We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Finger Vein Recognition using Rotated Wavelet Filters

by Santosh P. Shrikhande, H. S. Fadewar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 149 - Number 7
Year of Publication: 2016
Authors: Santosh P. Shrikhande, H. S. Fadewar
10.5120/ijca2016911474

Santosh P. Shrikhande, H. S. Fadewar . Finger Vein Recognition using Rotated Wavelet Filters. International Journal of Computer Applications. 149, 7 ( Sep 2016), 28-33. DOI=10.5120/ijca2016911474

@article{ 10.5120/ijca2016911474,
author = { Santosh P. Shrikhande, H. S. Fadewar },
title = { Finger Vein Recognition using Rotated Wavelet Filters },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 149 },
number = { 7 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume149/number7/26011-2016911474/ },
doi = { 10.5120/ijca2016911474 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:54:07.671524+05:30
%A Santosh P. Shrikhande
%A H. S. Fadewar
%T Finger Vein Recognition using Rotated Wavelet Filters
%J International Journal of Computer Applications
%@ 0975-8887
%V 149
%N 7
%P 28-33
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Finger vein biometric have been recognized as the most effective and promising recognition method due to its accuracy and security. This paper discusses a method for finger vein image features extraction using 2-D Rotated Wavelet Filters (RWF) and Discrete Wavelet Transform (DWT) jointly. A set of 2-D RWF filters improves characterization of diagonally oriented texture features from a finger vein image. The 2-D RWF and DWT jointly used for decomposition of a finger vein image ROI up to third level. The standard deviation and energy of each subband from every decomposition level are used for the creation of features vector. Then Canberra distance classifier is used for the classification of finger vein images. The performance of this method has evaluated on the standard finger vein image database of Shandong University (SDUMLA), China. Experimental results have shown that the method with RWF and DWT jointly gives better results as compare to the traditional DWT based methods.

References
  1. Kang Ryoung Park, “Finger Vein Recognition by Combining Global and Local Features on SVM”, Computing and Informatics, Vol. 30, pp. 295–309, 2011
  2. Santosh P. Shrikhande and H. S. Fadewar, “Finger Vein Recognition Using Discrete Wavelet Packet Transform Based Features”, International Conference on Advances in Computing, Communications and Informatics (ICACCI), Vol. 1, pp. 1646-1651, 2015
  3. Naoto Miura, Akio Nagasaka, Takafumi Miyatake, “Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification”, Machine Vision and Applications, 15: pp. 194–203, 2004
  4. Naoto Miura, Akio Nagasaka, “Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles”, IAPR Conference on Machine Vision Applications, Tsukuba Science City, Japan, pp. 347-50, May 2005
  5. Jinfeng Yang, Yihua Shi, Jinli Yang, “Personal identification based on finger-vein feature”, Computers in Human Behavior 27 (Elsevier) pp. 1565–1570, November 2010
  6. Cheng Bo Yu, Hua Feng Qin, Lian Zhang, Yan-Zhe Cui, “Finger vein image recognition combining modified hausdorff distance with minutiae feature matching”, J. Biomedical Science and Engineering, pp. 261-272, August 2009
  7. Liu, J B Xie, W Yan, P Q Li and HZ Lu, “An algorithm for finger-vein segmentation based on modified repeated line tracking”, The Imaging Science Journal Vol 61, pp. 491-502
  8. Eui Chul Lee, Hyunwoo Jung and Daeyeoul Kim, “New Finger Biometric Method Using Near Infrared Imaging”, Sensors, pp. 2319-2333, February 2011
  9. Xianjing Meng, Gongping Yang, Yilong Yin and Rongyang Xiao, “ Finger Vein Recognition Based on Local Directional Code”, Sensors, pp. 14937-14952, November 2012
  10. Bakhtiar Affendi Rosdi, Chai Wuh Shing and Shahrel Azmin Suandi, “Finger Vein Recognition Using Local Line Binary Pattern”, Sensors 11, pp. 11357-11371, November 2011
  11. Jinfeng Yang, Yihua Shi and Renbiao Wu, “Finger-Vein Recognition Based on Gabor Features”, Biometric Systems, Design and Applications, Published by Intech, pp. 17-32, 2011
  12. Manesh Kokare, P.K. Biswas, B.N. Chatterji, “Texture image retrieval using rotated wavelet filters”, Pattern Recognition Letters 28, pp. 1240–1249, February 2007
  13. Sangita Bharkad, Manesh Kokare, “Rotated Wavelet Filters-Based Fingerprint Recognition”, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 26, No. 3, pp. 1256008-1- 21, Septmber 2012
  14. Yilong Yin, Lili Liu, and Xiwei Sun., “SDUMLA-HMT, A Multimodal Biometric Database”, Springer-Verlag Berlin Heidelberg, LNCS 7098, pp. 260-268, 2011
  15. Sangita Bharkad, Manesh Kokare, “Fingerprint Matching using Discreet Wavelet Packet Transform”, 3rd IEEE International Advance Computing Conference (IACC), pp. 1183-1188, 2013
  16. Naresh Babu N. T, Annis Fathima A and V. Vaidehi, “An Efficient Face Recognition System Using DWT-ICA features”, IEEE, International Conference on Digital Image Computing: Techniques and Applications, pp. 146-151, 2011
  17. Santosh P. Shrikhande, Hanumant S. Fadewar, “Personal Identification Using Different Biometrics: A Review”, International Journal of Engineering Research & Technology (IJERT), Vol. 3 Issue 2, pp. 1104-1109, February 2014
  18. Shahid Akbar, Ashfaq Ahmad and Maqsood Hayat, “Identification of Fingerprint Using Discrete Wavelet Transform in Conjunction with Support Vector Machine”, International Journal of Computer Science Issues (IJCSI), Vol. 11, Issue 5, No 1, pp. 189-199, September 2014
  19. Nabeel Younus Khan, M.Younus Javed, “Efficient Fingerprint Matching Technique Using Wavelet Based Features”, IEEE International Conference on Digital Image Computing Techniques and Applications, pp. 253-259, 2007
  20. Jinfeng Yang, Yihua Shi, “Finger–vein ROI localization and vein ridge enhancement”, Pattern Recognition Letters, pp. 1559-1579, May 2012
  21. Sunita Lokhande, Vishram. N. Bapat, “Wavelet Packet Based Iris Texture Analysis for Person Authentication”, International Journal of Signal & Image Processing (SIPIJ), Vol.4, No.2, pp. 91-104, April 2013
  22. Nurhafizah Mahri, Shahrel Azmin Sundi Suandi, and Bakhtiar Affendi Rosdi, “Finger Vein Recognition Algorithm Using Phase Only Correlation”, IEEE International Conference on Emerging Techniques and Challenges for Hand-Based Biometrics (ETCHB), pp. 1-6, August 2010
  23. Rongyang Xiao, Gongping Yang, Yilong Yin, and Lu Yang, “A Novel Matching Strategy for Finger Vein Recognition”, Springer -Verlag Berlin Heidelberg LNCS 7751, pp. 364-371, 2013
  24. Zhi Liu and Shangling Song, “An Embedded Real-Time Finger-Vein Recognition System for Mobile Devices”, IEEE Transactions on Consumer Electronics, Vol. 58, No. 2, pp. 522-527, May 2012
  25. Gongping Yang, Xiaoming Xi, and Yilong Yin, “Finger Vein Recognition Based on a Personalized Best Bit Map”,  Hand-Based Biometrics Sensors and Systems, 12 pp.1738-1757, February 2012
Index Terms

Computer Science
Information Sciences

Keywords

Finger Vein Recognition Discrete Wavelet Transform Rotated Wavelet Filters.

Powered by PhDFocusTM