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Accurate Palmprint Recognition Using Spatial Bags of Local Layered Descriptors

  • Yufei Han
  • Tieniu Tan
  • Zhenan Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

State-of-the-art palmprint recognition algorithms achieve high accuracy based on component based texture analysis. However, they are still sensitive to local variations of appearances introduced by deformation of skin surfaces or local contrast variations. To tackle this problem, this paper presents a novel palmprint representation named Spatial Bags of Local Layered Descriptors (SBLLD). This technique works by partitioning the whole palmprint image into sub-regions and describing distributions of layered palmprint descriptors inside each sub-region. Through the procedure of partitioning and disordering, local statistical palmprint descriptions and spatial information of palmprint patterns are integrated to achieve accurate image description. Furthermore, to remove irrelevant and attributes from the proposed feature representation, we apply a simple but efficient ranking based feature selection procedure to construct compact and descriptive statistical palmprint representation, which improves classification ability of the proposed method in a further step. Our idea is verified through verification test on large-scale PolyU Palmprint Database Version 2.0. Extensive experimental results testify efficiency of our proposed palmprint representation.

Keywords

Gabor Filter Minimum Classification Error Palmprint Image Palmprint Recognition Local Image Patch 
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.

References

  1. 1.
    Jain, A.K., Bolle, R.M., Pankanti, S. (eds.): Biometrics: Personal Identification in Networked Society. Kluwer, Norwell (1999) Google 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) Google Scholar
  3. 3.
    Wu, X.Q., Wang, K.Q., Zhang, D.: Palmprint Recognition using Directional Line Energy Feature. In: Proceedings of the 17th ICPR, vol. 4, pp. 475–478 (2004) Google Scholar
  4. 4.
    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 Systems for Video Technology 14(2), 234–243 (2004) Google Scholar
  5. 5.
    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) Google Scholar
  6. 6.
    Kong, W.K., Zhang, D.: Competitive Coding Scheme for Palmprint Verification. In: Proceedings of the 17th ICPR, vol. 1, pp. 520–523 (2004) Google Scholar
  7. 7.
    Sun, Z.N., Tan, T.N., Wang, Y.H., Li, S.Z.: Ordinal Palmprint Representation for Personal Identification. In: Proceedings of CVPR 2005, vol. 1, pp. 279–284 (2005) Google Scholar
  8. 8.
    Han, Y.F., Sun, Z.N., Tan, T.N.: Palmprint Recognition Based on Directional Features and Graph Matching. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 1164–1173. Springer, Heidelberg (2007) Google Scholar
  9. 9.
    Chen, H.F., Belhumeur, P.N., Jacobs, D.W.: In Search of Illumination Invariants. In: Proceedings of CVPR 2000, pp. I:254–261 (2000) Google Scholar
  10. 10.
    Leung, T., Malik, J.: Representing and recognizing the visual appearance of materials using three-dimensional textons. International Journal of Computer Vision 43, 29–44 (2001) Google Scholar
  11. 11.
    Yang, Y., Pedersen, J.O.: A Comparative Study on Features Selection in Text Categorization. In: Proceedings of the 14th ICML, pp. 412–420 (1997) Google Scholar
  12. 12.
    Lazebnik, S., Schmid, C., Ponce, J.: Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In: Proceedings of CVPR 2006, vol. 2, pp. 2169–2178 (2006) Google Scholar
  13. 13.
    PolyU Palmprint Database, http://www.comp.polyu.edu.hk/~biometrics/ Google Scholar
  14. 14.
    Daugman, J., Williams, G.: A Proposed Standard for Biometric Decidability. In: Proceedings of CardTech/ SecureTech Conference, Atlanta, GA, pp. 223–234 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yufei Han
    • 1
  • Tieniu Tan
    • 1
  • Zhenan Sun
    • 1
  1. 1.Center for Biometrics and Security Research, National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesChina

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