文章基本信息

标题：Online Handwritten Digit Recognition Using Gaussian Based Classifier
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作者：Manish Vyas ; Prof Amit Singhal ; Prof.Neetesh Gupta 等
期刊名称：International Journal of Computer Technology and Applications
电子版ISSN：2229-6093
出版年度：2012
卷号：3
期号：1
页码：425-430
出版社：Technopark Publications
摘要：Discrete Hidden Markov Model (HMM) and hybrid of Neural Network (NN) and HMM are popular methods in handwritten word recognition system. The hybrid system gives better recognition result due to better discrimination capability of the NN. A major problem in handwriting recognition is the huge variability and distortions of patterns. Elastic models based on local observations and dynamic programming such HMM are not efficient to absorb this variability. But their vision is local. But they cannot face to length variability and they are very sensitive to distortions. Then the SVM is used to estimate global correlations and classify the pattern. Support Vector Machine (SVM) is an alternative to NN. In Handwritten recognition, SVM gives a better recognition result. The aim of this paper is to develop an approach which improve the efficiency of handwritten recognition using artificial neural network
关键词：Handwriting recognition; Support Vector Machine; Neural Network