Character representation of handwritten Arabic numerals based on wavelet analysis and EMD

被引：0

作者：

Li H.-L. ^{[1
]}

Wang W.-B. ^{[2
]}

Zhang G.-X. ^{[1
]}

机构：

[1] Department of Electronic Commerce, South China University of Technology, Guangzhou 510006, Guangdong

[2] Department of Information and Computing Science, Wuhan University of Science and Technology, Wuhan 430065, Hubei

来源：

Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | 2010年 / 38卷 / 06期

关键词：

Curvature; Empirical mode decomposition (EMD); Feature extraction; Wavelet transform;

D O I：

10.3969/j.issn.1000-565X.2010.06.015

中图分类号：

学科分类号：

摘要：

As the empirical mode decomposition (EMD) can accurately recognize the structure of the original signal, this paper proposes a new feature extraction algorithm of handwritten Arabic numerals based on wavelet transform and EMD. In this algorithm, first, smooth contours of numeral image are obtained by preprocessing the maximum module of the G wavelet transform. Then, an EMD analysis is performed to decompose the normalized curvature sequences into their components, which produces more compact curvature features. Finally, the obtained curvature features are clustered and recognized. Experimental results show that the proposed algorithm is superior to the classic feature extraction algorithm in terms of clustering effect and classifier design ability.

引用

页码：78 / 83

页数：5

共 20 条

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