Optimization of fingerprint size for registration

• Autorzy: Jan Hamid , Ali Amjad

Identyfikatory

DOI

10.23743/acs-2019-10

• Języki publikacji: EN

Abstrakty

EN

The propose algorithm finds the optimal reduced size of latent fingerprint. he 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.

Słowa kluczowe

EN

optimization; correlation methods; fingerprint registration; latent fingerprint; empirical modes

PL

optymalizacja; metody korelacji; rejestracja odcisków palców; ukryty odcisk palca; tryby empiryczne

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2019
• Tom: Vol. 15, no 2
• Strony: 19--30
• Opis fizyczny: Bibliogr. 12 poz., fig., tab.

Twórcy

autor

Jan Hamid

• Sarhad University of Science & Information Technology, Landi Akhun Ahmad, Hayatabad Link, Ring Road, Peshawar 25000, Pakistan

autor

Ali Amjad

• Sarhad University of Science & Information Technology, Landi Akhun Ahmad, Hayatabad Link, Ring Road, Peshawar 25000, Pakista

Bibliografia

• [1] 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.
• [2] 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.
• [3] 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. doi:10.1109/ CASSP.2008.4517859
• [4] Guryanov, F., & Krylov, A. S. (2017). Fast medical image registration using bidirectional empirical mode decomposition. Signal Processing: Image Communication, 59, 12–17. doi:10.1016/ .image.2017.04.003
• [5] Yager, N., & Amin, A. (2004). Fingerprint verification based on minutiae features:a review. Pattern Analysis and Applications, 7(1), 94–113. doi:10.1007/s10044-003-0201-2
• [6] Jain, A., Hong, L., & Bolle, R. (1997). On-line fingerprint verification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19 (4), 302–314. doi:10.1109/34.587996
• [7] 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. doi: 10.1109/ICPR.2000.906252
• [8] Maes, F., Vandermeulen, D., & Suetens, P. (2003). Medical Image Registration Using Mutual Information. Proceedings of the IEEE, 91(10), 1699–1722. doi:10.1109/JPROC.2003.817864
• [9] 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. doi:10.1109/TCSVT.2003.818355
• [10] 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. doi:10.1109/34.531800
• [11] Sharat, S. C. (2005). Online fingerprint Verification System (Unpublished dissertation). University of New York Buffalo, USA.
• [12] Zhao, Y., Yao, R., Ouyang, L., Ding, H., Zhang, T., Zhang, K., Cheng, S., & Sun, W. (2014). Three-Dimensional Printing of Hela Cells for Cervical Tumor Model in Vitro. Biofabrication, 6(3), 035001. doi:10.1088/1758-5082/6/3/035001

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).