Open Access
Subscription Access
A Novel Approach to Address Sensor Interoperability Using Gabor Filter
Biometric authentication using fingerprint is one of the unique and reliable method of verification processes. Biometric System suffers a signiucant loss of performance when the sensor is changed during enrollment and authentication process. In this paper fingerprint sensor interoperability problem is addressed using Gaborulter and classifying images into good and poor quality. Gaborulters play an important role in many application areas for the enhancement of various types of fingerprint images. Gaborulters can remove noise, preserve the real ridges and valley structures, and it is used for fingerprint image enhancement. Experimental results on the FVC2004 databases show improvements of this approach.
Keywords
Biometrics, Fingerprint Sensor, Sensor Interoperability, Gabor Filter.
User
Font Size
Information
- R Raghavendra, Rao Ashok, and G Hemantha Kumar, “Multimodal biometric score fusion using gaussian mixture model and monte carlo method”, Journal of Computer Science and Technology, 25(4):771–782, 2010.
- Renu Bhatia, “Biometrics and face recognition techniques,” International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), vol. 3, issue5, pp. 93-99, May 2013.
- Arun Ross, Chair Lawrence Hornak, Xin Li, “Facilitating Sensor Interoperability and Incorporating Quality in Fingerprint Matching Systems”, Lane Department of Computer Science and Electrical Engineering, November 2014
- L. Shen, A. Kot, and W. Koo, “Quality measure of ûngerprint images,” in Audio - and Video-based Biometric Person Authentication (AVBPA), 2001, pp. 266–271.
- G. Vallarino, G. Gianarelli, J. Baratttini, A. Gomez, A. Fernandez, and A. Pardo, “Performance improvement in a ûngerprint classiûcation system using anisotropic diûusion,” CIARP - Iberoamerican Congress of Pattern Recognition, vol. LNCS 3287, pp. 582–588, 2004.
- F. Alonso-Fernandez, J. Fierrez-Aguilar and J. Ortega-Garcia, “An enhanced Gabor ûlterbased segmentation algorithm for ûngerprint recognition systems”, Proc. 4th Int. Symposium on Image and Signal Processing and Analysis (ISPA2), Zagreb, Croatia, pp. 239-244, 2005.
- Carsten Gottschlich, “Curved Gabor Filters for Fingerprint Image Enhancement”, arXiv: 1104.4298v2 [cs.CV] 25 Jul 2014.
- Chaohong Wu, Sergey Tulyakov and Venu Govindaraju, “Image Quality Measures for Fingerprint Image Enhancement”, Center for Uniûed Biometrics and Sensors (CUBS) SUNY at Buffalo, USA.
- Shahzad Memon, Mojtaba Sepasian, Wamadeva Balachandran, “Review of Fingerprint Sensing Technologies”, Conference Paper January 2009.
- Salil Prabhakar, Alexander Ivanisov, and Anil Jain, “Biometric recognition: sensor characteristics and image quality,” IEEE Instrumentation & Measurement Magazine, pp. 1094-6969, June 2011.
- Davide Maltoni, Dario Maio, Anil Jain, Salil, Handbook of Fingerprint Recognition, Chapter 2.
- A. Ross, K. Nandakumar, and A.K. Jain, Handbook of multibiometrics, Springer, 2006.
- Emanuela Marasco, Zachary Chapman, Bojan Cukic, “Improving Fingerprint Interoperability by Integrating Wavelet Entropy and Binarized Statistical Image Features”, 2016.
- Lugini, L.; Marasco, E.; Cukic, B.; Gashi, I.: Interoperability in Fingerprint Recognition: a Large-Scale Study. Workshop on Reliability and Security Data Analysis (RSDA), Budapest, pp. 1–6, June 2013.
- Marasco, E.; Lugini, L.; Cukic, B.: Minimizing the Impact of Low Interoperability between Optical Fingerprint Sensors. Biometrics: Theory, Applications and Systems (BTAS), pp. 1–8, 2013.
- Marasco, E.; Lugini, L.; Cukic, B.: Automatic Enhancement of Interoperability between Optical Fingerprint Sensors. NIST International Biometric Performance Testing Conference (IBPC), 2014.
- Satish kumar Chavan, Parth Mundada, Devendra Pal, “Fingerprint Authentication using Gabor Filter based Matching Algorithm”, 2015 International Conference on Technologies for Sustainable Development (ICTSD2015), Feb. 04 – 06, 2015, Mumbai, India.
- Sunpreet Singh Arora, “fingerprint recognition: contributions to latent matching and 3d fingerprint target generation”, Michigan State University in partial fulûllment of the requirements for the degree of Computer Science – Doctor of Philosophy 2016.
- Lu Yang, Gongping Yang, Lizhen Zhou, Yilong Yin, “Super pixel based finger vein roi extraction with sensor interoperability,” IEEE International Conference on Advances in Biometric (ICB) 2015, pp. 444-451, May 19-22, 2015.
Abstract Views: 224
PDF Views: 2