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An Efficient Face Spoofing Detection Technique for Big Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 164 - Number 3 |
| Year of Publication: 2017 |
| Authors: Shivakumar Dalali, Suresh L. |
10.5120/ijca2017913598
|
Shivakumar Dalali, Suresh L. . An Efficient Face Spoofing Detection Technique for Big Data. International Journal of Computer Applications. 164, 3 ( Apr 2017), 12-17. DOI=10.5120/ijca2017913598
Abstract
Big data refers to huge information whose quantity is beyond the capacity of the system to manage, process and capture. On the basis of the biological and behavioral characteristics of the human, information gathered from which person can be recognized and referred as biometrics. Example includes finger print, face, voice and behavioral analysis etc. Among these, face recognition will not make use of any physical contact with the biometrics system; it is more secure and effective. Hence face recognition becomes one of the best technologies in the biometrics field. Although plenty of efforts have been carried out in the field of face recognition, this work has mark with many challenges in general settings. The criteria behind the successful face recognition systems are developed only under constrained situations with small sized data bases. Hence there is necessary to work under general setting that fit to big data for face recognition. This paper, aims to increase performance and accuracy of face recognition by considering face spoofing attack (veracity). Result analysis of our proposed work ensures increase in accuracy compared to other methods.
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