CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Fingerprint-based Age and Gender Detector System using Fingerprint Pattern Analysis

by A. S. Falohun, O. D. Fenwa, F. A. Ajala
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 4
Year of Publication: 2016
Authors: A. S. Falohun, O. D. Fenwa, F. A. Ajala
10.5120/ijca2016908474

A. S. Falohun, O. D. Fenwa, F. A. Ajala . A Fingerprint-based Age and Gender Detector System using Fingerprint Pattern Analysis. International Journal of Computer Applications. 136, 4 ( February 2016), 43-48. DOI=10.5120/ijca2016908474

@article{ 10.5120/ijca2016908474,
author = { A. S. Falohun, O. D. Fenwa, F. A. Ajala },
title = { A Fingerprint-based Age and Gender Detector System using Fingerprint Pattern Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 4 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number4/24145-2016908474/ },
doi = { 10.5120/ijca2016908474 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:09.839352+05:30
%A A. S. Falohun
%A O. D. Fenwa
%A F. A. Ajala
%T A Fingerprint-based Age and Gender Detector System using Fingerprint Pattern Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 4
%P 43-48
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Humans have distinctive and unique traits which can be used to distinguish them thus, acting as a form of identification. Biometrics identify people by measuring some aspect of individual’s anatomy or physiology such as hand geometry or fingerprint which consists of a pattern of interleaved ridges and valleys. The year 2015 election in Nigeria was greeted by some petitions including under-aged voters. The need for an age and gender detector system is a major concern for organizations at all levels where integrity of information cannot be compromised. This work developed a system that determines human age-range and gender using fingerprint analysis trained with Back Propagation Neural Network (for gender classification) and DWT+PCA (for age classification). A total of 280 fingerprint samples of people with various age and gender were collected. 140 of these samples were used for training the system’s Database; 70 males and 70 females respectively. This was done for age groups 1-10, 11-20, 21-30, 31-40, 41-50, 51-60 and 61-70 accordingly. In order to determine the gender of an individual, the Ridge Thickness Valley Thickness Ratio (RTVTR) of the person was put into consideration. Result showed 80.00 % classification accuracy for females and 72.86 % for males while 115 subjects out of 140 (82.14%) were correctly classified in age.

References
  1. Acree M.A. 1999. Is there a gender difference in fingerprint ridge density? Forensic Science International, 102: 35–44.
  2. Babler. 1991 Handbook of fingerprint recognition. Springer Verlag.
  3. Badawi Ahmed, Mohamed Mahfouz, Rimon Tadross, Richard Jantz. 2008 Fingerprint- Based Gender Classification.
  4. Cappelli R., Lumini A., Maio D., and Maltoni D. 2007 “Fingerprint Image Reconstruction from Standard Templates”, IEEE Transactions, Vol.29, pp.1489-1503.
  5. Cote Karine, Earls Christopher M, and. Lalumiere Martin L.2002 “Birth Order, Birth Interval, and Deviant Sexual Preferences Among Sex Offenders.” Sexual Abuse: A Journal of Research and Treatment, Vol. 14, No. 1.
  6. Cummins, H. 1943. Fingerprints, Palms and soles.
  7. Falohun A.S., Oke A.O., Gbadamosi O.A 2015. Development of an Electronic Attendance Biometric Registration System. International Journal of Computer Trends and Technology (IJCTT) 27(3):126-130, September 2015.
  8. Gu J., Zhou J., and Yang C. 2006 Fingerprint Recognition by combining global structure and local clues.IEEETransactionsonImageProcessing,15(7):1924{1964.
  9. Hall, J. A. Y. and Kimura D. 1994 “Dermatoglyphic Asymmetry and Sexual Orientation in Men.” Behavioral Neuroscience, 108, 1203-1206,
  10. Hicklin R. Austin, Christopher L. Reedy, 2002 “Implications of the IDENT/IAFIS Image Quality Study for Visa Fingerprint Processing”, Mitertek Systems (MTS).
  11. http://shodhganga.inflibnet.ac.in/bitstream/10603/6681/8/09_chapter2 .pdf referenced on 14 Mar. 2015.
  12. Jain A.K, Sarat C. Dass, and Karthik Nandakumar. 2004 Soft Biometric Traits for Personal Recognition Systems Proceedings of International Conference on Biometric Authentication, LNCS 3072, pp. 731-738, Hong Kong.
  13. Komarinski Peter 2004 Automated Fingerprint Identification System (AFIS) Academy Press.
  14. Kralik M., Novotny V. (2003) Epidermal Ridge Breadth: An Indicator of Age and Sex in Paleodermatoglyphics. Variability and Evolution. Vol-11; 5-30.
  15. Maltoni D. Jain A.K., Maio D. and Prabhakar S. (2003) Handbook of Fingerprint Recognition. Springer, New York.
  16. Omidiora E.O.,Ojo O.,Yekini N.A.and Tubi T.O (2012) Analysis, Design and Implementation of Human Fingerprint Patterns System “Towards Age & Gender Determination, Ridge Thickness To Valley Thickness Ratio (RTVTR) & Ridge Count On Gender Detection (IJARAI) International Journal of Advanced Research in Artificial Intelligence, Vol. 1, No. 2, 2012 pp:57-63.
Index Terms

Computer Science
Information Sciences

Keywords

Authentication Histogram equalization Ridge Gender Age.

Powered by PhDFocusTM