一个支持向量机希腊字符识别器

Int. J. Intell. Def. Support Syst. Pub Date : 1900-01-01 DOI:10.1504/IJIDSS.2008.025018

F. Camastra

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引用次数: 1

摘要

提出了一种基于支持向量机(svm)的手写体希腊字符识别器。该识别系统由两个模块组成:第一个模块是特征提取器，第二个模块是通过支持向量机实现的分类器。该识别器在超过22000个希腊手写字符的数据库中进行了测试，结果令人满意。在识别率方面，svm与流行的神经分类器(如学习向量量化(LVQ)和多层感知器(MLP))相比明显更好。

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A SVM Greek character recogniser

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).

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Int. J. Intell. Def. Support Syst.

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