ABSTRACT This paper presents a handwritten Greek character recognizer based on Support Vector Machines (SVMs) . The recognizer is composed of two modules: the first one is a feature extractor, the second one, the classifier, is performed by means of SVMs. The recognizer, tested on a database of more than 22000 handwritten Greek characters, has shown satisfactory performances. SVMs compare notably better, in terms of recognition rates, with popular neural classifiers, such as Learning Vector Quantization and Multi-layer Perceptron.

A SVM GREEK CHARACTER RECOGNISER

CAMASTRA, Francesco
2008

Abstract

ABSTRACT This paper presents a handwritten Greek character recognizer based on Support Vector Machines (SVMs) . The recognizer is composed of two modules: the first one is a feature extractor, the second one, the classifier, is performed by means of SVMs. The recognizer, tested on a database of more than 22000 handwritten Greek characters, has shown satisfactory performances. SVMs compare notably better, in terms of recognition rates, with popular neural classifiers, such as Learning Vector Quantization and Multi-layer Perceptron.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/19095
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