Tampered image detection method based on deep learning

Abstract

The invention discloses a tampered image detection method based on deep learning, and relates to the field of passive evidence obtaining of images. The tampered image detection method includes the steps: constructing a convolution layer based on multi-scale noise constraint to obtain a high-frequency noise residual error in the image; performing tampered image detection by using a double-flow network; utilizing a multi-task learning method to simultaneously realize classification of whether an image area is tampered and detection and segmentation tasks of the tampered area; when the network isoptimized, extracting the output characteristics of the four parts of the region of interest extraction network, the tampering classification branch, the tampering region detection branch and the tampering region segmentation branch, calculating the error of the network for back propagation, and further adjusting the network parameters, so that the network achieves the optimal solution. The tampered image detection method can identify whether the image is tampered or not, and can accurately detect and segment the tampered area in the tampered image, so that the tampered image is suitable foractual application scenes. The tampered image detection method can detect authenticity of the image through a deep learning method, so that the problem of malicious tampering of the image is solved, and the accuracy and generalization ability of tampering detection are improved.

Description

technical field [0001] The invention relates to the field of image passive forensics, in particular to a method for detecting tampered images based on deep learning. Background technique [0002] With the rapid development of information science and technology, digital images have penetrated into every corner of social life. The wide application of digital images also promotes the rapid development of digital image editing software, and the appearance of image processing software makes it easier to retouch and modify digital images. However, while this is convenient for ordinary users, it also gives some criminals an opportunity. Criminals edit and disseminate the content of images taken by others without authorization; or maliciously synthesize false images in order to falsify facts. Although image tampering can beautify the image to a certain extent, it is still deceptive in nature. If it is illegally used and disseminated without restriction, it will cause adverse conse...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problems existing in the existing tampered image detection technology, and to provide a tampered image detection method based on deep learning for the camera fingerprint features and image statistical features contained in digital images

Images