CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Finger Vein Verification System based on Three Methodologies of Feature Extraction

by Abbas H. Hassin Alasadi, Zainab N. Nemer
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 172 - Number 5
Year of Publication: 2017
Authors: Abbas H. Hassin Alasadi, Zainab N. Nemer
10.5120/ijca2017915144

Abbas H. Hassin Alasadi, Zainab N. Nemer . Finger Vein Verification System based on Three Methodologies of Feature Extraction. International Journal of Computer Applications. 172, 5 ( Aug 2017), 7-11. DOI=10.5120/ijca2017915144

@article{ 10.5120/ijca2017915144,
author = { Abbas H. Hassin Alasadi, Zainab N. Nemer },
title = { Finger Vein Verification System based on Three Methodologies of Feature Extraction },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2017 },
volume = { 172 },
number = { 5 },
month = { Aug },
year = { 2017 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume172/number5/28245-2017915144/ },
doi = { 10.5120/ijca2017915144 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:19:30.890172+05:30
%A Abbas H. Hassin Alasadi
%A Zainab N. Nemer
%T Finger Vein Verification System based on Three Methodologies of Feature Extraction
%J International Journal of Computer Applications
%@ 0975-8887
%V 172
%N 5
%P 7-11
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As a new manner of biometrics measurement, human finger vein pattern has been developed. Many researchers have paid close attention to this topic. In this paper, three methodologies of features extraction are used for finger vein verification system. These methods are; Grey Level Co-occurrence Matrix (GLCM), Tamura, and Scale Invariant Feature Transform (SIFT). Empirically, the results of the proposed algorithm was acceptable and better.

References
  1. Shrikhande, Santosh P., and H. S. Fadewar. 2015 Finger vein recognition using Discrete Wavelet Packet Transform based features. In Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on, pp. 1646-1651. IEEE.
  2. Kauba, Christof, and Andreas Uhl. 2015 Sensor ageing impact on finger-vein recognition. In Biometrics (ICB), 2015 International Conference on, pp. 113-120. IEEE.
  3. Nandhini, S., and D. Shyam. 2014 Real-Time Finger-Vein Recognition for Security and Monitoring System. In Applied Mechanics and Materials, vol. 550, pp. 194-203. Trans Tech Publications.
  4. Qin, Huafeng, Lan Qin, Lian Xue, Xiping He, Chengbo Yu, and Xinyuan Liang. 2013 Finger-vein verification based on multi-features fusion. Sensors, 13, no. 11, pp, 15048-15067.
  5. Nguyen, Dat Tien, Young Ho Park, Kwang Yong Shin, Seung Yong Kwon, Hyeon Chang Lee, and Kang Ryoung Park. 2013 Fake finger-vein image detection based on fourier and wavelet transforms. Digital Signal Processing 23, no. 5 , pp. 1401-1413.
  6. Peng, J., Li, Q., El Latif, A. A. A., Wang, N., & Niu, X. 2013 Finger vein recognition with gabor wavelets and local binary patterns. IEICE TRANSACTIONS on Information and Systems 96, no. 8, pp. 1886-1889.
  7. Mohan, Man, R. Prem Kumar, Rachit Agrawal, Surbhi Sharma, Malay Kishore Dutta, Carlos M. Travieso, and Jesus B. Alonso-Hernandez. 2015 Finger vein recognition using Integrated Responses of Texture features. In Bioinspired Intelligence (IWOBI), 2015 4th International Work Conference on, pp. 209-214. IEEE.
  8. Liu, Tong, Jianbin Xie, Wei Yan, Peiqin Li, and Huanzhang Lu. 2015 Finger-vein recognition with modified binary tree model. Neural Computing and Applications 26, no. 4, pp. 969-977.
  9. Eleyan, Alaa, and Hasan Demirel. 2011 Co-occurrence matrix and its statistical features as a new approach for face recognition. Turkish Journal of Electrical Engineering & Computer Sciences 19, no. 1, pp. 97-107.
  10. Howarth, P. and Rüger, S. 2004 Evaluation of texture features for content-based image retrieval, International Conference on Image and Video Retrieval, July, pp.326–334, Springer, Berlin Heidelberg.
  11. Lowe, David G. 2004 Distinctive image features from scale-invariant keypoints. International journal of computer vision 60, no. 2 ,pp. 91-110.
  12. Asaari, Mohd Shahrimie Mohd, Shahrel A. Suandi, and Bakhtiar Affendi Rosdi. 2014 Fusion of band limited phase only correlation and width centroid contour distance for finger based biometrics. Expert Systems with Applications 41, no.7, pp. 3367-3382.
  13. Elnasir, Selma, and Siti Mariyam Shamsuddin. 2014 Palm Vein Recognition based on 2D-Discrete Wavelet Transform and Linear Discrimination Analysis. Int. J. Advance Soft Compu. Appl 6, no. 3, pp. 43-59.
Index Terms

Computer Science
Information Sciences

Keywords

Finger vein Feature extraction  GLCM  Tamura SIFT Matching Algorithm.

Powered by PhDFocusTM