Texture and quality analysis for face spoofing detection

With the wide applications of face recognition techniques, spoofing detection is playing an important role in the security systems and has drawn much attention. This research presents a multispectral face anti-spoofing method working with both visible (VIS) and near-infrared (NIR) spectra imaging, which exploits VIS–NIR image consistency for spoofing detection. First, we use part-based methods to extract illumination robust local descriptors, and then the consistency is calculated to perform spoofing detection. In order to further exploit multispectral correlation in local patches and to be free from manually chosen regions, we learn a confidence factor map for all the patches, which is used in final classifier. Experimental results of self-collected datasets, public Msspoof and PolyU-HSFD datasets show that the proposed approach gains promising results for both intra-dataset and cross-dataset testing scenarios, and that our method can deal with different illumination and both photo and screen spoofing.

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Video Based Face Spoofing Detection Using Fourier Transform and Dense-SIFT

Journal of KIISE ◽

10.5626/jok.2015.42.4.483 ◽

2015 ◽

Vol 42 (4) ◽

pp. 483-486

Author(s):

Hotaek Han ◽

Unsang Park

Keyword(s):

Fourier Transform ◽

Spoofing Detection ◽

Face Spoofing

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Detection of Face Spoofing using Color Texture and Edge Features

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.e1008.0285s20 ◽

2020 ◽

Vol 8 (5S) ◽

pp. 33-37

Keyword(s):

Recognition System ◽

Replay Attack ◽

Authorized User ◽

Detection Techniques ◽

Detection Approach ◽

Spoofing Detection ◽

Wide Scale ◽

Edge Features ◽

Face Spoofing ◽

Color Texture

The wide scale use of facial recognition systems has caused concerns about spoofing attacks. Security is essential requirement for a face recognition system to provide reliable protection against spoofing attacks. Spoofing happens in situations where someone tries to behave as an authorized user to obtain illicitly access the protected system to gain advantage over it. In order to identify spoofing attacks, face spoofing detection approaches have been used. Traditional face spoofing detection techniques are not good enough as most of them focus only on the gray scale information and discarding the color information. Here a face spoofing detection approach with color texture and edge analysis is presented. The approach for investigating the texture of input images, Local binary pattern and Edge Histogram descriptor are proposed. Experiments on a publicly available dataset, Replay attack, showed excellent results compared to existing works.

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