CN106530204B

CN106530204B - Adaptive image information hiding method based on critical value

Info

Publication number: CN106530204B
Application number: CN201611021446.8A
Authority: CN
Inventors: 唐明伟; 蒋忠远; 陈晓亮; 曾晟珂; 夏梅宸; 何明星; 赵成芳; 邓英; 高振伟
Original assignee: Xihua University
Current assignee: Xihua University
Priority date: 2016-11-21
Filing date: 2016-11-21
Publication date: 2020-02-18
Anticipated expiration: 2036-11-21
Also published as: CN106530204A

Abstract

The invention provides a method for hiding self-adaptive image information based on a critical value, which provides an AIHC information hiding algorithm by combining the critical value of a sub-block and a self-adaptive judgment critical block. The AIHC algorithm increases the capacity for image concealment and the security is enhanced by the adaptive embedded secret information. The algorithm can be completed under the polynomial time complexity, and is simple to implement. The AIHC algorithm does not require additional information in extracting the secret information. The capacity is increased while maintaining the image quality. The performance of the proposed AIHC algorithm is obviously better than that of other similar algorithms.

Description

Adaptive image information hiding method based on critical value

Technical Field

The invention belongs to the field of information processing, and relates to a self-adaptive image information hiding method based on a critical value.

Background

The method for hiding graphic information in the prior art comprises TBPC Hou, C. -L, Lu, C, Tsai, S. -C, & Tzeng, W. -G. (2011). An optional data recording scheme with tree-based syntax, IEEE Transactions on Image Processing, 20(3), 880-886. Although the TBPC algorithm has larger capacity, the safety is poorer.

EALSB-MR is Luo, W., Huang, F., & Huang, J. (2010). Edge adaptive image based on LSB matched accessed revising IEEE transaction information Formations and Security, 5(2), 201-. Luo et al designed the EALSB-MR algorithm. The algorithm breaks the association between the vertical direction and the horizontal direction, and the security of the algorithm needs to be improved.

SEMX Hayat Al-Dmour, Ahmed Al-Ani (2016), A steganographic embedded method based on information and XOR coding, Expert Systems Withapplications,46, 293-. Hayat Al-Dmour et Al propose an SEMX algorithm that uses boundary values and XOR operations to improve security, but has limited capacity.

Disclosure of Invention

In view of the defects of the prior art, the present invention aims to provide a simple adaptive image information hiding method based on a critical value, which improves the capacity of image hiding and enhances the security of the adaptively embedded secret information.

In order to achieve the purpose, the technical solution of the invention is as follows:

a method for hiding self-adaptive image information based on a critical value comprises the following steps:

step one, defining a pixel block B of non-overlapped images, wherein the size of the pixel block B is nxn, and n is a positive integer;

step two, defining the maximum difference D, D = MAX (B) of the pixel block B_i）- MIN（B_i）

Wherein, MAX (B)_i) Represents the maximum value, MIN, of the pixel block B (B)_i) Represents the minimum value of the pixel block B;

step three, defining critical value TH and setting secret information m₁，m₂Let a pixel I₁，I₂And I₃Then, then

(1) If LSB (I)₁）⊕LSB（I₂) Is not equal to m₁And LSB (I)₁）⊕LSB（I₃) Is not equal to m₂Then modify I₁Is S₁And ensure MIN (B)_i）<S₁<MAX（B_i）；

(2) If LSB (I)₁）⊕LSB（I₂) Is not equal to m₁And LSB (I)₁）⊕LSB（I₃) Etc. ofAt m₂Then modify I₂Is S₂And ensure MIN (B)_i）<S₂<MAX（B_i）；

(3) If LSB (I)₁）⊕LSB（I₂) Is equal to m₁And LSB (I)₁）⊕LSB（I₃) Is not equal to m₂Then modify I₃Is S₃And ensure MIN (B)_i）<S₃<MAX（B_i）；

LSB（I₁) Get I₁Is the least significant bit, LSB (I)₂) Get I₂Is the least significant bit, LSB (I)₃) Get I₃The least significant bit of;

(4) otherwise, remain unchanged;

whether the pixel block B is a critical block and is used for information hiding is determined by calculating the maximum difference D of the pixel block B in the image.

The invention avoids missing critical blocks, and improves the hidden capacity; self-adaptive embedded information, and the safety of the embedded information is improved; and the method in the third step is adopted, so that the modification to the image is reduced, and the quality of the image is improved.

By combining the critical value of the sub-block and the self-adaptive judgment critical block, an AIHC information hiding algorithm is provided. The AIHC algorithm increases the capacity for image concealment and the security is enhanced by the adaptive embedded secret information. The algorithm can be completed under the polynomial time complexity, and is simple to implement. The AIHC algorithm does not require additional information in extracting the secret information. The capacity is increased while maintaining the image quality. The performance of the proposed AIHC algorithm is obviously better than that of other similar algorithms.

Drawings

FIG. 1.3 × 3 pixel block

FIG. 2 is a flow chart of the AIHC algorithm

FIG. 3. graph of embedding rate and MSE

FIG. 4 is a graph of embedding rate and PSNR (dB)

FIG. 5.300 Capacity comparison of the sub-images

FIG. 6. AIHC algorithm for randomly selecting 300 images compares the rate of SEMX increase;

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention are described below clearly and completely, and it is obvious that the described embodiments are some, not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention comprises the following steps:

define 1. non-overlapping blocks of pixels B of the image, of size n × n, such as n =3, as shown in fig. 1.

Define 2. maximum difference of blocks D

D=MAX（B_i）- MIN（B_i）

Wherein, MAX (B)_i) Denotes the maximum value of block B, MIN (B)_i) Representing the minimum value of block B.

Definition 3. threshold value TH

Rule 1. let secret information m₁，m₂Let a pixel I₁，I₂And I₃Then, then

(1) If LSB (I)₁）⊕LSB（I₂) Is not equal to m₁And LSB (I)₁）⊕LSB（I₃) Is not equal to m₂Then modify I₁Is S₁And ensure MIN (B)_i）<S₁<MAX（B_i）。

(2) If LSB (I)₁）⊕LSB（I₂) Is not equal to m₁And LSB (I)₁）⊕LSB（I₃) Is equal to m₂Then modify I₂Is S₂And ensure MIN (B)_i）<S₂<MAX（B_i）。

(3) If LSB (I)₁）⊕LSB（I₂) Is equal to m₁And LSB (I)₁）⊕LSB（I₃) Is not equal to m₂Then modify I₃Is S₃And ensure MIN (B)_i）<S₃<MAX（B_i）。

(4) Otherwise, remain unchanged

FIG. 2 is a flow chart of the AIHC algorithm

(1) Start of

(2) An image is input, and a TH value is set.

(3) The image I is divided into non-adjacent blocks of size n × n.

(4) If the block has been selected to be completed, step (9), otherwise, step (5).

(5) And selecting the ith block B, and calculating the maximum difference value D of the ith block.

(6) If D is greater than or equal to the critical TH, which is a critical block, step (7); otherwise, step (4).

(7) If MIN (B)<B_i<MAX (B), then I_i=B_iSecret information is embedded according to rule 1.

(8) If the secret information is embedded completely, step (9); otherwise, step (4).

(9) And outputting the secret image.

(10) End up

3. Results of the experiment

The gallery of experiments is from UCID and internet. The experimental tool used MATLAB version R2009. At the beginning of the experiment, all images will be converted to grayscale images. 1338 images from the test gallery were selected as the experimental images. Next, the results of some experiments will prove the validity of the proposed AIHC algorithm.

Experiment one: from these 1338 images, one of which was randomly selected, the results of the comparisons of the TBPC algorithm, the easbs-MR algorithm, the SEMX algorithm, and the AIHC algorithm are shown in fig. 3 and 4. Fig. 3 shows that in the test results of the TBPC algorithm, the easbl-MR algorithm, the SEMX algorithm, and the AIHC algorithm, the MSE of the AIHC algorithm is minimum, which indicates that the modification of the image by the AIHC algorithm is minimum and the distortion is kept low.

Fig. 4 shows that the PSNR values of the AIHC algorithm are taught among the test results of the TBPC algorithm, the easbl-MR algorithm, the SEMX algorithm, and the AIHC algorithm, indicating that the AIHC algorithm has the best authenticity of image retention.

Experiment two: from these 1338 images, 300 of them were randomly selected, and the results of the comparison of the SEMX algorithm and the AIHC algorithm are shown in FIGS. 5 and 6. Fig. 5 shows that, in the test results of the SEMX algorithm and the AIHC algorithm, the capacity of the AIHC algorithm is large, indicating that the capacity of embedding the image by the AIHC algorithm is large.

Fig. 6 shows the capacity of the AIHC algorithm in the SEMX algorithm improvement rate IC in the test results of the SEMX algorithm and the AIHC algorithm. Of the 1338 images, IC was positive for 89.09%. This indicates that the capacity of the AIHC algorithm is higher than the SEMX algorithm.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A method for hiding adaptive image information based on a critical value is characterized by comprising the following steps:

defining 1, defining a pixel block B of non-overlapped images, wherein the size of the pixel block B is nxn, and n is a positive integer;

definition 2: defining a block of pixels B with a maximum difference D, D-MAX (B)_i)-MIN(B_i)

definition 3: critical value TH

Rule 1: setting secret information m₁，m₂Let a pixel I₁，I₂And I₃Then, then

(1) If it is notIs not equal to m₁And is and

is not equal to m₂Then modify I₁Is S₁And ensure MIN (B)_i)<S₁<MAX(B_i)；

(2) If it is not

Is not equal to m₁And is and

is equal to m₂Then modify I₂Is S₂And ensure MIN (B)_i)<S₂<MAX(B_i)；

(3) If it is not

Is equal to m₁And is and

is not equal to m₂Then modify I₃Is S₃And ensure MIN (B)_i)<S₃<MAX(B_i)；

LSB(I₁) Get I₁Is the least significant bit, LSB (I)₂) Get I₂Is the least significant bit, LSB (I)₃) Get I₃The least significant bit of;

(4) otherwise, remain unchanged;

determining whether the pixel block B is a critical block and is used for information hiding by calculating the maximum difference D of the pixel block B in the image;

the AIHC algorithm includes the following steps:

(1) start of

(2) Inputting an image and setting a TH value;

(3) dividing the image into non-adjacent blocks with the size of n multiplied by n;

(4) if the block is used up, step (9), otherwise, step (5);

(5) selecting an ith block B, and calculating the maximum difference D of the ith block;

(6) if D is greater than or equal to the critical TH, which is a critical block, step (7); otherwise, step (4);

(7) if MIN (B)_i)<B_ij<MAX(B_i) Then, I_k＝B_ijEmbedding secret information according to rule 1;

(8) if the secret information is embedded completely, step (9); otherwise, step (4);

(9) outputting a secret-carrying image;

(10) and (6) ending.