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Smooth filtering evidence obtaining method based on end-to-end deep network

A technology of smooth filtering and deep network, applied in image enhancement, image analysis, instrument, etc., to achieve good universality

Active Publication Date: 2020-06-23
SHANGHAI UNIV OF ENG SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for image forensics it is impractical to detect only one type of filtering operation

Method used

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  • Smooth filtering evidence obtaining method based on end-to-end deep network
  • Smooth filtering evidence obtaining method based on end-to-end deep network
  • Smooth filtering evidence obtaining method based on end-to-end deep network

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Embodiment Construction

[0049] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0050] Such as Figure 1 to Figure 5 As shown, a smoothing filter forensics method based on end-to-end deep network, the model framework of this method includes three groups, the first group is two 3╳3 convolution, the second group mainly includes Inception-Residual module, SE module As well as the Reduction module, the last group completes the classification, with a total of 13 layers of networks. The method specifically includes the following steps:

[0051] Step 1. Extract local features through convolution processing.

[0052]...

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Abstract

The invention relates to a smooth filtering evidence obtaining method based on an end-to-end deep network, and the method comprises the steps: 1) reading a to-be-obtained grayscale image, extracting the local features of the grayscale image through employing a convolutional neural network, and activating each feature after convolution through a ReLu activation function; 2) extracting deep featuresof the local features by using an Inception-Reference module, and performing dimension reduction by using a Reduction module; 3) extracting global information by using a compression reward and punishment module, and adaptively selecting effective features; compared with the prior art, the method has the advantages that the universality is good, the detection precision is high, the influence of image content irrelevant to the smooth filtering effect is restrained, and the like.

Description

technical field [0001] The invention relates to the technical field of image forensics, in particular to an end-to-end deep network-based smoothing filter forensics method. Background technique [0002] With the wide application of image processing software, it is easy for people to edit, modify or even forge the image content, which seriously threatens the originality and authenticity of the image. For example, one image can be cropped and stitched onto another, and then blurred, scaled, and rotated to make tampering difficult to detect. Therefore, image tampering forensics is an urgent problem to be solved. [0003] Smoothing filtering is a common image blurring and noise reduction operation, and is usually used as post-processing of image tampering to reduce the traces left by malicious operations. Smoothing filtering is generally divided into two categories, namely linear smoothing filtering and nonlinear smoothing filtering. Linear smoothing filtering mainly includes...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06K9/62
CPCG06T2207/20084G06T2207/20081G06F18/213G06F18/24G06T5/70
Inventor 张玉金余洛张立军吴飞
Owner SHANGHAI UNIV OF ENG SCI