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A Cylinder Code-Based Partial Fingerprint Matching Algorithm for Small Fingerprint Scanners

  • Xiangwen Kong
  • Yumeng Wang
  • Rongsheng Wang
  • Changlong Jin
  • Hakil Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)

Abstract

To solve the problem of partial fingerprint matching difficulty caused by very small fingerprint sensors on mobile terminals, this paper presents a Cylinder Code-based partial fingerprint matching algorithm. The algorithm is inspired by the Minutia Cylinder Code (MCC) structure, and keeps the original MCC structure characteristics while reducing data redundancy. In addition, ridge points are added in the algorithm, which solve the feature loss caused by the small size of the sensors. The proposed algorithm are tested on the FVC2002 database and compared with four well-known matching algorithms. The results show the proposed method has excellent comprehensive performance and ability to apply to light architecture that other algorithms cannot match.

Keywords

Partial fingerprint Matching Minutia cylinder code Ridge point 

Notes

Acknowledgments

This work is supported by the Natural Science Foundation of Shandong Province, China (No. ZR2014FM004).

References

  1. 1.
    Chen, Y., Jain, A.: Dots and incipients: extended features for partial fingerprint matching. In: Proceedings of the 2nd Biometrics Symposium, pp. 1–6 (2007)Google Scholar
  2. 2.
    Jain, A.K., Chen, Y., Demirkus, M.: Pores and ridges high-resolution fingerprint matching using level 3 features. IEEE Comput. Soc. 29, 15–27 (2007)Google Scholar
  3. 3.
    Kryszczuk, K.M., Drygajlo, A., Morier, P.: Extraction of level 2 and level 3 features for fragmentary fingerprints. In: Proceedings of the Second Cost Action Workshop, vol. 27, pp. 290–304 (2004)Google Scholar
  4. 4.
    Zhao, Q., Zhang, D., Zhang, L., Luo, N.: High resolution partial fingerprint alignment using pore-valley descriptors. Patt. Recogn. 43, 1050–1061 (2010)CrossRefGoogle Scholar
  5. 5.
    Yamazaki, M., Li, D., Isshiki, T., Kunieda, H.: Sift-based algorithm for fingerprint authentication on smartphone. In: Proceedings of the 6th International Conference of Information and Communication Technology for Embedded Systems, pp. 1–5 (2015)Google Scholar
  6. 6.
    Mathur, S., Vijay, A., Shah, J., Das, S., Malla, A.: Methodology for partial fingerprint enrollment and authentication on mobile devices. In: Proceedings of the 9th International Conference on Biometrics, pp. 1–8 (2016)Google Scholar
  7. 7.
    Feng, J., Ouyang, Z., Cai, A.: Fingerprint matching using ridges. Patt. Recogn. 39, 2131–2140 (2006)CrossRefGoogle Scholar
  8. 8.
    Fang, G., Srihari, S.N., Srinivasan, H.: Use of ridge points in partial fingerprint matching. In: Biometric Technology for Human Identification IV, pp. 4–35 (2007)Google Scholar
  9. 9.
    Cappelli, R., Ferrara, M., Maltoni, D.: Minutia cylinder-code: a new representation and matching technique for fingerprint recognition. IEEE Trans. Patt. Anal. Mach. Intell. 32, 2128–2141 (2010)CrossRefGoogle Scholar
  10. 10.
    Lee, W., Cho, S., Choi, H., Kim, J.: Partial fingerprint matching using minutiae and ridge shape features for small fingerprint scanners. Expert Syst. Appl. 87, 183–198 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Xiangwen Kong
    • 1
  • Yumeng Wang
    • 1
  • Rongsheng Wang
    • 1
  • Changlong Jin
    • 1
  • Hakil Kim
    • 2
  1. 1.Department of Computer ScienceShandong University at WeihaiWeihaiChina
  2. 2.School of Information and Communication EngineeringINHA UniversityIncheonKorea

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