Recently palmprint recognition received many researchers' attention because of it's low
resolution and cheap devices. As other features recognition, algebraic feature is the …

PCA (principal component analysis) is a successful feature detection method for pattern
recognition. It is the optimal dimension compression technique based on second-order …

Computer-aided personal recognition is becoming increasingly important in our information
society. Human palmprint recognition has become an active area of research over the last …

In this paper, a novel method using wavelet decomposition and 2D Principal component
analysis (2DPCA) for palmprint recognition is presented. Firstly, 2D wavelet transform is …

This paper investigates palmprint recognition using Principal Component Analysis (PCA)
and the Adaptive Principal component EXtraction (APEX) which is one of the PCA …

Palmprint Recognition Systems (PRS) with multi-feature can increase the recognition
performance of PRS. For such a purpose, effectively distinguished information with low …

This paper presents a novel palmprint recognition method using Gabor wavelets and 2-
Dimensional Principal Component Analysis (2-DPCA) and PCA. Different from the Gabor …

A feature extraction method of palmprint recognition based on Two-Dimensional Principal
Component Analysis (2DPCA) is proposed in this work. A series of experiments were …

A new palmprint recognition method based on local Fisher discriminant analysis (LFDA) is
proposed. In order to solve the singularity of the eigenvalue equation matrix in small-size …

This paper presents a novel palmprint recognition approach based on Generalized
Discriminant Analysis (GDA). The method uses GDA to extract palmprint features for …