CFP last date
20 December 2024
Reseach Article

A Secure Bio- Metric Fingerprint Recognition using Neural Network

by Manpreet Kaur, Sumandeep Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 147 - Number 8
Year of Publication: 2016
Authors: Manpreet Kaur, Sumandeep Kaur
10.5120/ijca2016911142

Manpreet Kaur, Sumandeep Kaur . A Secure Bio- Metric Fingerprint Recognition using Neural Network. International Journal of Computer Applications. 147, 8 ( Aug 2016), 37-40. DOI=10.5120/ijca2016911142

@article{ 10.5120/ijca2016911142,
author = { Manpreet Kaur, Sumandeep Kaur },
title = { A Secure Bio- Metric Fingerprint Recognition using Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 147 },
number = { 8 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume147/number8/25677-2016911142/ },
doi = { 10.5120/ijca2016911142 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:51:23.915848+05:30
%A Manpreet Kaur
%A Sumandeep Kaur
%T A Secure Bio- Metric Fingerprint Recognition using Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 147
%N 8
%P 37-40
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Finger Print authentication system is one of the most common and often used bio metric analysis through which several organizations register the presence of their workers and employees. There are also some organizations in which verification of user is so critical that un-authorized access may harm the organization to a great level. So, this research work presents a unique verification system which is called finger print biometric authentication using Back Propagation Neural Network method. Mat lab 2010a version is being used to develop an algorithm. This technique can be made more reliable by using GA optimization method.

References
  1. Hartwing Fronthaler, Klaus kollreider, and Josef Bigun, “Local Features for Enhancement and Minutiae Extraction in Fingerprints”, IEEE Transactions on Image Processing, vol. 17, no, 3, pp. 354- 363, (2008).
  2. M. R. Girgisa, A. A. Sewisyb and R. F. Mansourc, “Employing Generic Algorithms for Precise Fingerprint Matching Based on Line Extraction”, Graphics, Vision and Image Procession Journal, vol. 7, pp. 51-59, (2007).
  3. Duresuoquian Miao, Qingshi Tang, and Wenjie Fu, “Fingerprint Minutiae Extraction Based on Principal Cures”, the Journal of the Pattern Recognition Letters, vol. 28, pp. 2184-2189, (2007).
  4. Luping Ji, Zhang Yi, “Fingerprint Orientation field Estimation using Ridge Protection”, The Journal of the Pattern Recognition, vol. 41, pp. 1491-1503, (2008).
  5. G.Sambasiva Rao, C. NagaRaju, L. S. S. Reddy and E. V. Prasad, “A Novel Fingerprints Identification System Based on the Edge Detection”, International Journal of Computer Science and Network Security, vol. 8, pp. 394-397, (2008).
  6. Jinwei Gu, Jie Zhou, and Chunyu Yang, “Fingerprint Recognition by Combining Global Structure and Local Cues”, IEEE Transactions on Image Processing, vol. 15, no. 7, pp. 1952 – 1964, (2006).
  7. V. Vijaya Kumari and N. Suriyanarayanan, “Performance Measure of Local Operators in Fingerprint Detection”, Academic Open Internet Journal, vol. 23, pp. 1-7, (2008).
  8. Raju Sonavane and B. S. Sawant, “Noisy Fingerprint Image Enhancement Technique for Image Analysis: A Structure Similarity Measure Approach”, Journal of Computer Science and Network Security, vol. 7 no. 9, pp. 225-230, (2007).
  9. Eric P. Kukula, Christine R. Blomeke, Shimon K. Modi, and Tephen J. Elliott, “Effect of Human Interaction on Fingerprint Matching Performance, Image Quality, and Minutiae Count”, International Conference on Information Technology and Applications, pp. 771-776, (2008).
  10. Mana Tarjoman, and Shaghayegh Zarei, “Automatic Fingerprint Classification using Graph Theory”, Proceedings of World Academy of Science, Engineering and Technology, vol. 30, pp. 831-835, (2008).
  11. Bhupesh Gour, T. K. Bandopadhyaya and Sudhir Sharma, “Fingerprint Feature Extraction using Midpoint Ridge Contour Method and Neural Network”, International Journal of Computer Science and Network Security, vol. 8, no, 7, pp. 99-109, (2008).
Index Terms

Computer Science
Information Sciences

Keywords

Neural Network Genetic Algorithm Fingerprint Verification.