Earticle

초록

영어

Discriminant locality preserving projection(DLPP) can not obtain optimal discriminant vectors which utmostly optimize the objective of DLPP. This paper proposed a Gabor based optimized discriminant locality preserving projections (ODLPP) algorithm which can directly optimize discriminant locality preserving criterion on high-dimensional Gabor feature space via simultaneous diagonalization, without any dimensionality reduction preprocessing. The proposed method is applied to face and finger vein recognition problems and is compared with some other related Gabor based dimensionality reduction techniques. Experimental results conducted on the VALID face database and a subset of PKU finger vein database indicates the effectiveness of the proposed algorithm.

목차

Abstract
 1. Introduction
 2. Optimized Discriminant Locality Preserving Projection in GaborFeature Space
  2.1 Overview of Discriminant Locality Preserving Projection
  2.2 Optimized Discriminant Locality Preserving Projection
  2.3 Analysis of Eigenvalues-eigenvectors in High Dimensional Spaces
 3. Experimental Evaluation
  3.1 Database
  3.2 Error Recognition Rate versus Feature Dimension
  3.3 Error Recognition Rate with Different Number of Training Samples
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• Xi Chen [ The School of Information Engineering and Automation, Kunming University of Science and Technology, Si-Chuan province Key Lab of Signal and Information Processing at Southwest Jiaotong University ]
• Jiashu Zhang [ Si-Chuan province Key Lab of Signal and Information Processing at Southwest Jiaotong University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605