Results 1 to 10 of about 388 (209)
Face liveness detection using defocus. [PDF]
Sensors (Basel), 2015 In order to develop security systems for identity authentication, face recognition (FR) technology has been applied. One of the main problems of applying FR technology is that the systems are especially vulnerable to attacks with spoofing faces (e.g., 2D pictures).
Kim S, Ban Y, Lee S.
europepmc +8 more sources
Optimizing Deep CNN Architectures for Face Liveness Detection. [PDF]
Entropy (Basel), 2019 Face recognition is a popular and efficient form of biometric authentication used in many software applications. One drawback of this technique is that it is prone to face spoofing attacks, where an impostor can gain access to the system by presenting a photograph of a valid user to the sensor.
Koshy R, Mahmood A.
europepmc +7 more sources
Face liveness detection using a light field camera. [PDF]
Sensors (Basel), 2014 A light field camera is a sensor that can record the directions as well as the colors of incident rays. This camera is widely utilized from 3D reconstruction to face and iris recognition. In this paper, we suggest a novel approach for defending spoofing face attacks, like printed 2D facial photos (hereinafter 2D photos) and HD tablet images, using the ...
Kim S, Ban Y, Lee S.
europepmc +6 more sources
Face Liveness Detection Using Thermal Face-CNN with External Knowledge [PDF]
Symmetry, 2019 Face liveness detection is important for ensuring security. However, because faces are shown in photographs or on a display, it is difficult to detect the real face using the features of the face shape. In this paper, we propose a thermal face-convolutional neural network (Thermal Face-CNN) that knows the external knowledge regarding the fact that the ...
Jongwoo Seo 0001, In-Jeong Chung
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Enhanced Deep Learning Architectures for Face Liveness Detection for Static and Video Sequences. [PDF]
Entropy (Basel), 2020 Koshy R, Mahmood A.
europepmc +2 more sources
An Ensemble Model for Face Liveness Detection
CoRR, 2022 In this paper, we present a passive method to detect face presentation attack a.k.a face liveness detection using an ensemble deep learning technique. Face liveness detection is one of the key steps involved in user identity verification of customers during the online onboarding/transaction processes.
Shashank Shekhar +3 more
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Face Liveness Detection : An Overview
International Journal of Scientific Research in Science and Technology, 2021 As the world becomes more and more digitized, the threat to security grows at an alarming rate. The mass usage of technology has garnered the attention and curiosity of people with foul intentions, whose aim is to exploit this use of technology to commit theft and other heinous crimes.
Shweta Policepatil +1 more
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An Overview of Face Liveness Detection
International Journal on Information Theory, 2014 Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures
Saptarshi Chakraborty, Dhrubajyoti Das
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Face liveness detection using dynamic texture [PDF]
EURASIP Journal on Image and Video Processing, 2014 Abstract User authentication is an important step to protect information, and in this context, face biometrics is potentially advantageous. Face biometrics is natural, intuitive, easy to use, and less human-invasive. Unfortunately, recent work has revealed that face biometrics is vulnerable to spoofing attacks using cheap low-tech equipment ...
Tiago de Freitas Pereira +6 more
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International Journal of Scientific Research in Engineering and ManagementAbstract In the modern digital era, the rapid advancement of image editing and deepfake technologies has made it increasingly difficult to distinguish authentic visual content from manipulated media. The misuse of altered images poses significant risks in areas such as social media, journalism, digital forensics, and identity verification.
Ritu Chauhan +3 more
openaire +1 more source