OcrV1, Main, Exploration, bibRecord, 002027

The bible, truth, and multilingual OCR evaluation

Identifieur interne : 002027 ( Main/Exploration ); précédent : 002026; suivant : 002028

The bible, truth, and multilingual OCR evaluation

Auteurs : T. Kanungo [États-Unis, Japon] ; P. Resnik [Japon, États-Unis]

Source :

SPIE proceedings series [ 1017-2653 ] ; 1999.

RBID : Pascal:99-0297905

Descripteurs français

Pascal (Inist)
- Traitement image document, Reconnaissance optique caractère, Reconnaissance forme, Recherche documentaire, Analyse documentaire, Multilinguisme.
Wicri :
- topic : Recherche documentaire, Multilinguisme.

English descriptors

KwdEn :
- Document analysis, Document image processing, Document retrieval, Multilingualism, Optical character recognition, Pattern recognition.

Abstract

Multilingual OCR has emerged as an important information technology, thanks to the increasing need for cross-language information access. While many research groups and companies have developed OCR algorithms for various languages, it is difficult to compare the performance of these OCR algorithms across languages. This difficulty arises because most evaluation methodologies rely on the use of a document image dataset in each of these languages and it is difficult to find document datasets in different languages that are similar in content, layout, and fonts. In this paper we propose to use the Bible as a dataset for comparing OCR accuracy across languages. Besides being available in a wide range of languages Bible translations are closely parallel in content, carefully translated, surprisingly relevant with respect to modern-day language, and quite inexpensive. A project at University of Maryland is currently implementing this idea. We have created a scanned image dataset with groundtruth from an Arabic Bible. We have also used image degradation models to create synthetically degraded images of a French Bible. We hope to generate similar Bible datasets for other languages, and we are exploring alternative corpora with similar properties such the Koran and the Bhagavad Gita. Quantitative OCR evaluation based on the Arabic Bible dataset is currently in progress.

Affiliations:

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

to stream PascalFrancis, to step Corpus: 000821
to stream PascalFrancis, to step Curation: 000B73
to stream PascalFrancis, to step Checkpoint: 000755
to stream Main, to step Merge: 002136
to stream Main, to step Curation: 002027

Le document en format XML

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<front><div type="abstract" xml:lang="en">Multilingual OCR has emerged as an important information technology, thanks to the increasing need for cross-language information access. While many research groups and companies have developed OCR algorithms for various languages, it is difficult to compare the performance of these OCR algorithms across languages. This difficulty arises because most evaluation methodologies rely on the use of a document image dataset in each of these languages and it is difficult to find document datasets in different languages that are similar in content, layout, and fonts. In this paper we propose to use the Bible as a dataset for comparing OCR accuracy across languages. Besides being available in a wide range of languages Bible translations are closely parallel in content, carefully translated, surprisingly relevant with respect to modern-day language, and quite inexpensive. A project at University of Maryland is currently implementing this idea. We have created a scanned image dataset with groundtruth from an Arabic Bible. We have also used image degradation models to create synthetically degraded images of a French Bible. We hope to generate similar Bible datasets for other languages, and we are exploring alternative corpora with similar properties such the Koran and the Bhagavad Gita. Quantitative OCR evaluation based on the Arabic Bible dataset is currently in progress.</div>
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The bible, truth, and multilingual OCR evaluation

The bible, truth, and multilingual OCR evaluation

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