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Published in:

Volume 4 Issue 7
July-2017
eISSN: 2349-5162

Unique Identifier

JETIR1707027

Page Number

141-143

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Title

REAL TIME FACE SPOOF DETECTION

ISSN

2349-5162

Cite This Article

"REAL TIME FACE SPOOF DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 7, page no.141-143, July-2017, Available :http://www.jetir.org/papers/JETIR1707027.pdf

Authors

Abstract

Automatic face recognition is now widely used in applications ranging from deduplication of identity to authentication of mobile payment. This popularity of face recognition has raised concerns about face spoof attacks (also known as biometric sensor presentation attacks), where a photo or video of an authorized person’s face could be used to gain access to facilities or services. While a number of face spoof detection techniques have been proposed, their generalization ability has not been adequately addressed. We propose an efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA). Four different features (specular reflection, blurriness, chromatic moment, and color diversity) are extracted to form the IDA feature vector. An ensemble classifier, consisting of multiple SVM classifiers trained for different face spoof attacks (e.g., printed photo and replayed video), is used to distinguish between genuine (live) and spoof faces. The proposed approach is extended to multiframe face spoof detection in videos using a voting-based scheme. We also collect a face spoof database, MSU mobile face spoofing database (MSU MFSD), using two mobile devices (Google Nexus 5 and MacBook Air) with three types of spoof attacks (printed photo, replayed video with iPhone 5S, and replayed video with iPad Air). Experimental results on two public-domain face spoof databases (Idiap REPLAY-ATTACK and CASIA FASD), and the MSU MFSD database show that the proposed approach outperforms the state-of-the-art methods in spoof detection. Our results also highlight the difficulty in separating genuine and spoof faces, especially in cross-database and cross-device scenarios.

Key Words

FACE RECOGNITION,SPOOF DETECTION,IMAGE DISTORTION ANALYSIS

Cite This Article

"REAL TIME FACE SPOOF DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 7, page no. pp141-143, July-2017, Available at : http://www.jetir.org/papers/JETIR1707027.pdf

Publication Details

Published Paper ID: JETIR1707027
Registration ID: 170524
Published In: Volume 4 | Issue 7 | Year July-2017
DOI (Digital Object Identifier):
Page No: 141-143
ISSN Number: 2349-5162

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Cite This Article

"REAL TIME FACE SPOOF DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 7, page no. pp141-143, July-2017, Available at : http://www.jetir.org/papers/JETIR1707027.pdf




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