A SVM Greek character recogniser
by Francesco Camastra
International Journal of Intelligent Defence Support Systems (IJIDSS), Vol. 1, No. 4, 2008

Abstract: This paper presents a handwritten Greek character recogniser based on Support Vector Machines (SVMs). The recogniser is composed of two modules: the first one is a feature extractor, the second one, the classifier, is performed by means of SVMs. The recogniser, 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 Quantisation (LVQ) and Multi-layer Perceptron (MLP).

Online publication date: Sat, 09-May-2009

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