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학술지 Face Recognition Performance Comparison between Fake Faces and Live Faces
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저자
조미영, 정영숙
발행일
201706
출처
Soft Computing, v.21 no.12, pp.3429-3437
ISSN
1432-7643
출판사
Springer
DOI
https://dx.doi.org/10.1007/s00500-015-2019-4
협약과제
15PC1500, 이동/조작/HRI/통신 성능 등 서비스로봇 성능평가 및 표준화 기술 개발, 정영숙
초록
Face recognition is a widely used biometric technology because it is both user friendly and more convenient to use than other biometric approaches. However, na챦ve face recognition systems that do not support any type of liveness detection can be easily spoofed using just a photograph of a valid user. Face liveness detection is a key issue in the field of security systems that use a camera. Unfortunately, it is not easy to detect face liveness using existing methods, assuming that there are print failures and overall image blur. With the development of display devices and image capturing technology, it is possible to reproduce face images similar to real faces. Therefore, the number of attacks using a photograph or video displayed on a screen rather than paper will increase. In this study, we compare test results using live faces and high-definition face videos from light-emitting diode (LED) display devices and analyze the changes in face recognition performance according to the lighting direction. Experimental results show that there is no significant difference between live faces and not live faces under good lighting conditions. We suggest the use of gamma to reduce the performance gap between the two faces under poor lighting conditions. From these results, we can provide key solutions to resolve the issues associated with texture-based approaches.
키워드
Display device, Face authentication, Face recognition, Face video, Fake face
KSP 제안 키워드
Display device, Face Authentication, Face Image, Face Recognition system, Face Videos, Face liveness detection, High definition, Image blur, Lighting conditions, Performance comparison, Texture-based