东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2012, Vol. 33 ›› Issue (5): 613-617.DOI: -

• 论著 • 上一篇    下一篇

基于核主元分析和局部保持投影的手背静脉识别

刘晶;薛定宇;崔建江;贾旭;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(61174145)

Palm-dorsa vein recognition based on kernel principal component analysis and locality preserving projection methods

Liu, Jing (1); Xue, Ding-Yu (1); Cui, Jian-Jiang (1); Jia, Xu (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Liu, J.
  • About author:-
  • Supported by:
    -

RichHTML

0

PDF (PC)

763

摘要： 为了保持手背静脉空间的局部结构,运用局部保持投影(LPP)方法进行手背静脉识别.但是对于小样本图像识别,LPP中的特征方程矩阵通常存在奇异性.为了解决这个问题,提出首先利用核主元分析(KPCA)降低手背静脉空间的维数,再对低维图像应用LPP提取局部特征.对已有手背静脉图像库进行测试,实验结果表明,与传统的PCA和PCA+LPP相比,该方法大大提高了系统的识别率,而且特征提取时间为2.6 s,满足实时系统的要求.

关键词: 手背静脉识别, 局部保持投影, 主成分分析, 核主成分分析, 流形

Abstract: In order to preserve the local structure of the palm-dorsa vein space, locality preserving projection (LPP) was applied to palm-dorsa vein recognition. In small-sized sample cases such as image recognition, the matrix of the eigenvalue equation is usually singular. To solve the problem, kernal principal component analysis (KPCA) method was presented to reduce the palm-dorsa vein space dimensions. Then LPP was used to extract the local features. The algorithm was tested in the existing palm-dorsa vein database. The results showed that the new method has much higher recognition rate and the feature extraction time is 2.6 s, so it satisfies the real-time system specifications.

中图分类号: