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Face liveness detection

Authors: Dhananjay Garud; S.S. Agrwal;

Face liveness detection

Abstract

Biometric system is widely used to recognize the authorized person based on either behavioral characteristics or physical. But this can be spoofed using various traits. Spoofing attack is nothing but attacking or harming biometric recognition system using security features to use system without permission of authorized user. These biometric systems can be easily attacked by spoofs like peoples face images, masks and videos which are easily available from social media. In the proposed work, method is discuss to detect the spoofing attack. Spoofing methods like photo, mask or video image can be easily recognized by this method. This method depends on illumination and some other characteristics of face which are used to detect spoofed face. The goal of this work is to develop a efficient protection method against these types of attacks. By last, proposed work efficiently detects the live face using illumination characteristics in MATLAB tool.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Average
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