Image recognition method, system and apparatus for feature distribution of face tampered image

Abstract

The invention belongs to the field of image recognition, particularly relates to an image recognition method, system and apparatus for feature distribution of a face tampered image, and aims to solve the problem that the recognition accuracy of the tampered image is insufficient due to the fact that an existing face tampered image recognition technology cannot well process face artifacts. The method comprises: obtaining a standard global feature image of a to-be-detected image through a deep residual network, a cavity convolutional network and a convolutional layer, generating a space attention weight through a Sigmoid activation function based on the standard global feature image, multiplying the space attention weight by the standard global feature image to obtain a weighted attention feature graph, and obtaining a true and false face recognition result from the global attention feature map through a maximum pooling layer, a full connection layer and a nonlinear layer. The distribution characteristics of the artifact features and the counterfeit features are detected through the dilated convolution and the attention mechanism, and the accuracy of tampered image recognition is improved.

Description

technical field [0001] The invention belongs to the field of image recognition, and in particular relates to an image recognition method, system and equipment aimed at feature distribution of face tampered images. Background technique [0002] With the rapid development of deep learning and the emergence of a large number of open source data sets, the threshold of deep forgery technology is getting lower and lower, making more and more "fake face" pictures spread through the network, which brings hidden dangers to cyberspace information security. Deepfake technology is Deepfake in English, which is a face forgery technology based on deep learning. Since then, a large number of deepfake videos began to emerge, and the algorithm of this technology has become more and more mature, and the fake face images generated have reached the level where it is difficult for human eyes to distinguish the authenticity. [0003] Face deep tampering technology is mainly based on generative a...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above-mentioned problems in the prior art, that is, the existing face tampering image recognition technology cannot deal with face artifacts so that the accuracy of tampering image recognition is insufficient, the present invention provides a method for face tampering An image recognition method for image feature distribution, the method comprising:

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