원문정보
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
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