NMF-Based Approach to Font Classification of Printed English Alphabets for Document Image Understanding
Identifieur interne : 000354 ( Istex/Curation ); précédent : 000353; suivant : 000355NMF-Based Approach to Font Classification of Printed English Alphabets for Document Image Understanding
Auteurs : Woo Lee [Corée du Sud] ; Keechul Jung [Corée du Sud]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2005.
Abstract
Abstract: This paper proposes an approach to font classification for document image understanding using non-negative matrix factorization (NMF). The basic idea of the proposed method is based on that the characteristics of each font are derived from parts of the individual characters in each font rather than holistic textures. Spatial localities, parts composing of font images, are automatically extracted using NMF. These parts are used as features representing each font. In the experimental results, the distribution of features and the appropriateness of use of the characteristics specifying each font are investigated. Add to that, the proposed method is compared with the method based on principal component analysis (PCA), in which various distance metrics are tested in the feature space. It expects that the proposed method will increase the performance of optical character recognition (OCR) systems or document indexing and retrieval systems if such systems adopt the proposed font classifier as a preprocessor.
Url:
DOI: 10.1007/11526018_35
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: Pour aller vers cette notice dans l'étape Curation :000359
Links to Exploration step
ISTEX:8D70EE7AE36F82535B88D00E2BD7ADCD1AED3109Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct:series"><teiHeader><fileDesc><titleStmt><title xml:lang="en">NMF-Based Approach to Font Classification of Printed English Alphabets for Document Image Understanding</title>
<author><name sortKey="Lee, Woo" sort="Lee, Woo" uniqKey="Lee W" first="Woo" last="Lee">Woo Lee</name>
<affiliation wicri:level="1"><mods:affiliation>Dept. of Computer Information Science, Kunsan National University, 573-701, Kunsan, Jeollabuk-do, S. Korea</mods:affiliation>
<country xml:lang="fr">Corée du Sud</country>
<wicri:regionArea>Dept. of Computer Information Science, Kunsan National University, 573-701, Kunsan, Jeollabuk-do</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><mods:affiliation>E-mail: leecw@kunsan.ac.kr</mods:affiliation>
<country wicri:rule="url">Corée du Sud</country>
</affiliation>
</author>
<author><name sortKey="Jung, Keechul" sort="Jung, Keechul" uniqKey="Jung K" first="Keechul" last="Jung">Keechul Jung</name>
<affiliation wicri:level="1"><mods:affiliation>School of Media, College of Information Science, Soongsil University, 156-743, Seoul, S. Korea</mods:affiliation>
<country xml:lang="fr">Corée du Sud</country>
<wicri:regionArea>School of Media, College of Information Science, Soongsil University, 156-743, Seoul</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><mods:affiliation>E-mail: kcjung@ssu.ac.kr</mods:affiliation>
<country wicri:rule="url">Corée du Sud</country>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:8D70EE7AE36F82535B88D00E2BD7ADCD1AED3109</idno>
<date when="2005" year="2005">2005</date>
<idno type="doi">10.1007/11526018_35</idno>
<idno type="url">https://api.istex.fr/document/8D70EE7AE36F82535B88D00E2BD7ADCD1AED3109/fulltext/pdf</idno>
<idno type="wicri:Area/Istex/Corpus">000359</idno>
<idno type="wicri:Area/Istex/Curation">000354</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">NMF-Based Approach to Font Classification of Printed English Alphabets for Document Image Understanding</title>
<author><name sortKey="Lee, Woo" sort="Lee, Woo" uniqKey="Lee W" first="Woo" last="Lee">Woo Lee</name>
<affiliation wicri:level="1"><mods:affiliation>Dept. of Computer Information Science, Kunsan National University, 573-701, Kunsan, Jeollabuk-do, S. Korea</mods:affiliation>
<country xml:lang="fr">Corée du Sud</country>
<wicri:regionArea>Dept. of Computer Information Science, Kunsan National University, 573-701, Kunsan, Jeollabuk-do</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><mods:affiliation>E-mail: leecw@kunsan.ac.kr</mods:affiliation>
<country wicri:rule="url">Corée du Sud</country>
</affiliation>
</author>
<author><name sortKey="Jung, Keechul" sort="Jung, Keechul" uniqKey="Jung K" first="Keechul" last="Jung">Keechul Jung</name>
<affiliation wicri:level="1"><mods:affiliation>School of Media, College of Information Science, Soongsil University, 156-743, Seoul, S. Korea</mods:affiliation>
<country xml:lang="fr">Corée du Sud</country>
<wicri:regionArea>School of Media, College of Information Science, Soongsil University, 156-743, Seoul</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><mods:affiliation>E-mail: kcjung@ssu.ac.kr</mods:affiliation>
<country wicri:rule="url">Corée du Sud</country>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series><title level="s">Lecture Notes in Computer Science</title>
<imprint><date>2005</date>
</imprint>
<idno type="ISSN">0302-9743</idno>
<idno type="eISSN">1611-3349</idno>
<idno type="ISSN">0302-9743</idno>
</series>
<idno type="istex">8D70EE7AE36F82535B88D00E2BD7ADCD1AED3109</idno>
<idno type="DOI">10.1007/11526018_35</idno>
<idno type="ChapterID">35</idno>
<idno type="ChapterID">Chap35</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: This paper proposes an approach to font classification for document image understanding using non-negative matrix factorization (NMF). The basic idea of the proposed method is based on that the characteristics of each font are derived from parts of the individual characters in each font rather than holistic textures. Spatial localities, parts composing of font images, are automatically extracted using NMF. These parts are used as features representing each font. In the experimental results, the distribution of features and the appropriateness of use of the characteristics specifying each font are investigated. Add to that, the proposed method is compared with the method based on principal component analysis (PCA), in which various distance metrics are tested in the feature space. It expects that the proposed method will increase the performance of optical character recognition (OCR) systems or document indexing and retrieval systems if such systems adopt the proposed font classifier as a preprocessor.</div>
</front>
</TEI>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Istex/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000354 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Curation/biblio.hfd -nk 000354 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= OcrV1 |flux= Istex |étape= Curation |type= RBID |clé= ISTEX:8D70EE7AE36F82535B88D00E2BD7ADCD1AED3109 |texte= NMF-Based Approach to Font Classification of Printed English Alphabets for Document Image Understanding }}
This area was generated with Dilib version V0.6.32. |