Image design work plagiarism detection method based on adversarial network

A technology of image design and detection method, applied in the direction of neural learning method, biological neural network model, calculation, etc., can solve the problems that the detection of plagiarism of image design works cannot be realized, achieve superior performance of plagiarism identification, improve accuracy, and realize The effect of tamper detection

Pending Publication Date: 2020-10-09
JIANGNAN UNIV
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Problems solved by technology

For image design works, due to the limitation of fewer samples, the existing

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  • Image design work plagiarism detection method based on adversarial network
  • Image design work plagiarism detection method based on adversarial network
  • Image design work plagiarism detection method based on adversarial network

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Embodiment Construction

[0035] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0036] The present invention designs a plagiarism detection method based on an adversarial network for image design works, including an image detection model construction method, and applying the image detection model to detect images to be discriminated, and obtain a tampered mask image corresponding to the image to be discriminated; practical application Among them, such as figure 1 As shown, the image detection model construction method specifically performs the following steps A to L.

[0037] Step A. For the preset number of training sample images I respectively containing tampered image areas, the image features specified in the training sample image I are used as input, and the different image features in the training sample image I for which the gap is greater than the preset corresponding image feature threshold...

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Abstract

The invention relates to an image design work plagiarism detection method based on an adversarial network. Existing image design works are lack of tampered samples. The problem that traditional deep neural network training is difficult to realize is solved; design of brand-new logic strategy, tampering the mask image for a model generated by the generation network according to the original plagiarism image; an artificially marked tampered mask image is combined; judging which mask image is manually marked by using a judgment network; therefore, the accuracy of the generation network and the judgment network is represented based on whether the judgment result is correct or not; executing a corresponding feedback training operation; the accuracy of the two networks is continuously improved;in this way, through continuous confrontation iteration, the accuracy of the two networks reaches a final balance state, the obtained generation network is an image detection model and has excellent work plagiarism recognition performance, a tampered mask image of a to-be-discriminated image can be obtained by applying the image detection model, and tampering detection of an image design work is efficiently achieved.

Description

technical field [0001] The invention relates to a method for detecting plagiarism of image design works based on an adversarial network, and belongs to the technical field of tampering detection of image works. Background technique [0002] Plagiarism detection and identification of design works has always been an unavoidable problem in the design and academic circles. Plagiarism identification is the detection of similarities between works and the determination of similar content. Judging from the forms of plagiarism, there are acts of copying other people's works intact or basically intact, and there are also acts of stealing other people's original elements protected by copyright after modification. The intellectual property rights of graphic design works are mainly reflected in the use of image color, composition and artistry of expression. However, the current method of defining plagiarism in design works mainly stays in the stage of manual identification, which is tim...

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Application Information

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IPC IPC(8): G06K9/62G06N3/08G06N3/04
CPCG06N3/08G06N3/045G06F18/214
Inventor 杨滨丘晓琳
Owner JIANGNAN UNIV
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