Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (22): 189-191.DOI: 10.3778/j.issn.1002-8331.2008.22.056

• 图形、图像、模式识别 • Previous Articles     Next Articles

Palmprint recognition based on Gabor wavelet transform and optimal discriminant features

LI Yun-feng,SHANG Zhen-dong   

  1. College of Electromechanical Engineering,Henan University of Technology,Luoyang,Henan 471003,China
  • Received:2007-10-11 Revised:2008-01-11 Online:2008-07-11 Published:2008-07-11
  • Contact: LI Yun-feng



  1. 河南科技大学 机电工程学院,河南 洛阳 471003
  • 通讯作者: 李云峰

Abstract: A feature extraction method for palmprint image is proposed,the implementation procedure of this method is as follows:firstly,the 2D Gabor wavelet transform coefficient amplitudes are computed at the equispaced discrete positions on the palmprint image,and they are used as original features of the palmprint image;then,the dimension of the Gabor wavelet feature is reduced by principal component analysis;lastly,the optimal discriminant features that are most advantageous for classification are extracted by linear discriminant analysis.Experimental results show the effectiveness of this method.

Key words: palmprint recognition, Gabor wavelet transform, principal component analysis, linear discriminant analysis

摘要: 提出了一种提取掌纹图像特征的方法,该方法的实现过程如下:首先,计算掌纹图像上均布离散位置的二维Gabor小波变换系数的幅值,将其作为掌纹图像的原始特征;其次,利用主分量分析实现Gabor小波特征的降维;最后,通过线性判别分析提取最有利于分类的最佳鉴别特征。实验结果表明了该方法的有效性。

关键词: 掌纹识别, Gabor小波变换, 主分量分析, 线性判别分析