The Fisherface method is a most representative method of the linear discrimination analysis
(LDA) technique. However, there persist in the Fisherface method at least two areas of …

Linear discriminant analysis (LDA)-based methods have been very successful in face and
palmprint recognition. Recently, a class of post-processing approaches has been proposed …

Discriminant analysis is effective in extracting discriminative features and reducing
dimensionality. In this paper, we propose an optimal subset-division based discrimination …

In the field of image processing and recognition, discrete cosine transform (DCT) and linear
discrimination are two widely used techniques. Based on them, we present a new face and …

Abstract In existing Linear Discriminant Analysis (LDA) models, the class population mean is
always estimated by the class sample average. In small sample size problems, such as face …

As a feature extraction method, PCA has been wildly used in biometrics. Recently research
shows that removing the first 3 eigenvectors can enhance the system performance for face …

Feature fusion of palmprint and face based on Kernel Fisher discriminant analysis (KFDA)
was proposed in the paper. The essence of KFDA is Kernel Principal Component Analysis …

Discrimination power analysis (DPA) is a statistical analysis combining discrimination
concept with discrete cosine transform coefficients (DCTCs) properties. Unfortunately there …

Recently, a class of post-processing approaches has been proposed to improve the
recognition performance of LDA in face recognition. In-depth analysis, however, has not …

In this paper, a linear discriminant analysis method with L1 norm (LDA-L1) for palmprint
recognition is proposed. The traditional linear discriminant analysis method based on L2 …