OcrV1, Main, Exploration, bibRecord, 002863

Validation of image defect models for optical character recognition

Identifieur interne : 002863 ( Main/Exploration ); précédent : 002862; suivant : 002864

Validation of image defect models for optical character recognition

Auteurs : Y. Li [États-Unis] ; D. Lopresti ; George Nagy (informaticien) [États-Unis] ; A. Tomkins

Source :

IEEE Transactions on Pattern Analysis and Machine Intelligence [ 0162-8828 ] ; 1996.

RBID : Pascal:96-0139394

Descripteurs français

Pascal (Inist)
- Théorie, Traitement image, Structure donnée, Distorsion signal, Calcul erreur, Balayage, Logiciel, Simulation ordinateur, Système reconnaissance forme, Reconnaissance optique caractère.
Wicri :
- topic : Logiciel.

English descriptors

KwdEn :
- Character image generators, Computer simulation, Computer software, Data structures, Defect model validation, Error analysis, Error classification, Image defect models, Image processing, Optical character recognition, Pattern recognition systems, Real scanned documents, Scanning, Signal distortion, Theory.

Abstract

In this paper, we consider the problem of evaluating character image generators that model distortions encountered in optical character recognition (OCR). While a number of such defect models have been proposed, the contention that they produce the desired result is typically argued in an ad hoc and informal way. We introduce a rigorous and more pragmatic definition of when a model is accurate: we say a defect model is validated if the OCR errors induced by the model are indistinguishable from the errors encountered when using real scanned documents. We describe four measures to quantify this similarity, and compare and contrast them using over ten million scanned and synthesized characters in three fonts. The measures differentiate effectively between different fonts and different scans of the same font regardless of the underlying text.

Affiliations:

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: 000A17
to stream PascalFrancis, to step Curation: 000981
to stream PascalFrancis, to step Checkpoint: 000921
to stream Main, to step Merge: 002A08
to stream Main, to step Curation: 002863

Le document en format XML

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<author><name sortKey="Li, Y" sort="Li, Y" uniqKey="Li Y" first="Y." last="Li">Y. Li</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>GARI Software</s1>
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<country>États-Unis</country>
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<author><name sortKey="Lopresti, D" sort="Lopresti, D" uniqKey="Lopresti D" first="D." last="Lopresti">D. Lopresti</name>
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<author><name sortKey="Nagy, G" sort="Nagy, G" uniqKey="Nagy G" first="G." last="Nagy">George Nagy (informaticien)</name>
<affiliation><country>États-Unis</country>
<placeName><settlement type="city">Troy (New York</settlement>
<region type="state">État de New York</region>
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<orgName type="lab" n="5">Institut polytechnique Rensselaer</orgName>
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<author><name sortKey="Tomkins, A" sort="Tomkins, A" uniqKey="Tomkins A" first="A." last="Tomkins">A. Tomkins</name>
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<series><title level="j" type="main">IEEE Transactions on Pattern Analysis and Machine Intelligence</title>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Character image generators</term>
<term>Computer simulation</term>
<term>Computer software</term>
<term>Data structures</term>
<term>Defect model validation</term>
<term>Error analysis</term>
<term>Error classification</term>
<term>Image defect models</term>
<term>Image processing</term>
<term>Optical character recognition</term>
<term>Pattern recognition systems</term>
<term>Real scanned documents</term>
<term>Scanning</term>
<term>Signal distortion</term>
<term>Theory</term>
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<keywords scheme="Pascal" xml:lang="fr"><term>Théorie</term>
<term>Traitement image</term>
<term>Structure donnée</term>
<term>Distorsion signal</term>
<term>Calcul erreur</term>
<term>Balayage</term>
<term>Logiciel</term>
<term>Simulation ordinateur</term>
<term>Système reconnaissance forme</term>
<term>Reconnaissance optique caractère</term>
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<front><div type="abstract" xml:lang="en">In this paper, we consider the problem of evaluating character image  generators that model distortions encountered in optical character recognition (OCR).  While a number of such defect models have been proposed, the contention that they produce the desired result is typically argued in an ad hoc and informal way.  We introduce a rigorous and more pragmatic definition of when a model is accurate: we say a defect model is validated if the OCR errors induced by the model are indistinguishable from the errors encountered when using real scanned documents.  We describe four measures to quantify this similarity, and compare and contrast them using over ten million scanned and synthesized characters in three fonts.  The measures differentiate effectively between different fonts and different scans of the same font regardless of the underlying text.</div>
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<country name="États-Unis"><region name="Géorgie (États-Unis)"><name sortKey="Li, Y" sort="Li, Y" uniqKey="Li Y" first="Y." last="Li">Y. Li</name>
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<name sortKey="Nagy, G" sort="Nagy, G" uniqKey="Nagy G" first="G." last="Nagy">George Nagy (informaticien)</name>
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   |texte=   Validation of image defect models for optical character recognition
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Validation of image defect models for optical character recognition

Validation of image defect models for optical character recognition

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri