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A Fingerprint Verification System Based on Triangular Matching and Dynamic Time Warping
November 2000 (vol. 22 no. 11)
pp. 1266-1276

Abstract—An effective fingerprint verification system is presented. It assumes that an existing reference fingerprint image must validate the identity of a person by means of a test fingerprint image acquired online and in real-time using minutiae matching. The matching system consists of two main blocks: The first allows for the extraction of essential information from the reference image offline, the second performs the matching itself online. The information is obtained from the reference image by filtering and careful minutiae extraction procedures. The fingerprint identification is based on triangular matching to cope with the strong deformation of fingerprint images due to static friction or finger rolling. The matching is finally validated by Dynamic Time Warping. Results reported on the NIST Special Database 4 reference set, featuring 85 percent correct verification (15 percent false negative) and 0.05 percent false positive, demonstrate the effectiveness of the verification technique.

[1] A.K. Jain, L. Hong, and R. Bolle, On-Line Fingerprint Verification IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 302-314, Apr. 1997.
[2] L. Hong, and A. Jain., "Integrating Faces and Fingerprints for Personal Identification," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, 1998, pp. 1295-1307.
[3] The Science of Fingerprints: Classification and Uses, United States Dept. Justice, Federal Bureau of Investigation, Washington, DC, rev. 12–84, 1988.
[4] S. Umeyama, "Parameterized Point Pattern Matching and its Application to Recognition of Object Families," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 2, pp. 136-144, 1993.
[5] L. Coetzee and E. C. Botha, “Fingerprint Recognition in Low Quality Images,” Pattern Recognition, vol. 26, no. 10, pp. 1,441–1,460, Oct. 1993.
[6] M. Tartagni and R. Guerrieri, “A 390dpi Live Fingerprint Imager Based on Feedback Capacitive Sensing Scheme,” Proc. 1997 IEEE Int'l Solid-State Circuit Conf., pp. 200–201, 1997.
[7] R.S. Germain, “Large Scale Systems,” Biometrics: Personal Identification in Networked Soc., A. Jain, R. Bolle, and S. Pankanti, eds., pp. 311–325, 1998.
[8] NIST Special Database 4, 8-Bit Gray Scale Images of Fingerprint Image Groups—(FIGS), Image Recognition Group, Advanced Systems Division, Computer Systems Laboratory (CSL), Nat'l Inst. Standards and Tech nology, 1992.
[9] A. Farina, Z.M. Kovács-Vajna, and A. Leone, “Fingerprint Minutiae Extraction from Skeletonized Binary Images,” Pattern Recognition, vol. 32, no. 5, pp. 877–889, 1999.
[10] H. Yahagi, S. Igaki, and F. Yamagishi, “Moving-Window Algorithm for Fast Fingerprint Verification,” Proc. 1990 Southeastcon, vol. 1, pp. 343–348, 1990.
[11] L.R. Rabiner and B.H. Juang, Fundamentals of Speech Recognition, Prentice Hall, Upper Saddle River, N.J., 1993.
[12] G.T. Candela, P.J. Grother, C.I. Watson, R.A. Wilkinson, and C.L. Wilson, PCASYS—A Pattern-Level Classification Automation System for Fingerprints, 1995.
[13] A. Kramer, M. Sabatini, R. Canegallo, M. Chinosi, P.L. Rolandi, and P. Zabberoni, “Flash-Based Programmable Nonlinear Capacitor for Switched-Capacitor Implementation of Neural Networks,” Proc. IEEE IEDM 1994, pp. 449–452, 1994.
[14] Z.M. Kovács-Vajna, “Fingerprint Minutiae Matching Architecture Based on Analog Flash Memory,” U.S.A. Patent Application, Appl. No. 123,956, filing date: 28.07.1998 (patent pending).

Index Terms:
Fingerprint, fingerprint verification, dynamic time warping, triangular matching, NIST sdb 4.
Zsolt Miklós Kovács-Vajna, "A Fingerprint Verification System Based on Triangular Matching and Dynamic Time Warping," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 11, pp. 1266-1276, Nov. 2000, doi:10.1109/34.888711
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