Face recognition method and device based on facial veins
A face recognition and face technology, applied in the field of biometrics, can solve problems such as copying, achieve the effects of improving expression ability, efficient learning, and improving robustness
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Embodiment 1
[0055] Refer to attached figure 1 Shown, the present invention relates to a kind of face recognition method in conjunction with facial vein, and it comprises the following steps:
[0056] 1) Image acquisition and preprocessing: use infrared camera and RGB camera to collect 50 facial vein images and face images of 1000 people respectively, and fuse the facial vein images and face photos, that is, the single-channel facial vein images captured by the infrared camera Image and the three-channel face image captured by the RGB camera are merged to form a new four-dimensional face image, forming a live face image; the collected and preprocessed live face vein image is as follows: figure 2 shown. Then randomly select 500 people from these 1000 people, collect 50 non-living face images and facial vein images from their photos or screens according to the same method, and also perform merging operations to form non-living face images. After collection and preprocessing Non-living fa...
Embodiment 2
[0094] Refer to attached Figure 4 As shown, the present invention also relates to a face recognition device combined with facial veins, which includes:
[0095] 1) The image acquisition and preprocessing module is used for image acquisition and preprocessing, that is, the infrared camera is used to collect facial vein images, the RGB camera is used to collect living face images and non-living face images, and the facial vein images and face photos are processed. Fusion to form preprocessed living face images and non-living face images; the image acquisition and preprocessing module is used to realize the function of step 1) of embodiment 1.
[0096] 2) The network improvement module is used to improve the convolutional neural network, that is, for the convolutional neural network IResNet50, an attention mechanism is added to the channel of each residual block; the network improvement module is used to implement step 2 of Example 1 ) function.
[0097] 3) The training module...
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