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

by A. S. Falohun, O. D. Fenwa, F. A. Ajala
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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.

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Index Terms

Computer Science
Information Sciences

Keywords

Authentication Histogram equalization Ridge Gender Age.

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