Cursive Character Recognition by Learning Vector Quantization
Camastra, Francesco; Vinciarelli, Alessandro
2000

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Résumé

This paper presents a cursive character recognizer embedded in an off-line cursive script recognition system. The recognizer is composed of two modules: the first one is a feature extractor, the second one an LVQ. The selected feature set was compared to Zernike polynomials using the same classifier. Experiments are reported on a database of about 49000 isolated characters.

Détails

Titre Cursive Character Recognition by Learning Vector Quantization
Auteur(s) Camastra, Francesco ; Vinciarelli, Alessandro
Date 2000
Editeur IDIAP
Mots-clés (libres)
Note Accepted for publication by Pattern Recognition Letters
Lien supplémentaire URL
Laboratoires LIDIAP
Le document apparaît dans Production scientifique et compétences > STI - Faculté des sciences et techniques de l'ingénieur > IEM - Institute of Electrical and Micro Engineering > LIDIAP - Laboratoire de l'IDIAP
Production scientifique et compétences > Euler Center for Signal Processing
Travail produit à l'EPFL
Rapports techniques
Publié
Date de création de la notice 2006-03-10

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