In this paper, we propose a feature-level fusion approach for improving the efficiency of
palmprint identification. Multiple elliptical Gabor filters with different orientations are …

Principal component analysis (PCA) has been very successful in image recognition. Recent
research on PCA-based methods has mainly concentrated on two issues, namely: 1) feature …

Local binary pattern (LBP) is a powerful texture descriptor that is gray-scale and rotation
invariant according to T. Ojala et al.(2002). Because texture is one of the most clearly …

Locality preserving projections (LPP) is a new subspace feature extraction method which
seeks to preserve the local structure and intrinsic geometry of the data space. As the LPP …

Two-dimensional principal component analysis (2DPCA) is a novel image representation
approach recently developed for image recognition. One characteristic of 2DPCA is that it …

In this paper, a method for palmprint recognition, kernel Fisher discriminant analysis (KFDA),
is proposed. The method introduces KFDA to represent palmprint features for palmprint …

The hand recognition in biometric security was developed successfully for authentication or
identification. In this paper, we propose an original method of contact less biometric …

In today's world, biometrics system is used almost everywhere for the security and personal
recognition. The palmprint is one of the most reliable physiological characteristics that can …

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 …