Next Article in Journal
Precise Temperature Mapping of GaN-Based LEDs by Quantitative Infrared Micro-Thermography
Next Article in Special Issue
Performance Evaluation of Fusing Protected Fingerprint Minutiae Templates on the Decision Level
Previous Article in Journal
A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring
Previous Article in Special Issue
Scattering Removal for Finger-Vein Image Restoration
Article Menu

Export Article

Open AccessArticle

Multispectral Palmprint Recognition Using a Quaternion Matrix

Bio-Computing Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
The Institute of Automation of Heilongjiang Academy of Sciences, Harbin 150090, China
Department of Computer Science, Baoji University of Arts and Science, Xi’an 721013, China
Author to whom correspondence should be addressed.
Sensors 2012, 12(4), 4633-4647;
Received: 20 February 2012 / Revised: 21 March 2012 / Accepted: 21 March 2012 / Published: 10 April 2012
(This article belongs to the Special Issue Hand-Based Biometrics Sensors and Systems)
PDF [770 KB, uploaded 21 June 2014]


Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. View Full-Text
Keywords: multispectral palmprints; quaternion; PCA; DWT multispectral palmprints; quaternion; PCA; DWT
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Xu, X.; Guo, Z.; Song, C.; Li, Y. Multispectral Palmprint Recognition Using a Quaternion Matrix. Sensors 2012, 12, 4633-4647.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top