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CN109963159B - An Information Steganography Algorithm Based on STC Coding for Double Perturbation Scoring of Binary Image

Publication number

CN109963159B

CN109963159B CN201910041668.3A CN201910041668A CN109963159B CN 109963159 B CN109963159 B CN 109963159B CN 201910041668 A CN201910041668 A CN 201910041668A CN 109963159 B CN109963159 B CN 109963159B

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CN

China

Prior art keywords

image

pixel

disturbance

embeddable

secret

Prior art date

2019-01-16

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• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/46—Embedding additional information in the video signal during the compression process
  • H04N19/467—Embedding additional information in the video signal during the compression process characterised by the embedded information being invisible, e.g. watermarking

• Engineering & Computer Science (AREA)
• Multimedia (AREA)
• Signal Processing (AREA)
• Editing Of Facsimile Originals (AREA)
• Image Processing (AREA)

Technical Field

The invention relates to the field of information hiding, in particular to an information steganography algorithm of binary image double-disturbance scoring based on STC coding.

Background

The information hiding technology is to embed secret information into a public carrier, and the aim of secret information transmission is achieved through carrier transmission, and the essence of the technology is to hide the information by using visual masking effect and carrier redundancy. Compared with the traditional encryption technology, the information hiding has better non-detectability, and the original carrier and the secret-related carrier are difficult to distinguish only by visual sense, namely the technology hides the fact that the communication exists while protecting the secret information. In addition, the information hiding processing method has the characteristics of diversity, rich available carriers, good safety and the like, so that the technology has wide application prospect and has important application in the aspects of hiding information traces, copyright identification, secret communication, tampering detection and the like.

Generally, information hiding can be classified into image, video, audio, text and other hiding technologies according to carriers, wherein image-based steganography can be further subdivided into image steganography based on RGB, gray scale, binary and the like, binary images are not black or white, the representation form is simple, the visual disturbance generated by turning any one pixel is larger, and the influence on the image quality is more serious. However, a large number of binary images exist in life, such as fax images, medical images, digital signatures, checks and the like, and in order to ensure the security of binary image information and an information hiding technology using such images as carriers, deep research on binary image steganography is of great significance.

The existing binary image information hiding algorithm mainly uses block embedding, a reversible point set is searched by designing a binary image distortion measurement function, so that image embedding disturbance is minimum, and then secret information is hidden into a carrier image by using an efficient coding technology. When an image distortion measurement function is formulated, smoothness, connectivity and texture characteristics of an image are emphatically considered, and secret information is embedded in an image texture region as much as possible without destroying the smoothness and connectivity of pixels in the neighborhood of a block image. However, the distortion measurement function is often formulated according to the property of the carrier image, after the secret information is embedded, when the secret image is evaluated according to the same rule, the disturbance score of the embedded position neighborhood pixels is different from the disturbance score of the carrier image, and the disturbance score is easily detected by a corresponding steganalysis algorithm, and the non-detectability of the steganalysis algorithm faces a severe challenge.

Disclosure of Invention

In order to solve the defect that a binary image information hiding algorithm in the prior art is easy to detect by a corresponding steganalysis algorithm, the invention provides an information hiding algorithm of binary image double-disturbance scoring based on STC coding.

In order to realize the purpose, the technical scheme is as follows:

an STC coding-based binary image double disturbance scoring information steganography algorithm comprises the following steps:

step S1: constructing a distortion measurement function, and performing disturbance scoring on the carrier image X by using the distortion measurement function to obtain a disturbance score chart D and a disturbance score1(X, y) of each pixel point of the carrier image X;

step S2: setting a threshold T₁The value in the disturbance score map D is smaller than T₁The values of (A) are screened out to form an embeddable point set C₁；

Step S3: sequentially-turned embeddable point set C₁Pixel point of the included position, C₁The pixels of the positions contained in the set of points being directly inverted, i.e. having a value of 0The pixel is changed into 1, the pixel with the value of 1 is changed into 0, and the directly inverted secret image S is obtained₁；

Step S4: using distortion metric function to pair stego image S₁Carrying out disturbance scoring to obtain a secret disturbance score map D' and a secret image S₁Each pixel point perturbation score, score2(x, y);

step S5: setting threshold T according to embedding capacity₂When score1(x, y) and score2(x, y) are both less than T₂From the stego image S₁Middle screening embeddable point set C₂；

Step S6: removing embeddable point set C₂Neighborhood pixel, construct embeddable point set C₃Flipping a pixel affects the neighborhood pixels within a W block of the scanned image centered on the pixel, i.e., point set C₂The invention sets the line scanning priority principle and removes the point set C₂The neighborhood pixel points in each scanning image block ensure that only one C exists₂Point, in point set C₂Forming embeddable point set C after removing neighborhood pixel points₃；

Step S7: setting a threshold T₃From the set of embeddable points C₃Intermediate screening of the final embeddable Point set C₄Forming a carrier perturbation map D_map；

Step S8: for carrier image X and carrier disturbance map D

Partitioning processing is carried out, an embeddable image block is screened, an embeddable image block is discarded, and the secret message m is segmented; the binary image only has one bit plane, and the characteristic determines that a large number of completely black or completely white areas exist in the binary image, and turning over pixels in the areas will certainly cause great distortion, so that carrier image blocks suitable for embedding secret information need to be screened before embedding. Dividing the carrier image into n image blocks with L × L size by adopting non-overlapping block division idea, counting the total amount of black and white pixels in each image block, removing all-black and all-white image blocks and embedding information to obtain all-white or all-black pure image blocks, and finally obtaining n

An embeddable image block X

And n is

Non-embeddable carrier image block

Perturbing the carrier image into a map D

The same partitioning is carried out according to the carrier image partitioning rule, the same partitioning is carried out on the carrier image blocks which are partitioned, the carrier image blocks correspond to the partitioned carrier image blocks one by one, and the secret message m is partitioned into n

Segments, each segment having a length of l

；

Step S9: randomly scrambling the embeddable image block by using a secret key K and further dividing super pixels; because the random scrambling algorithm meets the unbiased condition in the random process, namely each arrangement is equal in probability, the random scrambling technology is utilized to shuffle the embeddable image blocks and the corresponding disturbance mapping maps, so that the distribution of black and white pixels in the image blocks is more uniform, namely the distribution of the turnover pixels in the carrier image blocks is more uniform. And keeping the corresponding relation between the pixel points in the image block and the disturbance score values in the disturbance mapping chart unchanged in the scrambling process. Wherein the key used in the scrambling process is K, and n

An embeddable carrier image block X

And disturbance map D

After scrambling, n is obtained

Individual out-of-order carrier image block

And n

Out-of-order distortion metric matrix block

Further dividing the scrambled embeddable image block into super pixels;

step S10: embedding the divided secret message m into the embeddable image block by using STC coding to form an out-of-order secret-carrying image block

The STC encoding process is a process of finding a codeword having a minimum hamming distance from a carrier in a coset of secret information m. The coding is realized on a grid, and meets HY

All Y of m can be represented by one path in the trellis and then the one with the smallest weight among all paths is filtered. Wherein m isThe secret information to be embedded, Y is the secret carrier and H is the parity check matrix. The check matrix H is generated based on STC coding, and comprises m sub-matrices with H × 1/α

And expanding, wherein h is a coding parameter, the complexity and the embedding efficiency of the algorithm are controlled by adjusting the size of h, and alpha is the embedding rate. H is composed of m sub-matrices

Sequentially translating one row downwards and 1/alpha column leftwards to obtain the final h-1

The corresponding row needs to be intercepted. After constructing the parity check matrix H, the STC embedding process can be solved by the Viterbi algorithm;

step S11: using secret key K to carry encrypted image block out of order

Carrying out reverse scrambling operation; obtaining the recovered secret-carrying image block Y

；

Step S12: for Y after reverse scrambling operation

Is recombined with

Replacing the corresponding part in the carrier image X with n

Each carrying a secret image block Y

And n in step S6

Non-embedded secret message image block

And recombining according to the original pixel arrangement sequence of the carrier image to obtain a secret carrying image Y with complete texture and embedded secret message.

Preferably, the specific construction process of the distortion metric function is as follows:

a) calculating a crmiLTP value for each pixel pattern;

the LTP value in the clockwise case is calculated and expressed by formula (1)

Wherein

Indicates the criltp result value, p, for the clockwise pixel (i, j)

Representing the central pixel point, p

Representing a neighborhood pixel of the central pixel, r representing an offset or a rotation angle, k representing a neighborhood pixel label, mod representing a remainder operation, and ^ an XOR operation.

The final result of (c) is the minimum of the results produced during the clockwise rotation.

Next, the value of LTP in the counterclockwise case is calculated, and can be expressed by equation (2):

wherein

Indicates the criltp result value, p, for the counter-clockwise pixel (i, j)

Representing the central pixel point, p

Representing a neighborhood pixel of the central pixel, r representing an offset or a rotation angle, k representing a neighborhood pixel label, mod representing a remainder operation, and ^ an XOR operation.

The final result of (c) is the minimum of the results produced during the counterclockwise rotation.

And the LTP results are clockwise

And counterclockwise

The smaller value of the result is expressed by formula (3):

b) calculating a disturbance score by using a crmiLTP and edge line segment similarity disturbance measurement method respectively;

(1) the perturbation measure is performed by using the variation of the crmirltp, and the perturbation effect is preliminarily measured by the variation of the number of the crmirltp values caused by turning over the pixels, which is expressed by (4):

wherein Δ

Indicating the change in the amount of the criltp value caused by the pixel (i, j) flipping,

and

from the carrier image X and the secret image Y, a crmiltP representing a value t, respectively

The above calculation of the resulting histogram coefficient can be expressed by equation (5):

wherein l

And l

Representing the width and height of the calculated image only if

When the utility model is in use,

the value of (A) is 1, and the remaining values are all 0; and then, each crmiLTP is used for correlating the disturbance score of the turnover pixel point with the statistic securityThe histogram coefficient is used as a feature to evaluate the embedding distortion capability of the histogram coefficient, quantitative calculation is carried out by utilizing Fisher criterion, and the first 20 with the maximum coefficient is reserved as weight W

The final perturbation score is expressed by equation (6):

(2) calculating disturbance score by using edge line segment similarity disturbance measurement method

The amount of change of two types of edge line segments before and after pixel inversion is determined and expressed by the following formulas (7) and (8):

let us consider each binary image pixel as a regular square, then b_iRepresenting the line segments separating the neighbourhood pixels around the central pixel, c_iA line segment constituting the center pixel is indicated.

Respectively recording the length l of the edge line segment before and after pixel inversion₁,l₂Then calculating a disturbance score;

c) the obtained final disturbance score can be represented by formula (10);

score＝(0.725D₁+0.475D₂)^0.5+0.5 (10)

preferably, the embeddable point set C is constructed in the step S5₂The process is as follows:

score1(X, y) when carrier image X is perturbed and stego image S₁The perturbation scores score2(x, y) are all less than T₂From the stego image S₁Middle sieveOptional embeddable point set C₂Satisfy the point set

C₂＝{(i,j)|score1(x,y)＜T₂And score2(x, y) < T₂}。

Preferably, the embeddable point set C is constructed in the step S6₃The process is as follows:

removing the point set C by adopting the line scanning priority principle₂The neighborhood pixel points in each scanning image block ensure that only one C exists₂Point, in point set C₂Forming embeddable point set C after removing neighborhood pixel points₃。

Preferably, the embeddable point set C is constructed in the step S7₄The process is as follows:

set of points C₃The carrier image X pixel perturbation score1(X, y) corresponding to the position of the element and the stego image S₁The perturbation score2(x, y) is subtracted from the set of points C₃The absolute value of the difference value of the two selected in the process is less than a threshold value T₃Constitute a final embeddable point set C₄。

Compared with the prior art, the invention has the beneficial effects that:

(1) small embedding distortion and good image visual quality

The embedded disturbance is small, on one hand, in the allowable disturbance of all pixels in a given image, STC can find the most appropriate covert vector by minimizing the total disturbance, and STC overturns the pixels with the smallest disturbance influence as much as possible to complete the embedding; on the other hand, the difference of the disturbance mapping images before steganography and after steganography is considered, different thresholds are set for searching the embeddable point set, the uniqueness of the embeddable points in the range of scanning image blocks is ensured, and the mutual influence among pixels is reduced.

(2) High safety performance

The image steganography safety is mainly considered from imperceptibility and non-detectability, the embedded disturbance distortion is small, the image visual quality is high, and the imperceptibility is good; on the other hand, the invention uses an improved criltp distortion metric function which takes the statistical security into consideration and has higher detection resistance.

Drawings

FIG. 1 is a flow chart of the present invention.

FIG. 2 is a flow chart of the steganographic algorithm of the present invention.

FIG. 3 is a flow chart of dual perturbation scoring according to the present invention.

Detailed Description

The drawings are for illustrative purposes only and are not to be construed as limiting the patent;

the invention is further illustrated below with reference to the figures and examples.

Example 1

As shown in fig. 1, fig. 2 and fig. 3, an embedding process of an information steganography algorithm based on STC-coded binary image double-disturbance score includes the following steps:

(1) calculating a disturbance score map D of the carrier image X by using a crmiltP disturbance measurement method to obtain a disturbance score1(X, y) of each pixel point, and screening an embeddable point set C₁；

(2) Sequentially-turned embeddable point set C₁The pixel points of the included positions recalculate the image S₁A disturbance mapping graph D' is obtained to obtain a disturbance score2(x, y) of each pixel point;

(3) setting a threshold T₂When score1(x, y) and score2(x, y) are both less than T₂From the stego image S₁Middle screening embeddable point set C₂；

(4) Removing point set C₂Neighborhood pixel points, screening an embeddable point set C₃；

(5) Setting a threshold T₃The difference is made between score1(x, y) and score2(x, y), from point set C₃The absolute value of the difference value of the two selected in the process is less than a threshold value T₃Constitute a final embeddable point set C₄And comparing the sizes of score1(x, y) and score2(x, y), and assigning the smaller value of the two values to the perturbation score corresponding to the carrier pixel at the corresponding position to form a new carrier perturbation map D_map；

(6) Partitioning the carrier image to obtain n image blocks with the size of LxL, wherein each image block takes the first element coordinate at the upper left as the coordinateSerial number marked with B

And simultaneously, partitioning the disturbance mapping chart to obtain D

And each D

And each B

Mapping one by one; all image blocks B

Selecting, removing image blocks which are not suitable for embedding according to rules, and finally obtaining n

An embeddable carrier image block X

And n is

Non-embeddable carrier image block

Splitting a secret message m into n

Segments, each segment having a length of l

；

(7) Using a random scrambling algorithm, for n

An embeddable carrier image block X

And disturbance map D

Scrambling to obtain n

Individual out-of-order carrier image block

And n

Out-of-order distortion metric matrix block D

And further dividing the super pixels;

(8) selecting the ith secret message m

And the ith carrier block

And its corresponding disturbance mapping block

Embedding the secret message into the carrier image block as an input parameter for STC encoding embedding to obtain a secret-carrying carrier block

(9) Repeating (8) until the n-th

Embedding the secret message into the image block of the carrier to obtain n

A secret carrier block

(10) To carry the dense carrier block

Scrambling recovery is carried out to obtain a secret carrying block Y for reverse scrambling recovery

；

(11) Repeating (10) until the nth

A secret carrier block

Reverse scrambling is completed to obtain n

Secret-carrying carrier image block Y for inverse scrambling recovery

；

(12) N is to be

Each carrying a secret image block Y

And n in step S6

Non-embedded secret message image block

And recombining according to the original pixel arrangement sequence of the carrier image to obtain a secret carrying image Y with complete texture and embedded secret message.

As shown in fig. 2, an extraction process of an information steganography algorithm based on STC coding binary image double disturbance score includes the following steps:

(1) carrying out non-overlapping partitioning on the secret carrying body Y by taking L as the length, screening out all non-completely black or completely white pure color image blocks to obtain n_aIndividual secret carrier image block Y_ij；

(2) Using a secret key K to n

Individual secret carrier image block Y

Random scrambling is carried out to obtain n

Secret-carrying image block out of order

(3) To n

Secret-carrying image block out of order

Further dividing the super pixels, wherein the dividing principle is the same as the embedding flow step (7);

(4) for the ith out-of-order secret-carrying image block

Decoding as input in STC decoding program to obtain ith secret message component m

；

(5) Repeating the step (4) until n_aAfter all the secret-carrying image blocks are extracted, the secret message components m are sequentially processed_iSplicing to obtain a complete secret message ciphertext m;

(6) the secret information is decrypted and restored to a visible, plain text form.

It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

1. An STC coding-based binary image double disturbance scoring information steganography algorithm is characterized by comprising the following steps:

step S1: constructing a distortion measurement function, and performing disturbance scoring on the carrier image X by using the distortion measurement function to obtain a disturbance score chart D and a disturbance score1(X, y) of each pixel point of the carrier image X;

step S2: setting a threshold T₁The value in the disturbance score map D is smaller than T₁The values of (A) are screened out to form an embeddable point set C₁；

Step S3: sequentially-turned embeddable point set C₁The pixel points of the included positions obtain a secret image S₁；

Step S4: using distortion metric function to pair stego image S₁Carrying out disturbance scoring to obtain a secret disturbance score map D' and a secret image S₁The perturbation score2(x, y) for each pixel point;

step S5: setting threshold T according to embedding capacity₂When is coming into contact withscore1(x, y) and score2(x, y) are both less than T₂From the stego image S₁Middle screening embeddable point set C₂；

Step S6: removing embeddable point set C₂Neighborhood pixel, construct embeddable point set C₃；

Step S7: setting a threshold T₃From the set of embeddable points C₃Intermediate screening of the final embeddable Point set C₄Forming a carrier perturbation map D_map；

Step S8: for carrier image X and carrier disturbance map D_mapPartitioning processing is carried out, an embeddable image block is screened, an embeddable image block is discarded, and the secret message m is segmented;

step S9: randomly scrambling the embeddable image block by using a secret key K and further dividing super pixels;

step S10: embedding the divided secret message m into the embeddable image block by using STC coding to form an out-of-order secret-carrying image block

Step S11: using secret key K to carry encrypted image block out of order

Performing inverse scrambling operation to obtain the recovered secret-carrying image block Y

；

Step S12: for Y after reverse scrambling operation_ijCarrying out recombination with Y_ijReplacing the corresponding part in the carrier image X;

constructing an embeddable point set C in the step S7₄The process is as follows:

set of points C₃The carrier image X pixel perturbation score1(X, y) corresponding to the position of the element and the stego image S₁The perturbation score2(x, y) is subtracted from the set of points C₃The absolute value of the difference value of the two selected in the process is less than a threshold value T₃Constitute a final embeddable point set C₄。

2. The STC coding based binary image dual disturbance score information steganography algorithm according to claim 1, wherein the distortion metric function is constructed by the following specific process:

a) calculating a crmiLTP value for each pixel pattern in the image;

the LTP value in the clockwise case is calculated and expressed by formula (1)

Wherein

Indicates the criltp result value, p, for the clockwise pixel (i, j)

Representing the central pixel point, p

Representing the neighborhood pixel of the center pixel, r represents the offset or rotation angle, k represents the neighborhood pixel label, mod represents the remainder operation,

which represents an exclusive-or operation, and,

the final result of (a) is the minimum of the results produced during clockwise rotation;

the value of LTP in the counterclockwise case is calculated and can be expressed by equation (2):

wherein

Indicates the criltp result value, p, for the counter-clockwise pixel (i, j)

Representing the central pixel point, p

Representing a neighborhood pixel point of the central pixel, r representing an offset or a rotation angle, k representing a neighborhood pixel label, mod representing a neighborhood pixel labelThe operation of taking the rest of the materials,

which represents an exclusive-or operation, and,

the final result of (a) is the minimum of the results produced during the counter-clockwise rotation;

results of LTP

Is clockwise

And counterclockwise

The smaller value of the result is expressed by formula (3):

b) calculating a disturbance score by using a crmiLTP and edge line segment similarity disturbance measurement method respectively;

(1) the effect of perturbation is initially measured by the change in the number of crmltp values caused by flipping pixels over the image, and is represented by (4):

wherein Δ

Indicating that the pixel (i, j) has caused a change in the number of values of the crmiLTP after the pixel (i, j) has been flipped,

and

from the carrier image X and the secret image Y, a crmiltP representing a value t, respectively

The above calculation of the resulting histogram coefficient can be expressed by equation (5):

wherein l

And l

Representing the width and height of the calculated image only if

When the utility model is in use,

the value of (A) is 1, and the remaining values are all 0; and then, by associating the disturbance score of the turnover pixel point with statistical security, evaluating the embedding distortion capability of each crmiLTP histogram coefficient by taking each crmiLTP histogram coefficient as a feature, and carrying out quantitative calculation by utilizing a Fisher criterion, wherein the first 20 with the largest coefficients are reserved as weights W

Disturbance score D

Expressed by the formula (6):

(2) calculating a disturbance score by using a similar disturbance measurement method of the edge line segment;

judging the variation of two types of edge line segments before and after pixel inversion on the image, and expressing the variation by formulas (7) and (8):

wherein b is_iRepresenting neighborhood pixels around a central pixelA line segment separating between c_iRepresenting a line segment constituting a center pixel;

respectively recording the length l of the edge line segment before and after pixel inversion₁,l₂And then calculating a disturbance score D₂；

c) The obtained final disturbance score can be represented by formula (10);

score＝(0.725D₁+0.475D₂)^0.5+0.5 (10) 。

3. the STC-encoded binary image double-disturbance-scoring steganography algorithm according to claim 1, wherein the step S6 is implemented by constructing an embeddable point set C₃The process is as follows:

removing the point set C by adopting the line scanning priority principle₂The neighborhood pixel points in each scanning image block ensure that only one C exists₂Point, in point set C₂Forming embeddable point set C after removing neighborhood pixel points₃。

• 2019
  • 2019-01-16 CN CN201910041668.3A patent/CN109963159B/en active Active

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