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Reseach Article

Performance Evaluation on KVKR- Face Database using Multi Algorithmic Multi Sensor Approach

Published on January 2018 by Siddharth B. Dabhade, Nagsen S. Bansod, Yogesh S. Rode, M. M. Kazi, K. V. Kale
International Conference on Cognitive Knowledge Engineering
Foundation of Computer Science USA
ICKE2016 - Number 1
January 2018
Authors: Siddharth B. Dabhade, Nagsen S. Bansod, Yogesh S. Rode, M. M. Kazi, K. V. Kale
0e9beea9-3fda-4aa3-b70c-2c71c51a44e2

Siddharth B. Dabhade, Nagsen S. Bansod, Yogesh S. Rode, M. M. Kazi, K. V. Kale . Performance Evaluation on KVKR- Face Database using Multi Algorithmic Multi Sensor Approach. International Conference on Cognitive Knowledge Engineering. ICKE2016, 1 (January 2018), 30-35.

@article{
author = { Siddharth B. Dabhade, Nagsen S. Bansod, Yogesh S. Rode, M. M. Kazi, K. V. Kale },
title = { Performance Evaluation on KVKR- Face Database using Multi Algorithmic Multi Sensor Approach },
journal = { International Conference on Cognitive Knowledge Engineering },
issue_date = { January 2018 },
volume = { ICKE2016 },
number = { 1 },
month = { January },
year = { 2018 },
issn = 0975-8887,
pages = { 30-35 },
numpages = 6,
url = { /proceedings/icke2016/number1/28946-6032/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Cognitive Knowledge Engineering
%A Siddharth B. Dabhade
%A Nagsen S. Bansod
%A Yogesh S. Rode
%A M. M. Kazi
%A K. V. Kale
%T Performance Evaluation on KVKR- Face Database using Multi Algorithmic Multi Sensor Approach
%J International Conference on Cognitive Knowledge Engineering
%@ 0975-8887
%V ICKE2016
%N 1
%P 30-35
%D 2018
%I International Journal of Computer Applications
Abstract

Biometric is emerging area in the computer science for the secure various systems. Day to day life peoples are preferred to use robust and highly acceptable security system which can surpass the human errors. Many scientists are engaged to develop strong biometric system but there are a lot of challenges in the real time application. It is observed and found that researchers are only working on too old laboratory databases such as ORL. But now a day's various cost effective data acquisition sensor are coming in the market with high resolution of data. When we are using different type of data capturing devices gives difference in performance of recognition rate. In this work we have proved that recognition rate is affected by the various sensor as well as database environment. For robust face recognition system suitable algorithms are suggested to different type of sensors.

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Index Terms

Computer Science
Information Sciences

Keywords

Face Recognition Kpca Kfa