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
Statistics
Abstract views: 131PDF downloads: 14
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Most read articles by the same author(s)
- Hamid JAN, Beena HAMID, THE APPLICATION OF FINGERPRINTS AUTHENTICATION IN DISTANCE EDUCATION , Applied Computer Science: Vol. 15 No. 3 (2019)
Similar Articles
- Sergio SOTO, Edmondo BONILLA, Alberto PORTILLA, Jose C. HERNANDEZ, Oscar ATRIANO, Perfecto M. QUINTERO, FOOD DELIVERY BASED ON PSO ALGORITHM AND GOOGLE MAPS , Applied Computer Science: Vol. 16 No. 1 (2020)
- Anupa ARACHCHIGE, Ranil SUGATHADASA, Oshadhi HERATH, Amila THIBBOTUWAWA, ARTIFICIAL NEURAL NETWORK BASED DEMAND FORECASTING INTEGRATED WITH FEDERAL FUNDS RATE , Applied Computer Science: Vol. 17 No. 4 (2021)
- Marcin MACIEJEWSKI, Barbara MACIEJEWSKA, Robert KARPIŃSKI, Przemysław KRAKOWSKI, ELECTROCARDIOGRAM GENERATION SOFTWARE FOR TESTING OF PARAMETER EXTRACTION ALGORITHMS , Applied Computer Science: Vol. 16 No. 4 (2020)
- Rafał WOJSZCZYK, VERIFICATION OF ACCURACY AND COST OF USE METHODS OF QUALITY ASSESSMENT OF IMPLEMENTATION OF DESIGN PATTERNS , Applied Computer Science: Vol. 15 No. 1 (2019)
- Robert KARPIŃSKI, Anna MACHROWSKA, Marcin MACIEJEWSKI, APPLICATION OF ACOUSTIC SIGNAL PROCESSING METHODS IN DETECTING DIFFERENCES BETWEEN OPEN AND CLOSED KINEMATIC CHAIN MOVEMENT FOR THE KNEE JOINT , Applied Computer Science: Vol. 15 No. 1 (2019)
- Nawazish NAVEED, Hayan T. MADHLOOM, Mohd Shahid HUSAIN, BREAST CANCER DIAGNOSIS USING WRAPPER-BASED FEATURE SELECTION AND ARTIFICIAL NEURAL NETWORK , Applied Computer Science: Vol. 17 No. 3 (2021)
- Katarzyna GOSPODAREK, DETERMINATION OF RELATIVE LENGTHS OF BONE SEGMENTS OF THE DOMESTIC CAT'S LIMBS BASED ON THE DIGITAL IMAGE ANALYSIS , Applied Computer Science: Vol. 15 No. 2 (2019)
- Józef MATUSZEK, Tomasz SENETA, Aleksander MOCZAŁA, FUZZY ASSESSMENT OF MANUFACTURABILITY DESIGN FOR MACHINING , Applied Computer Science: Vol. 15 No. 3 (2019)
- Karolina FERYSIUK, Karolina M. WÓJCIAK, Paulina KĘSKA, Dariusz M. STASIAK, INSTRUMENTAL COLOR MEASUREMENT OF MEAT AND MEAT PRODUCTS IN X-RITECOLOR® MASTER , Applied Computer Science: Vol. 16 No. 3 (2020)
- Weronika WACH, Kinga CHWALEBA, GAP FILLING ALGORITHM FOR MOTION CAPTURE DATA TO CREATE REALISTIC VEHICLE ANIMATION , Applied Computer Science: Vol. 20 No. 3 (2024)
You may also start an advanced similarity search for this article.
