High-resolution palmprint recognition is a challenging problem due to deficiencies in
images, such as poor quality, skin distortion, and unallocated images. Considering the …

This study presents a hierarchical palmprint feature extraction and recognition approach
based on multi‐wavelet and complex network (CN) since they can effectively decrease …

Palmprint recognition has been widely applied to security authentication due to its rich
characteristics, ie, local direction, wrinkle, and texture. However, different types of palmprint …

The increasing demand to develop a palmprint biometric system with a low-error rate has
prompted scientists to use multispectral imaging to overcome the limits of the techniques that …

Palmprint recognition has attracted various researchers in recent years due to its richness in
amount of features. In feature extraction, the single feature has become bottleneck in …

In recent years, palmprint recognition has gained increased interest and has been a focus of
significant research as a trustworthy personal identification method. The performance of any …

Palmprint is a promising biometric feature for use in access control and forensic
applications. Previous research on palmprint recognition mainly concentrates on low …

Palm-print recognition system is extensively deployed in a variety of applications, ranging
from forensic to mobile phones. This paper proposes a new feature extraction technique for …

Palmprint is one important biometric feature with uniqueness, stability and high
distinguishability, and its study has attracted much attention in the past decades. Although …

A palmprint recognition approach based on multi‐wavelet and convolutional neural network
(CNN) against noise and misalignment is given. CNN method has high robustness in …