Earticle

초록

영어

A new finger vein recognition method based on two-dimensional principal component analysis (2DPCA) and kernel maximum between-class margin criterion (KMMC) is developed. The algorithm includes four stages. Firstly, perform preprocessing steps which include normalizing and mean-filtering on the finger vein images, secondly, employ the 2DPCA to condense the dimension of image vector, thirdly, apply the KMMC to reduce the dimension of training samples further, and finally, take the match and recognition step by computing the Euclidean distance between each sample. Our experimental results indicate that the new method has good recognition effect.

목차

Abstract
 1. Introduction
 2. KMMC Algorithm
 3. Our Algorithm
 4. Experimental Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Lin You [ College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China ]
• Jiawan Wang [ College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China ]
• Hong Li [ College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China ]
• XueShuang Li [ College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605