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Reseach Article

Fingerprint based Automatic Human Gender Identification

by Prabha, Jitendra Sheetlani, Rajmohan Pardeshi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 170 - Number 7
Year of Publication: 2017
Authors: Prabha, Jitendra Sheetlani, Rajmohan Pardeshi
10.5120/ijca2017914910

Prabha, Jitendra Sheetlani, Rajmohan Pardeshi . Fingerprint based Automatic Human Gender Identification. International Journal of Computer Applications. 170, 7 ( Jul 2017), 1-4. DOI=10.5120/ijca2017914910

@article{ 10.5120/ijca2017914910,
author = { Prabha, Jitendra Sheetlani, Rajmohan Pardeshi },
title = { Fingerprint based Automatic Human Gender Identification },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2017 },
volume = { 170 },
number = { 7 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume170/number7/28079-2017914910/ },
doi = { 10.5120/ijca2017914910 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:17:49.398785+05:30
%A Prabha
%A Jitendra Sheetlani
%A Rajmohan Pardeshi
%T Fingerprint based Automatic Human Gender Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 170
%N 7
%P 1-4
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Human beings have unique and distinct characteristics which are helpful to distinguish one human being from another and thus acts as form of identification. Biometric allows us to identify individuals based on some anatomical structures of body such as fingerprints, face , hand-geometry ear and iris etc. Addition to this soft biometric traits such as gender, age and eye color, voice, accent etc. soft biometric traits help to support traditional biometrics by adding some extra meaningful information. In this context, gender identification becomes a significant task to improve the biometric systems[2]. Gender identification plays a vital role in many applications like human computer interaction, content based indexing, decision making, searching, surveillance and demographic studies. In this paper, we present multi-resolution features based method for gender identification using fingerprints. Our method involves three main steps preprocessing, feature extraction and classification. To do preprocessing we employed contrast limited adaptive histogram equalization, discrete wavelet transform for multi-resolution based feature extraction and classification using feed forward back propagation neural network. In our experiments, we have achieved progressive results on dataset of 750 fingerprints.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Discrete Wavelet Transform fingerprints Automatic Gender Identification Back Propagation Neural Networks