CN105160621B - A kind of image watermark detecting system - Google Patents
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- CN105160621B CN105160621B CN201510320221.1A CN201510320221A CN105160621B CN 105160621 B CN105160621 B CN 105160621B CN 201510320221 A CN201510320221 A CN 201510320221A CN 105160621 B CN105160621 B CN 105160621B
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Abstract
The invention discloses a kind of image watermark detecting system, which includes：Extraction module (21) extracts the watermark signal included in image to be detected, as the first watermark signal；Computing module (22) obtains the maximum coordinates point of correlation maximum；Correction module (23) according to the coordinate value of the maximum coordinates point, restores image to be detected to obtain correction image；And judgment module (24), it is based on the maximum related value in each correlation between region respectively consistent with the image shape size that reference watermark template is formed in the correction image and reference watermark template, judge whether the maximum related value is more than predetermined threshold value, and whether judged in the correction image comprising reference watermark signal according to judging result.The image digital watermark detecting system 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 for August in 2011 26 days, 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 detecting systems.
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 the part for people's daily life.One essential attribute of digital picture is very
It easily replicates, therefore brings serious digital publishing rights piracy and threaten.
A kind of technical method of protection digital picture copyright is using 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 establish 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 the environment of closing, 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 using 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, so as to have the function that frighten copyright infringement.
In digital image watermarking concrete application, detecting whether some digital picture includes watermark information or water
During 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 in the case of 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 copyright watermark information that the operations such as row rotation, scaling, shearing may include to make picture can not detected.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 and is not carried out down again by the original image carrier of geometric attack
The watermark information detection of one step.
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 problems to be solved by the invention are to need to provide a kind of resistance geometric attack image watermark detecting system.For
Solution above-mentioned technical problem, the present invention provides a kind of image watermark detecting system.The image watermark detecting system, including：
Extraction module (21) extracts the watermark signal included in image to be detected, as the first watermark signal；Computing module (22),
It obtains the maximum coordinates point of correlation maximum；Correction module (23), according to the coordinate value of the maximum coordinates point, to be checked
Altimetric image is restored to obtain correction image；And judgment module (24), it is based in the correction image respectively and benchmark
The maximum in each correlation between the consistent region of image shape size that watermark template is formed and reference watermark template
Correlation judges whether the maximum related value is more than predetermined threshold value, and according to judging result judge in the correction image whether
Include reference watermark signal；
The computing module (22) by handling the maximum coordinates point to obtain correlation maximum as follows：To first water
Official seal number carries out auto-correlation function calculating, to generate auto-correlation function image；By reference layout information and the auto-correlation function
Image is respectively mapped in log-polar system, obtains the maximum coordinates point for causing the two linear correlation values maximum, wherein, according to
Following expression to the cartesian coordinate mooring points P (x, y) of the reference layout information and the auto-correlation function image respectively into
Row mapping：
In formula, (r, θ) represents the polar diameter and polar angle of log-polar, M respectivelycFor constant；
Wherein, the reference layout information is to be attached to having for image in the watermark signal telescopiny of image to set
The information of rule.
According to one embodiment of present invention, wherein, the computing module (22) to the reference layout information with it is described
The mapping result of auto-correlation function image carries out matched filtering to obtain so that the maximum coordinates point of the two linear correlation values maximum.
According to one embodiment of present invention, wherein, the correction module (23) is according to the coordinate of the maximum coordinates point
Value obtains the geometric attack parameter of geometric attack for characterizing described image to be detected and being subject to, and utilizes the geometric attack parameter pair
Image to be detected is restored to obtain correction image.
According to one embodiment of present invention, the extraction module (21) is equal by the grey level histogram of described image to be detected
Weighing apparatusization obtains equalization image, based on first watermark included in image to be detected described in the equalization image zooming-out
Signal.
According to one embodiment of present invention, the extraction module (21) to the equalization image by carrying out prediction filter
Wave obtains the high-frequency part in described image to be detected, as the first watermark signal.
According to one embodiment of present invention, the extraction module (21) is high by Gauss high-pass filter or Butterworth
Bandpass filter carries out predictive filtering.
According to one embodiment of present invention, if the judgment module (24) judges that the correction image contains reference water
Official seal number then obtains the watermark signal in correction image and output is decoded to it.
According to one embodiment of present invention, the computing module (22) is 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 coordinates point of the linear correlation values maximum of the two.
According to one embodiment of present invention, the correction module (23) is obtained according to the coordinate value of the maximum coordinates point
It must be used to characterize the geometric attack parameter for the geometric attack that described image to be detected is subject to, be treated using the geometric attack parameter
Detection image is restored 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
System.The reference layout information that the system 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 for waiting 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 recovers correction image, and system high-ranking officers positive image carries out relevant matches with reference watermark template, is determined
Whether image to be detected if comprising if if decodes included watermark signal comprising reference watermark template.
Compared with prior art, the present invention has the following advantages：The image digital watermark detecting system of the present invention can support
Rotation, shearing and the compound geometric attack of scaling in anti-zone of reasonableness；The benchmark of image digital watermark detecting system in the present invention
Watermark template can be used as key, can not be detected even if be aware of detection algorithm in attacker in the case of not knowing key
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 being understood by implementing the present 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 the present invention, people in the art are described 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 included in appended right will
Ask all substitutes, amendment and 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
Example is applied together for explaining the present invention, is not 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 structure diagram of image watermark detecting system according to a second embodiment of the present invention；
Fig. 3 is the example images of auto-correlation function generation according to embodiments of the present invention.
Specific embodiment
Carry out the embodiment that the present invention will be described in detail below with reference to accompanying drawings and embodiments, how the present invention is applied whereby
Technological means solves technical problem, and the realization process for reaching technique effect can fully understand and implement according to this.It needs to illustrate
As long as not forming conflict, each embodiment in the present invention and each feature in each embodiment can be combined with each other,
The technical solution formed is 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 performed in system, although also, show logical order in flow charts, it in some cases, can be to be different from herein
Sequence perform 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 included 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 in following step 110 with being illustrated in 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 watermark signal is embedded in 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 insertion 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 forms 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 " represents bright in YUV color space models
Brightness (Luminance or Luma), that is, gray value；And " U " and " V " represent be coloration (Chrominance or
Chroma), effect is description colors of image and saturation degree, 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 of gained image to be detected data is obtained, grey level histogram is then subjected to histogram equalization,
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, then carries out histogram equalization, so that using the method for self-adapting histogram equilibrium
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 by the big of gray value to the intensity profile of all pixels of image
A kind of small statistical chart for showing its frequency of occurrences, is generally represented 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
Spacing increase or uniform gray level distribution, increase contrast are spent, is apparent from the details of image.
Step 120, the watermark signal in equalization image zooming-out image to be detected based on step 110 gained, 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
With Gauss high-pass filtering, the process of Gauss high-pass filtering may include：Gassian low-pass filter is carried out, then calculate to equalization image
The residual values of weighing apparatusization image and image after Gassian low-pass filter, to obtain image to be detected high frequency part, will be obtained
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, 3 × 3 wave filter represented, in wave 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.All coefficients in above-mentioned middle template and should be 16 because it is 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
To carry 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 represents the image generated to the periodical expansion of the first watermark signal progress；
X, y represent the coordinate value of the wide direction of image I and the coordinate value in high direction respectively；
M, N represent the width and height of image I respectively, equal with the width and height of image to be detected；
U, v represent the coordinate value of the wide direction of auto-correlation function and the coordinate value in high direction 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 employ 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 influenced caused by eliminating 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 is respectively mapped to logarithm pole to sit
In mark system, it is (referred to as maximum to obtain the coordinate points of linear correlation values maximum that matched filtering is then 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
Reference layout information is first subjected to coordinate transform, 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) then is carried out matched filtering, that is,
Related operation is carried out to obtain the coordinate points of linear correlation values maximum 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) represents 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 represents zooming parameter in formula.
Wherein, matched filtering refers to obtain 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 represent 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 according to obtained by step 140p,θp), image to be detected is carried out
Recovery obtains correction image.
More specifically, the geometric attack for characterizing described image to be detected and being subject to is obtained 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 for waiting 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 represented as follows：
In formula, s, d represents zooming parameter and rotation parameter respectively；
McFor constant；
N represents 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 equation below,
In this implementation, by the way that reference layout information and obtained auto-correlation function image are compared, treated with 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 the area consistent with reference watermark template image shape size any 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 reference watermark signal is included in image.
It is 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 therebetween, 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, so as to acquire above-mentioned maximum related value.Wherein,
Any image shape region of the same size formed with reference watermark template in correction image, with reference watermark template most
The acquisition of big correlation can be calculated as follows：
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, judge 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, it can be restored to obtain correction image similar mode with treating detection mode, according to 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, otherwise correct image and include reference watermark signal, and reference watermark signal is decoded 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 image is corrected 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 represent 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 arranges to generate reference watermark signal in order.
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 has 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
Binary message bit=0 is embedded in, 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 structure diagrams of image watermark detecting system according to a second embodiment of the present invention.Below with reference to Fig. 2
To illustrate that each section of the present embodiment forms.
With reference to 2 the present embodiment of figure extraction module (21) perform first embodiment step 110 and step 120 operation,
Computing module (22) performs 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 performed respectively.It is no longer developed in details herein.
Those skilled in the art should be understood that each module of the above-mentioned present invention or each step can use general calculating
Device realizes that they can concentrate on single computing device or be distributed in the network that multiple computing devices are formed
On, optionally, they can be realized with the program code that computing device can perform, it is thus possible to be stored in storage
They are either fabricated to each integrated circuit modules respectively or will be more in them by computing device to perform in device
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 as above, the content only to facilitate understand the present invention and adopt
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 (10)
1. a kind of image watermark detecting system, which is characterized in that including：
Extraction module (21) extracts the watermark signal included in image to be detected, as the first watermark signal；
Computing module (22) obtains the maximum coordinates point of correlation maximum；
Correction module (23) according to the coordinate value of the maximum coordinates point, restores image to be detected to be corrected
Image；And
Judgment module (24), based on the image shape size phase respectively formed in the correction image with reference watermark template
Whether the maximum related value in each correlation between consistent region and reference watermark template, judge the maximum related value
Whether judge in the correction image comprising reference watermark signal more than predetermined threshold value, and according to judging result；
The computing module (22) by handling the maximum coordinates point to obtain correlation maximum as follows：
Auto-correlation function calculating is carried out to first watermark signal, to generate auto-correlation function image, wherein, according to such as following table
Auto-correlation function calculating is carried out to first watermark signal up to formula, to generate auto-correlation function image：
In formula, I represents the image generated to the periodical expansion of the first watermark signal progress；
X, y represent the coordinate value of the wide direction of image I and the coordinate value in high direction respectively；
M, N represent the width and height of image I respectively, equal with the width and height of image to be detected；
U, v represent the coordinate value of the wide direction of auto-correlation function and the coordinate value in high direction 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, obtained so that the two line
The maximum coordinates point of property correlation maximum, wherein, according to following expression to the reference layout information and the auto-correlation letter
The cartesian coordinate mooring points P (x, y) of number image is mapped respectively：
In formula, (r, θ) represents the polar diameter and polar angle of log-polar, M respectivelycFor constant；
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. system according to claim 1, which is characterized in that
The computing module (22) matches the reference layout information with the mapping result of the auto-correlation function image
Filtering is to obtain so that the maximum coordinates point of the two linear correlation values maximum.
3. system according to claim 1 or 2, which is characterized in that
The correction module (23) is subject to according to the coordinate value of the maximum coordinates point to obtain the described image to be detected of characterization
The geometric attack parameter of geometric attack restores image to be detected using the geometric attack parameter to obtain correction chart
Picture.
4. system according to claim 1, which is characterized in that
The gray-level histogram equalization of described image to be detected is obtained equalization image, based on institute by the extraction module (21)
State first watermark signal included in image to be detected described in equalization image zooming-out.
5. system according to claim 4, which is characterized in that
The extraction module (21) is obtained by carrying out predictive filtering to the equalization image in described image to be detected
High-frequency part, as the first watermark signal.
6. system according to claim 5, which is characterized in that
The extraction module (21) carries out predictive filtering by Gauss high-pass filter or butterworth high pass filter.
7. system according to claim 1, which is characterized in that
If the judgment module (24) judges that the correction image contains reference watermark signal, the water in correction image is obtained
Official seal number is simultaneously decoded it output.
8. according to the system described in claim 1,2, any one of 4 to 7, which is characterized in that
The computing module (22) matches the reference layout information with the mapping result of the auto-correlation function image
Filtering is to obtain so that the maximum coordinates point of the linear correlation values maximum of the two.
9. system according to claim 3, which is characterized in that
The computing module (22) matches the reference layout information with the mapping result of the auto-correlation function image
Filtering is to obtain so that the maximum coordinates point of the linear correlation values maximum of the two.
10. system according to claim 1, which is characterized in that
The correction module (23) according to the coordinate value of the maximum coordinates point come obtain for characterize described image to be detected by
The geometric attack parameter of the geometric attack arrived restores image to be detected to be corrected using the geometric attack parameter
Image.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510320221.1A CN105160621B (en) | 2011-08-26 | 2011-08-26 | A kind of image watermark detecting system |
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| CN201110248307.XA CN102956025B (en) | 2011-08-26 | 2011-08-26 | Image watermark detection method and system |
| CN201510320221.1A CN105160621B (en) | 2011-08-26 | 2011-08-26 | A kind of image watermark detecting system |
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| CN201110248307.XA Active CN102956025B (en) | 2011-08-26 | 2011-08-26 | Image watermark detection method and system |
| CN201510320221.1A Expired - Fee Related CN105160621B (en) | 2011-08-26 | 2011-08-26 | A kind of image watermark detecting system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105160619B (en) * | 2011-08-26 | 2018-07-06 | 北京中盈信安科技发展有限责任公司 | A kind of image watermark detection method |
| 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 |
| CN105160618A (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 system |
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- 2011-08-26 CN CN201510319483.6A patent/CN105160618B/en not_active Expired - Fee Related
- 2011-08-26 CN CN201110248307.XA patent/CN102956025B/en active Active
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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 |
| CN105160618A (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 system |
Also Published As
| Publication number | Publication date |
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| CN102956025A (en) | 2013-03-06 |
| CN105160620A (en) | 2015-12-16 |
| CN105160619B (en) | 2018-07-06 |
| CN105160620B (en) | 2018-09-25 |
| CN105160618B (en) | 2018-07-06 |
| CN102956025B (en) | 2015-05-06 |
| CN105160621A (en) | 2015-12-16 |
| CN105160618A (en) | 2015-12-16 |
| CN105160619A (en) | 2015-12-16 |
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