OcrV1, Main, Exploration, bibRecord, 000547

Robust Keyword Retrieval Method for OCRed Text

Identifieur interne : 000547 ( Main/Exploration ); précédent : 000546; suivant : 000548

Robust Keyword Retrieval Method for OCRed Text

Auteurs : Yusaku Fujii [Japon] ; Hiroaki Takebe [Japon] ; Hiroshi Tanaka [Japon] ; Yoshinobu Hotta [Japon]

Source :

Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2011.

RBID : Pascal:11-0279163

Descripteurs français

Pascal (Inist)
- Imagerie, Mot clé, Reconnaissance optique caractère, Gestion document, Document électronique, Recherche documentaire, Recherche information, Reconnaissance caractère, Segmentation, Robustesse, 0130C, 4230.
Wicri :
- topic : Document électronique, Recherche documentaire.

English descriptors

KwdEn :
- Character recognition, Document management, Document retrieval, Electronic document, Imagery, Information retrieval, Keyword, Optical character recognition, Robustness, Segmentation.

Abstract

Document management systems have become important because of the growing popularity of electronic filing of documents and scanning of books, magazines, manuals, etc., through a scanner or a digital camera, for storage or reading on a PC or an electronic book. Text information acquired by optical character recognition (OCR) is usually added to the electronic documents for document retrieval. Since texts generated by OCR generally include character recognition errors, robust retrieval methods have been introduced to overcome this problem. In this paper, we propose a retrieval method that is robust against both character segmentation and recognition errors. In the proposed method, the insertion of noise characters and dropping of characters in the keyword retrieval enables robustness against character segmentation errors, and character substitution in the keyword of the recognition candidate for each character in OCR or any other character enables robustness against character recognition errors. The recall rate of the proposed method was 15% higher than that of the conventional method. However, the precision rate was 64% lower.

Affiliations:

Japon

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

to stream PascalFrancis, to step Corpus: 000132
to stream PascalFrancis, to step Curation: 000641
to stream PascalFrancis, to step Checkpoint: 000101
to stream Main, to step Merge: 000553
to stream Main, to step Curation: 000547

Le document en format XML

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<front><div type="abstract" xml:lang="en">Document management systems have become important because of the growing popularity of electronic filing of documents and scanning of books, magazines, manuals, etc., through a scanner or a digital camera, for storage or reading on a PC or an electronic book. Text information acquired by optical character recognition (OCR) is usually added to the electronic documents for document retrieval. Since texts generated by OCR generally include character recognition errors, robust retrieval methods have been introduced to overcome this problem. In this paper, we propose a retrieval method that is robust against both character segmentation and recognition errors. In the proposed method, the insertion of noise characters and dropping of characters in the keyword retrieval enables robustness against character segmentation errors, and character substitution in the keyword of the recognition candidate for each character in OCR or any other character enables robustness against character recognition errors. The recall rate of the proposed method was 15% higher than that of the conventional method. However, the precision rate was 64% lower.</div>
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Serveur d'exploration sur l'OCR

Robust Keyword Retrieval Method for OCRed Text

Robust Keyword Retrieval Method for OCRed Text

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