Image tampering detection method and device based on dual-channel U-Net model

A tamper detection, dual-channel technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as inability to effectively identify tampered areas, inability to identify tampering types, and single tampering detection technology, to achieve unity and subjective Sexual defects, strong robustness and generalization ability, and the effect of improving detection performance

Active Publication Date: 2020-12-29
WUHAN UNIV
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the existing technical problems, the present invention proposes a method and device for image tampering detection based on a dual-channel U-Net model to overcome the inability of the prior art to effectively identify the tampered area, the inability to identify the tampered type, and the single tampering detection technology problem, and the U-Net model proposed by the present invention is an improved U-Net model

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  • Image tampering detection method and device based on dual-channel U-Net model
  • Image tampering detection method and device based on dual-channel U-Net model
  • Image tampering detection method and device based on dual-channel U-Net model

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Embodiment 1

[0053] figure 1 It is a flow chart of a tampered image identification method based on deep learning shown according to an exemplary embodiment, refer to figure 1 As shown, the method includes the following steps:

[0054] Step S1: select a number of unprocessed images as original images, and use image editing software to perform image tampering operations to obtain tampered images.

[0055] Step S2: Perform ground truth image rendering for each tampered image in step S1.

[0056] Step S3: extract the noisy image using the Spatial Rich Model (SRM) method for the tampered image.

[0057] Step S4, build a dual-channel U-Net model, the dual-channel U-Net model includes two channels, channel 1 is a U-Net model, including an encoder and a decoder structure, the input is a tampered image, and the tampered image is extracted by the encoder The RGB feature of the image, and then locate the tampered image area through the binary classification output of the decoder; channel 2 is a co...

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Abstract

The invention provides an image tampering detection method and device based on a dual-channel U-Net model, and aims to solve the problems that in the prior art, a tampering area cannot be effectivelyrecognized, a tampering type cannot be recognized, and a tampering detection technology is single. The U-Net model provided by the invention is an improved U-Net model. A Res-Block structure module, afeature fusion module and a Res-Dilated module are added to the improved U-Net model, so that the use efficiency of features is improved, the information loss is reduced, and a semantic gap between low-dimensional features in an encoder and high-dimensional features in a decoder is solved. According to the method, the defects of singleness and subjectivity of traditional manual feature extractionare overcome, the features extracted through a deep network have higher robustness and better generalization ability, the tampering type of the image can be effectively detected, and the tampering area can be effectively positioned.

Description

technical field [0001] The invention relates to the technical field of computer applications, in particular to a safe active image tampering detection method and device. Background technique [0002] Multimedia information, such as digital images, is often used in many important occasions, such as evidence in criminal investigations and military scenarios. However, with the availability and popularity of digital image editing tools, this information can easily be modified or tampered with without leaving any visual trace of the modification. Among tampering techniques, splicing, copy-moving, and deletion are the most common operations. Image stitching is copying and pasting an area in a real image into another image, copy moving is copying and pasting an area in the same image, and deletion is erasing and patching an area in a real image. Efficient tampering technology that makes it difficult to identify tampered areas even with close inspection. Therefore, in multimedia ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0002G06T2207/20081G06T2207/20084G06F18/217G06F18/24G06F18/253G06F18/214
Inventor 崔晓晖丁红卫朴杨鹤然陶启赵坤
Owner WUHAN UNIV
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