Palmprint Recognition Based on Minutiae Quadruplets

  • A. Tirupathi RaoEmail author
  • N. Pattabhi Ramaiah
  • C. Krishna Mohan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 460)


Palmprint recognition is a variant of fingerprint matching as both the systems share almost similar matching criteria and the minutiae feature extraction methods. However, there is a performance degradation with palmprint biometrics because of the failure of extracting genuine minutia points from the region of highly distorted ridge information with huge data. In this paper, we propose an efficient palmprint matching algorithm using nearest neighbor minutiae quadruplets. The representation of minutia points in the form of quadruplets improves the matching accuracy at nearest neighbors by discarding scope of the global matching on false minutia points. The proposed algorithm is evaluated on publicly available high resolution palmprint standard databases, namely, palmprint benchmark data sets (FVC ongoing) and Tsinghua palmprint database (THUPALMLAB). The experimental results demonstrate that the proposed palmprint matching algorithm achieves the state-of-the-art performance.


Palmprint recognition k-Nearest neighbors Minutiae and quadruplets 



We are sincerely thankful to FVC and Tsinghua university for providing data sets for research. The first author is thankful to Technobrain India Pvt Limited, for providing support in his research.


  1. 1.
  2. 2.
    Liu N, Yin Y, Zhang H: Fingerprint Matching Algorithm Based On Delauny Triangulation Net. In: Proc. of the 5th International Conference on Computer and information Technology, 591–595 (2005)Google Scholar
  3. 3.
    Jain A, Chen Y, Demirkus M: Pores and Ridges: Fingerprint Matching Using level 3 features. In Proc. of 18th International Conference on Pattern Recognition (ICPR’06), 477–480 (2006)Google Scholar
  4. 4.
    Awate, I. and Dixit, B.A.: Palm Print Based Person Identification. In Proc. of Computing Communication Control and Automation (ICCUBEA), 781–785 (2015)Google Scholar
  5. 5.
    Ito, K. and Sato, T. and Aoyama, S. and Sakai, S. and Yusa, S. and Aoki, T.: Palm region extraction for contactless palmprint recognition. In Proc. of Biometrics (ICB), 334–340 (2015)Google Scholar
  6. 6.
    George, A. and Karthick, G. and Harikumar, R.: An Efficient System for Palm Print Recognition Using Ridges. In Proc. of Intelligent Computing Applications (ICICA), 249–253 (2014)Google Scholar
  7. 7.
    D. Zhang, W.K. Kong, J. You, and M. Wong: Online Palmprint Identification. IEEE Trans. Pattern Analysis and Machine Intelligence 25(9), 1041–1050 (2003)Google Scholar
  8. 8.
    W. Li, D. Zhang, and Z. Xu: Palmprint Identification by Fourier Transform. Pattern Recognition and Artificial Intelligence 16(4), 417–432 (2002)CrossRefGoogle Scholar
  9. 9.
    J. You, W. Li, and D. Zhang: Hierarchical Palmprint Identification via Multiple Feature Extraction. Pattern Recognition 35(4), 847–859 (2002)CrossRefzbMATHGoogle Scholar
  10. 10.
    N. Duta, A.K. Jain, and K. Mardia: Matching of Palmprints. Pattern Recognition Letters 23(4), 477–486 (2002)CrossRefzbMATHGoogle Scholar
  11. 11.
    A.K. Jain and J. Feng: Latent Palmprint Matching. IEEE Trans. Pattern Analysis and Machine Intelligence 31(6), 1032–1047 (2009)Google Scholar
  12. 12.
    J. Dai and J. Zhou: Multifeature-Based High-Resolution Palmprint Recognition. IEEE Trans. Pattern Analysis and Machine Intelligence 33(5), 945–957 (2011)Google Scholar
  13. 13.
    B. Dorizzi, R. Cappelli, M. Ferrara, D. Maio, D. Maltoni, N. Houmani, S. Garcia-Salicetti and A. Mayoue: Fingerprint and On-Line Signature Verification Competitions at ICB 2009. In Proc. of International Conference on Biometrics (ICB), 725–732 (2009)Google Scholar
  14. 14.
  15. 15.
    Dai, Jifeng and Feng, Jianjiang and Zhou, Jie: Robust and efficient ridge-based palmprint matching. IEEE Trans. Pattern Analysis and Machine Intelligence 34(8), 1618–1632 (2012)Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  • A. Tirupathi Rao
    • 1
    Email author
  • N. Pattabhi Ramaiah
    • 1
  • C. Krishna Mohan
    • 1
  1. 1.Visual Learning and Intelligence Lab (VIGIL), Department of Computer Science and EngineeringIndian Institute of Technology HyderabadHyderabadIndia

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