Palm Vein based Authentication

Authors

  • Zaheema Banu  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India
  • D S Rajesh  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India
  • Sheethal G  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India

DOI:

https://doi.org/10.32628/CSEIT206379

Keywords:

Palm vein, biometrics, SVM, LBP

Abstract

The palm vein authentication technology offers a high level of accuracy. Palm vein authentication uses the vascular patterns of an individual’s palm as personal identification data. If we compare with a finger or the back of a hand, a palm has a broader and more complicated vascular pattern and thus contains a wealth of differentiating features for personal identification. The importance of biometrics in the current field of Security has been depicted in this work. We have processed the raw image from the dataset before implementing authentication algorithm. After getting the suitable image after pre- processing, we have used local binary pattern (LBP) for feature extraction purpose & then using a machine learning algorithm, with support vector machine (SVM), we tried to match the vascular vein pattern for authentication. Result of the matching algorithm is not only optimized as per the proposed approach but also quite efficient.

References

  1. J. Wu, S. Ye, “Driver identification using finger-vein patterns with Radon transform and neural network”, Expert Systems with Applications, Vol. 36, pp. 5793–5799, 2009.
  2. W. Song, T. Kim, H. C. Kim, J. H. Choi, H. Kong, S. Lee, “A finger-vein verification system using mean curvature “, Pattern Recognition Letters, Vol. 32, pp.1541– 1547, 2011.
  3. J. Lee, “A novel biometric system based on palm vein image: Pattern Recognition Letters, Vol. 33, pp. 1520–1528, 2012.
  4. Y.-B. Zhang, Q. Li, J. You, and P. Bhattacharya, “Palm vein extractionand matching for personal authentication,” in International Conference on Advances in Visual Information Systems. Springer, 2007, pp. 154–164.
  5. Y. Wang, Y. Fan, W. Liao, K. Li, L.-K. Shark, and M. R. Varley, “Handvein recognition based on multiple keypoints sets,” in 2012 5th IAPR International Conference on Biometrics (ICB). IEEE, 2012, pp. 367–371.
  6. W.-Q. Yuan and W. Li, “A palm vein feature extraction method based on affine invariant,” in 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2012, pp. 2323–2326.
  7. Y.Zhang, X. Han, and S.-l. Ma, “Feature extraction of hand-vein patternsbased on ridgelet transform and local interconnection  structure neural network,” in Intelligent Computing in Signal Processing and Pattern Recognition. Springer, 2006, pp. 870–875.
  8. W.-Y. Han and J.-C. Lee, “Palm vein recognition using adaptive gabor filter,” Expert Systems with Applications, vol. 39, no. 18, pp. 13 225–13 234, 2012.
  9. A. M. Al-juboori, W. Bu, X. Wu, and Q. Zhao, “Palm vein verification using gabor filter,” International Journal of Computer Science Issues (IJCSI), vol. 10, no. 1, p. 678, 2013.
  10. J. Sun and W. Abdulla, “Palm vein recognition by combining curvelet transform and gabor filter,” in Chinese Conference on Biometric Recognition. Springer, 2013, pp. 314–321.
  11. J. Liu and Y. Zhang, “Palm-dorsa vein recognition based on two-dimensional fisher linear discriminant,” in International Conference on Image Analysis and Signal Processing, 2011, pp. 550– 552.
  12. Q. Li, Y. Zeng, X. Peng, and K. Yang, “Curvelet-based palm vein biometric recognition,” Chin. Opt. Lett., vol. 8, no. 6, pp. 577–579, Jun 2010.
  13. J. Sun and W. Abdulla, “Palm vein recognition using curvelet transform,” in Proceedings of the 27th Conference on Image and Vision Computing New Zealand, ser. IVCNZ ’12, 2012, pp. 435–439.

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Published

2020-06-30

Issue

Section

Research Articles

How to Cite

[1]
Zaheema Banu, D S Rajesh, Sheethal G, " Palm Vein based Authentication" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 3, pp.380-384, May-June-2020. Available at doi : https://doi.org/10.32628/CSEIT206379