Two-Dimensional Principal Component Analysis (2DPCA) has been widely used for feature
extraction in palmprint recognition. However, it is sensitive to variable illumination. In this …

This paper presents a palmprint recognition algorithm using principal component analysis
(PCA) of phase information in 2D (two-dimensional) discrete Fourier transforms (DFTs) of …

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 …

In this paper, we propose an information fusion-based palmprint recognition method. Firstly,
three different kinds of palmprint features including texture, principal line and appearance …

A major approach for palmprint recognition today is to extract feature vectors corresponding
to individual palmprint images and to perform palmprint matching based on some distance …

In this paper, we propose a novel approach for palmprint recognition, which combine band-
limited phase-only correlation method and directional representation of palmprint. We also …

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 …

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 …

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 …

This paper proposed an enhanced algorithm of palmprint recognition. The 2D Gabor was
done firstly to filter in the main direction and strengthen the primary line's information. Then …