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Titolo:
Cursive character recognition by learning vector quantization
Autore:
Camastra, F; Vinciarelli, A;
Indirizzi:
Epsag Spa, I-16154 Genoa, Italy Epsag Spa Genoa Italy I-16154Epsag Spa, I-16154 Genoa, Italy IDIAP, Inst Dalle Molle Intelligence Artif Percept, CH-1920 Martigny, Switzerland IDIAP Martigny Switzerland CH-1920 ercept, CH-1920 Martigny, Switzerland
Titolo Testata:
PATTERN RECOGNITION LETTERS
fascicolo: 6-7, volume: 22, anno: 2001,
pagine: 625 - 629
SICI:
0167-8655(200105)22:6-7<625:CCRBLV>2.0.ZU;2-4
Fonte:
ISI
Lingua:
ENG
Soggetto:
HANDWRITTEN;
Keywords:
cursive character recognition; feature extraction; cross-validation; learning vector quantization;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
12
Recensione:
Indirizzi per estratti:
Indirizzo: Camastra, F Epsag Spa, Via Puccini 2, I-16154 Genoa, Italy Epsag Spa Via Puccini 2 Genoa Italy I-16154 6154 Genoa, Italy
Citazione:
F. Camastra e A. Vinciarelli, "Cursive character recognition by learning vector quantization", PATT REC L, 22(6-7), 2001, pp. 625-629

Abstract

This paper presents a cursive character recognizer embedded in an off-linecursive script recognition system. The recognizer is composed of two modules: the first one is a feature extractor, the second one a learning vector quantizer. The selected feature set was compared to Zernike polynomials using the same classifier. Experiments are reported on a database of about 49,000 isolated characters. (C) 2001 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 04/04/20 alle ore 12:31:26