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Correlation filter based fingerprint Verification System

Published on None 2011 by Suvarna Joshi, Dr. Abhay Kumar
journal_cover_thumbnail

International Conference on VLSI, Communication & Instrumentation
Foundation of Computer Science USA
ICVCI - Number 15
None 2011
Authors: Suvarna Joshi, Dr. Abhay Kumar
adf37077-ea56-4071-b6e9-8945fc8bcf05

Suvarna Joshi, Dr. Abhay Kumar . Correlation filter based fingerprint Verification System. International Conference on VLSI, Communication & Instrumentation. ICVCI, 15 (None 2011), 19-22.

@article{
author = { Suvarna Joshi, Dr. Abhay Kumar },
title = { Correlation filter based fingerprint Verification System },
journal = { International Conference on VLSI, Communication & Instrumentation },
issue_date = { None 2011 },
volume = { ICVCI },
number = { 15 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 19-22 },
numpages = 4,
url = { /proceedings/icvci/number15/2742-1563/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on VLSI, Communication & Instrumentation
%A Suvarna Joshi
%A Dr. Abhay Kumar
%T Correlation filter based fingerprint Verification System
%J International Conference on VLSI, Communication & Instrumentation
%@ 0975-8887
%V ICVCI
%N 15
%P 19-22
%D 2011
%I International Journal of Computer Applications
Abstract

Biometrics is an important security tool which can be used for Human identification and authentication to offer a higher level of security than conventional identification methods. Among all available biometrics, Fingerprints are a good choice as they are unique to a person. Fingerprint recognition is a complex pattern recognition problem. This paper proposes fingerprint verification based on correlation filters because of their properties shift invariance, ability to accommodate in-class image variability and closed form expressions. The performance of a specific type of correlation filter called the minimum average correlation energy (MACE) filter [1] has been evaluated using a FVC database.

References
  1. A. Mahalanobis, B.V.K. Vijaya Kumar, and D.Casasent, “Minimum average correlation energy filters,” Appl. Opt. 26, pp. 3633-3630 (1987).
  2. A. Jain, Lin Hong and R. Bolle, "On-Line Fingerprint Verification," IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 19, Issue 4, 302-314, 1997.
  3. A. Jain, Lin Hong, S. Pankati and R. Bolle, "An Identity-Authentication System Using Fingerprints," Proceedings Of The IEEE, Vol. 85, Issue: 9, 1365-1388, 1997.
  4. Xudong Jiang, We Yun Yau and Wee Ser, 1999. Minutiae Extraction By Adaptive Tracing The Gray Level Ridge Of The Fingerprint Image.International Conference On Image Processing,Vol. 2,852-856,.
  5. A. Mahalanobis, D. W. Carlson, and B.V.K. Vijaya Kumar, “Evaluation of MACH and DCCF correlation filters for SAR ATR using MSTAR public database,”Algorithms for Synthetic Aperture Radar Imagery V (E. G. Zelnio, ed.), Vol. 3370, pp. 460-468, Photo-Opt.Instrum. Eng, (1998).
  6. C. F. Hester and D. Casasent, 1980.Multivariant technique for multiclass pattern recognition, Appl. Opt. 19,pp.1758-1761
  7. M. Savvides, and BVK VijayaKumar,2003. Efficient Design of Advanced Correlation Filters for Robust Distortion-Tolerant Face Identification, Proc. IEEE International Conference on Advanced Video and Signal Based Surveillance (AVVS), pp. 45-52,.
  8. B.V.K. Vijaya Kumar, "Minimum Variance Synthetic discriminant Functions," J.Opt. Soc.Am.-A, Vol. 3, 1579-1584, 1986.
  9. A. Mahalanobis, B.V.K. Vijaya Kumar, and I). Casasent, "Minimum Average Correlation Energy Filters," Applied Optics, Vol.26, 3633-3640, 1987.
  10. http://bias.csr.unibo.it/fvc2000/databases.asp
Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint Recognition correlation filter Minimum average correlation energy