A face anti-counterfeiting method based on face depth information and edge image fusion

Abstract

The present invention proposes a face anti-counterfeiting method based on the fusion of face depth information and edge image. The edge information and depth map information of the face image are respectively extracted through a dual-stream network, and the two types of features are fused and then learned through a feature fusion classification network. And categorized. Among them, the Sobel operator is used to extract the edge information of the face image, and the PRNe is used to obtain the three-dimensional structure information of the preprocessed face of the living object, and then the Z-Buffer algorithm is used to project the corresponding depth label of the living face. The depth information extraction network branch in the dual-stream network extracts the discriminative depth information of live and non-living faces, and uses weighted matrix and entropy loss supervision to strengthen the depth distinction between face regions and background regions. Compared with the prior art, the invention is less affected by factors such as image quality and illumination, improves the problem of high cost of extracting depth information by hardware, expands the characteristics of background information and weakens the learning of redundant noise.

Description

technical field [0001] The invention relates to a living body detection technology, in particular to a face anti-counterfeiting technology based on face depth information and edge image fusion. Background technique [0002] As the application fields of face recognition technology become more and more extensive, various challenges related to it are gradually emerging, and the security of the identity recognition system based on face biometrics has aroused widespread public concern. When a malicious attacker uses the facial information of a legitimate user to impersonate the user's identity in the form of photos or videos, the system may misidentify the attacking user and judge it as legitimate, which will pose a serious threat to identity security. In the face recognition system, face anti-counterfeiting technology is the guarantee of system security. At present, the method research on face anti-counterfeiting technology can be roughly divided into two categories: methods ba...

AI Technical Summary

Problems solved by technology

However, traditional feature methods are easily affected by lighting and image quality, and the parts involving interactive discrimination are also easily seen by replay attacks.

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