Living body identification method and device based on frequency spectrum analysis, terminal and readable medium

Abstract

The embodiment of the invention discloses a living body recognition method and device based on spectrum analysis, a terminal and a computer readable medium, and the method comprises the steps: obtaining a to-be-recognized image, carrying out the face recognition of the to-be-recognized image, and obtaining a first face image region corresponding to the to-be-recognized image; obtaining a first frequency response feature vector corresponding to the first face image region through a preset feature extraction algorithm; and inputting the first frequency response feature vector into a trained target classifier, and outputting a living body recognition result corresponding to the to-be-recognized image. The living body identification method and device based on frequency spectrum analysis, the terminal and the computer readable medium are adopted. In the face recognition scene, the living body recognition result corresponding to the face in the to-be-recognized image is correspondingly detected through frequency difference of the living body and the non-living body, and the accuracy of living body recognition in the face recognition scene is improved.

Description

technical field [0001] The invention relates to the technical fields of image processing and face recognition, in particular to a method, device, terminal and computer-readable medium for living body recognition based on spectrum analysis. Background technique [0002] With the development of computer technology and artificial intelligence technology, face recognition technology has become relatively mature and widely used. For example, in many application scenarios, face recognition is used to identify user identities. Although the face recognition technology has high accuracy, there is also a problem, that is, how to detect that the image is confirmed as a real person, rather than a photo, video or other display media, or a deceptive image such as a mask; that is, in the user How to identify whether the currently detected face is alive when the face in the photo or video is used instead of the actual face. [0003] At present, there are mainly the following methods for li...

AI Technical Summary

Problems solved by technology

Although the face recognition technology has high accuracy, there is also a problem, that is, how to detect that the image is confirmed as a real person, rather than a photo, video or other display media, or a deceptive image such as a mask; that is, in the user How to identify whether the currently detected face is alive when replacing the actual face with a face in a photo or video

[0003] At present, there are mainly the following methods for live body recognition: the first one, based on actions, requires the user to actively cooperate to make specified actions, such as blinking, shaking the head, etc. This method can prevent photo spoofing, but for video or mask spoofing and other behaviors, this method has less effect; the second, based on the optical flow field, calculates the optical flow field change of the face position through several consecutive frames of images to distinguish between plane and 3D objects, but for deceptive behaviors such as masks, this method The third method is based on color texture, by analyzing the difference between the color texture of the real person and the color texture of photos, videos, masks and other images to confirm whether it is a real person. In theory, this method can identify various forms of deception, however The recognition method based on color texture in the prior art, because it cannot accurately locate the face position, loses color information when extracting LBP (Local Binary Pattern, local binary pattern) features, and does not highlight obvious position features in the calculation, there is also a problem of accurate recognition. low rate problem

[0004] That is to say, in the existing technical solution of living body recognition in the face recognition scene, there is a certain deficiency in the recognition accuracy of living body recognition

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