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Reseach Article

Person Identification using Multiple Fingerprint Matching

Published on April 2014 by K. Sindhu, L. Latha
Machine Learning: Challenges and Opportunities Ahead
Foundation of Computer Science USA
MLCONF - Number 1
April 2014
Authors: K. Sindhu, L. Latha
48258db6-267f-436a-acdb-a58991832266

K. Sindhu, L. Latha . Person Identification using Multiple Fingerprint Matching. Machine Learning: Challenges and Opportunities Ahead. MLCONF, 1 (April 2014), 27-30.

@article{
author = { K. Sindhu, L. Latha },
title = { Person Identification using Multiple Fingerprint Matching },
journal = { Machine Learning: Challenges and Opportunities Ahead },
issue_date = { April 2014 },
volume = { MLCONF },
number = { 1 },
month = { April },
year = { 2014 },
issn = 0975-8887,
pages = { 27-30 },
numpages = 4,
url = { /proceedings/mlconf/number1/16136-1014/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Machine Learning: Challenges and Opportunities Ahead
%A K. Sindhu
%A L. Latha
%T Person Identification using Multiple Fingerprint Matching
%J Machine Learning: Challenges and Opportunities Ahead
%@ 0975-8887
%V MLCONF
%N 1
%P 27-30
%D 2014
%I International Journal of Computer Applications
Abstract

In biometric security system still fingerprint authentication is a challenging task for the altered and compressed images. Apart from the Automatic Fingerprint Identification System(AFIS), the altered, blurred and compressed images are still having quality issues. This paper presents an efficient multi-model biometric system based on multiple fingerprint images which includes altered fingerprint images also. The system utilizes fingerprint scanner to simultaneously collect fingerprints of multiple fingers on a hand in one image. The collected multi-finger images are first segmented to get individual fingers. Quality of each individual finger is analysed and its minutiae points are extracted. The minutiae points of each finger is extracted from multiple fingerprint images and compared with the corresponding individual finger of the input fingerprint image to get matching score of that finger. Matching score between two or more fingerprint images is obtained by fusing matching scores of various fingers along with their respective image quality and relative accuracies. Prediction of genuine user or impostor user is based on the fused matching score.

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Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint Altered Images Fusion Image Quality.