信息与控制2016，Vol.45Issue(2)：193-198,6.DOI:10.13976/j.cnki.xk.2016.0193
基于改进非负矩阵分解的手背静脉识别算法
Dorsal Hand Vein Recognition Algorithm Based on Improved Nonnegative Matrix Factorization
摘要
Abstract
To enhance feature effectiveness during hand dorsal vein recognition,we propose a new recognition algo-rithm based on improved nonnegative matrix factorization (NMF ).Firstly,after dividing vein image into blocks,we use the mean and the average gradient amplitude of sub-image as image original features.Second-ly,we apply NMF in the feature matrix which is formed by combining the original feature vectors of all train-ing samples,where the coefficient vectors are imposed by sparse and discriminant constraints,and the im-proved NMF model can be acquired.Thirdly,we use a projected gradient method to solve the NMF model, and new feature basis and feature vectors are obtained.Finally,new feature vectors are classified by K-nea-rest neighbour (KNN),and the vein object is identified successfully.Experiment results show that the pro-posed algorithm has high correct recognition rate and good real-time performance.关键词
非负矩阵分解/静脉识别/特征提取/梯度投影法Key words
nonnegative matrix factorization/vein recognition/feature extraction/projected gradient method分类
信息技术与安全科学引用本文复制引用
贾旭,崔建江,孙福明,曹玉东..基于改进非负矩阵分解的手背静脉识别算法[J].信息与控制,2016,45(2):193-198,6.基金项目
国家自然科学基金资助项目 （）
