Palm lines are the most important features for palmprint recognition. They are best
considered as typical multiscale features, where the principal lines can be represented at a …

This paper introduces a generalized palmprint identification framework to unify several state-
of-art 2D and 3D palmprint methods. Through this framework, we argue that the methods …

Palmprint recognition is an important and widely used modality in biometric systems. It has a
high reliability, stability and user acceptability. This paper proposes a new and effective …

Deep convolutional neural networks (DCNN) have been applied successfully for finger vein
recognition and have achieved promising performance in the past three years. However …

This paper presents a comprehensive survey examining the prevailing feature extraction
methodologies employed within biometric palmprint recognition models. It encompasses a …

Over the past few decades, hand-based multimodal biometrics systems have achieved
significant attention because of their high security, accuracy, and anti-counterfeiting. Various …

This paper presents a new evolutionary approach for adaptive combination of multiple
biometrics to ensure the optimal performance for the desired level of security. The adaptive …

There is an urgent need, accelerated by the COVID-19 pandemic, for methods that allow
clinicians and neuroscientists to remotely evaluate hand movements. This would help detect …

In this article, we propose a collaborative palmprint-specific binary feature learning method
and a compact network consisting of a single convolution layer for efficient palmprint feature …

In the past years, deep convolutional neural networks (CNNs) have become extremely
popular in the computer vision and pattern recognition community. The computational power …