OcrV1, Main, Exploration, bibRecord, 000A97

A probabilistic method for keyword retrieval in handwritten document images

Identifieur interne : 000A97 ( Main/Exploration ); précédent : 000A96; suivant : 000A98

A probabilistic method for keyword retrieval in handwritten document images

Auteurs : HUAIGU CAO [États-Unis] ; Anurag Bhardwaj [États-Unis] ; Venugopal Govindaraju [États-Unis]

Source :

Pattern recognition [ 0031-3203 ] ; 2009.

RBID : Pascal:09-0430764

Descripteurs français

Pascal (Inist)
- Approche probabiliste, Mot clé, Caractère manuscrit, Traitement image document, Reconnaissance écriture, Lexique, Reconnaissance optique caractère, Méthode alternative, Modélisation, Segmentation, Algorithme, Recherche information, Traitement image, Reconnaissance forme.

English descriptors

KwdEn :
- Algorithm, Alternative method, Document image processing, Handwriting recognition, Image processing, Information retrieval, Keyword, Lexicon, Manuscript character, Modeling, Optical character recognition, Pattern recognition, Probabilistic approach, Segmentation.

Abstract

Keyword retrieval in handwritten document images is a challenging task because handwriting recognition does not perform adequately to produce the transcriptions, specially when using large lexicons. Existing methods build indices using OCR distances or image features for the purpose of retrieval. These alternative methods are complimentary to the traditional approaches that build indices on OCR'ed text. In this paper, we describe an improvement to the existing keyword retrieval (word spotting) methods by modeling imperfect word segmentation as probabilities and integrating these probabilities into the word spotting algorithm. The scores returned by the word recognizer are also converted into probabilities and integrated into the probabilistic word spotting model.

Affiliations:

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

to stream PascalFrancis, to step Corpus: 000211
to stream PascalFrancis, to step Curation: 000568
to stream PascalFrancis, to step Checkpoint: 000214
to stream Main, to step Merge: 000B08
to stream Main, to step Curation: 000A97

Le document en format XML

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<front><div type="abstract" xml:lang="en">Keyword retrieval in handwritten document images is a challenging task because handwriting recognition does not perform adequately to produce the transcriptions, specially when using large lexicons. Existing methods build indices using OCR distances or image features for the purpose of retrieval. These alternative methods are complimentary to the traditional approaches that build indices on OCR'ed text. In this paper, we describe an improvement to the existing keyword retrieval (word spotting) methods by modeling imperfect word segmentation as probabilities and integrating these probabilities into the word spotting algorithm. The scores returned by the word recognizer are also converted into probabilities and integrated into the probabilistic word spotting model.</div>
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A probabilistic method for keyword retrieval in handwritten document images

A probabilistic method for keyword retrieval in handwritten document images

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