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Image artificial blur detection method based on multi-domain coupling

A technology of artificial blur and detection method, applied in the field of image artificial blur detection based on multi-domain coupling

Pending Publication Date: 2020-02-11
BAOJI POWER SUPPLY COMPANY OF STATE GRID SHAANXI ELECTRIC POWER
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But nowadays, the tampering of digital image content is becoming easier and easier, and people can edit and modify images almost without leaving any traces without professional technology, which brings challenges to the authenticity and security of digital images

Method used

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  • Image artificial blur detection method based on multi-domain coupling
  • Image artificial blur detection method based on multi-domain coupling
  • Image artificial blur detection method based on multi-domain coupling

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Experimental program
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Embodiment 1

[0059] Such as figure 1 As shown, an image artificial blur detection method based on multi-domain coupling includes the following steps:

[0060] S1: Grayscale conversion: For the input original test image, it is first converted into a single-channel grayscale image I, and the conversion formula is,

[0061] I=0.299*R+0.587*G+0.114*B (1)

[0062] Among them, R, G, and B are the pixel values ​​of the image on the three color channels.

[0063] S2: Secondary blurring operation: use Gaussian blurring to perform global blurring operation on the grayscale image I in step S1 to obtain the image I after secondary blurring b for later I and I on each field b The comparison of similarity is expressed as

[0064] I b =I*G (2)

[0065] Where * is a convolution operation, and G is a Gaussian blur kernel. In this embodiment, the parameter blur kernel size of G is n=25, and the standard deviation σ=1.

[0066] S3: Extract features in the DCT domain: For a pixel point p on I, the degr...

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Abstract

The invention discloses an image artificial fuzzy detection method based on multi-domain coupling, and the method comprises the steps: firstly carrying out partitioning DCT of an image, calculating the similarity of DCT coefficients of each pixel before and after secondary fuzzy, and obtaining an artificial fuzzy degree estimation mapping graph corresponding to a test image in a DCT domain; secondly, conducting binary segmentation on the mapping image, denoising and hole filling are conducted through image morphology, and acquiring an artificially blurred candidate area and finally, in the spatial domain of each image, comprehensively screening the candidate artificial fuzzy regions by utilizing the texture descriptors of the image, including gray statistics, smoothness and information entropy, so as to obtain a final positioning result. The advantages of DCT domain and spatial domain features of the image are comprehensively utilized, a new artificial blurring measurement method is obtained, and the method has good detection efficiency and positioning accuracy.

Description

technical field [0001] The invention relates to the technical field of digital image information, in particular to an image artificial blur detection method based on multi-domain coupling. Background technique [0002] With the popularity of networks and smart devices, the transmission of multimedia information has become ubiquitous. As an important carrier of information transmission, digital image has become the top priority. But nowadays, the tampering of digital image content is becoming easier and easier, and people can edit and modify images almost without leaving any traces without professional technology, which brings challenges to the authenticity and security of digital images. Therefore, the research on digital image forensics is of great significance to maintain the security of network information. [0003] As an important branch of digital image forensics technology, image artificial blur tampering detection is aimed at detecting whether there are artificial b...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06T7/136G06T7/155
CPCG06T7/0002G06T7/11G06T7/136G06T7/155G06T2207/30168G06T2207/20052G06T2207/20076
Inventor 张超邰炜蔡忠林刘子瑞白晓斌孙红宝杨海文余洁杨小宁
Owner BAOJI POWER SUPPLY COMPANY OF STATE GRID SHAANXI ELECTRIC POWER