Face Anti-spoofing in Biometric Systems
Despite the great deal of progress in face recognition, current systems are vulnerable to spoofing attacks. Several anti-spoofing methods have been proposed to determine whether there is a live person or an artificial replica in front of the camera of face recognition system. Yet, developing efficie...
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Published in | Biometric Security and Privacy pp. 299 - 321 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2016
Springer International Publishing |
Series | Signal Processing for Security Technologies |
Subjects | |
Online Access | Get full text |
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Summary: | Despite the great deal of progress in face recognition, current systems are vulnerable to spoofing attacks. Several anti-spoofing methods have been proposed to determine whether there is a live person or an artificial replica in front of the camera of face recognition system. Yet, developing efficient protection methods against this threat has proven to be a challenging task. In this chapter, we present a comprehensive overview of the state-of-the-art in face spoofing and anti-spoofing, describing existing methodologies, their pros and cons, results and databases. Moreover, after a comprehensive review of the available literature in the field, we present a new face anti-spoofing method based on color texture analysis, which analyzes the joint color-texture information from the luminance and the chrominance channels using color local binary pattern descriptor. The experiments on two challenging spoofing database exhibited excellent results. In particular, in inter-database evaluation, the proposed approach showed very promising generalization capabilities. We hope this case study stimulates the development of generalized face liveness detection. Lastly, we point out some of the potential research directions in face anti-spoofing. |
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Bibliography: | The original version of this chapter was revised: All the figures are updated. The correction to this chapter is available at https://doi.org/10.1007/978-3-319-47301-7_17 |
ISBN: | 9783319473000 331947300X |
ISSN: | 2510-1498 2510-1501 |
DOI: | 10.1007/978-3-319-47301-7_13 |