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Article:A Robust Technique to Characterize the Palmprint using Radon Transform and Delaunay Triangulation

by Amel Bouchemha, Amine Nait-Ali, Nourredine Doghmane
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 10 - Number 10
Year of Publication: 2010
Authors: Amel Bouchemha, Amine Nait-Ali, Nourredine Doghmane
10.5120/1515-1895

Amel Bouchemha, Amine Nait-Ali, Nourredine Doghmane . Article:A Robust Technique to Characterize the Palmprint using Radon Transform and Delaunay Triangulation. International Journal of Computer Applications. 10, 10 ( November 2010), 35-42. DOI=10.5120/1515-1895

@article{ 10.5120/1515-1895,
author = { Amel Bouchemha, Amine Nait-Ali, Nourredine Doghmane },
title = { Article:A Robust Technique to Characterize the Palmprint using Radon Transform and Delaunay Triangulation },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 10 },
number = { 10 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 35-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume10/number10/1515-1895/ },
doi = { 10.5120/1515-1895 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:59:24.307648+05:30
%A Amel Bouchemha
%A Amine Nait-Ali
%A Nourredine Doghmane
%T Article:A Robust Technique to Characterize the Palmprint using Radon Transform and Delaunay Triangulation
%J International Journal of Computer Applications
%@ 0975-8887
%V 10
%N 10
%P 35-42
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

For the purpose of biometric applications, we explore in this paper a new robust approach to characterizing palmprint features. Instead of processing the acquired image in the spatial domain, the proposed technique extracts palmprint features using Radon transform and a geometric Delaunay triangulation jointly. In such a process, Radon transform enables the extraction of directional characteristics from the palm of the hand. Afterwards, the most significant information is structured using Delaunay triangulation, thus providing a specific palmprint signature. In order to compare the uniqueness as well as the stability of the palmprint signature, Hausdorff distance has been used as a criterion of similarity. As will be shown in this paper, the palmprint signature is very robust even when considering a low Signal-to-Noise Ratio (SNR). Promising results are obtained from a local database containing 200 palmprint images. This technique is mainly appropriate for authentication applications.

References
  1. A. Kumar, D. Zhang, “Personal authentication using multiple palmprint representation”, Pattern Recognition, vol. 38, 2005, 1695–1704
  2. A. Kumar, K. V. Prathysha, “Personal Authentication using hand vein triangulation”, IEEE Transactions on Image Processing, vol. 18, 2009, 2127-2136.
  3. C-B. Yu, H-F. Qin, Y-Z. Cui and XQ. Hu, “Finger-Vein Image Recognition Combining Modified Hausdorff Distance with Minutiae Feature Matching”, Interdiscip Sci Comput Life Sci, vol. 1, 2009, 280–289.
  4. C-C Hana, H.L Chengb, C.L Linb and K.C. Fanb, “Personal authentication using palm-print features”, Pattern Recognition, vol. 36, 2003, 371 – 381
  5. C-H.T. Yanga, S-H. Lai and L-W. Chang, “Hybrid image matching combining Hausdorff distance with normalized gradient matching”, Pattern Recognition, vol. 40, 2007, 1173 – 1181.
  6. C. Zhao, W. Shi and Y. Deng, “A new Hausdorff distance for image matching”, Pattern Recognition Letters, vol. 26, 2005, 581–586.
  7. D.P. Huttenlocher, G.A. Klanderman and W.J. Rucklidge, “Comparing images using the Hausdorff distance”, IEEE Trans Pattern Anal Mach Intel, vol 15, n°9, 1993, 850–863.
  8. D. S Huang, W. Jia and D. Zhang, “Palmprint verification on principal lines”, Pattern Recognition, vol. 41, 2008, 1316-1328.
  9. D.V. Jadhav, R. Holambe, “Feature extraction using Radon and wavelet transforms with application to face recognition”, Neuro computing, vol.72, 2009, 1951–1959.
  10. D. Zhang, A. Kong, J. You and M. Wong, “Online palmprint identification”, IEEE Trans. Pattern Anal. Mach. Intel, vol. 25, n°9, 2003, 1041–1050.
  11. E.P. Vivek, N. Sudha, “Gray Hausdorff distance measure for comparing face images”, IEEE Transactions on Information, Forensics and Security, vol. 1, 2006, 342–349.
  12. F. Li, M. K.H. Leung and C.S. Chian, “Making Palm Print Matching Mobile”, (IJCSIS) Inter. Journal of Computer Science and Information Security, vol.6, n° 2, 2009.
  13. G. Kah Ong Michael, T. Connie and A. Beng Jin Teoh, “Touch-less palm print biometrics: Novel design and implementation”, Image and Vision Computing, vol. 26, 2008, 1551–1560.
  14. G. Lu, D. Zhang and K. Wang, “Palmprint recognition using eigenpalms features”, Pattern Recognition. Letters, vol. 24, 2003, 1463–1467.
  15. G.Y. Chen, W.F. Xie, “Pattern recognition with SVM and dual-tree complex wavelets”, Image Vis. Computing, vol. 6, 2007, 960–966.
  16. L. Zhang, D. Zhang, “Characterization of palmprints by wavelet signatures via directional context modeling”, IEEE trans. Syst. Man, and cybernetics, Part B: Cybernetics, vol. 34, n°3, 2004, 1335-1347.
  17. Q. Zhang, I. Couloiger, ”Accurate Centerline Detection and Line width estimation of thick Lines Using the Radon Transform”, IEEE Trans. On Image processing, vol. 16, n° 2, 2007, 310-316.
  18. S. Tabbone, L. Wending and J.P Salmon, “A new shape descriptor defined on the Radon transform”, in Computer Vision and Image Understanding, vol.102, 2006, 42-51.
  19. T. Connie, A.T. Beng Jin, M. Goh Kah Ong and D. Ngo Chek Ling, “An automated palmprint recognition system”, Image and Vision Computing, vol. 23, 2005, 501–515.
  20. T. UZ, G. Bebis, A. Erol and S. Prabhekar, “Minutiae- based template synthesis and matching for fingerprint authentication”, Computer vision and Image Understanding, vol. 113, 2009, 979-992.
  21. W. Jia, B.Ling, K-W. Cha and L. Heutte, “Palmprint identification using restricted fusion”, Applied Mathematics and Computation vol. 205, 2008, 927–934.
  22. W. Li, J. You, “Texture-based palmprint retrieval using a layered search scheme for personal identification”, IEEE Trans. Multimedia, vol. 7, n°5, 2005, 891–898.
  23. W. Li, L. Zhang, D. Zhang and J. Yan, “Principle line based ICP alignment for palmprint verification”, ICIP 2009, 1961-1964.
  24. X. Wang, B. Xian, J-F. Ma and X-L. Bi, “Scaling and rotation invariant analysis approach to object recognition based on Radon and Fourier–Mellin transforms”, Pattern Recognition, vol. 40, 2007, 3503-3508.
  25. X.Wang, F.X Guo, B. Xiao and J-F. Ma, “Rotation analysis and orientation estimation method for texture classification based on Radon transform analysis”, J. Vis. Commun. Image, vol. 21, 2010, 29-32.
  26. X. Wu, D. Zhang and K. Wang, “Fisherpalms based palmprint recognition”, Pattern Recognition. Letters, vol. 24, 2003, 2829–2838.
  27. Y. W. Chen, Y.Q Chen, “Invariant descriptor and retrieval for planar shapes using Radon composite features”, IEEE transaction on signal processing, vol. 56, n° 10, 2008, 4762-4771.
Index Terms

Computer Science
Information Sciences

Keywords

Biometric Palmprint Radon transform Delaunay triangulation Hausdorff distance Authentication