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

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  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]

2009 (5)

B. Kang and K. Park, “Multimodal biometric authenticationbased on the fusion of finger vein and finger geometry,”Opt. Eng. 48, 090501 (2009).
[CrossRef]

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]

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]

X. Pan and Q. Ruan, “Palmprint recognition using Gabor-basedlocal invariant features,” Neurocomputing 72, 2040-2045(2009).
[CrossRef]

V. Struc and N. Pavesic, “Phase congruency features forpalm-print verification,” IET Signal Processing 3, 258-268(2009).
[CrossRef]

2008 (1)

W. Jia, D. Huang, and D. Zhang, “Palmprint verificationbased on robust line orientation code,” Pattern Recognition41, 1504-1513 (2008).
[CrossRef]

2007 (2)

M. Ekinci and M. Aykut, “Gabor-based kernel PCA forpalmprint recognition,” Electron. Lett. 43, 1077-1079 (2007).
[CrossRef]

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.

2006 (1)

D. Zhang, X. Jing, and J. Yang, Biometric Image DiscriminationTechnologies (Idea Group Publishing, USA, 2006), Chapter 1.

2005 (3)

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.

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]

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]

2004 (2)

A. Kong and D. Zhang, “Competitive coding scheme forpalmprint verification,” in Proc. The 17th ICPR (Cambridge,UK, August 2004), pp. 520-523.

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.

2003 (6)

X. Wu, D. Zhang, and K. Wang, “Fisherpalms basedpalmprint recognition,” Pattern Recognition Letters 24, 2829-2838(2003).
[CrossRef]

D. Zhang, W. Kong, J. You, and M. Wong, “Onlinepalmprint identification,” IEEE Transactions on PAMI 25,1041-1050 (2003).
[CrossRef]

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.

G. Lu, D. Zhang, and K. Wang, “Palmprint recognitionusing eigenpalms features,” Pattern Recognition Letters 24,1463-1467 (2003).
[CrossRef]

L. Huang, A. Shimizu, Y. Hagihara, and H. Kobatake,“Gradient feature extraction for classification-based facedetection,” Pattern Recognition 36, 2501-1511 (2003).
[CrossRef]

J. Daugman, “The importance of being random: statisticalprinciples of iris recognition,” Pattern Recognition 36,279-291 (2003).
[CrossRef]

1971 (1)

R. Kirsch, “Computer determination of the constituent structureof biological images,” Computers & Biomedical Research4, 315-328 (1971).
[CrossRef]

Computers & Biomedical Research (1)

R. Kirsch, “Computer determination of the constituent structureof biological images,” Computers & Biomedical Research4, 315-328 (1971).
[CrossRef]

Electron. Lett. (1)

M. Ekinci and M. Aykut, “Gabor-based kernel PCA forpalmprint recognition,” Electron. Lett. 43, 1077-1079 (2007).
[CrossRef]

IEEE Transactions on PAMI (2)

D. Zhang, W. Kong, J. You, and M. Wong, “Onlinepalmprint identification,” IEEE Transactions on PAMI 25,1041-1050 (2003).
[CrossRef]

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]

IET Signal Processing (1)

V. Struc and N. Pavesic, “Phase congruency features forpalm-print verification,” IET Signal Processing 3, 258-268(2009).
[CrossRef]

Journal of Computer Science and Technology (1)

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]

Journal of the Optical Society of Korea (1)

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]

Neurocomputing (1)

X. Pan and Q. Ruan, “Palmprint recognition using Gabor-basedlocal invariant features,” Neurocomputing 72, 2040-2045(2009).
[CrossRef]

Opt. Eng. (2)

B. Kang and K. Park, “Multimodal biometric authenticationbased on the fusion of finger vein and finger geometry,”Opt. Eng. 48, 090501 (2009).
[CrossRef]

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]

Pattern Recognition (3)

W. Jia, D. Huang, and D. Zhang, “Palmprint verificationbased on robust line orientation code,” Pattern Recognition41, 1504-1513 (2008).
[CrossRef]

L. Huang, A. Shimizu, Y. Hagihara, and H. Kobatake,“Gradient feature extraction for classification-based facedetection,” Pattern Recognition 36, 2501-1511 (2003).
[CrossRef]

J. Daugman, “The importance of being random: statisticalprinciples of iris recognition,” Pattern Recognition 36,279-291 (2003).
[CrossRef]

Pattern Recognition Letters (2)

X. Wu, D. Zhang, and K. Wang, “Fisherpalms basedpalmprint recognition,” Pattern Recognition Letters 24, 2829-2838(2003).
[CrossRef]

G. Lu, D. Zhang, and K. Wang, “Palmprint recognitionusing eigenpalms features,” Pattern Recognition Letters 24,1463-1467 (2003).
[CrossRef]

Proc. The 17th ICPR (1)

A. Kong and D. Zhang, “Competitive coding scheme forpalmprint verification,” in Proc. The 17th ICPR (Cambridge,UK, August 2004), pp. 520-523.

Proc. The 2nd ICB, LNCS (1)

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.

Proc. The 3rd ICMLC (1)

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.

Proc. The 4th AVBPA, LNCS (1)

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.

Proc. The 5th AVBPA, LNCS (1)

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.

Other (2)

D. Zhang, X. Jing, and J. Yang, Biometric Image DiscriminationTechnologies (Idea Group Publishing, USA, 2006), Chapter 1.

PolyU Palmprint Database, available at http://www4.comp.polyu.edu.hk/~biometrics/.

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