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Fingerprint Synthesis

Fingerprint Synthesis. An Hong Tran. Outline. Introduction Haar Wavelet Transform Fingerprint Synthesis Application Results Conclusion. Introduction. Verification Test Large Database Use Parameter Varying techniques New approach Extract features from parents. Decomposition.

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Fingerprint Synthesis

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  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. Decomposition Reconstruction F C F D Haar Wavelet Transform

  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

  10. 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

  13. Fingerprint Synthesis Application – O-map switch

  14. 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

  17. Fingerprint Synthesis Application – O-map manip

  18. Fingerprint Synthesis Application – O-map manip

  19. Fingerprint Synthesis Application – O-map manip

  20. 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

  23. Fingerprint Synthesis Application – O-map merge

  24. Fingerprint Synthesis Application – O-map merge

  25. Fingerprint Synthesis Application – O-map merge

  26. Fingerprint Synthesis Application – O-map merge

  27. Result • Nnew = N + 3Σk=2NCk , • Nnewis the number of sample in the new database, • Nis number of original samples • NCkis the Combination operation,6C2 = 15. • Nnew = N + 3(2n – 1)

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

  29. References • 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. • A. Adler, “Can Images Be Regenerated from Biometric Templates,” Proc. Biometrics Consortium Conf., Sept. 2003. • R. Cappelli, “Synthetic Fingerprint Generation,” Handbook of Fingerprint Recognition, D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, eds., Springer, 2003. • Anil K. Jain , David Maltoni, Handbook of Fingerprint Recognition, Springer-Verlag New York, Inc., Secaucus, NJ, 2003 • B. Sherlock and D. Monro, “A Model for Interpreting Fingerprint Topology”, in Pattern Recognition, v. 26, no. 7, 1993, pp. 1047-1095. • P. Vizcaya and L. Gerhardt, “A Nonlinear Orientation Model for Global Description of Fingerprints”, in Pattern Recognition, V29, no. 7, 1996, pp. 1221-1231. • S. Yanushkevich, V. Shmerko, and D. Popel, Biometric Inverse Problem, CRC Press, 2005.

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