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Image tampering detection method and system and storage medium

A technology of tampering detection and image, which is applied in the field of image processing, can solve the problem of low detection accuracy, achieve the effect of avoiding semantic gap, improving tamper detection accuracy, and high tamper detection accuracy

Active Publication Date: 2021-05-28
HUNAN UNIV
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Problems solved by technology

However, multiple features are only fused at both ends of the model, the gap between multiple features is difficult to bridge, and the detection accuracy is still low

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  • Image tampering detection method and system and storage medium
  • Image tampering detection method and system and storage medium
  • Image tampering detection method and system and storage medium

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Embodiment Construction

[0024] Such as figure 2 As shown, the specific implementation process of the embodiment of the present invention is as follows:

[0025]Step one, considering the strong learning ability and generalization ability of convolutional neural network, we use it to learn the tampering features of images. To be precise, we are using the first 3 blocks of the Resnet50 network. Such as figure 1 The RGB stream is shown. Because the input is a 3-channel RGB image, we call it an RGB stream. However, a well-known problem is that convolutional neural networks usually learn content features of images rather than tampered features. We believe that under the correct guidance, it can suppress its learning content features and guide it to learn tampering features.

[0026] Technical solution: use the first three blocks of the Resnet50 network (a convolutional neural network) (corresponding to figure 1 The Conv_1x Group, Conv_2x Group and Conv_3x Group in the medium RGB stream are the first...

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Abstract

The invention discloses an image tampering detection method and system and a storage medium. The method in one embodiment comprises a double-branch image tampering detection method. One branch comprises the steps: learning a convolution kernel similar to a high-pass filter, wherein the branch can filter content features of the image and adaptively extract high-frequency features of the image; obtaining RGB features guided by the high-frequency features; inputting the RGB features obtained through guide learning into a detection model to judge whether the image is tampered or not, and positioning a tampered area. At present, most of the advanced image tampering detection methods adopt a fusion mode to combine several features beneficial to tampering detection, but the multiple features are fused only at the two ends of a model, and a gap between the features is difficult to span. According to the method, two features are combined, but the proposed method uses one feature to guide the learning of the other feature, so that a semantic gap problem between different features in a fusion method is effectively avoided while multiple features are well combined.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image tampering detection method, system and storage medium. Background technique [0002] With the rapid development of digital devices such as cameras, mobile phones, tablets, and video cameras, image generation has become very easy. In addition, with the rapid development of computers and the Internet, the storage and transmission of images has become very simple. Compared with using text as a carrier, it is more intuitive and credible to convey information through images. In the past, people believed that "seeing is believing" and "pictures tell the truth", but with the continuous development of digital media technology, this credibility is constantly being destroyed. Nowadays, the popularity of image editing software such as Photoshop, Meitu Xiuxiu, Beauty Camera, etc. has made image modification easier and easier, and ordinary people can easily process and mod...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/46G06K9/20G06N3/04
CPCG06N3/04G06V10/22G06V10/56G06F18/24
Inventor 杨超王志宇李慧州蒋斌
Owner HUNAN UNIV
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