Cursive character recognition by learning vector quantization

Camastra, F. and Vinciarelli, A. (2001) Cursive character recognition by learning vector quantization. Pattern Recognition Letters, 22(6-7), pp. 625-629. (doi:10.1016/S0167-8655(01)00008-3)

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Publisher's URL: http://dx.doi.org/10.1016/S0167-8655(01)00008-3

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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vinciarelli, Professor Alessandro
Authors: Camastra, F., and Vinciarelli, A.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Pattern Recognition Letters
Publisher:Elsevier BV
ISSN:0167-8655
ISSN (Online):1872-7344
Published Online:11 April 2001

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