Earticle

초록

영어

The importance of biometric identification technology in the field of information security is increasingly prominent, in various of recognition technology, hand vein recognition technology attracts more and more researchers’ attentions because of its high security and high recognition rate; The traditional template matching method based on vein skeletal morphology inevitably brings about problems such as long training time and too much space occupation of sample storage; the passage applies feature extraction method based on the subspace to the vein recognition on the basis of analysis of the principal component analysis method, which is called (2D)2FPCA algorithm combining the traditional 2DPCA and 2DFLD technology; the new algorithm has many advantages including reduction of the preprocessing algorithm steps and small space occupation of characteristics vectors with high processing speed; Finally, simulation experiments with the new algorithm are carried out in 500 vein image database, which proves that the method not only has better recognition accuracy but also improves the recognition rate while reducing the storage space.

목차

Abstract
 1. Introduction
 2. The Basic Concept of 2DPCA
 3. The Basic Concept of (2D)2FPCA
  3.1. (2D)2FPCA Algorithm
  3.2. The Transform of DFLD
 4. Feature Matching
  4.1. The Training Phase:
  4. 2. The Recognition Stage：
 5. Experimental Results
 Acknowledgements
 References

키워드

저자

• Jun Wang [ School of Information and Electrical Engineering, China University of Mining and Technology ]
• Hanjun Li [ Air Force Logistics Academy ]
• Guoqing Wang [ School of Information and Electrical Engineering, China University of Mining and Technology ]
• Ming Li [ School of Information and Electrical Engineering, China University of Mining and Technology ]
• Dong Li [ School of Information and Electrical Engineering, China University of Mining and Technology ]

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