Erratum to: Appearance-based bidirectional representation for palmprint recognition

A Spectral Representation for Appearance-Based Classification and Recognition

We present a spectral representation for appearancebased image classification and object recognition. Based on a generative process, the representation is derived by partitioning the frequency domain into small disjoint regions. This gives rise to a set of filters and a representation consisting of marginal distributions of those filter responses. We use a neural network to learn a classifier t...

Palmprint Recognition Using Directional Representation and Compresses Sensing

In this study, based on directional representation for palmprint images and compressed sensing, we propose a novel approach for palmprint recognition. Firstly, the directional representation for appearance based approaches is obtained by the anisotropy filter to efficiently capture the main palmprint image characters. Compared with the traditional Gabor representations, the new representations ...

Palmprint Recognition Based on Local Texture Features

In this paper, we propose and evaluate palmprint recognition method based on local Haralick features. The Haralick features are extracted from overlapping square subimages of a palmprint region of interest (ROI). A biometric template is composed of N m-component feature vectors, where N is the total number of overlapping subimages, and m is the number of local Haralick features per subimage in ...

Palmprint Recognition by Applying Wavelet Subband Representation and Kernel PCA

This paper presents a novel Daubechies-based kernel Principal Component Analysis (PCA) method by integrating the Daubechies wavelet representation of palm images and the kernel PCA method for palmprint recognition. The palmprint is first transformed into the wavelet domain to decompose palm images and the lowest resolution subband coefficients are chosen for palm representation. The kernel PCA ...

Texture Representation for Low - resolution Palmprint Recognition to attend the public defense