CN105160620B - A kind of image watermark detection method - Google Patents
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Abstract
The invention discloses a kind of image watermark detection method, this method includes：The watermark signal for including in extraction image to be detected, as the first watermark signal；Auto-correlation function calculating is carried out to first watermark signal, to generate auto-correlation function image；Reference layout information and the auto-correlation function image are respectively mapped in log-polar system, obtained so that the two maximum maximum coordinates point of linear correlation values；According to the coordinate value of the maximum coordinates point, image to be detected is restored to obtain correction image；Based on the maximum related value in each correlation between region and reference watermark template respectively consistent with the image shape size that reference watermark template is constituted in the correction image, judge in the correction image whether to include reference watermark signal.The image digital watermark detection method of the present invention can resist the compound geometric attacks such as rotation, shearing and scaling in zone of reasonableness, safe.
Description
The application is the applying date to be August in 2011 26, and application No. is 201110248307.X and invention and created names
For《A kind of image watermark detection method and its system》Divisional application.
Technical field
The present invention relates to a kind of digital image watermarking more particularly to a kind of image watermark detection methods.
Background technology
Along with the interconnections such as the development and e-commerce of digital photographic technology, digital publishing, news portal and social network sites
Net application is popularized, and digital picture has become a part for people's daily life.One essential attribute of digital picture is very
It is easy to replicate, therefore brings serious digital publishing rights piracy and threaten.
A kind of technical method of protection digital picture copyright is to use digital copyright management (Digital Rights
Management, abbreviation DRM) system.DRM operation principles are that guarantor is encrypted using key pair picture in digital picture supplier
Shield, while establishing the propagation of authorization center control digital picture.This means that DRM protection digital picture copyrights are needed in a phase
To being carried out in closed environment, if there is the malicious user in DRM system to travel to digital picture except system, DRM system
With regard to helpless.As it can be seen that DRM technology is difficult to apply in the open environment of today's society.
Another effective method of protection digital picture copyright is to use digital image watermarking, and copyright owner is first
Copyright owner's information is embedded into picture, third party can be submitted to detect the copyright that infringement picture is included after finding to encroach right
Owner information, to have the function that frighten copyright infringement.
In digital image watermarking concrete application, detecting whether some digital picture includes watermark information or water
When the partial content of official seal breath, it is difficult to obtain the corresponding original image of the picture.This requires used image digitizations
Digital watermark can carry out blind Detecting, even if can be also detected without using original image information.
The ultimate challenge that image digital watermark blind Detecting is faced is usually geometric attack, i.e., to the picture comprising watermark into
The operations such as row rotation, scaling, shearing can not detected to the copyright watermark information for making picture that may include.It is attacked for geometry
It hits, the countermeasure of image watermark detection algorithm usually first detects the template watermark that image-carrier includes, and is believed by template watermark
Breath determines the geometric attack parameter that image can suffer from, and then recovers the original image carrier not by geometric attack and carries out down again
The watermark information of one step detects.
Current existing blind Detecting Arithmetic on Digital Watermarking of Image can not effectively solve geometry shearing attack mostly, especially exist
In the case that shearing attack and rotation, scaling attack combine.
Invention content
The technical problem to be solved by the present invention is to need to provide a kind of resistance geometric attack image watermark detection method.
In order to solve the above technical problem, the present invention provides a kind of image watermark detection methods.The image watermark detects
Method includes：Step 1 extracts the watermark signal for including in image to be detected, as the first watermark signal；Step 2, to described
First watermark signal carries out auto-correlation function calculating, to generate auto-correlation function image；Step 3, by reference layout information and institute
It states auto-correlation function image to be respectively mapped in log-polar system, obtain so that the two maximum maximum coordinates of linear correlation values
Point, wherein according to following expression to the cartesian coordinate mooring points P of the reference layout information and the auto-correlation function image
(x, y) is mapped respectively：
In formula, (r, θ) indicates the polar diameter and polar angle of log-polar, M respectivelycFor constant；
Step 4 is restored image to be detected according to the coordinate value of the maximum coordinates point to obtain correction image；
And step 5, based on area respectively consistent with the image shape size that reference watermark template is constituted in the correction image
It is default to judge whether the maximum related value is more than for the maximum related value in each correlation between domain and reference watermark template
Threshold value, and judge in the correction image whether to include reference watermark signal according to judging result, wherein the reference layout information
It is the information with setting rule that image is attached in the watermark signal telescopiny of image.
According to one embodiment of present invention, in the step 1, the grey level histogram of described image to be detected is equal
Weighing apparatusization obtains equalization image；And based on include in image to be detected described in the equalization image zooming-out described first
Watermark signal.
According to one embodiment of present invention, in the step 1, by carrying out prediction filter to the equalization image
Wave obtains the high-frequency part in described image to be detected, as the first watermark signal.
According to one embodiment of present invention, it is carried out by Gauss high-pass filter or butterworth high pass filter pre-
Survey filtering.
According to one embodiment of present invention, if judging, the correction image contains reference watermark signal, obtains school
Watermark signal in positive image is simultaneously decoded it output.
According to one embodiment of present invention, in the step 3, to the reference layout information and the auto-correlation
The mapping result of functional image carries out matched filtering to obtain so that the maximum maximum coordinates point of linear correlation values of the two.
According to one embodiment of present invention, it is obtained according to the coordinate value of the maximum coordinates point for characterizing described wait for
The geometric attack parameter for the geometric attack that detection image is subject to restores image to be detected using the geometric attack parameter
To obtain correction image.
In brief, for this deficiency of existing blind Detecting image algorithm, the present invention provides a kind of image watermark detection
Method.The reference layout information that this method is embedded in advance according to image to be detected calculates rotation, the contracting that image to be detected is subjected to
Put the geometric attack parameter of equal geometric attacks.It then, will be to be detected according to the geometric attack parameter of the geometric attacks such as rotation, scaling
Image is restored, and correction image is recovered, and this method high-ranking officers positive image carries out relevant matches with reference watermark template, determines
Whether image to be detected includes reference watermark template, and included watermark signal is decoded if comprising if.
Compared with prior art, the present invention has the following advantages：The image digital watermark detection method of the present invention can support
Rotation, shearing in anti-zone of reasonableness and the compound geometric attack of scaling；The benchmark of image digital watermark detection method in the present invention
Watermark template can be used as key use, and in the case where not knowing key, attacker can not detect being aware of detection algorithm
Or watermark of erasing；Image digital watermark detection algorithm calculation amount the best part is convolutional calculation in the present invention, and convolutional calculation
It can realize that this, which allows for this algorithm, can obtain faster calculating speed by the fast Fast Fourier Transform (FFT) of arithmetic speed.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
It obtains it is clear that understand through the implementation of the invention.The purpose of the present invention and other advantages can be by specification, rights
Specifically noted structure is realized and is obtained in claim and attached drawing.
Although describing the present invention, people in the art hereinafter in connection with some exemplary implementations and application method
Member is it should be appreciated that be not intended to limit the invention to these embodiments.It is on the contrary, it is intended to which that covering is wanted included in appended right
Seek all substitutes, amendment and the equivalent in spirit and scope of the invention defined in book.
Description of the drawings
Attached drawing is used to provide further understanding of the present invention, and a part for constitution instruction, the reality with the present invention
It applies example to be used to explain the present invention together, not be construed as limiting the invention.In the accompanying drawings：
Fig. 1 is the flow diagram of image watermark detection method according to a first embodiment of the present invention；
Fig. 2 is the structural schematic diagram of image watermark detecting system according to a second embodiment of the present invention；
Fig. 3 is the example images that auto-correlation function according to the ... of the embodiment of the present invention generates.
Specific implementation mode
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings and examples, how to be applied to the present invention whereby
Technological means solves technical problem, and the realization process for reaching technique effect can fully understand and implement.It needs to illustrate
As long as not constituting conflict, each embodiment in the present invention and each feature in each embodiment can be combined with each other,
It is formed by technical solution within protection scope of the present invention.
In addition, step shown in the flowchart of the accompanying drawings can be in the department of computer science of such as a group of computer-executable instructions
It is executed in system, although also, logical order is shown in flow charts, and it in some cases, can be to be different from herein
Sequence execute shown or described step.
First embodiment
Fig. 1 shows the flow diagram of image watermark detection method according to a first embodiment of the present invention.Below with reference to Fig. 1
To illustrate each step of the present embodiment.
The watermark signal for including in extraction image to be detected.Image to be detected is in watermark telescopiny before,
It is embedded in watermark signal.Since image to be detected may receive geometric attack, the watermark signal extracted also may be used
It can be the watermark signal influenced by geometric attack.For convenience of description, the water that will be extracted from image to be detected in lower section
Official seal number is referred to as the first watermark signal.Detail will be illustrated in following step 110 with step 120.
It should be noted that in image to be detected of the present embodiment, reference layout information attached in advance.For example, can be with
During being embedded in watermark signal to image to be detected before, synchronization template is embedded in image to be detected, wherein the synchronization mould
Plate can be the size image that defines peak value of pulse point equal with image to be detected.It for another example, can also be right before
During image to be detected is embedded in watermark signal, first (but invisibly) cloth regularly in the watermark information to be embedded in
Several peak value of pulse points of office, as long as so that after the reference layout information of ancillary rules, embedded watermark in image to be detected
Information area can show the layout information of certain rule.In brief, reference layout information is the watermark in image
The information with certain (setting) rule of image is attached in signal telescopiny, certain rule herein can be arbitrary default
Rule.
Step 110, by the gray-level histogram equalization of image to be detected, equalization image is obtained.
Specifically, first, the half-tone information of described image to be detected is extracted as image to be detected data.If mapping to be checked
As being coloured image, then it is transformed on YUV color space models, then the Y channel informations on extraction model are as to be checked
Altimetric image data；If image to be detected is gray level image, directly using its half-tone information as image to be detected data.
Specifically, for the input of the color digital picture of the formats such as BMP, JPG, PNG, first by color digital picture into
Row decoding, then carries out YUV color space conversions by decoded image.Wherein, " Y " indicates bright in YUV color space models
Brightness (Luminance or Luma), that is, gray value；And " U " and " V " indicate be coloration (Chrominance or
Chroma), effect is description colors of image and saturation degree, is used for the color of specified pixel.
Decoded image represented by RGB color template is subjected to color space conversion, that is, by RGB face
Information in colour space template is transformed on YUV color spaces, and color space conversion is shown below, and is carrying out color space change
After changing, extraction Y channel informations gray value is inputted as image to be detected data.
Y=0.299R+0.587G+0.114B
U=0.492 (B-Y)
V=0.877 (R-Y)
The grey level histogram for obtaining gained image to be detected data, then carries out histogram equalization by grey level histogram,
To obtain the image after grey level histogram is equalized.
Specifically, occurred in each gray level according to the gray scale of gray scale Data-Statistics image to be detected of image to be detected
Number, to obtain grey level histogram, the method for then using self-adapting histogram equilibrium carries out histogram equalization, so that
Probability density function p (s)=1 that gradation of image is distributed after weighing apparatus processing, that is, the probability that all image gray levels occur is identical.
It should be noted that the grey level histogram of image is to the intensity profile of all pixels of image by the big of gray value
A kind of small statistical chart for showing its frequency of occurrences, is generally indicated using two-dimensional coordinate system.Grey level histogram is equalized
It is to reduce the tonal gradation of image to exchange the expansion of contrast for, by carrying out homogenization amendment to histogram, makes the ash of image
It spends spacing increase or uniform gray level distribution, increase contrast, the details of image is made to be apparent from.
Step 120, based on the watermark signal in equalization image zooming-out image to be detected obtained by step 110, referred to as
First watermark signal.
The first watermark signal can be extracted by carrying out predictive filtering to equalization image.Preferably, the present embodiment is adopted
It may include with the process of Gauss high-pass filtering, Gauss high-pass filtering：Gassian low-pass filter is carried out to equalization image, then is calculated
Weighing apparatusization image and the residual values of image after Gassian low-pass filter will be obtained with obtaining image to be detected high frequency part
The high-frequency part taken is as the first watermark signal.It is highly preferred that the template of Gassian low-pass filter is as follows：
Specifically, the processing method of Gassian low-pass filter is to be multiplied by pixel with coefficient different in template, from coefficient value
It sees, other are even more important for some pixel ratios in template.It can be seen that from above formula, indicate 3 × 3 filter, be in filter
The coefficient value of other any pixels of the pixel ratio of center will be big.And other pixels of distance filter center farther out are just shown
Must be not too important, since the diagonal item distance center pixel more adjacent than orthogonal direction is farther, so its important ratio center is straight
It is low to connect four adjacent pixels.Among the above all coefficients in template and should be 16 because it be 2 integral number power convenient for meter
Calculation machine is realized.
In addition, in this step, other than using Gauss high-pass filter, butterworth high pass filter etc. can also be used
It carries out predictive filtering, or even can also be derived by natural image probability Distribution Model.
Step 130, auto-correlation function calculating is carried out to the watermark signal in image to be detected for being extracted in step 120,
To generate auto-correlation function image, it is denoted as f (u, v).Formula can be as follows：
Wherein, I indicates the image generated to the periodical expansion of the first watermark signal progress；
X, y indicate the coordinate value of the coordinate value and high direction of the wide direction of image I respectively；
M, N indicate the width and height of image I respectively, equal with the width and height of image to be detected；
U, v indicate the coordinate value of the coordinate value and high direction of the wide direction of auto-correlation function respectively；
Wherein, x, u=1 ... M；Y, v=1 ... N.
Auto-correlation function f (u, v) with u, the size variation of v and change, the change of certain periodization is presented in the value of f (u, v)
Change.
More specifically, since the watermark signal in image to be detected corresponds to the high-frequency part in image, extracted
The sequence that watermark signal (the first watermark signal) is made of the random number of normal distribution, zero-mean, and the first watermark signal
Random number number be less than image to be detected pixel number, therefore, in above formula use and the first watermark signal opened up
The periodic function opened up (repeat replication) and generated.
The present embodiment characterizes image to be detected by introducing autocorrelogram picture, both can preferably reflect image to be detected
Distribution characteristics and it is periodical the features such as, and can eliminate influence caused by translation this geometric deformation, while by mapping to be checked
The rotation of picture and scale these geometric attack deformation rotation for being mapped to its autocorrelogram picture one by one and scaling.
Step 140, the auto-correlation function image obtained by reference layout information and step 130 logarithm pole is respectively mapped to sit
In mark system, it is (referred to as maximum to obtain the maximum coordinate points of linear correlation values that matched filtering then is carried out to the mapping result of the two
Coordinate points) and its value Pm (rp,θp)。
Specifically, image log polar coordinate transform is to convert image to log-polar system from cartesian coordinate system.It is first
First reference layout information is coordinately transformed, obtained image is denoted as t (r, θ), then carries out auto-correlation function image
Obtained image is denoted as f (r, θ) by coordinate transform, and image t (r, θ) and image f (r, θ) is then carried out matched filtering, that is,
Related operation is carried out to obtain the maximum coordinate points of linear correlation values and its value Pm (rp,θp).Wherein, from point P (x, y) to logarithm
Polar mapping equation can be as follows：
In formula, (r, θ) indicates the polar diameter and polar angle of log-polar, M respectivelycFor constant.As available from the above equation, which becomes
A border circular areas of changing commanders is mapped to a rectangular area.When cartesian coordinate system hypograph scales, log-polar
Translation will be generated, log-polar has preferable scale and rotational invariance.As follows, s indicates zooming parameter in formula.
Wherein, matched filtering refers to obtaining so that reference layout information is respectively mapped to logarithm pole with auto-correlation function image
Maximum coordinates point Pm (r in coordinate systemp,θp) so that the two linear correlation values are maximum, that is, g (r, θ)=f (r, θ) ο t (r, θ) reach
To global peak.Correlation operation can be shown below,
In formula, " ο " expression " correlation " operation；M, N indicate auto-correlation function image and reference layout information right respectively
Width and height under number polar coordinate system are equal with the width and height of image to be detected；F (r, θ), t (r, θ) are autocorrelation function graph respectively
The representation of picture and reference layout information under log-polar system.
Step 150, the coordinate value Pm (r of the maximum coordinates point obtained by step 140p,θp), image to be detected is carried out
Recovery obtains correction image.
More specifically, obtaining the geometric attack for characterizing described image to be detected and being subject to according to the coordinate value of maximum coordinates point
Geometric attack parameter, image to be detected is restored using geometric attack parameter with obtain correction image, below will more in detail
Carefully illustrate.
According to the coordinate value Pm (r of maximum coordinates pointp,θp), obtain rotation and/or contracting that characterization image to be detected is subjected to
Put the geometric attack parameter of equal geometric attacks.In case of rotate and scale, need to obtain rotation parameter and contracting
Parameter is put, according to the property of log-polar coordinate mapping, formula can be indicated as follows：
In formula, s, d indicates zooming parameter and rotation parameter respectively；
McFor constant；
N indicates height of the autocorrelogram picture under log-polar system, equal with the height of image to be detected.
And using gained rotation parameter d and zooming parameter s, image to be detected is restored to obtain without geometry
The correction image of attack, shown in following formula,
In formula,Indicate image to be detected pixel coordinate；
Indicate correction image pixel coordinates.
In this implementation, by the way that reference layout information to be compared with obtained auto-correlation function image, waited for correction
Geometric attack suffered by detection image.Since reference layout information data can be more much smaller than image to be detected data, so
Its matching speed is fast, saves the calculating time of correlation operation, improves work efficiency.
Step 160, based on any area consistent with reference watermark template image shape size in above-mentioned correction image
Maximum related value C in correlation between domain and reference watermark template image (abbreviation reference watermark image)max, judge the correction
Whether include reference watermark signal in image.
For example, first that one centered on the center for correcting image is consistent with reference watermark template image shape size
Region (abbreviation central area) compared with reference watermark template, obtain correlation between the two, then by central area
The consistent region of each shape size on side (for example, central point to the left, upper, right or down offset by the region of 1 or several pixel),
It is compared with reference watermark template, obtains corresponding correlation, and so on, to acquire above-mentioned maximum related value.Wherein,
Any image shape region of the same size constituted with reference watermark template in correction image, with reference watermark template most
The acquisition of big correlation can be calculated as follows：
Wherein, Wr(x, y) indicates reference watermark template, is made of L modulator block, Wr(x, y)=(wr[1],...,wr
[i],...,wr[L]), wr[i] indicates i-th of modulator block；Bc(x, y) indicates central area (examined fritter), corresponds to benchmark
Watermark template is also made of corresponding L element, Bc(x, y)=(B [1] ..., B [i] ..., B [L]), during wherein B [i] is
The region corresponding to i-th of modulator block in heart district domain；P (x, y) indicates the point (point slided into) of correction image；*mIndicate convolution
A kind of modification of operation,* shown herein as convolution operation.
For example, when maximum related value is more than a certain predetermined threshold value, it is judged as containing reference watermark signal.
If in addition, judging that correcting image contains reference watermark signal, obtains correction chart based on above-mentioned maximum related value
The watermark signal of picture is simultaneously decoded it output.
For example, can be restored to obtain correction image similar mode with detection mode is treated, obtained by step 140
Maximum coordinates point coordinate value Pm (rp,θp), the watermarking images after being corrected are restored to the first watermark signal image,
Then output is decoded to the watermarking images after correction.
It for another example, can also be from the above-mentioned maximum related value C of acquirementmaxCorrection image in region in extraction watermark signal simultaneously
It is decoded.
Specifically, judge the maximum correlation value C of gainedmaxWhether satisfaction is less than predetermined threshold value T, the correction chart if meeting
As not including reference watermark signal, it includes reference watermark signal otherwise to correct image, and is decoded to reference watermark signal defeated
Go out.Reference watermark signal included in output calibration image is decoded by following steps：
1) length for inputting preset reference watermark template is L bits；
2) i=1 is set, i-th of modulator block of watermark template on the basis of i；
If 3) the normalization linear correlation values in i-th of modulator block of reference watermark template region corresponding with central area
CiMore than ThThen accordingly output is 1 to watermark information, otherwise exports 0.Wherein, ThIt is preset threshold value, can be generally set as 0.This
In central area refer in correcting image with reference watermark template carry out correlation operation obtained by maximum related value center
Domain.Wherein, CiCalculation formula can be as follows：
In formula, MiIt is i-th of modulator block of reference watermark template；
BiBe central area correspond to i-th of modulator block region；
N is BiThe length in region, m indicate BiThe mean value in region.
4) i is from increasing 1, if i<=L, then return to step 3)；Otherwise terminate.By obtained each corresponding positions watermark information
It is arranged in order to generate reference watermark signal.
It should be noted that reference watermark signal is set by concrete application, it can generally be expressed as white noise (power density spectrum
It is uniformly distributed) form of sequence.Reference watermark signal can be binary form or Gaussian noise form and its by reference water
Die plate is modulated, such as noise sequence modulated reference watermark signal 0100011011 (as reference watermark template).Specifically
Ground, i-th of modulator block modulate binary message 0 or 1, can be as follows：
According to above formula, it is binary message bit=1 to embedded reference watermark signal, is then actually embedded in wr[i]；If
It is embedded in binary message bit=0, then is actually embedded in-wr[i]。wr[i] is usually white noise sequence, wrThe combination of [i] is
Reference watermark template Wr。
Second embodiment
Fig. 2 shows the structural schematic diagrams of image watermark detecting system according to a second embodiment of the present invention.Below with reference to Fig. 2
To illustrate each section composition of the present embodiment.
With reference to 2 the present embodiment of figure extraction module (21) execute first embodiment step 110 and step 120 operation,
Computing module (22) executes the operation of the step 130 and step 140 of first embodiment, correction module (23) and judgment module (24)
The step 150 and step 160 of first embodiment are executed respectively.It is no longer developed in details herein.
Those skilled in the art should be understood that each module of the above invention or each step can use general calculating
Device realizes that they can be concentrated on a single computing device, or be distributed in network constituted by multiple computing devices
On, optionally, they can be realized with the program code that computing device can perform, it is thus possible to be stored in storage
It is performed by computing device in device, either they are fabricated to each integrated circuit modules or will be more in them
A module or step are fabricated to single integrated circuit module to realize.In this way, the present invention is not limited to any specific hardware and
Software combines.
Although disclosed herein embodiment it is as above, the content is only to facilitate understanding the present invention and adopting
Embodiment is not limited to the present invention.Any those skilled in the art to which this invention pertains are not departing from this
Under the premise of the disclosed spirit and scope of invention, any modification and change can be made in the implementing form and in details,
But the scope of patent protection of the present invention, still should be subject to the scope of the claims as defined in the appended claims.
Claims (7)
1. a kind of image watermark detection method, which is characterized in that including：
Step 1 extracts the watermark signal for including in image to be detected, as the first watermark signal；
Step 2 carries out auto-correlation function calculating, to generate auto-correlation function image to first watermark signal, wherein
Auto-correlation function calculating is carried out to first watermark signal according to following expression, to generate auto-correlation function image：
In formula, I indicates the image generated to the periodical expansion of the first watermark signal progress；
X, y indicate the coordinate value of the coordinate value and high direction of the wide direction of image I respectively；
M, N indicate the width and height of image I respectively, equal with the width and height of image to be detected；
U, v indicate the coordinate value of the coordinate value and high direction of the wide direction of auto-correlation function respectively；
Wherein, x, u=1 ... M；Y, v=1 ... N；
Reference layout information and the auto-correlation function image are respectively mapped in log-polar system, are made by step 3
Both the maximum maximum coordinates point of linear correlation values, wherein according to following expression to the reference layout information with it is described
The cartesian coordinate mooring points P (x, y) of auto-correlation function image is mapped respectively：
In formula, (r, θ) indicates the polar diameter and polar angle of log-polar, M respectivelycFor constant；
Step 4 is restored image to be detected according to the coordinate value of the maximum coordinates point to obtain correction image；And
Step 5, based on area respectively consistent with the image shape size that reference watermark template is constituted in the correction image
It is default to judge whether the maximum related value is more than for the maximum related value in each correlation between domain and reference watermark template
Threshold value, and judge in the correction image whether to include reference watermark signal according to judging result,
Wherein, the reference layout information is to be attached to having for image in the watermark signal telescopiny of image to set rule
Information.
2. according to the method described in claim 1, it is characterized in that, in the step 1,
By the gray-level histogram equalization of described image to be detected, equalization image is obtained；And
Based on first watermark signal for including in image to be detected described in the equalization image zooming-out.
3. according to the method described in claim 2, it is characterized in that, in the step 1,
The high-frequency part in described image to be detected is obtained by carrying out predictive filtering to the equalization image, as the
One watermark signal.
4. according to the method described in claim 3, it is characterized in that,
Predictive filtering is carried out by Gauss high-pass filter or butterworth high pass filter.
5. according to the method described in claim 1, it is characterized in that,
If judging, the correction image contains reference watermark signal, obtains the watermark signal in correction image and is carried out to it
Decoding output.
6. the method according to any one of claims 1 to 5, it is characterized in that,
In the step 3, matching filter is carried out to the mapping result of the reference layout information and the auto-correlation function image
Wave is to obtain so that the maximum maximum coordinates point of linear correlation values of the two.
7. according to the method described in claim 6, it is characterized in that,
It is obtained according to the coordinate value of the maximum coordinates point for characterizing the several of geometric attack that described image to be detected is subject to
What attack parameter restores image to be detected using the geometric attack parameter to obtain correction image.
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| CN102956025B (en) * | 2011-08-26 | 2015-05-06 | 北京中盈信安科技发展有限责任公司 | Image watermark detection method and system |
| CN105976304B (en) * | 2016-05-30 | 2019-05-10 | 北京奇艺世纪科技有限公司 | A kind of insertion of image watermark, detection method and device |
| CN106780281B (en) * | 2016-12-22 | 2019-12-03 | 辽宁师范大学 | Digital image watermarking method based on Cauchy's statistical modeling |
| CN108648132B (en) * | 2018-04-16 | 2020-08-14 | 深圳市联软科技股份有限公司 | Method, system, terminal and medium for generating watermark according to image |
| CN111833231B (en) * | 2019-04-15 | 2023-02-10 | 阿里巴巴集团控股有限公司 | Watermark extraction method, device and system |
| CN110956737B (en) * | 2020-01-07 | 2021-10-12 | 武汉卓目科技有限公司 | Safety line identification method and device |
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| EP1022678A2 (en) * | 1999-01-25 | 2000-07-26 | Nippon Telegraph and Telephone Corporation | Method, apparatus and program storage medium for embedding and detecting a digital watermark |
| CN101286224A (en) * | 2008-05-13 | 2008-10-15 | 南京航空航天大学 | Watermark embedding and extraction method based on fractal image coding |
| CN101330610A (en) * | 2008-07-22 | 2008-12-24 | 华为技术有限公司 | Method and apparatus for embedding and extracting watermark as well as processing system |
| CN102122385A (en) * | 2011-02-28 | 2011-07-13 | 北京工业大学 | Digital watermark method capable of simultaneously resisting various attacks |
| CN102156952A (en) * | 2011-03-08 | 2011-08-17 | 南京师范大学 | Copyright-protection-service-oriented remote sensing image digital watermarking method |
| CN105160619A (en) * | 2011-08-26 | 2015-12-16 | 北京中盈信安科技发展有限责任公司 | Image watermark detection method |
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| EP1022678A2 (en) * | 1999-01-25 | 2000-07-26 | Nippon Telegraph and Telephone Corporation | Method, apparatus and program storage medium for embedding and detecting a digital watermark |
| CN101286224A (en) * | 2008-05-13 | 2008-10-15 | 南京航空航天大学 | Watermark embedding and extraction method based on fractal image coding |
| CN101330610A (en) * | 2008-07-22 | 2008-12-24 | 华为技术有限公司 | Method and apparatus for embedding and extracting watermark as well as processing system |
| CN102122385A (en) * | 2011-02-28 | 2011-07-13 | 北京工业大学 | Digital watermark method capable of simultaneously resisting various attacks |
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| CN102956025B (en) | 2015-05-06 |
| CN105160618B (en) | 2018-07-06 |
| CN105160619B (en) | 2018-07-06 |
| CN102956025A (en) | 2013-03-06 |
| CN105160618A (en) | 2015-12-16 |
| CN105160621B (en) | 2018-07-06 |
| CN105160619A (en) | 2015-12-16 |
| CN105160620A (en) | 2015-12-16 |
| CN105160621A (en) | 2015-12-16 |
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