Research Article
Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 168 - Issue 12 |
| Published: Jun 2017 |
| Authors: Bhanu Vadhwani, Vineet Khanna, Sandeep Kumar Gupta, Shubhlakshmi Agarwal |
10.5120/ijca2017913797
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Bhanu Vadhwani, Vineet Khanna, Sandeep Kumar Gupta, Shubhlakshmi Agarwal . Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System. International Journal of Computer Applications. 168, 12 (Jun 2017), 1-2. DOI=10.5120/ijca2017913797
@article{ 10.5120/ijca2017913797,
author = { Bhanu Vadhwani,Vineet Khanna,Sandeep Kumar Gupta,Shubhlakshmi Agarwal },
title = { Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 168 },
number = { 12 },
pages = { 1-2 },
doi = { 10.5120/ijca2017913797 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Bhanu Vadhwani
%A Vineet Khanna
%A Sandeep Kumar Gupta
%A Shubhlakshmi Agarwal
%T Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System%T
%J International Journal of Computer Applications
%V 168
%N 12
%P 1-2
%R 10.5120/ijca2017913797
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Ear biometric recognition is used in a lot of applications as person identification in criminal cases, investigation, and security purpose. Feature optimization stage has an important role for accuracy of correct recognition. Gabor filter have a problem of high dimension and high redundancy. Sampling filter is a problem of not reducing features optimum way. In the proposed Gabor feature extraction technique the Gabor features are filtered using proposed mean filter and obtained optimum features for ear biometric dataset.
References
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