OcrV1, Main, Exploration, bibRecord, 000D30

An OCR Based Approach for Word Spotting in Devanagari Documents

Identifieur interne : 000D30 ( Main/Exploration ); précédent : 000D29; suivant : 000D31

An OCR Based Approach for Word Spotting in Devanagari Documents

Auteurs : Anurag Bhardwaj [États-Unis] ; Suryaprakash Kompalli [États-Unis] ; Srirangaraj Setlur [États-Unis] ; Venugopal Govindaraju [États-Unis]

Source :

Proceedings electronic imaging science and technology

RBID : Pascal:08-0400006

Descripteurs français

Pascal (Inist)
- Etude expérimentale, Reconnaissance optique caractère, Document imprimé, Similitude, Requête, Reconnaissance parole, Aspect économique, Analyse coût, Traitement image document, Reconnaissance forme, 0130C, 4230S.

English descriptors

KwdEn :
- Cost analysis, Document image processing, Economic aspect, Experimental study, Optical character recognition, Pattern recognition, Printed document, Query, Similarity, Speech recognition.

Abstract

This paper describes an OCR-based technique for word spotting in Devanagari printed documents. The system accepts a Devanagari word as input and returns a sequence of word images that are ranked according to their similarity with the input query. The methodology involves line and word separation, pre-processing document words, word recognition using OCR and similarity matching. We demonstrate a Block Adjacency Graph (BAG) based document cleanup in the pre-processing phase. During word recognition, multiple recognition hypotheses are generated for each document word using a font-independent Devanagari OCR. The similarity matching phase uses a cost based model to match the word input by a user and the OCR results. Experiments are conducted on document images from the publicly available ILT and Million Book Project dataset. The technique achieves an average precision of 80% for 10 queries and 67% for 20 queries for a set of 64 documents containing 5780 word images. The paper also presents a comparison of our method with template-based word spotting techniques.

Affiliations:

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Le document en format XML

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<front><div type="abstract" xml:lang="en">This paper describes an OCR-based technique for word spotting in Devanagari printed documents. The system accepts a Devanagari word as input and returns a sequence of word images that are ranked according to their similarity with the input query. The methodology involves line and word separation, pre-processing document words, word recognition using OCR and similarity matching. We demonstrate a Block Adjacency Graph (BAG) based document cleanup in the pre-processing phase. During word recognition, multiple recognition hypotheses are generated for each document word using a font-independent Devanagari OCR. The similarity matching phase uses a cost based model to match the word input by a user and the OCR results. Experiments are conducted on document images from the publicly available ILT and Million Book Project dataset. The technique achieves an average precision of 80% for 10 queries and 67% for 20 queries for a set of 64 documents containing 5780 word images. The paper also presents a comparison of our method with template-based word spotting techniques.</div>
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An OCR Based Approach for Word Spotting in Devanagari Documents

An OCR Based Approach for Word Spotting in Devanagari Documents

Source :

Descripteurs français

English descriptors

Abstract

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

Le document en format XML

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