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General video steganalysis method based on video pixel space-time relevance

A space-time correlation and video steganography technology, applied in image communication, image data processing, image data processing, etc., can solve problems such as inability to fully describe the correlation of adjacent pixels

Active Publication Date: 2013-09-04
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, these methods only select a small number of directions when describing the correlation between adjacent pixels, and cannot fully describe the correlation between adjacent pixels.

Method used

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  • General video steganalysis method based on video pixel space-time relevance
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  • General video steganalysis method based on video pixel space-time relevance

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Embodiment Construction

[0019] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0020] figure 1 It is a flow chart of the general video steganalysis method based on the temporal-spatial correlation of video pixels in the present invention, such as figure 1 As shown, the general video steganalysis method based on video pixel spatiotemporal correlation comprises the following steps, wherein steps S1-S5 are training procedures, and steps S6-S7 are classification procedures:

[0021] Step S1, decompressing each video in the training set, extracting a plurality of image segments according to a fixed length, performing slices on each image segment to obtain a plurality of sliced ​​images corresponding to each image segment;

[0022] The length of the image segment can be adjusted as required. In an embodi...

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Abstract

The invention discloses a general video steganalysis method based on video pixel space-time relevance. The method comprises the steps that a video in a training set is decompressed, a plurality of image sections are extracted, and each image section is sliced so that a plurality of spliced images can be obtained; difference filtering and threshold processing are conducted on each spliced image; two or more difference images are selected from all the difference images in each spliced image, a plurality of joint probability distribution matrixes corresponding to the spliced images are obtained through the description of a pixel neighborhood relation, and elements of each matrix are combined to be a one-dimensional vector which serves as a feature vector; the feature vectors are marked according to classes and input into a classifier, so that a classifier model is obtained; according to the steps, feature vectors of a video to be analyzed are extracted and input into the classifier model to be classified, so that a steganalysis result is obtained. According to the general video steganalysis method based on video pixel space-time relevance, the time domain relevance of the video is fully used, so that steganalysis effect is improved and the method can be used in analysis systems of various types of steganograph algorithms.

Description

technical field [0001] The invention relates to the field of passive blind forensics of images and videos, in particular to a steganalysis method for video steganography based on temporal and spatial correlation of video pixels. Background technique [0002] Steganography is to hide the secret information in the carrier information, without affecting the sensory effect and use value of the host signal, making it difficult for possible attackers to judge whether the secret information exists, and it is even more difficult to intercept, so as to ensure the smoothness of information transmission. safety. Due to the openness and universality of Internet communication, steganographic technology may also be used by criminals or even terrorist organizations to achieve the purpose of evading monitoring and disseminating illegal information. Therefore, research on steganalysis has important theoretical value and practical significance. [0003] Images are the most common carrier of...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N1/32G06T1/00
Inventor 谭铁牛董晶许锡锴
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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