In this paper, a new Palmprint recognition technique is introduced based on the gray-level
co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the …

In this paper, a new Palmprint recognition technique is introduced based on the gray-level
co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the …

During the last decade, palmprint recognition has received an increasing attention due to
the abundant features that can be extracted from the captured palmprint image. However, a …

In this paper, unique features of the segmented image samples are extracted by using two
major feature extraction techniques: Local Binary Pattern (LBP) and Histogram of Oriented …

This paper presents a palmprint recognition system with palmprint images collected by a
high-resolution color scanner. The scanned RGB image of the palmprint is pre-processed …

This paper proposes a palmprint identification system using Finite Ridgelet Transform (FRIT)
and Bayesian classifier. FRIT is applied on the ROI (region of interest), which is extracted …

In the field of palmprint recognition, the orientation information of the principal lines and
winkles has long been considered the most dominant and reliable feature. Numerous …

As a reliable biometric characteristic, the palmprint recognition has recently represented an
emerging trend in the pattern recognition field. It is a human physiological feature that …

Palmprint identification refers to searching in a database for the palmprint template, which is
from the same palm as a given palmprint input. The identification process involves …

The presented paper proposes an algorithm for palmprint recognition using seven different
machine learning algorithms. First of all, we have proposed a region of interest (ROI) …