1. Fingerprint Synthesis An Hong Tran

2. Outline Introduction Haar Wavelet Transform Fingerprint Synthesis Application Results Conclusion

3. Introduction Verification Test  Large Database Use Parameter Varying techniques New approach  Extract features from parents

4. Haar Wavelet Transform FC D F DecompositionReconstruction

5. Haar Wavelet Transform

6. Fingerprint Synthesis Application Direct (pixel value) Orientation map (O-map) switching Orientation map (O-map) manipulation Orientation map (O-map) merging

7. Fingerprint Synthesis Application Direct (pixel value) O-map switching O-map manipulation O-map merging

8. Fingerprint Synthesis Application – Direct (a) (b)

9. Fingerprint Synthesis Application – Direct

11. Fingerprint Synthesis Application Direct (pixel value) O-map Switching O-map manipulation O-map merging

12. Fingerprint Synthesis Application – O-map switch

15. Fingerprint Synthesis Application Direct (pixel value) O-map switching O-map manipulation O-map merging

16. Fingerprint Synthesis Application – O-map manip

21. Fingerprint Synthesis Application Direct (pixel value) O-map switching O-map manipulation O-map merging

22. Fingerprint Synthesis Application – O-map merge

27. Result N new = N + 3 Σ k=2 N C k,  N new is the number of sample in the new database,  N is number of original samples  N C k is the Combination operation, 6 C 2 = 15. N new = N + 3(2 n – 1)

28. Conclusion & Future Work Show good promises. Merging features from parents. Weight Vector analysis.  Balance between uniqueness and realism.

29. References 1.Local B-spline Multiresolution with Examples in Iris Synthesis and Volumetric Rendering, Faramarz F. Samavati, Richard.H. Bartels and Luke Olsen, Image Pattern Recognition: Synthesis and Analysis in Biometrics, Series in Machine Perception and Artificial Intelligence, Vol. 67, World Scientific Publishing, 2007. 2.A. Adler, “Can Images Be Regenerated from Biometric Templates,” Proc. Biometrics Consortium Conf., Sept. 2003. 3.R. Cappelli, “Synthetic Fingerprint Generation,” Handbook of Fingerprint Recognition, D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, eds., Springer, 2003. 4.Anil K. Jain, David Maltoni, Handbook of Fingerprint Recognition, Springer-Verlag New York, Inc., Secaucus, NJ, 2003 5.B. Sherlock and D. Monro, “A Model for Interpreting Fingerprint Topology”, in Pattern Recognition, v. 26, no. 7, 1993, pp. 1047-1095. 6.P. Vizcaya and L. Gerhardt, “A Nonlinear Orientation Model for Global Description of Fingerprints”, in Pattern Recognition, V29, no. 7, 1996, pp. 1221-1231. 7.S. Yanushkevich, V. Shmerko, and D. Popel, Biometric Inverse Problem, CRC Press, 2005.