Face fusion detection method based on color texture dual-channel convolutional neural network and recurrent neural network

Abstract

The invention discloses a face fusion detection method based on a color texture dual-channel convolutional neural network and a recurrent neural network, and the method comprises the following steps:1, carrying out the face region extraction of an input image, carrying out the resampling of a face region, enabling the face region to be in a fixed size, and enabling the face region to be divided into non-overlapped image blocks; 2, preprocessing each image block to extract a color component and a texture component; 3, inputting the color and texture components extracted from each image block into the trained dual-channel convolutional neural network to obtain high-dimensional feature expression; 4, taking the high-dimensional feature expressions of all the image blocks obtained in the step3 as the input of the spatial recurrent neural network to obtain the output score of the network; comparing the output score with a preset threshold value, and judging whether the input image is a face fusion image or not. According to the method, the detection performance under the conditions that the number of training samples is limited and the image acquisition environment is complex is effectively improved, and the robustness of malicious post-processing operation is enhanced.

Description

technical field [0001] The invention relates to the technical field of image tampering detection methods, in particular to a face fusion detection algorithm based on a color texture dual-channel convolutional neural network and a cyclic neural network. Background technique [0002] With the development of biological information technology, applications based on biological information identification have widely existed in people's daily life, such as transaction payment and identity authentication. Among them, the recognition technology based on face information has gained more and more applications due to its advantages of fast collection speed and no need to touch collection equipment. However, the existing digital image processing technology has been able to fuse face images from two users (face morphing) to obtain a picture with a high degree of similarity to the two users. like figure 1 As shown, the pictures generated by face fusion technology often have high visual q...

AI Technical Summary

Problems solved by technology

Since face fusion is a special form of image tampering, among the currently published patents, the following patents have certain similarities with the method of the present invention; the publication number is CN108510483A, entitled "A Computing Method Using VLAD Coding and SVM Generate color image tampering detection method" patent uses ResNet network to generate color features, then VLAD codes the features, and finally uses SVM classifier to judge whether the image has undergone tampering operation. This method is not good for the detection performance of face fusion images in complex acquisition environments. Good, and does not consider the impact of malicious post-processing operations

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