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Using typography in document image analysis

Identifieur interne : 000150 ( Istex/Corpus ); précédent : 000149; suivant : 000151

Using typography in document image analysis

Auteurs : Frédéric Bapst ; Rolf Ingold

Source :

RBID : ISTEX:1C19DB348F74414008B94DB97A375E3E1847F087

Abstract

Abstract: Even if font usage plays an important role in Document Image Analysis (DIA), recognition systems generally take the concept of font management in a weaker sense than in the production cycle. With the point of view of the document recognition community, we show how typographic information (characters bitmap, metrics, etc.) can improve existing analysis methods. After a brief survey of font recognition issues, we present the advantages of a font software support in the design of recognition systems. Concrete algorithms are proposed in the subtopics of a posteriori font recognition, monofont Optical Character Recognition (OCR), and word segmentation. The reported experiments and results indicate that there are still substantial benefits to expect from the design of typographyaware analyzers.

Url:
DOI: 10.1007/BFb0053274

Links to Exploration step

ISTEX:1C19DB348F74414008B94DB97A375E3E1847F087

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<abstract lang="en">Abstract: Even if font usage plays an important role in Document Image Analysis (DIA), recognition systems generally take the concept of font management in a weaker sense than in the production cycle. With the point of view of the document recognition community, we show how typographic information (characters bitmap, metrics, etc.) can improve existing analysis methods. After a brief survey of font recognition issues, we present the advantages of a font software support in the design of recognition systems. Concrete algorithms are proposed in the subtopics of a posteriori font recognition, monofont Optical Character Recognition (OCR), and word segmentation. The reported experiments and results indicate that there are still substantial benefits to expect from the design of typographyaware analyzers.</abstract>
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