A Novel Approach for Word Spotting Using Merge-Split Edit Distance
Identifieur interne : 000A27 ( Main/Exploration ); précédent : 000A26; suivant : 000A28A Novel Approach for Word Spotting Using Merge-Split Edit Distance
Auteurs : Khurram Khurshid [France] ; Claudie Faure [France] ; Nicole Vincent [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2009.
Abstract
Abstract: Edit distance matching has been used in literature for word spotting with characters taken as primitives. The recognition rate however, is limited by the segmentation inconsistencies of characters (broken or merged) caused by noisy images or distorted characters. In this paper, we have proposed a Merge-split edit distance which overcomes these segmentation problems by incorporating a multi-purpose merge cost function. The system is based on the extraction of words and characters in the text and then attributing each character with a set of features. Characters are matched by comparing their extracted feature sets using Dynamic Time Warping (DTW) while the words are matched by comparing the strings of characters using the proposed Merge-Split Edit distance algorithm. Evaluation of the method on 19th century historical document images exhibits extremely promising results.
Url:
DOI: 10.1007/978-3-642-03767-2_26
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 000D61
- to stream Istex, to step Curation: 000D32
- to stream Istex, to step Checkpoint: 000549
- to stream Main, to step Merge: 000A35
- to stream Main, to step Curation: 000A27
Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">A Novel Approach for Word Spotting Using Merge-Split Edit Distance</title><author><name sortKey="Khurshid, Khurram" sort="Khurshid, Khurram" uniqKey="Khurshid K" first="Khurram" last="Khurshid">Khurram Khurshid</name></author><author><name sortKey="Faure, Claudie" sort="Faure, Claudie" uniqKey="Faure C" first="Claudie" last="Faure">Claudie Faure</name></author><author><name sortKey="Vincent, Nicole" sort="Vincent, Nicole" uniqKey="Vincent N" first="Nicole" last="Vincent">Nicole Vincent</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:8C1F3989D2466FF4A187343DA0F0E8326A4176F7</idno><date when="2009" year="2009">2009</date><idno type="doi">10.1007/978-3-642-03767-2_26</idno><idno type="url">https://api.istex.fr/document/8C1F3989D2466FF4A187343DA0F0E8326A4176F7/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000D61</idno><idno type="wicri:Area/Istex/Curation">000D32</idno><idno type="wicri:Area/Istex/Checkpoint">000549</idno><idno type="wicri:doubleKey">0302-9743:2009:Khurshid K:a:novel:approach</idno><idno type="wicri:Area/Main/Merge">000A35</idno><idno type="wicri:Area/Main/Curation">000A27</idno><idno type="wicri:Area/Main/Exploration">000A27</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">A Novel Approach for Word Spotting Using Merge-Split Edit Distance</title><author><name sortKey="Khurshid, Khurram" sort="Khurshid, Khurram" uniqKey="Khurshid K" first="Khurram" last="Khurshid">Khurram Khurshid</name><affiliation wicri:level="4"><country xml:lang="fr">France</country><wicri:regionArea>Laboratoire CRIP5 – SIP, Université Paris Descartes, 45 rue des Saints-Pères, 75006, Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region><settlement type="city">Paris</settlement></placeName><orgName type="university">Université Paris Descartes</orgName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Faure, Claudie" sort="Faure, Claudie" uniqKey="Faure C" first="Claudie" last="Faure">Claudie Faure</name><affiliation wicri:level="3"><country xml:lang="fr">France</country><wicri:regionArea>UMR CNRS 5141 - GET ENST, 46 rue Barrault, 75634, Paris Cedex 13</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Vincent, Nicole" sort="Vincent, Nicole" uniqKey="Vincent N" first="Nicole" last="Vincent">Nicole Vincent</name><affiliation wicri:level="4"><country xml:lang="fr">France</country><wicri:regionArea>Laboratoire CRIP5 – SIP, Université Paris Descartes, 45 rue des Saints-Pères, 75006, Paris</wicri:regionArea><placeName><region type="region" nuts="2">Île-de-France</region><settlement type="city">Paris</settlement></placeName><orgName type="university">Université Paris Descartes</orgName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">France</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2009</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">8C1F3989D2466FF4A187343DA0F0E8326A4176F7</idno><idno type="DOI">10.1007/978-3-642-03767-2_26</idno><idno type="ChapterID">26</idno><idno type="ChapterID">Chap26</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Edit distance matching has been used in literature for word spotting with characters taken as primitives. The recognition rate however, is limited by the segmentation inconsistencies of characters (broken or merged) caused by noisy images or distorted characters. In this paper, we have proposed a Merge-split edit distance which overcomes these segmentation problems by incorporating a multi-purpose merge cost function. The system is based on the extraction of words and characters in the text and then attributing each character with a set of features. Characters are matched by comparing their extracted feature sets using Dynamic Time Warping (DTW) while the words are matched by comparing the strings of characters using the proposed Merge-Split Edit distance algorithm. Evaluation of the method on 19th century historical document images exhibits extremely promising results.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Île-de-France</li></region><settlement><li>Paris</li></settlement><orgName><li>Université Paris Descartes</li></orgName></list><tree><country name="France"><region name="Île-de-France"><name sortKey="Khurshid, Khurram" sort="Khurshid, Khurram" uniqKey="Khurshid K" first="Khurram" last="Khurshid">Khurram Khurshid</name></region><name sortKey="Faure, Claudie" sort="Faure, Claudie" uniqKey="Faure C" first="Claudie" last="Faure">Claudie Faure</name><name sortKey="Faure, Claudie" sort="Faure, Claudie" uniqKey="Faure C" first="Claudie" last="Faure">Claudie Faure</name><name sortKey="Khurshid, Khurram" sort="Khurshid, Khurram" uniqKey="Khurshid K" first="Khurram" last="Khurshid">Khurram Khurshid</name><name sortKey="Vincent, Nicole" sort="Vincent, Nicole" uniqKey="Vincent N" first="Nicole" last="Vincent">Nicole Vincent</name><name sortKey="Vincent, Nicole" sort="Vincent, Nicole" uniqKey="Vincent N" first="Nicole" last="Vincent">Nicole Vincent</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000A27 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000A27 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= OcrV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= ISTEX:8C1F3989D2466FF4A187343DA0F0E8326A4176F7
|texte= A Novel Approach for Word Spotting Using Merge-Split Edit Distance
}}
| This area was generated with Dilib version V0.6.32. |  |