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Journal of the Optical Society of Korea

Journal of the Optical Society of Korea

| PUBLISHED BY THE OPTICAL SOCIETY OF KOREA

  • Vol. 15, Iss. 1 — Mar. 1, 2011
  • pp: 15–21

Palmprint Verification Using Multi-scale Gradient Orientation Maps

Min-Ki Kim  »View Author Affiliations


Journal of the Optical Society of Korea, Vol. 15, Issue 1, pp. 15-21 (2011)


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Abstract

This paper proposes a new approach to palmprint verification based on the gradient, in which a palm image is considered to be a three-dimensional terrain. Principal lines and wrinkles make deep and shallow valleys on a palm landscape. Then the steepest slope direction in each local area is first computed using the Kirsch operator, after which an orientation map is created that represents the dominant slope direction of each pixel. In this study, three orientation maps were made with different scales to represent local and global gradient information. Next, feature matching based on pixel-unit comparison was performed. The experimental results showed that the proposed method is superior to several state-of-the-art methods. In addition, the verification could be greatly improved by fusing orientation maps with different scales.

© 2011 Optical Society of Korea

OCIS Codes
(070.4560) Fourier optics and signal processing : Data processing by optical means
(070.5010) Fourier optics and signal processing : Pattern recognition
(100.2000) Image processing : Digital image processing

History
Original Manuscript: December 30, 2010
Revised Manuscript: February 23, 2011
Manuscript Accepted: February 23, 2011
Published: March 25, 2011

Citation
Min-Ki Kim, "Palmprint Verification Using Multi-scale Gradient Orientation Maps," J. Opt. Soc. Korea 15, 15-21 (2011)
http://www.opticsinfobase.org/josk/abstract.cfm?URI=josk-15-1-15


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References

  1. D. Zhang, X. Jing, and J. Yang, Biometric Image DiscriminationTechnologies (Idea Group Publishing, USA, 2006), Chapter 1.
  2. B. Kang and K. Park, “Multimodal biometric authenticationbased on the fusion of finger vein and finger geometry,”Opt. Eng. 48, 090501 (2009). [CrossRef]
  3. M. Jeong, “Analysis of fingerprint recognition characteristicsbased on new CGH direct comparison method and nonlinearjoint transform correlator,” J. Opt. Soc. Korea 13, 445-450(2009). [CrossRef]
  4. A. Kumar, D. Wong, H. Shen, and A. Jain, “Personal verificationusing palmprint and hand geometry biometric,” inProc. The 4th AVBPA (Guilford, UK, June 2003), LNCS2688, pp. 668-678.
  5. A. Kong and D. Zhang, “Competitive coding scheme forpalmprint verification,” in Proc. The 17th ICPR (Cambridge,UK, August 2004), pp. 520-523.
  6. F. Yue, W. Zuo, D. Zhang, and K. Wang, “Competitivecode-based fast palmprint identification using a set ofcover trees,” Opt. Eng. 48, 067204 (2009). [CrossRef]
  7. X. Wu, K. Wang, and D. Zhang, “Palmprint authentication based on orientation code matching,” in Proc. The 5thAVBPA (New York, USA, July 2005), LNCS 3546, pp.555-562.
  8. W. Jia, D. Huang, and D. Zhang, “Palmprint verificationbased on robust line orientation code,” Pattern Recognition41, 1504-1513 (2008). [CrossRef]
  9. G. Lu, D. Zhang, and K. Wang, “Palmprint recognitionusing eigenpalms features,” Pattern Recognition Letters 24,1463-1467 (2003). [CrossRef]
  10. M. Ekinci and M. Aykut, “Gabor-based kernel PCA forpalmprint recognition,” Electron. Lett. 43, 1077-1079 (2007). [CrossRef]
  11. X. Wu, D. Zhang, and K. Wang, “Fisherpalms basedpalmprint recognition,” Pattern Recognition Letters 24, 2829-2838(2003). [CrossRef]
  12. G. Lu, K. Wang, and D. Zhang, “Wavelet based independentcomponent analysis for palmprint recognition,” in Proc.The 3rd ICMLC (Alberta, Canada, July 2004), pp. 3547-3550.
  13. Y. Han, T. Tan, and Z. Sun, “Palmprint recognition basedon directional features and graph matching,” in Proc. The2nd ICB (Seoul, Korea, August 2007), LNCS 4642, pp.1164-1173.
  14. X. Pan and Q. Ruan, “Palmprint recognition using Gabor-basedlocal invariant features,” Neurocomputing 72, 2040-2045(2009). [CrossRef]
  15. D. Zhang, W. Kong, J. You, and M. Wong, “Onlinepalmprint identification,” IEEE Transactions on PAMI 25,1041-1050 (2003). [CrossRef]
  16. V. Struc and N. Pavesic, “Phase congruency features forpalm-print verification,” IET Signal Processing 3, 258-268(2009). [CrossRef]
  17. R. Kirsch, “Computer determination of the constituent structureof biological images,” Computers & Biomedical Research4, 315-328 (1971). [CrossRef]
  18. L. Huang, A. Shimizu, Y. Hagihara, and H. Kobatake,“Gradient feature extraction for classification-based facedetection,” Pattern Recognition 36, 2501-1511 (2003). [CrossRef]
  19. PolyU Palmprint Database, available at http://www4.comp.polyu.edu.hk/~biometrics/.
  20. X. Wu, K. Wang, and D. Zhang, “Wavelet energy featureextraction and matching for palmprint recognition,” Journalof Computer Science and Technology 20, 411-418 (2005). [CrossRef]
  21. J. Daugman, “The importance of being random: statisticalprinciples of iris recognition,” Pattern Recognition 36,279-291 (2003). [CrossRef]
  22. R. Snelick, U. Uludag, A. Mink, M. Indovia, and A. Jain,“Large-scale evaluation of multimodal biometric authenticationusing state-of-the-art systems,” IEEE Transactions onPAMI 27, 450-455 (2005). [CrossRef]

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