We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

Biometrics Fingerprint Recognition using Discrete Cosine Transform (DCT)

by Muzhir Shaban Al-ani, Wasan M. Al-aloosi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 6
Year of Publication: 2013
Authors: Muzhir Shaban Al-ani, Wasan M. Al-aloosi
10.5120/11849-7598

Muzhir Shaban Al-ani, Wasan M. Al-aloosi . Biometrics Fingerprint Recognition using Discrete Cosine Transform (DCT). International Journal of Computer Applications. 69, 6 ( May 2013), 44-48. DOI=10.5120/11849-7598

@article{ 10.5120/11849-7598,
author = { Muzhir Shaban Al-ani, Wasan M. Al-aloosi },
title = { Biometrics Fingerprint Recognition using Discrete Cosine Transform (DCT) },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 6 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 44-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number6/11849-7598/ },
doi = { 10.5120/11849-7598 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:32.570669+05:30
%A Muzhir Shaban Al-ani
%A Wasan M. Al-aloosi
%T Biometrics Fingerprint Recognition using Discrete Cosine Transform (DCT)
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 6
%P 44-48
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biometric systems based on the fingerprint recognition are considered one of the most important identification techniques. It is a successful way to determine the identity of the person that cannot be faked or stolen easily. This study aims to identify fingerprint images through several steps and extract the features based on DCT technique. The fingerprint image is divided into sub-blocks and allows evaluating the statistical features from the DCT Coefficients . The matching process is implemented using the correlation between fingerprint images. The obtained results include an efficient recognition using DCT. These programs are implemented via MATLAB environment.

References
  1. Muzhir Sh. Al-Ani, Isra H. Al-Ani," Gait Recognition Based Improved Histogram", Journal of Emerging Trends in Computing and Information Sciences, VOL. 2, NO. 12, December 2011.
  2. Marios Savvides Carnegie Mellon CyLab & ECE, "Introduction to Biometric Recognition Technologies and Applications ".
  3. Jays Close, Viables "An introduction to biometrics", Motorola, Limited. Industrial Estate Basingstoke Hampshire, Rg 22, 4PG UNITED KINGDOM, August 2006.
  4. Martin Hanneghan, Biometrics and security, CMPCD1030 Computing and Society,11-2010, Liverpool John Moores University.
  5. Maltoni, D. Maio, A. K. Jain, and S. Prabhakar (Eds. ), "Handbook of Fingerprint Recognition ", 2009,second edition, Springer-Verlag.
  6. Helal. Mahmoud, "Fingerprint recognition using fractal geometry", MSc thesis, Al-Anbar University, February 2011.
  7. Abdullah . C? avus_og?lu , Salih Go¨rgu¨nog?lu, "A fast fingerprint image enhancement algorithm using a parabolic mask ", Computers and Electrical Engineering ,34 (2008) .
  8. Emanuela Marasco a,b, Carlo Sansone Pattern Recognition Letters,"Combining perspiration- and morphology-based static features for fingerprint livens detection", 33 (2012) 1148–1156.
  9. Lavanya B N1 and K B Raja1, "Performance Evaluation of Fingerprint Identification Based on DCT and DWT using Multiple Matching Techniques". IJCSI International Journal of Computer Science Issues, Vol. 8, No 1, 2011.
  10. Raju Rajkumar1, K Hemachandran2, "A Secondary Fingerprint Enhancement and Minutiae Extraction", Department of Computer Science, Assam University, Silchar, India, 2009.
  11. Ramachandra A C, K B Raja, Venugopal K R, L M Patnaik, " Non Minitia Fingerprint Recognition based on Segmentation ", International Journal of Issue-Innovative Technology and Exploring Engineering (IJITEE) , Vol. 1, July 2012.
  12. Indra Devi," Efficient Fingerprint Recognition Through Improvement of Feature Level Clustering ", Indexing and Matching Using Discrete Cosine Transform, Indra Ganesan College of Engineering, Tiruchirappalli ,India 2010.
  13. Asker M. Bazen, "Fingerprint Identification - Feature Extraction, Matching, and Database Search", August 19, 2002.
  14. Kulwinder Singh, Kiranbir Kaur, Ashok Sardana , "Fingerprint Feature Extraction ", Gulzar Group of Institutes, Khanna, Punjab, India 2010.
  15. T. Liu, G. Zhu, C. Zhang and P. Hao, "Fingerprint indexing based on Singular points ", International Conference on Image Processing 3, Septembe 2005.
  16. Allam Mousa & Zain S. " Barham Fingerprint Recognition using MATLAB", Graduation project Prepared, d voice characteristics.
  17. Fayadh, Adnan Maroof, Abed "Fingerprint image Pre- post processing Methods for minutiae extraction ". College of Computer and mathematics science. Tikrit University.
  18. Lin Hong, Student Member, IEEE, Yifei Wan, and Anil Jain, Fellow, IEEE," Fingerprint Image Enhancement", IEEE transaction on pattern analysis and machine intelligence, vol. 20, no. 8, august, 1998.
  19. Hafiz Imtiaz, Shubhra Aich, Shaikh Anowarul Fattah," A Novel Pre-processing Technique for DCT-domain Palm-print Recognition", International Journal of Scientific & Technology Research Volume 1, Issue 3, 2012.
  20. Kim-chyan Gan," Discrete Cosine Transform Basics ", Freescale Semiconductor Application Note, 11/2004
Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Fingerprint Recognition Feature Extraction DCT