The Community for Technology Leaders
RSS Icon
Issue No.02 - February (2011 vol.33)
pp: 209-223
Jianjiang Feng , Tsinghua University, Beijing
Anil K. Jain , Michigan State University, East Lansing and WCU Project, Korea University
Fingerprint matching systems generally use four types of representation schemes: grayscale image, phase image, skeleton image, and minutiae, among which minutiae-based representation is the most widely adopted one. The compactness of minutiae representation has created an impression that the minutiae template does not contain sufficient information to allow the reconstruction of the original grayscale fingerprint image. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. These techniques try to either reconstruct the skeleton image, which is then converted into the grayscale image, or reconstruct the grayscale image directly from the minutiae template. However, they have a common drawback: Many spurious minutiae not included in the original minutiae template are generated in the reconstructed image. Moreover, some of these reconstruction techniques can only generate a partial fingerprint. In this paper, a novel fingerprint reconstruction algorithm is proposed to reconstruct the phase image, which is then converted into the grayscale image. The proposed reconstruction algorithm not only gives the whole fingerprint, but the reconstructed fingerprint contains very few spurious minutiae. Specifically, a fingerprint image is represented as a phase image which consists of the continuous phase and the spiral phase (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 different impressions of the original fingerprint) using a commercial fingerprint recognition system. Given the reconstructed image from our algorithm, we show that both types of attacks can be successfully launched against a fingerprint recognition system.
Fingerprint synthesis, fingerprint reconstruction, interoperability, minutiae, phase image, orientation field, singularity, AM-FM.
Jianjiang Feng, Anil K. Jain, "Fingerprint Reconstruction: From Minutiae to Phase", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.33, no. 2, pp. 209-223, February 2011, doi:10.1109/TPAMI.2010.77
[1] J. Feng and A.K. Jain, "FM Model Based Fingerprint Reconstruction from Minutiae Template" Proc. Second Int'l Conf. Biometrics, pp. 544-553, June 2009.
[2] A.M. Bazen, G.T.B. Verwaaijen, S.H. Gerez, L.P.J. Veelenturf, and B.J. van der Zwaag, "A Correlation-Based Fingerprint Verification System," Proc. 11th Ann. Workshop Circuits Systems and Signal Processing, pp. 205-213, Nov. 2000.
[3] L.R. Thebaud, "Systems and Methods with Identity Verification by Comparison and Interpretation of Skin Patterns Such as Fingerprints," US Patent No. 5,909,501, 1999.
[4] J. Feng, Z. Ouyang, and A. Cai, "Fingerprint Matching Using Ridges," Pattern Recognition, vol. 39, no. 11, pp. 2131-2140, 2006.
[5] M. Hara and H. Toyama, "Method and Apparatus for Matching Streaked Pattern Image," US Patent No. 7,295,688, 2007.
[6] N.K. Ratha, R.M. Bolle, V.D. Pandit, and V. Vaish, "Robust Fingerprint Authentication Using Local Structural Similarity," Proc. Fifth IEEE Workshop Applications of Computer Vision, pp. 29-34, 2000.
[7] A.M. Bazen and S.H. Gerez, "Fingerprint Matching by Thin-Plate Spline Modelling of Elastic Deformations," Pattern Recognition, vol. 36, no. 8, pp. 1859-1867, Aug. 2003.
[8] FVC2004, the Third Int'l Fingerprint Verification Competition, http://bias.csr.unibo.itfvc2004/, 2010.
[9] M. Tico and P. Kuosmanen, "Fingerprint Matching Using an Orientation-Based Minutia Descriptor," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 1009-1014, Aug. 2003.
[10] J. Feng, "Combining Minutiae Descriptors for Fingerprint Matching," Pattern Recognition, vol. 41, no. 1, pp. 342-352, 2008.
[11] K. Asai, H. Izumisawa, K. Owada, S. Kinoshita, and S. Matsuno, "Method and Device for Matching Fingerprints with Precise Minutia Pairs Selected from Coarse Pairs," US Patent No. 4,646,352, 1987.
[12] C. Hill, "Risk of Masquerade Arising from the Storage of Biometrics," master's thesis, Australian Nat'l Univ., 2001.
[13] A. Ross, J. Shah, and A.K. Jain, "From Template to Image: Reconstructing Fingerprints from Minutiae Points," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 4, pp. 544-560, Apr. 2007.
[14] R. Cappelli, A. Lumini, D. Maio, and D. Maltoni, "Fingerprint Image Reconstruction from Standard Templates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 9, pp. 1489-1503, Sept. 2007.
[15] S.O. Novikov and G.N. Glushchenko, "Fingerprint Ridges Structure Generation Models," Proc. SPIE Int'l Workshop Digital Image Processing and Computer Graphics, pp. 270-274, 1997.
[16] J.L. Araque, M. Baena, B.E. Chalela, D. Navarro, and P.R. Vizcaya, "Synthesis of Fingerprint Images," Proc. 16th Int'l Conf. Pattern Recognition, pp. 422-425, Aug. 2002.
[17] D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition. second ed. Springer-Verlag, 2009.
[18] B.G. Sherlock and D.M. Monro, "A Model for Interpreting Fingerprint Topology," Pattern Recognition, vol. 26, no. 7, pp. 1047-1055, 1993.
[19] W. Bicz, "The Idea of Description (Reconstruction) of Fingerprints with Mathematical Algorithms and History of the Development of This Idea at Optel," Optel, , 2003.
[20] P.R. Vizcaya and L.A. Gerhardt, "A Nonlinear Orientation Model for Global Description of Fingerprints," Pattern Recognition, vol. 29, no. 7, pp. 1221-1231, 1996.
[21] A. Witkin and M. Kass, "Reaction-Diffusion Textures," ACM SIGGRAPH Computer Graphics, vol. 25, no. 4, pp. 299-308, 1991.
[22] M. Kücken and A.C. Newell, "Fingerprint Formation," J. Theoretical Biology, vol. 235, no. 1, pp. 71-83, 2005.
[23] H. Cummins and M. Midlo, Finger Prints, Palms and Soles: An Introduction to Dermatoglyphics. Dover Publications, 1961.
[24] Neurotechnology Inc., VeriFinger, http:/www.neurotechnology. com, 2010.
[25] K.G. Larkin and P.A. Fletcher, "A Coherent Framework for Fingerprint Analysis: Are Fingerprints Holograms?" Optics Express, vol. 15, pp. 8667-8677, 2007.
[26] D.C. Ghiglia and M.D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software. John Wiley and Sons, 1998.
[27] J. Bigun and G.H. Granlund, "Optimal Orientation Detection of Linear Symmetry," Proc. First Int'l Conf. Computer Vision, pp. 433-438, June 1987.
[28] J. Zhou and J. Gu, "Modeling Orientation Fields of Fingerprints with Rational Complex Functions," Pattern Recognition, vol. 37, no. 2, pp. 389-391, 2004.
[29] R.M. Goldstein, H.A. Zebker, and C.L. Werner, "Satellite Radar Interferometry: Two Dimensional Phase Unwrapping," Radio Science, vol. 23, no. 4, pp. 713-720, 1988.
[30] K.G. Larkin, "Natural Demodulation of 2D Fringe Patterns," Proc. Fourth Int'l Workshop Automatic Processing of Fringe Patterns, 2001.
[31] FVC2002, the Second Int'l Fingerprint Verification Competition, http://bias.csr.unibo.itfvc2002/, 2010.
[32] NIST Special Database 4, NIST 8-Bit Gray Scale Images of Fingerprint Image Groups (FIGS),, 2010.
[33] K. Nandakumar, A.K. Jain, and S. Pankanti, "Fingerprint-Based Fuzzy Vault: Implementation and Performance," IEEE Trans. Information Forensics and Security, vol. 2, no. 4, pp. 744-757, Dec. 2007.
[34] K.A. Nixon and R.K. Rowe, "Multispectral Fingerprint Imaging for Spoof Detection," Biometric Technology for Human Identification II, A.K. Jain and N.K. Ratha, eds., pp. 214-225. SPIE, 2005.
[35] NIST Minutiae Interoperability Exchange Test (MINEX), http://fingerprint.nist.govminex04/, 2010.
15 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool