A Restoration and Segmentation Unit for the Historic Persian Documents
Identifieur interne : 001883 ( Istex/Corpus ); précédent : 001882; suivant : 001884A Restoration and Segmentation Unit for the Historic Persian Documents
Auteurs : Shahpour Alirezaee ; Shayesteh Fard ; Hassan Aghaeinia ; Karim FaezSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2005.
Abstract
Abstract: This paper aims to provide a document restoration and segmentation algorithm for the Historic Middle Persian or Pahlavi manuscripts. The proposed algorithm uses the mathematical morphology and connected component concept to segment the line, word, and character overlapped in the Middle-age Persian documents in preparation for OCR application. To evaluate the performance of the restoration algorithm, 200 pages of the Pahlavi documents are used as experimental data in our test. Numerical results indicate that the proposed algorithm can remove the noise and destructive effects. The results also show 99.14% accuracy on the baseline detection, 97.35% accuracy on the text line extraction and removing other lines overlaps, and 99.5% accuracy for segmenting the extracted text lines to their components.
Url:
DOI: 10.1007/11558484_85
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ISTEX:25A5B5A5BE3B1263DAEBBEBDAB6E9BA6A67855BBLe document en format XML
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The proposed algorithm uses the mathematical morphology and connected component concept to segment the line, word, and character overlapped in the Middle-age Persian documents in preparation for OCR application. To evaluate the performance of the restoration algorithm, 200 pages of the Pahlavi documents are used as experimental data in our test. Numerical results indicate that the proposed algorithm can remove the noise and destructive effects. The results also show 99.14% accuracy on the baseline detection, 97.35% accuracy on the text line extraction and removing other lines overlaps, and 99.5% accuracy for segmenting the extracted text lines to their components.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Shahpour Alirezaee</name><affiliations><json:string>Electrical Engineering Department, Islamic Azad University of Abhar, Abhar, Iran</json:string><json:string>E-mail: Alirezae@mail.znu.ac.ir</json:string></affiliations></json:item><json:item><name>Alireza Shayesteh Fard</name><affiliations><json:string>Electrical Engineering Department, Zanjan University, Zanjan, Iran</json:string><json:string>E-mail: Shayestehfard@mail.znu.ac.ir</json:string></affiliations></json:item><json:item><name>Hassan Aghaeinia</name><affiliations><json:string>Electrical Engineering Department, Amirkabir University of Technology, Hafez Ave., Tehran, Iran</json:string><json:string>E-mail: Aghaeinia@aut.ac.ir</json:string></affiliations></json:item><json:item><name>Karim Faez</name><affiliations><json:string>Electrical Engineering Department, Amirkabir University of Technology, Hafez Ave., Tehran, Iran</json:string><json:string>E-mail: faez@aut.ac.ir</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><abstract>Abstract: This paper aims to provide a document restoration and segmentation algorithm for the Historic Middle Persian or Pahlavi manuscripts. 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The proposed algorithm uses the mathematical morphology and connected component concept to segment the line, word, and character overlapped in the Middle-age Persian documents in preparation for OCR application. To evaluate the performance of the restoration algorithm, 200 pages of the Pahlavi documents are used as experimental data in our test. Numerical results indicate that the proposed algorithm can remove the noise and destructive effects. The results also show 99.14% accuracy on the baseline detection, 97.35% accuracy on the text line extraction and removing other lines overlaps, and 99.5% accuracy for segmenting the extracted text lines to their components.</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>I22021</label><label>I2203X</label><label>I22013</label><label>I21017</label><item><term>Computer Science</term></item><item><term>Image Processing and Computer Vision</term></item><item><term>Pattern Recognition</term></item><item><term>Computer Graphics</term></item><item><term>Artificial Intelligence (incl. 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University</OrgName><OrgAddress><City>Pittsburgh</City><State>PA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff3"><OrgName>University of Surrey</OrgName><OrgAddress><City>Guildford</City><Country>UK</Country></OrgAddress></Affiliation><Affiliation ID="Aff4"><OrgName>Cornell University</OrgName><OrgAddress><City>Ithaca</City><State>NY</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff5"><OrgName>ETH Zurich</OrgName><OrgAddress><Country>Switzerland</Country></OrgAddress></Affiliation><Affiliation ID="Aff6"><OrgName>Stanford University</OrgName><OrgAddress><City>CA</City><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff7"><OrgName>Weizmann Institute of Science</OrgName><OrgAddress><City>Rehovot</City><Country>Israel</Country></OrgAddress></Affiliation><Affiliation ID="Aff8"><OrgName>University of Bern</OrgName><OrgAddress><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><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff11"><OrgName>Massachusetts Institute of Technology</OrgName><OrgAddress><City>MA</City><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff12"><OrgName>New York University</OrgName><OrgAddress><City>NY</City><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>Saarbruecken</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>978-3-540-32046-3</BookID><BookTitle>Advanced Concepts for Intelligent Vision Systems</BookTitle><BookSubTitle>7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings</BookSubTitle><BookVolumeNumber>3708</BookVolumeNumber><BookSequenceNumber>3708</BookSequenceNumber><BookDOI>10.1007/11558484</BookDOI><BookTitleID>126672</BookTitleID><BookPrintISBN>978-3-540-29032-2</BookPrintISBN><BookElectronicISBN>978-3-540-32046-3</BookElectronicISBN><BookChapterCount>90</BookChapterCount><BookCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2005</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I22021" Priority="1" Type="Secondary">Image Processing and Computer Vision</BookSubject><BookSubject Code="I2203X" Priority="2" Type="Secondary">Pattern Recognition</BookSubject><BookSubject Code="I22013" Priority="3" Type="Secondary">Computer Graphics</BookSubject><BookSubject Code="I21017" Priority="4" Type="Secondary">Artificial Intelligence (incl. Robotics)</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff16"><EditorName DisplayOrder="Western"><GivenName>Jacques</GivenName><FamilyName>Blanc-Talon</FamilyName></EditorName><Contact><Email>blanc@etca.fr</Email></Contact></Editor><Editor AffiliationIDS="Aff17"><EditorName DisplayOrder="Western"><GivenName>Wilfried</GivenName><FamilyName>Philips</FamilyName></EditorName><Contact><Email>Wilfried.Philips@ugent.be</Email></Contact></Editor><Editor AffiliationIDS="Aff18"><EditorName DisplayOrder="Western"><GivenName>Dan</GivenName><FamilyName>Popescu</FamilyName></EditorName><Contact><Email>Dan.Popescu@csiro.au</Email></Contact></Editor><Editor AffiliationIDS="Aff19"><EditorName DisplayOrder="Western"><GivenName>Paul</GivenName><FamilyName>Scheunders</FamilyName></EditorName><Contact><Email>paul.scheunders@ua.ac.be</Email></Contact></Editor><Affiliation ID="Aff16"><OrgName>DGA/D4S/MRIS</OrgName><OrgAddress><Postcode>94114</Postcode><City>Arcueil</City><Country>France</Country></OrgAddress></Affiliation><Affiliation ID="Aff17"><OrgName>Ghent University</OrgName><OrgAddress><Postcode>9000</Postcode><City>Gent</City><Country>Belgium</Country></OrgAddress></Affiliation><Affiliation ID="Aff18"><OrgDivision>Wireless Technologies Lab</OrgDivision><OrgName>CSIRO ICT Centre</OrgName><OrgAddress><Postcode>NSW 2122</Postcode><City>Marsfield</City><Country>Australia</Country></OrgAddress></Affiliation><Affiliation ID="Aff19"><OrgName>University of Antwerp</OrgName><OrgAddress><Postcode>2610</Postcode><City>Wilrijk</City><Country>Belgium</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part9"><PartInfo TocLevels="0"><PartID>9</PartID><PartSequenceNumber>9</PartSequenceNumber><PartTitle>Noise Reduction and Restauration</PartTitle><PartChapterCount>9</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Advanced Concepts for Intelligent Vision Systems</BookTitle></PartContext></PartInfo><Chapter ID="Chap85" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingDepth="2" NumberingStyle="ContentOnly" TocLevels="0"><ChapterID>85</ChapterID><ChapterDOI>10.1007/11558484_85</ChapterDOI><ChapterSequenceNumber>85</ChapterSequenceNumber><ChapterTitle Language="En">A Restoration and Segmentation Unit for the Historic Persian Documents</ChapterTitle><ChapterFirstPage>674</ChapterFirstPage><ChapterLastPage>680</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2005</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>9</PartID><BookID>978-3-540-32046-3</BookID><BookTitle>Advanced Concepts for Intelligent Vision Systems</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff20"><AuthorName DisplayOrder="Western"><GivenName>Shahpour</GivenName><FamilyName>Alirezaee</FamilyName></AuthorName><Contact><Email>Alirezae@mail.znu.ac.ir</Email></Contact></Author><Author AffiliationIDS="Aff21"><AuthorName DisplayOrder="Western"><GivenName>Alireza</GivenName><GivenName>Shayesteh</GivenName><FamilyName>Fard</FamilyName></AuthorName><Contact><Email>Shayestehfard@mail.znu.ac.ir</Email></Contact></Author><Author AffiliationIDS="Aff22"><AuthorName DisplayOrder="Western"><GivenName>Hassan</GivenName><FamilyName>Aghaeinia</FamilyName></AuthorName><Contact><Email>Aghaeinia@aut.ac.ir</Email></Contact></Author><Author AffiliationIDS="Aff22"><AuthorName DisplayOrder="Western"><GivenName>Karim</GivenName><FamilyName>Faez</FamilyName></AuthorName><Contact><Email>faez@aut.ac.ir</Email></Contact></Author><Affiliation ID="Aff20"><OrgDivision>Electrical Engineering Department</OrgDivision><OrgName>Islamic Azad University of Abhar</OrgName><OrgAddress><City>Abhar</City><Country>Iran</Country></OrgAddress></Affiliation><Affiliation ID="Aff21"><OrgDivision>Electrical Engineering Department</OrgDivision><OrgName>Zanjan University</OrgName><OrgAddress><City>Zanjan</City><Country>Iran</Country></OrgAddress></Affiliation><Affiliation ID="Aff22"><OrgDivision>Electrical Engineering Department</OrgDivision><OrgName>Amirkabir University of Technology</OrgName><OrgAddress><Street>Hafez Ave.</Street><City>Tehran</City><Country>Iran</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>This paper aims to provide a document restoration and segmentation algorithm for the Historic Middle Persian or Pahlavi manuscripts. The proposed algorithm uses the mathematical morphology and connected component concept to segment the line, word, and character overlapped in the Middle-age Persian documents in preparation for OCR application. To evaluate the performance of the restoration algorithm, 200 pages of the Pahlavi documents are used as experimental data in our test. Numerical results indicate that the proposed algorithm can remove the noise and destructive effects. The results also show 99.14% accuracy on the baseline detection, 97.35% accuracy on the text line extraction and removing other lines overlaps, and 99.5% accuracy for segmenting the extracted text lines to their components.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>A Restoration and Segmentation Unit for the Historic Persian Documents</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>A Restoration and Segmentation Unit for the Historic Persian Documents</title></titleInfo><name type="personal"><namePart type="given">Shahpour</namePart><namePart type="family">Alirezaee</namePart><affiliation>Electrical Engineering Department, Islamic Azad University of Abhar, Abhar, Iran</affiliation><affiliation>E-mail: Alirezae@mail.znu.ac.ir</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Alireza</namePart><namePart type="given">Shayesteh</namePart><namePart type="family">Fard</namePart><affiliation>Electrical Engineering Department, Zanjan University, Zanjan, Iran</affiliation><affiliation>E-mail: Shayestehfard@mail.znu.ac.ir</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Hassan</namePart><namePart type="family">Aghaeinia</namePart><affiliation>Electrical Engineering Department, Amirkabir University of Technology, Hafez Ave., Tehran, Iran</affiliation><affiliation>E-mail: Aghaeinia@aut.ac.ir</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Karim</namePart><namePart type="family">Faez</namePart><affiliation>Electrical Engineering Department, Amirkabir University of Technology, Hafez Ave., Tehran, Iran</affiliation><affiliation>E-mail: faez@aut.ac.ir</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">2005</dateIssued><copyrightDate encoding="w3cdtf">2005</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 aims to provide a document restoration and segmentation algorithm for the Historic Middle Persian or Pahlavi manuscripts. The proposed algorithm uses the mathematical morphology and connected component concept to segment the line, word, and character overlapped in the Middle-age Persian documents in preparation for OCR application. To evaluate the performance of the restoration algorithm, 200 pages of the Pahlavi documents are used as experimental data in our test. Numerical results indicate that the proposed algorithm can remove the noise and destructive effects. The results also show 99.14% accuracy on the baseline detection, 97.35% accuracy on the text line extraction and removing other lines overlaps, and 99.5% accuracy for segmenting the extracted text lines to their components.</abstract><relatedItem type="host"><titleInfo><title>Advanced Concepts for Intelligent Vision Systems</title><subTitle>7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Jacques</namePart><namePart type="family">Blanc-Talon</namePart><affiliation>DGA/D4S/MRIS, 94114, Arcueil, France</affiliation><affiliation>E-mail: blanc@etca.fr</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Wilfried</namePart><namePart type="family">Philips</namePart><affiliation>Ghent University, 9000, Gent, Belgium</affiliation><affiliation>E-mail: Wilfried.Philips@ugent.be</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Dan</namePart><namePart type="family">Popescu</namePart><affiliation>Wireless Technologies Lab, CSIRO ICT Centre, NSW 2122, Marsfield, Australia</affiliation><affiliation>E-mail: Dan.Popescu@csiro.au</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Paul</namePart><namePart type="family">Scheunders</namePart><affiliation>University of Antwerp, 2610, Wilrijk, Belgium</affiliation><affiliation>E-mail: paul.scheunders@ua.ac.be</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2005</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book Subject Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book Subject Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I22021">Image Processing and Computer Vision</topic><topic authority="SpringerSubjectCodes" authorityURI="I2203X">Pattern Recognition</topic><topic authority="SpringerSubjectCodes" authorityURI="I22013">Computer Graphics</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic></subject><identifier type="DOI">10.1007/11558484</identifier><identifier type="ISBN">978-3-540-29032-2</identifier><identifier type="eISBN">978-3-540-32046-3</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">126672</identifier><identifier type="BookID">978-3-540-32046-3</identifier><identifier type="BookChapterCount">90</identifier><identifier type="BookVolumeNumber">3708</identifier><identifier type="BookSequenceNumber">3708</identifier><identifier type="PartChapterCount">9</identifier><part><date>2005</date><detail type="part"><title>Noise Reduction and Restauration</title></detail><detail type="volume"><number>3708</number><caption>vol.</caption></detail><extent unit="pages"><start>674</start><end>680</end></extent></part><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 2005</recordOrigin></recordInfo></relatedItem><relatedItem type="series"><titleInfo><title>Lecture 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type="personal"><namePart type="given">Friedemann</namePart><namePart type="family">Mattern</namePart><affiliation>ETH Zurich, Switzerland</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">John</namePart><namePart type="given">C.</namePart><namePart type="family">Mitchell</namePart><affiliation>Stanford University, CA, USA</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Moni</namePart><namePart type="family">Naor</namePart><affiliation>Weizmann Institute of Science, Rehovot, Israel</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Oscar</namePart><namePart type="family">Nierstrasz</namePart><affiliation>University of Bern, Switzerland</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">C.</namePart><namePart 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type="first">M</forename><surname>Bulacu</surname></persName></author></analytic><monogr><title level="j">IEEE Trans. on Pattern Analysis and Machine Intelligence</title><imprint><biblScope unit="volume">26</biblScope><biblScope unit="issue">6</biblScope><date type="published" when="2004"></date></imprint></monogr></biblStruct><biblStruct xml:id="b14"><analytic><title></title></analytic><monogr><title level="j">Pahlavy Handwritten Documents</title><imprint><date type="published" when="1972"></date></imprint></monogr></biblStruct></listBibl></back></text></istex:refBibTEI></enrichments></istex></record>Pour manipuler ce document sous Unix (Dilib)
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