OPTIMIZATION OF FINGERPRINT SIZE FOR REGISTRATION
Hamid JAN
hod.csit@suit.edu.pk* Sarhad University of Science & Information Technology, Landi Akhun Ahmad, Hayatabad Link, Ring Road, Peshawar 25000 (Pakistan)
Amjad ALI
* Sarhad University of Science & Information Technology, Landi Akhun Ahmad, Hayatabad Link, Ring Road, Peshawar 25000 (Pakistan)
Abstract
The propose algorithm finds the optimal reduced size of latent fingerprint. The algorithm accelerates the correlation methods of fingerprint registration. The Algorithm is based on decomposition and reduction of fingerprint to one dimension form by using the adoptive method of empirical modes. We choose the most appropriate internal mode to determine the minimum distance between the extremes of empirical modes. We can estimate how many times the fingerprint in the first step of the comparison can be reduced so as not to lose the accuracy of registration. This algorithm shows best results as compared to conventional fingerprint matching techniques that strongly depends on local features for registration. The algorithm was tested on latent fingerprints using FVC2002, FVC2004 and FVC2006 databases.
Keywords:
optimization, correlation methods, fingerprint registration, latent fingerprint, empirical modesReferences
Bansal, R., Sehgal, P., & Bedi, P. (2011). Minutiae Extraction from Fingerprint Images – a Review. IJCSI International Journal of Computer Science Issues, 8(5), 74–85.
Google Scholar
Bazen, A., Verwaaijen, G., Gerez, S., Veelenturf, L., & Zwaag, B. (2000). A correlation-based fingerprint verification system. In: Proceedings of the Workshop on Circuits Systems and Signal Processing (pp. 205–213). Veldhoven, The Netherlands.
Google Scholar
Bhuiyan, S. M. A., Adhami, R. R., & Khan, J. F. (2008). A novel approach of fast and adaptive bidimensional empirical mode decomposition. In IEEE International Conference on Acoustics, Speech and Signal Processing (pp.1313–1316). Las Vegas, NV. https://doi.org/10.1109/CASSP.2008.4517859
DOI: https://doi.org/10.1109/ICASSP.2008.4517859
Google Scholar
Guryanov, F., & Krylov, A. S. (2017). Fast medical image registration using bidirectional empirical mode decomposition. Signal Processing: Image Communication, 59, 12–17. https://doi.org/10.1016/.image.2017.04.003
DOI: https://doi.org/10.1016/j.image.2017.04.003
Google Scholar
Yager, N., & Amin, A. (2004). Fingerprint verification based on minutiae features: a review. Pattern Analysis and Applications, 7(1), 94–113. https://doi.org/10.1007/s10044-003-0201-2
DOI: https://doi.org/10.1007/s10044-003-0201-2
Google Scholar
Jain, A., Hong, L., & Bolle, R. (1997). On-line fingerprint verification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19 (4), 302–314. https://doi.org/10.1109/34.587996
DOI: https://doi.org/10.1109/34.587996
Google Scholar
Jiang, X., & Yau, W. (2000). Fingerprint minutiae matching based on the local and global structures. In: Proceedings 15th International Conference on Pattern Recognition. ICPR-2000 (pp. 1038–1041). Barcelona, Spain. https://doi.org/10.1109/ICPR.2000.906252
DOI: https://doi.org/10.1109/ICPR.2000.906252
Google Scholar
Maes, F., Vandermeulen, D., & Suetens, P. (2003). Medical Image Registration Using Mutual Information. Proceedings of the IEEE, 91(10), 1699–1722. https://doi.org/10.1109/JPROC.2003.817864
DOI: https://doi.org/10.1109/JPROC.2003.817864
Google Scholar
Park, C., Lee, J., Smith, M., Park, S., & Park, K. (2004). Directional filter bank-based fingerprint feature extraction and matching. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 74–85. https://doi.org/10.1109/TCSVT.2003.818355
DOI: https://doi.org/10.1109/TCSVT.2003.818355
Google Scholar
Ratha, N., Karu, K., Chen, S., & Jain, A. (1996). A real-time matching system for large fingerprint databases. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(8), 799–813. https://doi.org/10.1109/34.531800
DOI: https://doi.org/10.1109/34.531800
Google Scholar
Sharat, S. C. (2005). Online fingerprint Verification System (Unpublished dissertation). University of New York Buffalo, USA.
Google Scholar
Zhao, Y., Yao, R., Ouyang, L., Ding, H., Zhang, T., Zhang, K., Cheng, S., & Sun, W. (2014). ThreeDimensional Printing of Hela Cells for Cervical Tumor Model in Vitro. Biofabrication, 6(3), 035001. https://doi.org/10.1088/1758-5082/6/3/035001
DOI: https://doi.org/10.1088/1758-5082/6/3/035001
Google Scholar
Authors
Hamid JANhod.csit@suit.edu.pk
* Sarhad University of Science & Information Technology, Landi Akhun Ahmad, Hayatabad Link, Ring Road, Peshawar 25000 Pakistan
Authors
Amjad ALI* Sarhad University of Science & Information Technology, Landi Akhun Ahmad, Hayatabad Link, Ring Road, Peshawar 25000 Pakistan
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