CLASSIFICATION OF MACHINE-PRINTED AND HANDWRITTEN TEXTS USING CHARACTER BLOCK LAYOUT VARIANCE
Identifieur interne : 002145 ( Main/Exploration ); précédent : 002144; suivant : 002146CLASSIFICATION OF MACHINE-PRINTED AND HANDWRITTEN TEXTS USING CHARACTER BLOCK LAYOUT VARIANCE
Auteurs : Kuo-Chin Fan [République populaire de Chine] ; Liang-Shen Wang [République populaire de Chine] ; Yin-Tien Tu [République populaire de Chine]Source :
- Pattern Recognition [ 0031-3203 ] ; 1997.
Abstract
Machine-printed and handwritten texts always intermixedly appear in several kinds of documents, such as form documents. The classification of machine-printed and handwritten texts is thus a prerequisite to facilitate later optical character recognition task. In this paper, we will present a machine-printed and handwritten text classification method to automatically identify the identity of texts segmented from a document image. In our approach, the orientation of a text block is first divided into horizontal or vertical direction by analyzing the widths of valleys of X and Y projection profiles of a text block image. Then, a reduced X–Y cut algorithm is utilized to obtain the base blocks from a text block image. Last, the spatial feature, character block layout variance, is devised to achieve the classification goal. Our method can be applied to either English or Chinese document images. Experimental results reveal the feasibility of our proposed method in classifying handwritten and machine-printed texts.
Url:
DOI: 10.1016/S0031-3203(97)00143-X
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 000880
- to stream Istex, to step Curation: 000870
- to stream Istex, to step Checkpoint: 001649
- to stream Main, to step Merge: 002262
- to stream Main, to step Curation: 002145
Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title>CLASSIFICATION OF MACHINE-PRINTED AND HANDWRITTEN TEXTS USING CHARACTER BLOCK LAYOUT VARIANCE</title>
<author><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name>
</author>
<author><name sortKey="Wang, Liang Shen" sort="Wang, Liang Shen" uniqKey="Wang L" first="Liang-Shen" last="Wang">Liang-Shen Wang</name>
</author>
<author><name sortKey="Tu, Yin Tien" sort="Tu, Yin Tien" uniqKey="Tu Y" first="Yin-Tien" last="Tu">Yin-Tien Tu</name>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:B565160A87E511684422B53594B5BC62A067B109</idno>
<date when="1998" year="1998">1998</date>
<idno type="doi">10.1016/S0031-3203(97)00143-X</idno>
<idno type="url">https://api.istex.fr/document/B565160A87E511684422B53594B5BC62A067B109/fulltext/pdf</idno>
<idno type="wicri:Area/Istex/Corpus">000880</idno>
<idno type="wicri:Area/Istex/Curation">000870</idno>
<idno type="wicri:Area/Istex/Checkpoint">001649</idno>
<idno type="wicri:doubleKey">0031-3203:1998:Fan K:classification:of:machine</idno>
<idno type="wicri:Area/Main/Merge">002262</idno>
<idno type="wicri:Area/Main/Curation">002145</idno>
<idno type="wicri:Area/Main/Exploration">002145</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title level="a">CLASSIFICATION OF MACHINE-PRINTED AND HANDWRITTEN TEXTS USING CHARACTER BLOCK LAYOUT VARIANCE</title>
<author><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name>
<affiliation wicri:level="1"><country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Institute of Computer Science and Information Engineering, National Central University, Chung-Li, Taiwan</wicri:regionArea>
<wicri:noRegion>Taiwan</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Wang, Liang Shen" sort="Wang, Liang Shen" uniqKey="Wang L" first="Liang-Shen" last="Wang">Liang-Shen Wang</name>
<affiliation wicri:level="1"><country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Institute of Computer Science and Information Engineering, National Central University, Chung-Li, Taiwan</wicri:regionArea>
<wicri:noRegion>Taiwan</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Tu, Yin Tien" sort="Tu, Yin Tien" uniqKey="Tu Y" first="Yin-Tien" last="Tu">Yin-Tien Tu</name>
<affiliation wicri:level="1"><country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Institute of Computer Science and Information Engineering, National Central University, Chung-Li, Taiwan</wicri:regionArea>
<wicri:noRegion>Taiwan</wicri:noRegion>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series><title level="j">Pattern Recognition</title>
<title level="j" type="abbrev">PR</title>
<idno type="ISSN">0031-3203</idno>
<imprint><publisher>ELSEVIER</publisher>
<date type="published" when="1997">1997</date>
<biblScope unit="volume">31</biblScope>
<biblScope unit="issue">9</biblScope>
<biblScope unit="page" from="1275">1275</biblScope>
<biblScope unit="page" to="1284">1284</biblScope>
</imprint>
<idno type="ISSN">0031-3203</idno>
</series>
<idno type="istex">B565160A87E511684422B53594B5BC62A067B109</idno>
<idno type="DOI">10.1016/S0031-3203(97)00143-X</idno>
<idno type="PII">S0031-3203(97)00143-X</idno>
</biblStruct>
</sourceDesc>
<seriesStmt><idno type="ISSN">0031-3203</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass></textClass>
<langUsage><language ident="en">en</language>
</langUsage>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Machine-printed and handwritten texts always intermixedly appear in several kinds of documents, such as form documents. The classification of machine-printed and handwritten texts is thus a prerequisite to facilitate later optical character recognition task. In this paper, we will present a machine-printed and handwritten text classification method to automatically identify the identity of texts segmented from a document image. In our approach, the orientation of a text block is first divided into horizontal or vertical direction by analyzing the widths of valleys of X and Y projection profiles of a text block image. Then, a reduced X–Y cut algorithm is utilized to obtain the base blocks from a text block image. Last, the spatial feature, character block layout variance, is devised to achieve the classification goal. Our method can be applied to either English or Chinese document images. Experimental results reveal the feasibility of our proposed method in classifying handwritten and machine-printed texts.</div>
</front>
</TEI>
<affiliations><list><country><li>République populaire de Chine</li>
</country>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name>
</noRegion>
<name sortKey="Tu, Yin Tien" sort="Tu, Yin Tien" uniqKey="Tu Y" first="Yin-Tien" last="Tu">Yin-Tien Tu</name>
<name sortKey="Wang, Liang Shen" sort="Wang, Liang Shen" uniqKey="Wang L" first="Liang-Shen" last="Wang">Liang-Shen Wang</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 002145 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 002145 | 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:B565160A87E511684422B53594B5BC62A067B109 |texte= CLASSIFICATION OF MACHINE-PRINTED AND HANDWRITTEN TEXTS USING CHARACTER BLOCK LAYOUT VARIANCE }}
This area was generated with Dilib version V0.6.32. |