Abstract
Minutiae-based representation is the most widely adopted fingerprint representation scheme. The compactness of minutiae template has created an impression that the minutiae template does not contain sufficient information to allow the reconstruction of the original fingerprint image. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. However, these reconstruction techniques have a common weak point: many spurious minutiae, not included in the original minutiae template, are generated in the reconstructed image. Moreover, some of these techniques can only reconstruct a partial fingerprint. In this paper, a novel fingerprint reconstruction algorithm is proposed, which not only reconstructs the whole fingerprint, but the reconstructed fingerprint contains very few spurious minutiae. A fingerprint image is modeled as a 2D Frequency Modulation (FM) signal whose phase consists of the continuous part and the spiral part (which corresponds to minutiae). An algorithm is proposed to reconstruct the continuous phase from minutiae. The proposed reconstruction algorithm has been evaluated with respect to the success rates of type-I attack (match the reconstructed fingerprint against the original fingerprint) and type-II attack (match the reconstructed fingerprint against the different impressions of the original fingerprint) using a commercial fingerprint recognition system. Both types of attacks were shown to be successful in deceiving the fingerprint system.
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Hill, C.: Risk of masquerade arising from the storage of biometrics. Master’s thesis, Australian National University (2001)
Ross, A., Shah, J., Jain, A.K.: From template to image: Reconstructing fingerprints from minutiae points. IEEE Trans. Pattern Analysis and Machine Intelligence 29(4), 544–560 (2007)
Cappelli, R., Lumini, A., Maio, D., Maltoni, D.: Fingerprint image reconstruction from standard templates. IEEE Trans. Pattern Analysis and Machine Intelligence 29(9), 1489–1503 (2007)
Sherlock, B.G., Monro, D.M.: A model for interpreting fingerprint topology. Pattern Recognition 26(7), 1047–1055 (1993)
Vizcaya, P.R., Gerhardt, L.A.: A nonlinear orientation model for global description of fingerprints. Pattern Recognition 29(7), 1221–1231 (1996)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, Heidelberg (2003)
Novikov, S.O., Glushchenko, G.N.: Fingerprint ridges structure generation models. In: Proc. SPIE (International Workshop on Digital Image Processing and Computer Graphics), vol. 3346, pp. 270–274 (1997)
Araque, J.L., Baena, M., Chalela, B.E., Navarro, D., Vizcaya, P.R.: Synthesis of fingerprint images. In: Proc. 16th International Conference on Pattern Recognition, pp. 422–425 (2002)
Witkin, A., Kass, M.: Reaction-diffusion textures. SIGGRAPH Computer Graphics 25(4), 299–308 (1991)
Bicz, W.: The idea of description (reconstruction) of fingerprints with mathematical algorithms and history of the development of this idea at optel (2003), http://www.optel.pl/article/english/idea.htm
Larkin, K.G., Fletcher, P.A.: A coherent framework for fingerprint analysis: are fingerprints holograms? Optics Express 15(14), 8667–8677 (2007)
Neurotechnology Inc., VeriFinger, http://www.neurotechnology.com
Ghiglia, D.C., Pritt, M.D.: Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software. John Wiley and Sons, New York (1998)
FVC 2002: The Second International Competition for Fingerprint Verification Algorithms, http://bias.csr.unibo.it/fvc2002/
NIST SD4: NIST 8-Bit gray scale images of fingerprint image groups (FIGS), http://www.nist.gov/srd/nistsd4.htm
Nandakumar, K., Jain, A.K., Pankanti, S.: Fingerprint-based fuzzy vault: implementation and performance. IEEE Trans. Information Forensics and Security 2(4), 744–757 (2007)
Nixon, K.A., Rowe, R.K.: Multispectral fingerprint imaging for spoof detection. In: Proc. SPIE (Biometric Technology for Human Identification II), vol. 5779, pp. 214–225 (2005)
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Feng, J., Jain, A.K. (2009). FM Model Based Fingerprint Reconstruction from Minutiae Template. In: Tistarelli, M., Nixon, M.S. (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_56
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DOI: https://doi.org/10.1007/978-3-642-01793-3_56
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