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 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. © 2001 Elsevier Science B.V. All rights reserved.
Cursive Character Recognition by Learning Vector Quantization
CAMASTRA, Francesco;
2001-01-01
Abstract
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 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. © 2001 Elsevier Science B.V. All rights reserved.File in questo prodotto:
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