OcrV1, PascalFrancis, Curation, bibRecord, 000067

Extraction of type style-based meta-information from imaged documents

Identifieur interne : 000067 ( PascalFrancis/Curation ); précédent : 000066; suivant : 000068

Extraction of type style-based meta-information from imaged documents

Auteurs : B. B. Chaudhuri [Inde] ; U. Garain [Inde]

Source :

International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2001.

RBID : Pascal:01-0203316

Descripteurs français

Pascal (Inist)
- Reconnaissance caractère, Reconnaissance forme, Système intelligent, Méthode mesure, Evaluation performance, Caractère imprimé, Texte, Méthode heuristique, Analyse statistique, Reconnaissance optique caractère, Recherche information, Extraction information, Hypertexte, Métainformation.
Wicri :
- topic : Hypertexte.

English descriptors

KwdEn :
- Character recognition, Heuristic method, Hypertext, Information extraction, Information retrieval, Intelligent system, Measurement method, Optical character recognition, Pattern recognition, Performance evaluation, Printed character, Statistical analysis, Text.

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.

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A03		`1`		`@0 Int. j. doc. anal. recognit. : (Print)`
A05				`@2 3`
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A08	`01`	`1`	`ENG`	`@1 Extraction of type style-based meta-information from imaged documents`
A11	`01`	`1`		`@1 CHAUDHURI (B. B.)`
A11	`02`	`1`		`@1 GARAIN (U.)`
A14	`01`			`@1 Computer Vision & Pattern Recognition Unit, Indian Statistical Institute, 203 B.T. Road @2 Calcutta 700 035 @3 IND @Z 1 aut. @Z 2 aut.`
A20				`@1 138-149`
A21				`@1 2001`
A23	`01`			`@0 ENG`
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A44				`@0 0000 @1 © 2001 INIST-CNRS. All rights reserved.`
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A64	`01`	`1`		`@0 International journal on document analysis and recognition : (Print)`
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C01	`01`		`ENG`	@0 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.
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C03	`02`	`X`	`ENG`	`@0 Pattern recognition @5 02`
C03	`02`	`X`	`SPA`	`@0 Reconocimiento patrón @5 02`
C03	`03`	`X`	`FRE`	`@0 Système intelligent @5 03`
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C03	`06`	`X`	`FRE`	`@0 Caractère imprimé @5 06`
C03	`06`	`X`	`ENG`	`@0 Printed character @5 06`
C03	`06`	`X`	`SPA`	`@0 Carácter impreso @5 06`
C03	`07`	`X`	`FRE`	`@0 Texte @5 07`
C03	`07`	`X`	`ENG`	`@0 Text @5 07`
C03	`07`	`X`	`SPA`	`@0 Texto @5 07`
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C03	`08`	`X`	`ENG`	`@0 Heuristic method @5 08`
C03	`08`	`X`	`SPA`	`@0 Método heurístico @5 08`
C03	`09`	`X`	`FRE`	`@0 Analyse statistique @5 09`
C03	`09`	`X`	`ENG`	`@0 Statistical analysis @5 09`
C03	`09`	`X`	`SPA`	`@0 Análisis estadístico @5 09`
C03	`10`	`X`	`FRE`	`@0 Reconnaissance optique caractère @5 10`
C03	`10`	`X`	`ENG`	`@0 Optical character recognition @5 10`
C03	`10`	`X`	`SPA`	`@0 Reconocimento óptico de caracteres @5 10`
C03	`11`	`X`	`FRE`	`@0 Recherche information @5 11`
C03	`11`	`X`	`ENG`	`@0 Information retrieval @5 11`
C03	`11`	`X`	`SPA`	`@0 Recuperación información @5 11`
C03	`12`	`X`	`FRE`	`@0 Extraction information @5 12`
C03	`12`	`X`	`ENG`	`@0 Information extraction @5 12`
C03	`12`	`X`	`SPA`	`@0 Extractión información @5 12`
C03	`13`	`X`	`FRE`	`@0 Hypertexte @5 13`
C03	`13`	`X`	`ENG`	`@0 Hypertext @5 13`
C03	`13`	`X`	`SPA`	`@0 Hipertexto @5 13`
C03	`14`	`X`	`FRE`	`@0 Métainformation @4 INC @5 82`
N21				`@1 141`

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Le document en format XML

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Extraction of type style-based meta-information from imaged documents

Extraction of type style-based meta-information from imaged documents

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Descripteurs français

English descriptors

Abstract

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Links to Exploration step

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