OcrV1, PubMed, Corpus, bibRecord, 000065

Texture for script identification.

Identifieur interne : 000065 ( PubMed/Corpus ); précédent : 000064; suivant : 000066

Texture for script identification.

Auteurs : Andrew Busch ; Wageeh W. Boles ; Sridha Sridharan

Source :

IEEE transactions on pattern analysis and machine intelligence [ 0162-8828 ] ; 2005.

RBID : pubmed:16285372

English descriptors

KwdEn :
- Algorithms, Artificial Intelligence, Automatic Data Processing (methods), Documentation (methods), Handwriting, Image Enhancement (methods), Image Interpretation, Computer-Assisted (methods), Information Storage and Retrieval (methods), Models, Statistical, Numerical Analysis, Computer-Assisted, Pattern Recognition, Automated (methods), Reading, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Subtraction Technique.
MESH :
- methods : Automatic Data Processing, Documentation, Image Enhancement, Image Interpretation, Computer-Assisted, Information Storage and Retrieval, Pattern Recognition, Automated.
- Algorithms, Artificial Intelligence, Handwriting, Models, Statistical, Numerical Analysis, Computer-Assisted, Reading, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Subtraction Technique.

Abstract

The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.

DOI: 10.1109/TPAMI.2005.227
PubMed: 16285372

Links to Exploration step

pubmed:16285372

Le document en format XML

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<affiliation><nlm:affiliation>School of Microelectronic Engineering, Griffith University Nathan Campus, QLD, Australia. a.busch@griffith.edu.au</nlm:affiliation>
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<author><name sortKey="Boles, Wageeh W" sort="Boles, Wageeh W" uniqKey="Boles W" first="Wageeh W" last="Boles">Wageeh W. Boles</name>
</author>
<author><name sortKey="Sridharan, Sridha" sort="Sridharan, Sridha" uniqKey="Sridharan S" first="Sridha" last="Sridharan">Sridha Sridharan</name>
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<term>Information Storage and Retrieval</term>
<term>Pattern Recognition, Automated</term>
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<keywords scheme="MESH" xml:lang="en"><term>Algorithms</term>
<term>Artificial Intelligence</term>
<term>Handwriting</term>
<term>Models, Statistical</term>
<term>Numerical Analysis, Computer-Assisted</term>
<term>Reading</term>
<term>Reproducibility of Results</term>
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<front><div type="abstract" xml:lang="en">The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.</div>
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<Title>IEEE transactions on pattern analysis and machine intelligence</Title>
<ISOAbbreviation>IEEE Trans Pattern Anal Mach Intell</ISOAbbreviation>
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<ArticleTitle>Texture for script identification.</ArticleTitle>
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<Abstract><AbstractText>The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.</AbstractText>
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<MeshHeading><DescriptorName MajorTopicYN="N" UI="D011932">Reading</DescriptorName>
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<MeshHeading><DescriptorName MajorTopicYN="N" UI="D012680">Sensitivity and Specificity</DescriptorName>
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<MeshHeading><DescriptorName MajorTopicYN="N" UI="D012815">Signal Processing, Computer-Assisted</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName MajorTopicYN="N" UI="D013382">Subtraction Technique</DescriptorName>
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Texture for script identification.

Texture for script identification.

Source :

English descriptors

Abstract

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki