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

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 …

Because of its simple network structure and efficient learning mode, the Broad Learning
System (BLS) has achieved impressive performance in image classification tasks …

Linear discriminant analysis (LDA) as a classical supervised dimensionality reduction
method has shown powerful capability in various image classification tasks. The purpose of …

Deep learning-based palmprint recognition methods have made good progress and
obtained promising performance. However, most of them are mainly focused on …

This paper presents the framework of the smoothing group L 1/2 regularized discriminative
broad learning system for pattern classification and regression. The core idea is to improve …

Nowadays, both fingerprint and palmprint databases are massive and whose size has
exceeded millions. Therefore, applying a filtering technique, such as indexing, is vital for …

This work aims to address two issues that often exist in least square regression (LSR)
models for classification tasks, which are (1) learning a compact projection matrix for feature …

Abstract Discriminative Least Squares Regression (DLSR) is an approach that is more
popularly used in multi-classification tasks, which employs an ε-draggings technique to …

Binary pattern learning has been achieved promising recognition performance in palmprint
identification. However, most of direction representation-based methods are hand-crafted …