Abstract
Fingerprints are now widely employed in the security fields. A typical police fingerprint database may contain millions of template fingerprints. Consequently, fingerprint indexing plays an essential role to improve the performance of matching such a huge database. In this paper, the efficient index tree based on k-plet local patterns of minutiae for fingerprint database is proposed. The proposed algorithm is of robustness since the k-plet is translation-invariant and rotation-invariant, moreover, the multipath indexing strategy is introduced at the stage of indexing. As well, it is quite fast and effective due to look-up operation instead of complex computation. The performance testing was conducted in the datasets of FVC2002 DB1, NIST DB4 and NIST DB14, which concluded that the proposed algorithm is advantageous for fingerprint indexing since it achieves a high correct index performance with a fairly low penetration rate.
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References
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, New York (2009)
Henry, E.R.: Classification and Uses of Finger Prints. HM Stationery Office, London (1905)
Liu, T., Zhu, G., Zhang, C., Hao, P.: Fingerprint indexing based on singular point correlation. In: IEEE International Conference on Image Processing, vol. 3, pp. II-293–6 (2005)
Liu, M., Jiang, X., Kot, A.: Fingerprint retrieval by complex filter responses, In: 18th IEEE International Conference on Pattern Recognition, vol. 1, p. 1042 (2006)
Wang, Y., Hu, J., Phillips, D.: A fingerprint orientation model based on 2D fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing. IEEE Trans. Pattern Anal. Mach. Intell. 29, 573–585 (2007)
Liu, M., Jiang, X., Kot, A.C.: Efficient fingerprint search based on database clustering. Pattern Recogn. 40(6), 1793–1803 (2007)
Bhanu, B., Tan, X.: Fingerprint indexing based on novel features of minutiae triplets. IEEE Trans. Pattern Anal. Mach. Intell. 25, 616–622 (2003)
Iloanusi, O., Gyaourova, A., Ross, A : Indexing fingerprints using minutiae quadruplets. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 127–133 (2011)
Cappelli, R., Ferrara, M., Maltoni, D.: Fingerprint indexing based on minutia cylinder-code. IEEE Trans. Pattern Anal. Mach. Intell. 33, 1051–1057 (2011)
Chikkerur, S., Cartwright, A.N., Govindaraju, V.: K-plet and coupled BFS: a graph based fingerprint representation and matching algorithm. In: Zhang, D., Jain, A.K. (eds.) ICB 2005. LNCS, vol. 3832, pp. 309–315. Springer, Heidelberg (2005)
Maio, D., Maltoni, D., Cappelli, R., Wayman, J.L., Jain, A.K.: FVC2002: second fingerprint verification competition. IEEE Int. Conf. Pattern Recogn. 3, 811–814 (2002)
Watson, C., Wilson, C.: Nist Special Database 4. Fingerprint Database, National Institute of Standards and Technology (1992)
Watson, C.: Nist special database 14. Fingerprint Database, National Institute of Standards and Technology (1993)
Kayaoglu, M., Topcu, B., Uludag, U.: Standard fingerprint databases: Manual minutiae labeling and matcher performance analyses, CoRR, vol.3, abs/1305.1443 (2013)
GAFIS7.0, 2012. http://www.etgoldenfinger.com/
Acknowledgments
This work was funded by the Chinese National Natural Science Foundation (11331012, 71271204, 11101420)
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Bai, C., Zhao, T., Wang, W., Wu, M. (2015). An Efficient Indexing Scheme Based on K-Plet Representation for Fingerprint Database. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9225. Springer, Cham. https://doi.org/10.1007/978-3-319-22180-9_25
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