Biometric video playback attack detection method based on gray scale change
A technology of grayscale change and detection method, applied in the field of biometrics, can solve problems such as usability and reliability need to be improved, difficulty in meeting practical application requirements, poor user experience, etc.
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Embodiment 1
[0047] Take the video playback attack detection in the face recognition system as an example, the frame rate is 15fps. The specific detection process is as follows:
[0048] Step 1. Extract the relevant data of each gray level
[0049] First, the position of the sample in the video is determined by using the corresponding method in the original video, such as face detection in complex background and other technologies. From the video where the position of the face has been located, the feature points of the face are located and tracked, and the feature vector is extracted according to the coordinates of the located and tracked feature points.
[0050] The specific steps for extracting the classifiable signals above are as follows:
[0051] 1. The initial positioning of the recognized object in the video. For example, in face recognition, it is first necessary to detect faces in complex backgrounds.
[0052] 2. Select a frame of image, calculate the global average gray value...
Embodiment 2
[0060] The light source in Example 1 is changed to 808nm near-infrared light, the video acquisition device uses a common usb network camera, and other parameters and methods are the same as those in Example 1 to achieve the same recognition effect.
Embodiment 3
[0062] Using the same video sampling and lighting conditions as in Example 1, change the second step in Example 1 to calculate the global average gray value of each frame in 10 consecutive frames of pictures, denoted as G1 ~ G10, and calculate these 10 The average value of the value is G, and the average gray value of the face ROI in each frame of the 10 consecutive frames is calculated, and the average value of these 10 values is calculated as F1, and the variance of the G1~G10 sequence is calculated as Δ, set Threshold d=Δ*2. Similarly, after changing the lighting conditions, delay for 500 milliseconds, count the average gray value of the face ROI in each frame of 10 consecutive frames, and calculate the average of these 10 values as F2. Calculate the factor f according to G, F1, and F2, and compare it with the threshold d to determine the video playback attack.
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