Extraction of type style-based meta-information from imaged documents
Identifieur interne : 001C03 ( Main/Exploration ); précédent : 001C02; suivant : 001C04Extraction of type style-based meta-information from imaged documents
Auteurs : Bidyut Baran Chaudhuri [Inde] ; U. Garain [Inde]Source :
- International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2001.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Hypertexte.
English descriptors
- KwdEn :
Abstract
Extraction of some meta-information from printed documents without carrying out optical character recognition (OCR) is considered. It can be statistically verified that important terms in technical articles are mainly printed in italic, bold, and all-capital style. A quick approach to detecting them is proposed here. This approach is based on the global shape heuristics of these styles of any font. Important words in a document are sometimes printed in larger size as well. A smart approach for the determination of font size is also presented. Detection of type styles helps in improving OCR performance, especially for reading italicized text. Another advantage to identifying word type styles and font size has been discussed in the context of extracting: (i) different logical labels: and (ii) important terms from the document. Experimental results on the performance of the approach on a large number of good quality, as well as degraded, document images are presented.
Affiliations:
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Le document en format XML
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<term>Information extraction</term>
<term>Information retrieval</term>
<term>Intelligent system</term>
<term>Measurement method</term>
<term>Optical character recognition</term>
<term>Pattern recognition</term>
<term>Performance evaluation</term>
<term>Printed character</term>
<term>Statistical analysis</term>
<term>Text</term>
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<term>Reconnaissance forme</term>
<term>Système intelligent</term>
<term>Méthode mesure</term>
<term>Evaluation performance</term>
<term>Caractère imprimé</term>
<term>Texte</term>
<term>Méthode heuristique</term>
<term>Analyse statistique</term>
<term>Reconnaissance optique caractère</term>
<term>Recherche information</term>
<term>Extraction information</term>
<term>Hypertexte</term>
<term>Métainformation</term>
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<front><div type="abstract" xml:lang="en">Extraction of some meta-information from printed documents without carrying out optical character recognition (OCR) is considered. It can be statistically verified that important terms in technical articles are mainly printed in italic, bold, and all-capital style. A quick approach to detecting them is proposed here. This approach is based on the global shape heuristics of these styles of any font. Important words in a document are sometimes printed in larger size as well. A smart approach for the determination of font size is also presented. Detection of type styles helps in improving OCR performance, especially for reading italicized text. Another advantage to identifying word type styles and font size has been discussed in the context of extracting: (i) different logical labels: and (ii) important terms from the document. Experimental results on the performance of the approach on a large number of good quality, as well as degraded, document images are presented.</div>
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