Study on automatic person recognition by palmprint is currently a hot topic. In this paper, we propose a novel palmprint recognition method by transforming the typical palmprint phase code feature into its Fourier frequency domain. The resulting real-valued Fourier spectral features are further processed by horizontal and vertical 2DPCA method, which proves highly efficient in terms of computat...

In this paper, we propose a palmprint recognition method based on eigenspace technology. By means of the Karhunen–Loeve transform, the original palmprint images are transformed into a small set of feature space, called ‘‘eigenpalms’’, which are the eigenvectors of the training set and can represent the principle components of the palmprints quite well. Then, the eigenpalm features are extracted...

hand shape, etc. Two dimensional (2D) palmprint recognition [1-4, 16-18] has been widely studied in the past decade and it has been proven that palmprint is a unique biometric identifier. 2D palmprint systems have merits of high accuracy and user friendliness, etc. Nonetheless, 2D palmprint can be easily counterfeited and much three dimensional (3D) palm structural information is lost. Inspired...

Palmprint verification is an important tool for authentication of an individual and it can be of significant value in security and ecommerce applications. Palmprint identification has gained high impact over the other biometric modalities due to its reliability and high user acceptance. This paper presents a palmprint based identification approach which uses the Gabor wavelet to extract multipl...

Palmprint technology is a new branch of biometrics used to identify an individual. Palmprint has rich set of features like palm lines, wrinkles, minutiae points, texture, ridges, etc. Several line and texture extraction techniques for palmprint have been extensively studied. This paper presents an intramodal authentication system based on texture information extracted from the palmprint using t...

In recent years, researchers have found that palmprint is quite a promising biometric identifier as it has the merits of high distinctiveness, robustness, user friendliness, and cost effectiveness. Nearly all the existing palmprint recognition methods are based on one-to-one matching. However, recent studies have corroborated that matching based on image sets can usually lead to a better result...

This paper presents a new method for personal recognition using palmprints. This method uses inkless, normalized palmprint images to generate eigenpalms. Every palmprint image is thus characterized by a feature vector, consisting of weights from eigenpalm images. The performance of proposed method using two measures, i.e., minimum Euclidean distance and maximum similarity measure, is evaluated....

Palmprint recognition, as a reliable personal identity check method, has been receiving increasing attention during recent years. According to previous work, local texture analysis supplies the most promising framework for palmprint image representation. In this paper, we propose a novel palmprint recognition method by combining statistical texture descriptions of local image regions and their ...

Support vector machine (SVM) and HMAX model are two powerful recent techniques. SVMs are classifiers which have demonstrated high generalization capabilities in many different tasks, including the object recognition problem. HMAX is a feature extraction method and this method is motivated by a quantitative model of visual cortex. In this paper we combine these two techniques for the palmprint v...

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-sample cases such as image recognition, image down-sample is first used to reduce the palmprint space dimensionality. The LFDA is applied to extract the low projection vectors. Then the training images and test images...