Download presentation
Published byJanis Cameron Modified over 9 years ago
1
IQA(Image Quality Assessment) for Fake Biometric Detection
2
Vulnerability of Biometric Systems Security
introduction hypothesis method results conclusion more Vulnerability of Biometric Systems Security face recognition fingerprint iris
3
classification of attack & detection methods
introduction hypothesis method results conclusion more classification of attack & detection methods
4
requirement non-invasive user friendly fast low cost performance
introduction hypothesis method results conclusion more requirement non-invasive user friendly fast low cost performance
5
hypothesis entropy(信息熵)
introduction hypothesis method results conclusion more hypothesis It is expected that a fake image captured in an attack attempt will have different quality than a real sample acquired in the normal operation scenario for which the sensor was designed. degree of sharpness color and luminance level entropy(信息熵) structural distortion
6
none of current detection methods is general
introduction hypothesis method results conclusion more current problems none of current detection methods is general example: ridge and valley frequency amount of occlusion of eye gummy fingers made out of silicone & gelatin objection providing the method with multi-attack protection capability
7
introduction hypothesis method results conclusion more
8
introduction hypothesis method results conclusion more
9
introduction Main Page hypothesis Topic 1 method Topic 2 results Topic 3 conclusion Topic 4 more Topic 5
10
introduction hypothesis method results conclusion more
11
Edge_Based:Sobel operator
introduction hypothesis method results conclusion more Edge_Based:Sobel operator
12
SSIM(Structural Similarity Index Measure)
introduction hypothesis method results conclusion more SSIM(Structural Similarity Index Measure) contrast or brghtness changes (nonstructural disortions)
13
VIF:Visual Information Fidelity
introduction hypothesis method results conclusion more VIF:Visual Information Fidelity HVS: human visual system distortion change
14
JPEG Quality Index introduction hypothesis method results conclusion
more JPEG Quality Index
15
Experiments and Results
introduction hypothesis method results conclusion more Experiments and Results FGR:False Genuine Rate FFR:False Fake Rate HTER:HTER=(FGR+FFR)/2 AV TIME i.spoofing attack ii.synthetic sample attack iii.other methods 1.iris 2.fingerprint 3.2-D face
16
introduction hypothesis method results conclusion more
17
introduction hypothesis method results conclusion more
18
introduction hypothesis method results conclusion more
19
introduction hypothesis method results conclusion more
20
introduction hypothesis method results conclusion more
21
introduction hypothesis method results conclusion more
22
introduction hypothesis method results conclusion more
23
conclusion 1.validate the "quality difference" hypothesis
introduction hypothesis method results conclusion more conclusion 1.validate the "quality difference" hypothesis 2.show high potential of IQA for secruing biometric systems 3.proposal and validation of a new biometric protectiong method
24
introduction hypothesis method results conclusion more
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.