Next Article in Journal
A Choline Oxidase Amperometric Bioassay for the Detection of Mustard Agents Based on Screen-Printed Electrodes Modified with Prussian Blue Nanoparticles
Previous Article in Journal
An Overview of Distributed Microgrid State Estimation and Control for Smart Grids
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(2), 4326-4352; doi:10.3390/s150204326

Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices

1
School of Computer Science and Engineering, South China University of Technology, Higher Education Mega Center, Panyu, Guangzhou 510006, China
2
National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Medicine, Shenzhen University, Shenzhen 518060, China
3
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China
4
Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China
*
Authors to whom correspondence should be addressed.
Received: 6 January 2015 / Accepted: 6 February 2015 / Published: 12 February 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [18030 KB, uploaded 12 February 2015]   |  

Abstract

We propose a novel biometric recognition method that identifies the inner knuckle print (IKP). It is robust enough to confront uncontrolled lighting conditions, pose variations and low imaging quality. Such robustness is crucial for its application on portable devices equipped with consumer-level cameras. We achieve this robustness by two means. First, we propose a novel feature extraction scheme that highlights the salient structure and suppresses incorrect and/or unwanted features. The extracted IKP features retain simple geometry and morphology and reduce the interference of illumination. Second, to counteract the deformation induced by different hand orientations, we propose a novel structure-context descriptor based on local statistics. To our best knowledge, we are the first to simultaneously consider the illumination invariance and deformation tolerance for appearance-based low-resolution hand biometrics. Settings in previous works are more restrictive. They made strong assumptions either about the illumination condition or the restrictive hand orientation. Extensive experiments demonstrate that our method outperforms the state-of-the-art methods in terms of recognition accuracy, especially under uncontrolled lighting conditions and the flexible hand orientation requirement. View Full-Text
Keywords: inner knuckle print recognition; illumination-invariant feature extraction; deformation-tolerant matching inner knuckle print recognition; illumination-invariant feature extraction; deformation-tolerant matching
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Xu, X.; Jin, Q.; Zhou, L.; Qin, J.; Wong, T.-T.; Han, G. Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices. Sensors 2015, 15, 4326-4352.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

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