【摘要】 提出了一种基于小波分解和二维主成分分析-二维线性判别式分析(K2DPCA-2DLDA)的手背静脉识别方法,选用db4小波基对原图进行小波分解。对其低频子图进行K2DPCA映射获得低维空间特征,通过对此低维空间特征进行2DLDA变换得到最终特征表达,利用最近邻法则进行了分类。实验结果表明,该方法能提高手背静脉识别率,有效减少识别时间。更多还原

【Abstract】 Dorsal hand vein recognition based on wavelet decomposition and K2DPCA-2DLDA was proposed in this paper,and db4 wavelet was used to decompose the original image.K2DPCA transformation was used for the sub-image of low frequency to obtain low dimensional space characteristics.Then,2DLDA transformation was used to further reduce the dimension for obtaining the final feature expression.Finally,the features were classified according to the nearest neighbor classification rule.The experimental results show that the method can improve the hand dorsal vein recognition rate and reduce the recognition time effectively.更多还原