName>Mammass</FamilyName></EditorName><Contact><Email>driss_mammass@yahoo.fr</Email></Contact></Editor><Affiliation ID="Aff16"><OrgDivision>GREYC UMR CNRS 6072 ENSICAEN </OrgDivision><OrgName>Université de Caen Basse-Normandie</OrgName><OrgAddress><Street>6 Bd. Maréchal Juin</Street><Postcode>14050</Postcode><City>Caen</City><Country>France</Country></OrgAddress></Affiliation><Affiliation ID="Aff17"><OrgDivision>GREYC UMR CNRS 6072 ENSICAEN</OrgDivision><OrgName>Université de Caen Basse-Normandie </OrgName><OrgAddress><Street>6 Bd. Maréchal Juin</Street><Postcode>14050</Postcode><City>Caen</City><Country>France</Country></OrgAddress></Affiliation><Affiliation ID="Aff18"><OrgName>Université de Québec à Trois-Rivières </OrgName><OrgAddress><Street>C.P. 500 Trois-Riviéres</Street><Postcode>G9A 5H7</Postcode><State>Québec</State><Country>Canada</Country></OrgAddress></Affiliation><Affiliation ID="Aff19"><OrgName>Université IbnZohr </OrgName><OrgAddress><Postcode>BP.8106</Postcode><City>Hay Dakhla</City><State>Agadir</State><Country>Marocco</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part10"><PartInfo TocLevels="0"><PartID>10</PartID><PartSequenceNumber>10</PartSequenceNumber><PartTitle>Document Processing</PartTitle><PartChapterCount>5</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Image and Signal Processing</BookTitle></PartContext></PartInfo><Chapter ID="Chap55" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingDepth="2" NumberingStyle="ContentOnly" TocLevels="0"><ChapterID>55</ChapterID><ChapterDOI>10.1007/978-3-540-69905-7_55</ChapterDOI><ChapterSequenceNumber>55</ChapterSequenceNumber><ChapterTitle Language="En">Local Orientation Extraction for Wordspotting in Syriac Manuscripts</ChapterTitle><ChapterFirstPage>481</ChapterFirstPage><ChapterLastPage>489</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2008</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>10</PartID><BookID>978-3-540-69905-7</BookID><BookTitle>Image and Signal Processing</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff20"><AuthorName DisplayOrder="Western"><GivenName>P.</GivenName><FamilyName>Bilane</FamilyName></AuthorName><Contact><Email>petra.bilane@insa-lyon.fr</Email></Contact></Author><Author AffiliationIDS="Aff20"><AuthorName DisplayOrder="Western"><GivenName>S.</GivenName><FamilyName>Bres</FamilyName></AuthorName><Contact><Email>stephane.bres@insa-lyon.fr</Email></Contact></Author><Author AffiliationIDS="Aff20"><AuthorName DisplayOrder="Western"><GivenName>H.</GivenName><FamilyName>Emptoz</FamilyName></AuthorName><Contact><Email>hubert.emptoz@insa-lyon.fr</Email></Contact></Author><Affiliation ID="Aff20"><OrgDivision>LIRIS</OrgDivision><OrgName>INSA-Lyon</OrgName><OrgAddress><Postcode>F-69621</Postcode><Country>France</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>This paper presents a contribution to Word Spotting applied for digitized Syriac manuscripts. The Syriac language was wrongfully accused of being a dead language and has been set aside by the domain of handwriting recognition. Yet it is a very fascinating handwriting that combines the word structure and calligraphy of the Arabic handwriting with the particularity of being intentionally written tilted by an angle of approximately 45°. For the spotting process, we developed a method that should find all occurrences of a certain query word image, based on a selective sliding window technique, from which we extract directional features and afterwards perform a matching using Euclidean distance correspondence between features. The proposed method does not require any prior information, and does not depend of a word to character segmentation algorithm which would be extremely complex to realize due to the tilted nature of the handwriting.</Para></Abstract><KeywordGroup Language="En"><Heading>Keywords</Heading><Keyword>Word Spotting</Keyword><Keyword>orientation features</Keyword><Keyword>directional roses</Keyword></KeywordGroup></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Local Orientation Extraction for Wordspotting in Syriac Manuscripts</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Local Orientation Extraction for Wordspotting in Syriac Manuscripts</title></titleInfo><name type="personal"><namePart type="given">P.</namePart><namePart type="family">Bilane</namePart><affiliation>LIRIS, INSA-Lyon, F-69621, France</affiliation><affiliation>E-mail: petra.bilane@insa-lyon.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">S.</namePart><namePart type="family">Bres</namePart><affiliation>LIRIS, INSA-Lyon, F-69621, France</affiliation><affiliation>E-mail: stephane.bres@insa-lyon.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">H.</namePart><namePart type="family">Emptoz</namePart><affiliation>LIRIS, INSA-Lyon, F-69621, France</affiliation><affiliation>E-mail: hubert.emptoz@insa-lyon.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2008</dateIssued><copyrightDate encoding="w3cdtf">2008</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: This paper presents a contribution to Word Spotting applied for digitized Syriac manuscripts. The Syriac language was wrongfully accused of being a dead language and has been set aside by the domain of handwriting recognition. Yet it is a very fascinating handwriting that combines the word structure and calligraphy of the Arabic handwriting with the particularity of being intentionally written tilted by an angle of approximately 45°. For the spotting process, we developed a method that should find all occurrences of a certain query word image, based on a selective sliding window technique, from which we extract directional features and afterwards perform a matching using Euclidean distance correspondence between features. The proposed method does not require any prior information, and does not depend of a word to character segmentation algorithm which would be extremely complex to realize due to the tilted nature of the handwriting.</abstract><relatedItem type="host"><titleInfo><title>Image and Signal Processing</title><subTitle>3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1 - 3, 2008. Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Abderrahim</namePart><namePart type="family">Elmoataz</namePart><affiliation>GREYC UMR CNRS 6072 ENSICAEN, Université de Caen Basse-Normandie, 6 Bd. Maréchal Juin, 14050, Caen, France</affiliation><affiliation>E-mail: abderrahim.elmoataz-billah@unicaen.fr</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Olivier</namePart><namePart type="family">Lezoray</namePart><affiliation>GREYC UMR CNRS 6072 ENSICAEN, Université de Caen Basse-Normandie, 6 Bd. 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