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A New Feature Extraction Method for Recognition

J. Anne Wincy1 , Y. Jacob Vetha Raj2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-6 , Page no. 1386-1393, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i6.13861393

Online published on Jun 30, 2018

Copyright © J. Anne Wincy, Y. Jacob Vetha Raj . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: J. Anne Wincy, Y. Jacob Vetha Raj, “A New Feature Extraction Method for Recognition,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1386-1393, 2018.

MLA Style Citation: J. Anne Wincy, Y. Jacob Vetha Raj "A New Feature Extraction Method for Recognition." International Journal of Computer Sciences and Engineering 6.6 (2018): 1386-1393.

APA Style Citation: J. Anne Wincy, Y. Jacob Vetha Raj, (2018). A New Feature Extraction Method for Recognition. International Journal of Computer Sciences and Engineering, 6(6), 1386-1393.

BibTex Style Citation:
@article{Wincy_2018,
author = {J. Anne Wincy, Y. Jacob Vetha Raj},
title = {A New Feature Extraction Method for Recognition},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2018},
volume = {6},
Issue = {6},
month = {6},
year = {2018},
issn = {2347-2693},
pages = {1386-1393},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2357},
doi = {https://doi.org/10.26438/ijcse/v6i6.13861393}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.13861393}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2357
TI - A New Feature Extraction Method for Recognition
T2 - International Journal of Computer Sciences and Engineering
AU - J. Anne Wincy, Y. Jacob Vetha Raj
PY - 2018
DA - 2018/06/30
PB - IJCSE, Indore, INDIA
SP - 1386-1393
IS - 6
VL - 6
SN - 2347-2693
ER -

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Abstract

A biometric system is an automatic recognition of an individual based on physiological or behavioural characteristics. In the present study, a new method for feature extraction was proposed. The different samples of same user differ in the case of feature vectors. So detection of feature points is a vital role in the recognition system. Face, Palmprint and Finger knuckle print are the biometric traits used for this system. The features are obtained by SUSIFTGEN algorithm which gives unique feature sets. To classify the train dataset images, Support vector machine (SVM) is used. The unimodal system achieved good results but suffers from non-universality and spoofing problem. To minimize the problems occurred by unimodal, multimodal biometric system was introduced which combines the matching scores of different biometric systems. The similarity measure is used to find the matching scores of the images. The matching scores of the three biometric traits are fused at matching score level. The experimental results showed that the proposed system achieved excellent performance for the multimodal system than the unimodal

Key-Words / Index Term

Feature extraction; SUSIFTGEN; SVM; matching scores; Similarity Measure

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