Hardware Implementation of Palm Vein Biometric Modality for Access Control in Multi layered Security System

被引:12
作者
Athale, Sonal S. [1 ]
Patil, Dhiraj [2 ]
Deshpande, Pallavi [1 ]
Dandawate, Yogesh H. [3 ]
机构
[1] Vishwakarma Inst Informat Technol, Dept Elect & Telecommun, Pune, Maharashtra, India
[2] Vishwakarma Inst Informat Technol, Elect & Telecommun, Pune, Maharashtra, India
[3] Vishwakarma Inst Informat Technol, Dept Elect & Telecommun Engn, Pune, Maharashtra, India
来源
SECOND INTERNATIONAL SYMPOSIUM ON COMPUTER VISION AND THE INTERNET (VISIONNET'15) | 2015年 / 58卷
关键词
Biometrics; palm veins; Region of interest (ROT); PCA; Template matching; DSP processor; BF561; KNUCKLE-PRINT; PALMPRINT;
D O I
10.1016/j.procs.2015.08.013
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Among the biometric modalities palm veins are the most secure and difficult to duplicate. This palm vein verification system aims to recognize a person from its exclusive palm vein organization that cannot be forged easily since veins are situated in inner layers of skin. Embedded devices are gaining increased attention in biometrics due to reliability and cost efficient systems. An embedded palm vein recognition system is the need of today in institutes, industries, security places etc. The aim of this proposed work is to implement palm vein identification system on hardware unit so that it can be further build into a single standalone unit, where it can be used in final level security in multilayered security system without any possibility of hacking. The hardware platform used in the proposed work is Blackfin ADSP-561 processor and the algorithms used for matching of palm vein are performed using C language. The project focuses on storing images and implementing the matching algorithms on hardware platform itself such that PC or laptop is not needed for identification purpose. Principal component analysis (PCA) and template matching techniques are used as verification algorithms of palm veins. Finally, it can be concluded from the experimental results that this approach can verify an individual with an average accuracy of 92%. (C) 2015 The Authors. Published by Elsevier B.V.
引用
收藏
页码:492 / 498
页数:7
相关论文
共 13 条
[1]   Multifeature-Based High-Resolution Palmprint Recognition [J].
Dai, Jifeng ;
Zhou, Jie .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2011, 33 (05) :945-957
[2]   Palm vein recognition using adaptive Gabor filter [J].
Han, Wei-Yu ;
Lee, Jen-Chun .
EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (18) :13225-13234
[3]   Ant colony optimization based fuzzy binary decision tree for bimodal hand knuckle verification system [J].
Kumar, Amioy ;
Hanmandlu, Madasu ;
Gupta, H. M. .
EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (02) :439-449
[4]  
Prasanthi T.D., 2012, INT J ADV RES COMPUT, V1
[5]   Palm vein pattern-based biometric recognition system [J].
Shah, Gunjan ;
Shirke, Sagar ;
Sawant, Sonam ;
Dandawate, Yogesh H. .
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2015, 51 (02) :105-111
[6]   Embedded Palmprint Recognition System Using OMAP 3530 [J].
Shen, Linlin ;
Wu, Shipei ;
Zheng, Songhao ;
Ji, Zhen .
SENSORS, 2012, 12 (02) :1482-1493
[7]   Person recognition by fusing palmprint and palm vein images based on "Laplacianpalm" representation [J].
Wang, Han-Gang ;
Yau, Wei-Yun ;
Suwandy, Andy ;
Sung, Eric .
PATTERN RECOGNITION, 2008, 41 (05) :1514-1527
[8]   Online joint palmprint and palmvein verification [J].
Zhang, David ;
Guo, Zhenhua ;
Lu, Guangming ;
Zhang, Lei ;
Liu, Yahui ;
Zuo, Wangmeng .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (03) :2621-2631
[9]   Phase congruency induced local features for finger-knuckle-print recognition [J].
Zhang, Lin ;
Zhang, Lei ;
Zhang, David ;
Guo, Zhenhua .
PATTERN RECOGNITION, 2012, 45 (07) :2522-2531
[10]   Ensemble of local and global information for finger-knuckle-print recognition [J].
Zhang, Lin ;
Zhang, Lei ;
Zhang, David ;
Zhu, Hailong .
PATTERN RECOGNITION, 2011, 44 (09) :1990-1998