Feature extraction method and extraction system for digital image steganalysis

A technology of steganalysis and feature extraction, applied in image data processing, image data processing, instruments, etc., can solve the problem of poor performance, definition and steganalysis problems are not direct matching, and insufficient expression of correlation between image pixels of histogram features And other issues

Active Publication Date: 2017-05-17
SHENZHEN UNIV
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Problems solved by technology

The local binary model (LBP) is an operator that combines structure and statistics. Its histogram features are well applied in image texture classification. Using the local binary model histogram features in spatial steganalysis Some effects have been achieved, but its performance is still inferior to SRM. The

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  • Feature extraction method and extraction system for digital image steganalysis
  • Feature extraction method and extraction system for digital image steganalysis
  • Feature extraction method and extraction system for digital image steganalysis

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[0068] The present invention provides a digital image steganalysis feature extraction method and extraction system. In order to make the purpose, technical solution and effect of the present invention clearer and clearer, the present invention will be further described in detail below. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0069] Such as figure 1 As shown, it is a flowchart of an embodiment of a digital image steganalysis feature extraction method according to the present invention, and the method includes the following steps:

[0070] Step S100 , filtering the feature image to be extracted for steganalysis through 10 filters to obtain a residual image; wherein, the 10 filters include 4 non-directional filters and 6 directional filters.

[0071] For 4 non-directional filters, each filter can get a residual image, and for 6 directional filters, each filter can g...

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Abstract

The invention discloses a feature extraction method and extraction system for digital image steganalysis. The method comprises the steps of filtering a steganalysis feature image to be extracted by ten filters to obtain residual images, the ten filters including four non-directional filters and six directional filters; encoding the residual images according to an LBPriu2 model and/or a DLBP model to obtain coding graphs, obtaining second-order co-occurrence matrices in four different directions according to the coding graphs, and for the six directional filters, adding the co-occurrence matrices calculated in different directions; for the calculated co-occurrence matrices, combining the co-occurrence matrices in different directions and decreasing the dimensions of the co-occurrence matrices, and then performing LOG function mapping to obtain co-occurrence matrix features. According to the invention, similar performance to the existing mainstream general steganalysis method SRM is gained, and the classification effect has higher accuracy than that of the SRM.

Description

technical field [0001] The invention relates to the technical field of digital image steganalysis, in particular to a digital image steganalysis feature extraction method and extraction system. Background technique [0002] There are two types of digital image steganalysis: active steganalysis and passive steganalysis. Passive steganalysis mainly judges whether the carrier hides secret information, while active steganalysis needs to estimate whether the carrier has secret information. The parameters of the steganographic algorithm further extract the secret information. According to usage scenarios, steganalysis is divided into special steganalysis and general steganalysis. The general steganography method needs to detect a variety of steganographic algorithms. Its operation process is mainly divided into two parts: feature extraction and classifier classification. Among them, the feature design part is the main content of the research and the algorithm function link of thi...

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Application Information

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IPC IPC(8): G06T1/00
CPCG06T1/0021G06T2201/0065
Inventor 李斌李忠蓬黄继武
Owner SHENZHEN UNIV
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