CN102208097B - Network image copyright real-time distinguishing method - Google Patents

Network image copyright real-time distinguishing method Download PDF

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CN102208097B
CN102208097B CN2011101410724A CN201110141072A CN102208097B CN 102208097 B CN102208097 B CN 102208097B CN 2011101410724 A CN2011101410724 A CN 2011101410724A CN 201110141072 A CN201110141072 A CN 201110141072A CN 102208097 B CN102208097 B CN 102208097B
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sub
block
watermark
feature
coefficient
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CN102208097A (en
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叶天语
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Zhejiang Gongshang University
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Abstract

The invention provides a network image copyright real-time distinguishing method. Copyright protection is necessary for digital images during network communication, but the existing robust digital watermarking technology can not achieve the real-time copyright distinguishing. The method comprises the following steps: partitioning an original image to sub-blocks which are not overlapped with each other at an embedded end; processing each sub-block by discrete cosine transformation; generating a feature watermark by comparing the DC coefficient of each sub-block with the average DC coefficient of all sub-blocks; encrypting the Logistic chaotic sequence of the feature watermark; adjusting the magnitudes of two low-frequency coefficients of the discrete cosine transformation of each sub-block and self-embedding the encrypted feature watermark; and processing each sub-block by inverse discrete cosine transformation to obtain images with watermarks. The method has high robustness to attack. Substantially, the method provided by the invention can achieve complete blind detection by combining the self-embedding encrypted feature watermark with watermark blind extraction and authentication, thereby achieving real-time copyright distinguishing of network images.

Description

A kind of network image copyright real-time distinguishing method
Technical field
The present invention relates to information security field.The present invention designs a kind of network image copyright real-time distinguishing method, and the copyright of the digital picture of transmission over networks is differentiated in real time.
Background technology
Digital picture is propagated in network and is easily caused dispute over copyright, need to carry out copyright protection.The robust digital watermark technology can be used for the digital picture of transmission over networks is carried out copyright protection.
Classify according to the content of watermark, watermark can be divided into meaningful watermark and meaningless watermark.The content that meaningful watermark refers generally to watermark has concrete implication, such as bianry image, gray level image, trade mark, author's personal information etc.; The general corresponding pseudo-random sequence that there is no concrete meaning of meaningless watermark.In addition, hot spring etc. [1]Also propose " zero watermark ", zero watermark represents in fact certain feature of initial carrier.Therefore, zero watermark can be regarded as a kind of meaningful watermark of special shape.
Whether needs are by initial carrier according to the test side, and digital watermark technology can be divided into blind digital watermark technology and non-blind digital watermark technology.Often need to be by the information relevant to initial carrier when non-blind digital watermark technology detects watermark in the test side, blind digital watermark technology need to be by any information relevant to initial carrier in the test side.In some application scenarios, be subject to the restrictions such as transmission, storage, security, the test side often can't obtain the information relevant to initial carrier, and therefore blind digital watermark technology has more practicality than non-blind digital watermark technology.
The robust digital watermark algorithm judges copyright by the degree of correlation between the watermark of calculating original watermark and extraction usually in the test side.According to the test side whether needs by to initial carrier, information that original watermark is relevant, the detection behavior of present robust digital watermark algorithm can be divided into 4 classes: (1) the 1st class: the test side both need to be by the relevant information of initial carrier, again need to be by the relevant information of original watermark.(2) the 2nd classes: the test side need to be by the relevant information of initial carrier, but does not need the relevant information of original watermark.(3) the 3rd classes: the test side need to be by the relevant information of initial carrier, but need to be by the relevant information of original watermark.(4) the 4th classes: the test side neither need to be by the relevant information of initial carrier, also need to be by the relevant information of original watermark.Traditional non-blind robust watermarking algorithm has the 1st class or the 2nd class detects behavior, and practicality is poor.Blind meaningless robust watermarking algorithm with the 3rd class detection behavior [2]The relevant information by any initial carrier does not extract watermark from attacking carrier in the test side, but will produce original pseudorandom watermark sequence by key, then calculates both degree of correlation judgement copyrights.Blind meaningful robust watermarking algorithm with the 3rd class detection behavior [3-10]Do not extract watermark by the relevant information of any initial carrier from attacking carrier in the test side, the degree of correlation of then calculating between the watermark of the original watermark that transmits from built-in end and extraction judges copyright.Zero watermarking algorithm [1,11]Also to have the 3rd class to detect behavior.This be because: in the test side, zero watermarking algorithm need to take out being stored in notarize original zero watermark at center of third party, then calculate with the zero watermark of extracting between the degree of correlation judge copyright.Robust watermarking algorithm with the 4th class detection behavior does not almost occur, and the present invention claims that this class robust algorithm is complete blind detection robust watermarking algorithm.
Present blind robust watermarking algorithm has the 3rd class and detects behavior, still can't reach copyright and differentiate in real time, and its practical sexual needs further improve.This be because: need to be by the relevant information of any initial carrier in the test side although have blind robust watermarking algorithm that the 3rd class detects behavior, but need to weigh the degree of correlation between the watermark of original watermark and extraction to judge copyright by the partial information of original watermark or original watermark.So, built-in end transmission original watermark or its partial information to the test side (or third party notarize center) store and just need certain transmission cost and carrying cost, and the process of transmission is very difficult prevents ubiquitous passive attack on the internet fully.For example, the original watermark that assailant's success " eavesdropping " is transmitted or the partial information of original watermark, obtain embedded watermark and further forge watermark passing to the test side by analysis, can make real original watermark can't be used for differentiating copyright, reach the purpose of disturbing copyright to differentiate, thereby make watermarking algorithm can't resist interpretation Attack [12]
The self-embedding Fragile Watermarking Technique [13-17]Distinguishing feature be that feature that built-in end extracts initial carrier produces watermark and self-embedding authenticates to reach content integrity to initial carrier.At present, " self-embedding " thought only is applied to the Fragile Watermarking Technique field basically.
Comprehensive above the analysis, the present invention attempts " self-embedding " thought with the self-embedding Fragile Watermark Algorithm and is incorporated into the robust digital watermark field, design has the complete blind detection robust watermarking algorithm that the 4th class detects behavior, thereby a kind of network image copyright real-time distinguishing method is provided, reaches the copyright of the digital picture of transmission over networks is differentiated in real time.
List of references
[1] hot spring, grandson's lance cutting edge of a knife or a sword, Wang Shuxun. concept and the application [J] of zero watermark. electronic letters, vol, 2003,31 (2): 214-216.
[2]Wang Xiang-yang，Hou Li-min，and Wu Jun.A feature-based robust digital image watermarking against geometric attacks[J].Image and Vision Computing，2008，26：980-989.
[3] Niu Shaozhang, button heart Xin, Yang Yixian, Hu Wenqing. Data Hiding Algorithm for Halftone Images [J]. electronic letters, vol, 2004,32 (7): 1180-1183.
[4]Wang Xiang-yang and Cui Chang-ying.A novel image watermarking scheme against desynchronization attacks by SVR revision[J].Journal of Visual Communication and Image Representation，2008，19(5)：334-342.
[5] Li Xudong, Zhang Zhen jumps. the digital watermarking algorithm [J] of the double-deck division of image and svd. and journal of Zhejiang university (engineering version), 2006,40 (12): 2088-2092.
[6] Yuan Dayang, Xiao Jun, Wang Ying. digital figure watermark algorithm anti-geometry attack robust Journal of Sex Research [J]. electronics and information journal, 2008,30 (5): 1251-1256.
[7] Li Xudong. the spatial domain Arithmetic on Digital Watermarking of Image [J] of resist geometric attacks. robotization journal, 2008,34 (7): 832-837.
[8] Xu Wenli, Li Lei, Wang Yumin. the Robust Digital Watermarking Scheme [J] of antinoise, geometric distortion and JPEG compression attack. electronics and information journal, 2008,30 (4): 933-936.
[9] Li Leida, Guo Baolong, table Jin Feng. based on the spatial domain resist geometric attacks watermarking algorithm [J] of odd-even quantization. electronics and information journal, 2009,31 (1): 134-138.
[10]Leida Li，Jiansheng Qian，Jeng-Shyang Pan.Characteristic region based watermark embedding with RST invariance and high capacity.International Journal of Electronics and communications，2011，65：435-442.
[11] Ye Tianyu. the anti-secondary print and scan of discrete cosine transform domain Robust Zero watermarking algorithm [J]. photon journal, 2011,40 (1): 142-148.
[12] Li Qingcheng, Dou Yi. the interpretation Attack of digital watermarking and Relating Characteristic [J]. computer utility, 2005 (5): 115-117.
[13] Zhang Hongbin, poplar becomes. the self-embedding of image and the detection of altering and recovery algorithms [J]. and electronic letters, vol, 2004,32 (2): 196-199.
[14] and red outstanding person, Zhang Jiashu. based on the piecemeal Self-Embedding Watermarking Scheme [J] of Chaotic Scrambling. communication journal, 2006,27 (7): 80-86,93.
[15] Zhang Xianhai, Yang Yongtian. based on the image authentication algorithm research [J] of fragile watermark. electronic letters, vol, 2007,35 (1): 34-39.
[16] Wang Guodong, Liu Fenlin, Liu Yuan, Yao Gang. a kind of Fragile Watermark Algorithm [J] that can distinguish watermark or content tampering. electronic letters, vol, 2008,36 (7): 1349-1354.
[17] and red outstanding person, Zhang Jiashu. watermark information is distorted the Self-Embedding Watermarking Scheme [J] of robust. Journal of Software, 2009,20 (2): 437-450.
Summary of the invention
The objective of the invention is to design a kind of network image copyright real-time distinguishing method, the copyright of the digital picture of transmission over networks is differentiated in real time.
A kind of network image copyright real-time distinguishing method comprises following five processes:
A, feature watermark produce;
B, feature watermark are encrypted;
The feature watermark self-embedding of C, encryption;
D, feature watermark extract;
E, the blind extraction of authenticating water-mark and deciphering.
Steps A further comprises following content:
A1: the original image that is M * M with size is divided into the big or small not overlapping sub-block of m * m that is;
A2: each sub-block is carried out discrete cosine transform (Discrete Cosine Transformation, DCT), B i(0,0) represents direct current (Direct Current, the DC) coefficient of i sub-block, B Average(0,0) represents the average of all sub-block DC coefficients,
Figure BSA00000506003100051
A3: feature watermark W is by each sub-block DC coefficient B of contrast i(0,0) and all sub-block DC Coefficient Mean B AverageThe magnitude relationship of (0,0) produces.That is:
if B i(0，0)＞B average(0，0)
w i＝1；
else
w i＝0
end
Wherein, w iRepresent the i bit of W.Easily know, the length of feature watermark W is
Figure BSA00000506003100052
Step B further comprises following content:
B1: select a real number as initial value x in (1,1) 0, select a real number as γ in [0,2], then shine upon by Logistic
Figure BSA00000506003100053
Carry out iteration and produce chaos random number sequence { x 1, x 2, x 3....With initial value x 0With the first two key of parameter γ as the Logistic mapping.
B2: cast out front κ random number of chaos sequence, because initial random number is unstable.With κ+1 to
Figure BSA00000506003100054
Individual random number
Figure BSA00000506003100055
By l i = sgn ( x κ + i ) + 1 2 Two-value turn to GF (2) territory { 0,1} sequence L, sgn () they are sign function, l iBe the ibit of L,
Figure DEST_PATH_RE-RE-GSB00000919600700011
Logistic mapping average is 0, so select 0 to carry out binaryzation as threshold value.With three key of parameter κ as the Logistic mapping.
B3: utilize sequence L that feature watermark W is encrypted.Encryption method is:
Figure DEST_PATH_RE-RE-GSB00000919600700012
Wherein
Figure DEST_PATH_RE-RE-GSB00000919600700013
Be XOR,
Figure DEST_PATH_RE-RE-GSB00000919600700014
Be the feature watermark W that encrypts eIbit,
Figure DEST_PATH_RE-RE-GSB00000919600700015
Step C further comprises following content:
C1: original image is divided into size and is the not overlapping sub-block of m * m;
C2: each sub-block is carried out DCT;
C3: the feature watermark that self-embedding is encrypted is in the DCT medium and low frequency coefficient of each sub-block of original image:
if w i e = 0
if B i(r 1，s 1)＜B i(r 2，s 2)
B i ( r 1 , s 1 ) ↔ B i ( r 2 , s 2 ) ;
else
if B i(r 1，s 1)≥B i(r 2，s 2)
B i ( r 1 , s 1 ) ↔ B i ( r 2 , s 2 ) ;
end
η i＝μ×B i(0，0)；
if B i(r 1，s 1)＞B i(r 2，s 2)
if (B i(r 1，s 1)-B i(r 2，s 2))＜η i
B i ( r 1 , s 1 ) = B i ( r 1 , s 1 ) + η i 2
B i ( r 2 , s 2 ) = B i ( r 2 , s 2 ) - η i 2 ;
else
Figure DEST_PATH_GSB00001025044600011
Wherein, symbol
Figure DEST_PATH_RE-GSB00001025044600012
The size of expression exchange left and right two numbers; μ is
Figure DEST_PATH_RE-GSB00001025044600013
The scale factor that self-adaptation embeds, according to practical application to the requirement of invisibility and the robustness selection of compromising; B i(r j, s j) represent that i sub-block DCT matrix is at (r j, s j) coefficient located, j=1,2, require to satisfy r 1=r 2And s 1=s 2Can not set up simultaneously, and r 1=0 and s 1=0 can not set up simultaneously, r 2=0 and s 2=0 can not set up simultaneously.
C4: each sub-block is carried out inverse discrete cosine transform (Inverse Discrete Cosine Transformation, IDCT), obtains containing watermarking images after restructuring.
Step D further comprises following content:
D1: attack graph looks like to be divided into size and is the not overlapping sub-block of m * m;
D2: each sub-block is carried out DCT,
Figure DEST_PATH_RE-GSB00001025044600014
Represent the DC coefficient of i sub-block,
Figure DEST_PATH_RE-GSB00001025044600015
Represent the average of all sub-block DC coefficients,
Figure DEST_PATH_RE-GSB00001025044600016
D3: feature watermark W aBy contrasting each sub-block DC coefficient With all sub-block DC Coefficient Means
Figure DEST_PATH_RE-GSB00001025044600018
Magnitude relationship extract.That is:
Figure DEST_PATH_GSB00001025044600019
Wherein, Represent W aIb it.
Step e further comprises following content:
E1: attack graph looks like to be divided into size and is the not overlapping sub-block of m * m;
E2: each sub-block is carried out DCT;
E3: extract authenticating water-mark W from each sub-block DCT matrix by the following method a':
if B i(r 1，s 1)＞B i(r 2，s 2)
w i a ′ = 0
else
w i a ′ = 1
end
Wherein,
Figure BSA00000506003100085
Represent W a' ibit.
E4: utilize x 0Produce Logistic Map Chaotic { x with two keys of γ 1, x 2, x 3..., give up a front κ random number, with κ+1 to Individual random number
Figure BSA00000506003100087
By
Figure BSA00000506003100088
Two-value turns to { 0, the 1} sequence L in GF (2) territory.
E5: by
Figure BSA00000506003100089
To the authenticating water-mark W that extracts a' be decrypted, wherein
Figure BSA000005060031000810
Authenticating water-mark W after the representative deciphering a" ibit.
E6: calculate the feature watermark W that extracts after attacking aWith the authenticating water-mark W after deciphering a" between the normalization degree of correlation (Normalized Correlation, NC) estimate anti-attack robust with the judgement copyright.The NC value is defined as:
θ = ( Σ i = 1 ( M m ) 2 ( w i a × w i a ′ ′ ) ) / ( Σ i = 1 ( M m ) 2 ( w i a ) 2 × Σ i = 1 ( M m ) 2 ( w i a ′ ′ ) 2 ) .
The present invention provides a real-time novel identification method of copyright for the digital picture of transmission over networks.At first the present invention is divided into original image the sub-block of non-overlapping copies at built-in end, each sub-block is carried out DCT, magnitude relationship generation feature watermark between DC coefficient by each sub-block relatively and the average of all sub-block DC coefficients, feature watermark is carried out the Logistic encrypted chaotic array, then adjust the feature watermark that the big or small self-embedding of two DCT medium and low frequency coefficients of each sub-block is encrypted, each sub-block is carried out IDCT and is obtained containing watermarking images at last.In the test side, extract feature watermark and authenticating water-mark from the attack graph picture respectively.Process and built-in end feature watermark production process that feature watermark extracts are similar, and the blind leaching process of authenticating water-mark is the inverse process of the feature watermark self-embedding process of built-in end encryption.Experimental result shows: the feature watermark self-embedding algorithm that feature watermark produces algorithm and encryption all has very strong robustness to various attack.Therefore, algorithm of the present invention has the robustness of very strong opposing various attack.The present invention realizes complete blind Detecting in conjunction with feature watermark and blind extraction authenticating water-mark that self-embedding is encrypted in fact, realizes the copyright of network image is differentiated in real time.
Description of drawings
Fig. 1 is the algorithm flow chart that feature watermark produces.
Fig. 2 is the algorithm flow chart that feature watermark is encrypted.
Fig. 3 is the algorithm flow chart of the feature watermark self-embedding of encryption.
Fig. 4 is the algorithm flow chart that feature watermark extracts.
Fig. 5 is the algorithm flow chart of the blind extraction of authenticating water-mark and deciphering.
Fig. 6 is original Lena image, and Fig. 7 is original Barbara image, and Fig. 8 is original Elain image, and Fig. 9 contains watermark Lena image, and Figure 10 contains watermark Barbara image, and Figure 11 contains watermark Elain image.
Embodiment
Below in conjunction with drawings and Examples, technical scheme of the present invention is described further.
1 feature watermark produces
Fig. 1 is the algorithm flow chart that feature watermark produces, and comprises following process [11]:
A1: the original image that is M * M with size is divided into the big or small not overlapping sub-block of m * m that is;
A2: each sub-block is carried out DCT, B i(0,0) represents the DC coefficient of i sub-block, B Average(0,0) represents the average of all sub-block DC coefficients,
Figure BSA00000506003100101
A3: feature watermark W is by each sub-block DC coefficient B of contrast i(0,0) and all sub-block DC Coefficient Mean B AverageThe magnitude relationship of (0,0) produces.That is:
if B i(0，0)＞B average(0，0)
w i＝1；
else
w i＝0
end (1)
Wherein, w iRepresent the i bit of W.Easily know, the length of feature watermark W is
Figure BSA00000506003100102
Can be known by above process, W produces by the DC coefficient characteristics of extracting original image, and this process is not made any modification to original image in fact.Therefore, the present invention calls feature watermark to W.
2 feature watermarks are encrypted
In nonlinear dynamic system, chaos phenomenon is deterministic, similar random process, does not restrain and does not have periodically, and is very responsive to initial value.The Logistic chaotic maps is the nonlinear dynamic system of a widespread use, is defined as:
x n + 1 = 1 - γ x n 2 - - - ( 2 )
x n+1Span be (1,1), n=0,1,2,3 ...If γ is in [0,2] interior value, this mapping is in chaos state.The present invention utilizes the initial value susceptibility of Logistic mapping that the feature watermark that produces is encrypted.The process of Logistic mapping encrypting feature watermark is seen Fig. 2, comprises following process:
B1: select a real number as initial value x in (1,1) 0, select a real number as γ in [0,2], then carry out iteration by (2) formula and produce chaos random number sequence { x 1, x 2, x 3....With initial value x 0With the first two key of parameter γ as the Logistic mapping.
B2: cast out front κ random number of chaos sequence, because initial random number is unstable.With κ+1 to Individual random number
Figure DEST_PATH_RE-RE-GSB00000919600700032
Through type (3) two-value turn to GF (2) territory 0,1} sequence L, namely
l i = sgn ( x κ + i ) + 1 2 - - - ( 3 )
Wherein sgn () is sign function, l iBe the ibit of L,
Figure DEST_PATH_RE-RE-GSB00000919600700034
Logistic mapping average is 0, so select 0 to carry out binaryzation as threshold value.With three key of parameter κ as the Logistic mapping.
B3: utilize that binaryzation obtains { 0,1} sequence L is encrypted feature watermark W.Encryption method is:
w i e = w i ⊕ l i - - - ( 4 )
Wherein
Figure DEST_PATH_RE-RE-GSB00000919600700036
Be XOR,
Figure DEST_PATH_RE-RE-GSB00000919600700037
Be the feature watermark W that encrypts eIbit,
Figure DEST_PATH_RE-RE-GSB00000919600700038
The 3 feature watermark self-embeddings of encrypting
Fig. 3 is the algorithm flow chart of the feature watermark self-embedding of encryption, comprises following process:
C1: original image is divided into size and is the not overlapping sub-block of m * m;
C2: each sub-block is carried out DCT;
C3: the feature watermark that self-embedding is encrypted is in the DCT medium and low frequency coefficient of each sub-block of original image:
if w i e = 0
if B i(r 1，s 1)＜B i(r 2，s 2)
B i ( r 1 , s 1 ) ↔ B i ( r 2 , s 2 ) ;
else
Figure DEST_PATH_GSB00001025044600021
Wherein, symbol
Figure DEST_PATH_RE-GSB00001025044600022
The size of expression exchange left and right two numbers; μ is
Figure DEST_PATH_RE-GSB00001025044600023
The scale factor that self-adaptation embeds, according to practical application to the requirement of invisibility and the robustness selection of compromising; B i(r j, s j) represent that i sub-block DCT matrix is at (r j, s j) coefficient located, j=1,2, require to satisfy r 1=r 2And s 1=s 2Can not set up simultaneously, and r 1=0 and s 1=0 can not set up simultaneously, r 2=0 and s 2=0 can not set up simultaneously.
C4: each sub-block is carried out IDCT, obtains containing watermarking images after restructuring.
The feature watermark that the present invention selects DCT medium and low frequency coefficient to adjust self-embedding to encrypt in (5) formula.This is often not have very strong robustness to attacking because revise the DCT high frequency coefficient.
4 feature watermarks extract
Test side feature watermark leaching process and built-in end feature watermark production process are similar.Fig. 4 is the algorithm flow chart that feature watermark extracts, and comprises following process [11]:
D1: attack graph looks like to be divided into size and is the not overlapping sub-block of m * m;
D2: each sub-block is carried out DCT,
Figure BSA00000506003100131
Represent the DC coefficient of i sub-block,
Figure BSA00000506003100132
Represent the average of all sub-block DC coefficients,
Figure BSA00000506003100133
D3: feature watermark W aBy contrasting each sub-block DC coefficient
Figure BSA00000506003100134
With all sub-block DC Coefficient Means
Figure BSA00000506003100135
Magnitude relationship extract.That is:
if B i a ( 0,0 ) > B average a ( 0,0 )
w i a = 1 ;
else
w i a = 0
end (6)
Wherein, Represent W aIbit.
The 5 blind extraction of authenticating water-mark and deciphering
The leaching process of test side authenticating water-mark is the inverse process of the feature watermark self-embedding process of built-in end encryption.Fig. 5 is the algorithm flow chart of the blind extraction of authenticating water-mark and deciphering, comprises following process:
E1: attack graph looks like to be divided into size and is the not overlapping sub-block of m * m;
E2: each sub-block is carried out DCT;
E3: extract authenticating water-mark W from each sub-block DCT matrix by the following method a':
if B i(r 1，s 1)＞B i(r 2，s 2)
w i a ′ = 0
else
w i a ′ = 1
end (7)
Wherein,
Figure BSA00000506003100142
Represent W a' i bit.
E4: utilize x 0Produce Logistic Map Chaotic { x with two keys of γ 1, x 2, x 3..., give up a front κ random number, with κ+1 to
Figure BSA00000506003100143
Individual random number
Figure BSA00000506003100144
Through type (3) two-value turns to { 0, the 1} sequence L in GF (2) territory.
E5: the authenticating water-mark W of decryption method to extracting that through type (4) is corresponding a' be decrypted, namely
w i a ′ ′ = w i a ′ ⊕ l i - - - ( 8 )
Wherein, Authenticating water-mark W after the representative deciphering a" ibit.
E6: calculate the feature watermark W that extracts after attacking aWith the authenticating water-mark W after deciphering a" between NC estimate anti-attack robust with the judgement copyright.The NC value is defined as:
θ = ( Σ i = 1 ( M m ) 2 ( w i a × w i a ′ ′ ) ) / ( Σ i = 1 ( M m ) 2 ( w i a ) 2 × Σ i = 1 ( M m ) 2 ( w i a ′ ′ ) 2 ) . - - - ( 9 )
Reach blind extraction when obviously, authenticating water-mark is extracted in the test side.The present invention is W a' the reason that is called authenticating water-mark is that the test side is to W a' be decrypted rear for carrying out copyright authentication.By the 4th part and the 5th part as can be known, the test side only need to utilize the attack graph picture just can extract feature watermark respectively and authenticating water-mark calculates NC, need to be by the relevant information of any original image and original watermark.Therefore, the present invention can realize complete blind Detecting, realizes the copyright of network image is differentiated in real time.
Embodiment:
1 experiment parameter explanation
Selecting 256 grades of sizes is that 512 * 512 Lena, Barbara and Elain three width gray level images are as experimental image, respectively as shown in Fig. 6,7 and 8.The size of sub-block is all 16 * 16, so the length of feature watermark W is 1024bit.Logistic chaotic maps initial value x 0Value is 0.28, casts out front κ=200 random number when parameter γ value is 1.5, Logistic encrypted chaotic array feature watermark W.The feature watermark W that encrypts eThe original Lena of self-adaptation self-embedding, Barbara and each sub-block of Elain image are in the DCT coefficient of (3,5) and (4,4) position.
Figure BSA00000506003100151
The scale factor μ value that self-adaptation embeds is 0.028.Obtain contain watermark Lena, Barbara and the Elain image is seen respectively Fig. 9,10 and 11, and the PSNR between original Lena, Barbara and Elain image is 35.9595,36.1211 and 35.7637.Therefore, three width test patterns all had good invisibility.
2 anti-attack robust experiments
Weigh the robustness of opposing various attack with the NC value.Middle random erasure capable finger, begin to move up line by line from the following the first row of deleted row, and vacant row completion is black.Downward bias is divided a word with a hyphen at the end of a line and is referred to that whole image moves down several row, above a few row completions black, last several row shift out loss.Offset column refers to that whole image moves to right to the right, and several row completions in front are black, and last several row shift out loss.Resample and adopt the nearest method of interpolation.In each table, "/" below contains PSNR between watermarking images and original image for three width after attacking, and "/" top is two NC values between watermark sequence.
(1) the feature watermark W that extracts aWith the authenticating water-mark W after deciphering a" between the NC value
Do not exist when attacking, contain the feature watermark W that watermark Lena, Barbara and Elain image extract separately aWith the authenticating water-mark W after deciphering a" between the NC value be all 1.0000.Three width after attack contain the feature watermark W that watermarking images extracts separately aWith the authenticating water-mark W after deciphering a" between the NC value see Table 1.As can be seen from Table 1, algorithm of the present invention all shows very strong robustness to various attack.
(2) the feature watermark W that extracts aAnd the NC value between primitive character watermark W
Do not exist when attacking, contain the feature watermark W that watermark Lena, Barbara and Elain image extract separately aAnd the NC value between primitive character watermark W is all 1.0000.Three width after attack contain the feature watermark W that watermarking images extracts separately aAnd the NC value between primitive character watermark W sees Table 2.Therefore, feature watermark generation algorithm of the present invention all has very strong robustness to various attack.In addition, the data of contrast table 1 and table 2 can find, the anti-attack robust that feature watermark produces algorithm slightly is better than algorithm of the present invention.
(3) the authenticating water-mark W after the deciphering a" and the NC value between primitive character watermark W
Do not exist when attacking, contain the authenticating water-mark W after watermark Lena, Barbara and Elain image are deciphered separately a" and the NC value between primitive character watermark W is all 1.0000.The authenticating water-mark W that three width after attack contain watermarking images after deciphering separately a" and the NC value between primitive character watermark W sees Table 3.Therefore, the feature watermark self-embedding algorithm of encryption of the present invention all has very strong robustness to various attack.In addition, the data of contrast table 1 and table 3 can find, the anti-attack robust of the feature watermark self-embedding algorithm of encryption slightly is better than algorithm of the present invention.
Three width after table 1 is attacked contain the feature watermark W that watermarking images extracts separately aWith the authenticating water-mark W after deciphering a" between the NC value
Figure BSA00000506003100161
3 analyze and discuss
Algorithm of the present invention can be realized complete blind Detecting, its reason is to reach simultaneously following 2 points: (1) produces feature watermark from original image by feature extraction, original image is arrived in self-embedding after encrypting, rather than extra watermark form is embedded into original image; (2) the feature watermark self-embedding algorithm of encrypting itself just can reach blind extraction authenticating water-mark in the test side.
Three width after table 2 is attacked contain the feature watermark W that watermarking images extracts separately aAnd the NC value between primitive character watermark W
Figure BSA00000506003100171
The authenticating water-mark W that three width after table 3 is attacked contain watermarking images after deciphering separately a" and the NC value between primitive character watermark W
Figure BSA00000506003100172
Algorithm of the present invention has strong robustness to various attack, and its reason is to reach simultaneously following 2 points: (1) feature watermark produces algorithm itself and just has very strong anti-attack robust, can come as seen from Table 2.(2) the feature watermark self-embedding algorithm itself of encrypting just has very strong anti-attack robust, can come as seen from Table 3.In addition, the anti-attack robust of algorithm of the present invention slightly is worse than the reason that feature watermark produces the feature watermark self-embedding algorithm of algorithm and encryption and is that the feature watermark self-embedding meeting of encrypting has certain impact to the DC coefficient that produces feature watermark.
4 sum up
Present blind robust watermarking algorithm still need to be by the partial information of original image or original watermark in the test side, thereby can't really realize complete blind Detecting, thereby can't reach, the copyright of the digital picture of transmission over networks is differentiated in real time.For this problem, the present invention is incorporated into the robust watermarking field with " self-embedding " thought of Fragile Watermark Algorithm, proposes the complete blind detection robust watermarking algorithm of a kind of self-embedding, realizes the copyright of the digital picture of transmission over networks is differentiated in real time.Algorithm of the present invention possesses following 4 characteristics simultaneously:
(1) " self-embedding " characteristic: produce feature watermark by feature extracting method from original image, then the feature watermark self-embedding of encrypting is contained watermarking images to the original image generation.
(2) " complete blind extraction " characteristic: neither need to be by any information relevant to initial carrier during detection, again need to be by any information relevant to original watermark.In the test side, at first extract feature watermark from attacking the imagery exploitation feature extracting method identical with built-in end; Then blindly extract authenticating water-mark from the inverse process of attacking the feature watermark self-embedding algorithm that the imagery exploitation built-in end encrypts; Calculate at last the feature watermark of extraction and the NC between authenticating water-mark and judge copyright.Therefore, the test side only need to utilize the attack graph picture.
(3) robustness: the feature watermark self-embedding algorithm that feature watermark produces algorithm and encryption all has very strong robustness to various attack, and further, algorithm of the present invention has the robustness of very strong opposing various attack.
(4) security: first will carry out the Logistic encrypted chaotic array before feature watermark self-embedding original image, not know that the assailant of encryption key can't accurately decrypt feature watermark.
The complete blind detection robust digital watermark of self-embedding that the present invention proposes has very important Research Significance.This is embodied in:
(1) save transmission cost and carrying cost.Any information that built-in end need not to transmit initial carrier and original watermark to the test side (or third party notarize center) store, thereby save transmission cost and carrying cost.
(2) blocking-up interpretation Attack.Any information that built-in end need not to transmit original watermark can effectively be blocked interpretation Attack to the test side (or third party notarize center).
Therefore, the complete blind detection robust watermarking algorithm of self-embedding that the present invention proposes provides a kind of network image copyright real-time distinguishing method, and realization is differentiated in real time to the copyright of the digital picture of transmission over networks.

Claims (1)

1. network image copyright real-time distinguishing method, " self-embedding " thought of self-embedding Fragile Watermark Algorithm is incorporated into the robust digital watermark field, the test side neither need to be by the relevant information of initial carrier, need to be by the relevant information of original watermark yet, only need image to be detected, realize complete blind Detecting, the copyright of the digital picture of transmission over networks differentiated in real time, comprise following five processes:
A, feature watermark produce: the original image that (1) is M * M with size is divided into size and is the not overlapping sub-block of m * m; (2) each sub-block is carried out discrete cosine transform (Discrete Cosine Transformation, DCT), B i(0,0) represents direct current (Direct Current, the DC) coefficient of i sub-block, B Average(0,0) represents the average of all sub-block DC coefficients,
Figure DEST_PATH_FSB00000919600600011
(3) feature watermark W is by each sub-block DC coefficient B of contrast i(0,0) and all sub-block DC Coefficient Mean B AverageThe magnitude relationship of (0,0) produces, that is:
if B i(0，0)＞B average(0，0)
w i＝1；
else
w i＝0
end
Wherein, w iRepresent the i bit of W;
B, feature watermark are encrypted: (1) selects a real number as initial value x in (1,1) 0, select a real number as γ in [0,2], then shine upon by Logistic
Figure DEST_PATH_FSB00000919600600012
Carry out iteration and produce chaos random number sequence { x 1, x 2, x 3..., with initial value x 0With the first two key of parameter γ as the Logistic mapping; (2) cast out front κ random number of chaos sequence, because initial random number is unstable; With κ+1 to
Figure DEST_PATH_FSB00000919600600021
Individual random number
Figure DEST_PATH_FSB00000919600600022
By
Figure DEST_PATH_FSB00000919600600023
Two-value turn to GF (2) territory { 0,1} sequence L, sgn () they are sign function, l iBe the ibit of L,
Figure DEST_PATH_FSB00000919600600024
Logistic mapping average is 0, so select 0 to carry out binaryzation as threshold value; With three key of parameter κ as the Logistic mapping; (3) utilize sequence L that feature watermark W is encrypted, encryption method is:
Figure DEST_PATH_FSB00000919600600025
Wherein
Figure DEST_PATH_FSB00000919600600026
Be XOR,
Figure DEST_PATH_FSB00000919600600027
Be the ibit of the feature watermark We that encrypts,
Figure DEST_PATH_FSB00000919600600028
The feature watermark self-embedding of C, encryption: (1) original image is divided into size and is the not overlapping sub-block of m * m; (2) each sub-block is carried out DCT; (3) feature watermark of self-embedding encryption is in the DCT medium and low frequency coefficient of each sub-block of original image:
Figure DEST_PATH_FSB00000919600600029
if B i(r 1，s 1)＜B i(r 2，s 2)
else
if B i(r 1，s 1)≥B i(r 2，s 2)
end
η i＝μ×B i(0，0)；
if B i(r 1，s 1)＞B i(r 2，s 2)
if (B i(r 1，s 1)-B i(r 2，s 2))＜η i
Figure DEST_PATH_FSB000009196006000212
Figure DEST_PATH_FSB00000919600600031
else
if (B i(r 2，s 2)-B i(r 1，s 1))＜η i
Figure DEST_PATH_FSB00000919600600032
end
Wherein, symbol
Figure DEST_PATH_FSB00001025044500012
The size of expression exchange left and right two numbers; μ is
Figure DEST_PATH_FSB00001025044500013
The scale factor that self-adaptation embeds, according to practical application to the requirement of invisibility and the robustness selection of compromising; B i(r j, s j) represent that i sub-block DCT matrix is at (r j, s j) coefficient located, j=1,2, require to satisfy r 1=r 2And s 1=s 2Can not set up simultaneously, and r 1=0 and s 1=0 can not set up simultaneously, r 2=0 and s 2=0 can not set up simultaneously; (4) each sub-block is carried out inverse discrete cosine transform (Inverse Discrete Cosine Transformation, IDCT), obtains containing watermarking images after restructuring;
D, feature watermark extract: (1) attack graph looks like to be divided into size and is the not overlapping sub-block of m * m; (2) each sub-block is carried out DCT,
Figure DEST_PATH_FSB00001025044500014
Represent the DC coefficient of i sub-block, Represent the average of all sub-block DC coefficients,
Figure DEST_PATH_FSB00001025044500016
(3) feature watermark W aBy contrasting each sub-block DC coefficient With all sub-block DC Coefficient Means
Figure DEST_PATH_FSB00001025044500018
Magnitude relationship extract, that is:
Figure DEST_PATH_FSB000009196006000311
Figure DEST_PATH_FSB000009196006000312
else
Figure DEST_PATH_FSB000009196006000313
Wherein,
Figure FSB00000860294000042
Represent W aIbit;
E, the blind extraction of authenticating water-mark and deciphering: (1) attack graph looks like to be divided into size and is the not overlapping sub-block of m * m; (2) each sub-block is carried out DCT; (3) extract authenticating water-mark W from each sub-block DCT matrix by the following method a':
Figure FSB00000860294000043
Wherein,
Figure FSB00000860294000044
Represent W a' ibit; (4) utilize x 0Produce Logistic Map Chaotic { x with two keys of γ 1, x 2, x 3..., give up a front κ random number, with κ+1 to
Figure FSB00000860294000045
Individual random number x κ+1, x κ+2...,
Figure FSB00000860294000046
By
Figure FSB00000860294000047
Two-value turns to { 0, the 1} sequence L in GF (2) territory; (5) pass through To the authenticating water-mark W that extracts a' be decrypted, wherein
Figure FSB00000860294000049
Authenticating water-mark W after the representative deciphering a" ibit; (6) calculate the feature watermark W that extracts after attack aWith the authenticating water-mark W after deciphering a" between the normalization degree of correlation (Normalized Correlation, NC) estimate anti-attack robust with the judgement copyright, the NC value is defined as:
Figure FSB000008602940000410
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