Eigen Palmprint Authentication System Using Dimension Reduction of Singular Vector

  • Jin Soo Noh
  • Kang Hyeon Rhee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)


This paper introduces the palmprint classification and recognition method based on PCA (Principal Components Analysis) using the Palmprint Acquisition Device. And the 75dpi palmprint image which is obtained by the palmprint acquisition device is used for the effectual palmprint recognition system. PCA have been previously applied to other biometric authentication and classification tasks, but not to palmprint images. We describe how the extraction of feature in the palmprint surface using Optimized PCA. The proposed system consists of the palmprint acquisition device and the palmprint authentication algorithm.


Gabor Filter Personal Authentication Palmprint Image Palmprint Recognition Total Scatter Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Noh, J.S., Rhee, K.-H.: Palmprint Identification Algorithm Using Hu Invariant Moments. In: Wang, L., Jin, Y. (eds.) FSKD 2005. LNCS (LNAI), vol. 3614, pp. 91–94. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Zhang, D., Kong, W.K., You, J., Wong, M.: Online Palmprint Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9), 1041–1050 (2003)CrossRefGoogle Scholar
  3. 3.
    Zhang, D., Shu, W.: Two Novel Characteristics in Palmprint Verification: Datum Point Invariance and Line Feature Matching. Pattern Recognition 32(4), 691–702 (1999)CrossRefGoogle Scholar
  4. 4.
    Duta, N., Jain, A.K., Mardia, K.V.: Matching of Palmprint. Pattern Recognition Letters 23(4), 477–485 (2001)CrossRefGoogle Scholar
  5. 5.
    Li, W., Zhang, D., Xu, Z.: Palmprint Identification by Fourier Transform. International Journal of Pattern Recognition and Artificial Intelligence 16(4), 417–432 (2002)CrossRefGoogle Scholar
  6. 6.
    Lu, G., Zhang, D., Wang, K.: Palmprint Recognition Using Eigenpalms Features. Pattern Recognition Letters 24(9-10), 1463–1467 (2003)MATHCrossRefGoogle Scholar
  7. 7.
    Han, C.C., Cheng, H.L., Fan, K.C., Lin, C.L.: Personal Authentication Using Palmprint Features. Pattern Recognition 36(2), 371–381 (2003)CrossRefGoogle Scholar
  8. 8.
    Zhang, L., Zhang, D.: Characterization of Palmprints by Wavelet Signatures via Directional Context Modeling. IEEE Trans. on SMC. B 34(3), 1335–1347 (2004)Google Scholar
  9. 9.
    Zhang, D., Kong, W., You, J., Wong, M.: On-line Palmprint Identification. IEEE Trans. on PAMI 25(9), 1041–1050 (2003)Google Scholar
  10. 10.
    You, J., Kong, W.K., Zhang, D., Cheung, K.: On Hierarchical Palmprint Coding with Multi - features for Personal Identification in Large Databases. IEEE Transactions on Circuit Sys-tems for Video Technology 14(2), 234–243 (2004)CrossRefGoogle Scholar
  11. 11.
    Kong, W.K., Zhang, D.: Feature-Level Fusion for Effective Palmprint Authentication. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 761–767. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  12. 12.
    Kong, W.K., Zhang, D.: Competitive Coding Scheme for Palmprint Verification. In: Proc. of the 17th ICPR, vol. 1, pp. 520–523 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jin Soo Noh
    • 1
  • Kang Hyeon Rhee
    • 1
  1. 1.Dept. of Electronic Eng., Multimedia & Biometrics Lab.Chosun UniversityGwangju Metropolitan cityKorea(Daehanminkook)

Personalised recommendations