InforLorV4, Main, Exploration, bibRecord, 008818

Cross-learning in analytic word recognition without segmentation

Identifieur interne : 008818 ( Main/Exploration ); précédent : 008817; suivant : 008819

Cross-learning in analytic word recognition without segmentation

Auteurs : C. Choisy ; Abdel Belaïd [France]

Source :

International Journal on Document Analysis and Recognition [ 1433-2833 ] ; 2002-07-01.

RBID : ISTEX:55280B7BF363C76D9234E01C9077401C57C89EEB

Descripteurs français

Pascal (Inist)
- Causalité, Lettre alphabet, Modèle Markov caché, Mot, Métamodèle, Processus Markov, Reconnaissance caractère, Segmentation, Traitement image.

English descriptors

KwdEn :
- Causality, Character recognition, Hidden Markov model, Image processing, Key words:hmm, nshp-hmm, Cross-learning, Meta-models, Baum-Welch Algorithm, Letter, Markov process, Metamodel, Segmentation, Word.
mix :
- baum algorithm, cross-learning, hmm, meta-models, nshp.

Abstract

Abstract.: In this paper a method for analytic handwritten word recognition based on causal Markov random fields is described. The word models are hmms where each state corresponds to a letter modeled by a nshp-hmm (Markov field). The word models are built dynamically. Training is operated using Baum-Welch algorithm where the parameters are reestimated on the generated word models. The segmentation is unnecessary: the system determines itself during training the best repartition of the information within the letter models. First experiments on two real databases of French check amount words give very encouraging results up to 86% for recognition without rejection.

Url:

DOI: 10.1007/s100320200078

Affiliations:

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Serveur d'exploration sur la recherche en informatique en Lorraine

Cross-learning in analytic word recognition without segmentation

Cross-learning in analytic word recognition without segmentation

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

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