Image steganographic detection method and system based on nonlinear hybrid kernel feature map

A nonlinear hybrid and steganographic detection technology, applied in image data processing, image data processing, instruments, etc., can solve the problems of complex steganalysis and low accuracy

Active Publication Date: 2021-02-02
LANZHOU JIAOTONG UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide an image steganographic detection method and system based on nonlinear hybrid kernel feature mapping, which solves the problems of complex and low accuracy of general steganographic analysis in the prior art

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  • Image steganographic detection method and system based on nonlinear hybrid kernel feature map
  • Image steganographic detection method and system based on nonlinear hybrid kernel feature map
  • Image steganographic detection method and system based on nonlinear hybrid kernel feature map

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[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 belong to the protection scope of the present invention.

[0059] The purpose of the present invention is to provide an image steganographic detection method and system based on nonlinear hybrid kernel feature mapping, which solves the problems of complex and low accuracy of general steganographic analysis in the prior art.

[0060] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with...

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Abstract

The present invention relates to an image steganography detection method and system based on nonlinear mixed kernel feature mapping, comprising: obtaining an image to be tested, using a rich model type feature extraction method to extract features from the image to be tested, and determining the statistical characteristics of the image to be tested, Segment the statistical features of the image to be tested vertically and sequentially to obtain a set of statistical feature blocks of the image to be tested, and use the feature mapping algorithm based on the nonlinear hybrid kernel function to map each statistical feature block of the image to be tested in the set of statistical feature blocks of the image to be tested , to obtain a set of statistical feature blocks of the image to be tested after mapping, splicing each mapped statistical feature block of the image to be tested after mapping in the set of statistical feature blocks of the image to be tested to synthesize the high-dimensional and rich model features of the image to be tested, and according to the high-dimensional richness of the image to be tested Model features, using the trained integrated FLD classifier to determine whether the image to be tested contains steganographic information. The detection accuracy is improved through the above method of the present invention without increasing time complexity.

Description

technical field [0001] The invention relates to the technical field of image steganography, in particular to an image steganography detection method and system based on nonlinear mixed kernel feature mapping. Background technique [0002] Image steganography technology refers to embedding secret information into images by using the insensitivity of human senses and the redundancy of the signal itself, while image steganalysis is the reverse technology of image steganography, which is mainly dedicated to detecting hidden images, Extract cryptic messages and more. [0003] Existing steganalysis is mainly divided into two categories: one is dedicated steganalysis, which analyzes and tests known steganographic algorithms. Due to the prior knowledge of steganographic algorithms, the detection accuracy is higher , but the scope of application is relatively narrow. The other is general steganalysis, which judges the data to be detected without knowing the steganographic algorithm...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T1/00G06K9/62
CPCG06T1/0021G06T2201/0065G06F18/25G06F18/259
Inventor 党建武邓利芳王阳萍雍玖李吉元王文润岳彪
Owner LANZHOU JIAOTONG UNIV
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