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

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Defence Support Systems (IJIDSS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com