Paper Info
Title
Face Anti-Spoofing Based On Image Block Difference And Logistic Regression Analysis
Abstract
Face recognition is one of the most widely used physiological biometrics. However, a printed photo or smartphone recording of a face can easily be presented to a face recognition camera to gain illegitimate access to a system. This paper presents an efficient anti-spoofing approach that can detect whether the face in front of the camera is genuine or fake. The proposed method uses the difference between pairwise discrete cosine transform coefficients and logistic regression as a machine learning algorithm. The experimental results show that the proposed approach outperforms the local binary patterns method, which is a representative technique in this research field.
Year
Venue
Keywords
2015
2015 IEEE 5TH INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - BERLIN (ICCE-BERLIN)
Face anti-spoofing, image block difference, discrete cosine transform, machine learning
Field
DocType
Citations 
Facial recognition system,Computer vision,Pairwise comparison,Pattern recognition,Computer science,Local binary patterns,Discrete cosine transform,Feature extraction,Artificial intelligence,Biometrics,Logistic regression,Humanoid robot
Conference
0
PageRank 
References 
Authors
0.34
0
1
Name
Order
Citations
PageRank
Hyunho Kang185.68