As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese-Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established...

In this paper we present a comparison of the two dominant image preprocessing techniques for palmprint recognition, namely, histogram equalization and mean-variance normalization. We show that both techniques pursue a similar goal and that the difference in recognition efficiency stems from the fact that not all assumptions underlying the mean-variance normalization approach are always met. We ...

Palmprint attracts increasing attention due to its several advantages in the biometrics field. Deep learning has achieved remarkable performance computer vision area, so a large number of deep-learning-based methods have been proposed by research community for palmprint recognition. The outputs deep hashing network (DHN) can be represented as binary bit string, DHN reduce storage and accelerate...

In this paper, a multi-resolution feature extraction algorithm for palm-print recognition is proposed based on two-dimensional discrete wavelet transform (2D-DWT), which efficiently exploits the local spatial variations in a palmprint image. The entire image is segmented into several small spatial modules and a palm-print recognition scheme is developed, which extracts histogram-based dominant ...

Multi-biometric system stores multiple templates for the same user corresponding to the different biometric sources. Infallible security should be provided to the stored biometric templates as biometric is not revocable. In this work, multi-modal biometric template security for palmprint and fingerprint is proposed which is based on the fuzzy vault generation. At first, the preprocessing steps ...

This paper presents an approach for the personal authentication using rank-level fusion of multispectral palmprints, instead of using multiple biometric modalities and multiple matchers. The rank level fusion involving the non linear combination of hyperbolic tangent functions gives the best recognition rate for the Rank 1 obtained from two types of features, viz., sigmoid and fuzzy. The result...

Due to stable and discriminative features, palmprint-based biometrics has been gaining popularity in recent years. Most of the traditional palmprint recognition systems are designed with a group hand-crafted features that ignores some additional features. For tackling problem described above, Convolution Neural Network (CNN) model inspired by Alex-net learns from ROI images classifies using fuz...