CN106803229A - Image watermark method based on the correction of phase singularity value - Google Patents
Image watermark method based on the correction of phase singularity value Download PDFInfo
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- 239000011159 matrix material Substances 0.000 claims abstract description 10
- 230000009466 transformation Effects 0.000 claims abstract description 9
- 239000013598 vector Substances 0.000 claims abstract description 5
- 238000013139 quantization Methods 0.000 claims description 11
- 238000003780 insertion Methods 0.000 claims description 10
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/80—Geometric correction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2201/00—General purpose image data processing
- G06T2201/005—Image watermarking
- G06T2201/0065—Extraction of an embedded watermark; Reliable detection
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Abstract
The invention discloses a kind of image watermark method based on the correction of phase singularity value, the embedded watermark first in the low frequency sub-band of host image PDTDFB conversion；Secondly, altimetric image to be checked is extracted through the high-frequency sub-band phasing matrix after quaternary number two-dimensional wavelet transformation, and singular value decomposition is carried out to phasing matrix（SVD）, characteristic vector of preceding 4 singular values in principal singular value as training sample image is chosen, the training geometric transformation parameter such as zoom in and out, translate, rotate to sample learns, and obtains LS SVR training patterns；Then, the Mathematical Modeling containing watermarking images geometric correction to be detected is calculated, determines that model parameter carries out geometric correction using the LS SVR training patterns for obtaining；Finally, from corrected containing extracting watermark information in watermarking images.
Description
Technical field
Image watermark method the present invention relates to be based on geometric correction, it is more particularly to a kind of based on phase singularity value correction
Image watermark method, belongs to the copyright protection technology field of digital picture.
Background technology
With the fast development of multimedia and Internet technology, people have stepped into the information age, digital multimedia
Product（Such as image, audio, video）Use it is more and more extensive, digital product miscellaneous allows that people are more square
Just multimedia resource is efficiently obtained.But the multi-media safety problem brought therewith also becomes focus of concern, illegally
Copy becomes more and more easily with spreading digital media product, and this not only compromises the interests of copyright owner, and causes
Trust crisis of the society to multi-media safety.Digital image watermarking technology met the tendency of as the important branch in Information hiding field and
It is raw, a kind of effective means are provided to solve image information security crisis, in the content authentication and copyright protection of digital picture
Field has very big research and application value.
Digital image watermarking technology is that watermark information is hidden in digital picture product using data embedding strategy, with reality
Now to the copyright protection of the product owner., it is necessary to possess following four basic characteristics for digital image watermarking：Peace
Quan Xing, not robustness, sentience and watermark capacity.Here, robustness and sentience be not weigh watermarking algorithm it is most important
Two evaluation indexes, not sentience refer to the ability that original image quality will not be significantly reduced after embedded watermark information；
Robustness refers to that watermarking algorithm is attacked and the ability that embedded watermark information is extracted under geometric attack in normal signal.Realize the two bases
This feature, it is necessary to Image Watermarking Technique implement copyright protection when should ensure not influenceing the visual effect of initial carrier image,
Ensure still completely or partial to be extracted watermark information after carrier image is under attack again.Obviously, as
The means of intellectual property protection, digital figure watermark will necessarily be subject to various forms of attacks, therefore robustness is digital watermarking
One basic demand of system, is also the main research of digital figure watermark in recent years.
In recent years, digital image watermarking technology had the development advanced by leaps and bounds, and proposed a series of specific aims successively very
Strong digital image watermark detection method.But, it is conventional that notice has been placed on confrontation by most image watermark detection methods
Signal transacting（Such as lossy compression method, LPF, noise jamming）Research on, and such as rotate, scale, translating, ranks go
Except, shearing, etc. geometric attack resistance effect it is bad.
The content of the invention
The present invention is to solve the above-mentioned technical problem existing for prior art, it is proposed that one kind can simultaneously resist routine
The image watermark method based on the correction of phase singularity value of signal transacting and unclassified geometric attacks.
Technical solution of the invention is：A kind of image watermark method based on the correction of phase singularity value, its feature exists
In：Specifically include following steps：
Agreement：I refers to host image；X, y represent the line number and columns of image respectively；W refers to binary bitmap, and size is；
LL represents watermark coefficient to be embedded；It is quantization step；Represent and contain watermarking images；Represent it is corrected after containing watermark
Image；EW represents the watermark information for extracting；
A. initial setting up
Obtain host image and Initialize installation；
B. watermark insertion
B.1 host image I carries out the double tree anisotropic filter groups of two grades of pyramids（PDTDFB）Conversion；
B.2 the low frequency sub-band coefficient to PDTDFB conversion carries out piecemeal treatment, is per block size；
B.3 watermark coefficient to be embedded in each sub-block is changed according to following formula, the insertion of watermark information is carried out using quantization method：
；
B.4 low frequency sub-band merges with all high-frequency sub-bands after changing, and carries out inverse PDTDFB conversion and obtains containing watermarking images；
C. geometric correction
C.1 choose altimetric image to be checked rotated, scaled, X-axis translation, Y-axis translation attack after each 50 width image, as instruction
Practice sample set；
C.2 quaternary number two-dimensional wavelet transformation is carried out to every width training sample image and obtains phasing matrix, phasing matrix is carried out very
Different value is decomposed（SVD）；
C.3 preceding 4 characteristic vectors as training sample image in principal singular value are chosen, sample is zoomed in and out, is translated,
The training study of the geometric transformation parameters such as rotation, obtains LS-SVR training patterns；
C.4 calculate to be detected containing watermarking imagesThe Mathematical Modeling of geometric correction, it is true using the LS-SVR training patterns for obtaining
Rational method；
C.5 using model parameter to imageGeometric correction is carried out, obtains corrected containing watermarking images；
D. watermark extracting
D.1 to corrected containing watermarking imagesCarry out two grades of PDTDFB conversion；
D.2 the low frequency sub-band coefficient to PDTDFB conversion carries out piecemeal treatment, is per block size；
D.3 the extraction of watermark is carried out using quantization method in each sub-block, extraction process is expressed as：
D.4 it is right according to watermarking images correspondence positionBeing chosen selected, you can obtain the watermarking images for finally extracting more.
The present invention embedded watermark first in the low frequency sub-band of host image PDTDFB conversion；Secondly, mapping to be checked is extracted
As through the high-frequency sub-band phasing matrix after quaternary number two-dimensional wavelet transformation, singular value decomposition being carried out to phasing matrix（SVD）, choose
Preceding 4 singular values in principal singular value are zoomed in and out to sample, translate, rotated as the characteristic vector of training sample image
The training study of geometric transformation parameter, obtains LS-SVR training patterns；Then, calculate to be detected containing watermarking images geometric correction
Mathematical Modeling, determines that model parameter carries out geometric correction using the LS-SVR training patterns for obtaining；Finally, contain from corrected
Watermark information is extracted in watermarking images.Test result indicate that, the method for the present invention not only has preferable invisibility, and right
Normal signal treatment and unclassified geometric attacks are respectively provided with height robustness.
Compared with prior art, the invention has the advantages that：
First, due to LS-SVR has the phase information of good learning ability and quaternary number two-dimensional wavelet transformation can be comprehensive
Portray and describe characteristics of image, therefore under normal signal treatment and unclassified geometric attacks, watermark information can be carried correctly
Take out, it is achieved thereby that height robustness；
Second, using image array singular value stability and singular value decomposition save memory space the characteristics of so that the method
Time complexity it is smaller.
Brief description of the drawings
Fig. 1 is that the embodiment of the present invention is embedded in binary watermarking in the width image of Lena, Barbara, Mandrill, Peppers tetra-
Result figure containing watermark.
Fig. 2 be the embodiment of the present invention the width image of Lena, Barbara, Mandrill, Peppers tetra- insertion watermark after with
10 times of difference result figures of original image.
Fig. 3 is embodiment of the present invention invisibility（Y-PSNR）With quantization step relational result figure.
Fig. 4 is embodiment of the present invention robustness test result figure.
Fig. 5 is the flow chart of the embodiment of the present invention.
Specific embodiment
The method of the present invention includes three phases altogether：Watermark insertion, geometric correction, watermark extracting.
Agreement：I refers to host image；X, y represent the line number and columns of image respectively；W refers to binary bitmap, and size is；LL represents watermark coefficient to be embedded；It is quantization step；Represent and contain watermarking images；After representing corrected
Containing watermarking images；EW represents the watermark information for extracting.
Specific steps are as shown in Figure 5：
A. initial setting up
Obtain host image and Initialize installation；
B. watermark insertion
B.1 original image I carries out the double tree anisotropic filter groups of two grades of pyramids（PDTDFB）Conversion；
B.2 the low frequency sub-band coefficient to PDTDFB conversion carries out piecemeal treatment, is per block size；
B.3 watermark coefficient to be embedded in each sub-block is changed according to following formula, the insertion of watermark information is carried out using quantization method：
；
B.4 low frequency sub-band merges with all high-frequency sub-bands after changing, and carries out inverse PDTDFB conversion and obtains containing watermarking images；
C. geometric correction
C.1 choose altimetric image to be checked rotated, scaled, X-axis translation, Y-axis translation attack after each 50 width image, as instruction
Practice sample set；
C.2 quaternary number two-dimensional wavelet transformation is carried out to every width training sample image and obtains phasing matrix, phasing matrix is carried out very
Different value is decomposed（SVD）；
C.3 preceding 4 characteristic vectors as training sample image in principal singular value are chosen, LS-SVR training patterns are obtained；
C.4 calculate to be detected containing watermarking imagesThe Mathematical Modeling of geometric correction, it is true using the LS-SVR training patterns for obtaining
Rational method；
C.5 using model parameter to imageGeometric correction is carried out, obtains corrected containing watermarking images；
D. watermark extracting
D.1 to corrected containing watermarking imagesCarry out two grades of PDTDFB conversion；
D.2 the low frequency sub-band coefficient to PDTDFB conversion carries out piecemeal treatment, is per block size；
D.3 the extraction of watermark is carried out using quantization method in each sub-block, extraction process is expressed as：
D.4 it is right according to watermarking images correspondence positionBeing chosen selected, you can obtain the watermarking images for finally extracting more.
Experiment test and parameter setting：
Experiment is performed on MATLAB R2010b platforms, and involved is the gray level image that size is 512 × 512, can be from
Following website is downloaded：http://decsai.ugr.es/cvg/dbimagenes/index.php.
The embodiment of the present invention is aqueous the width image of Lena, Barbara, Mandrill, Peppers tetra- insertion binary watermarking
Print result is as shown in Figure 1.
The embodiment of the present invention the width image of Lena, Barbara, Mandrill, Peppers tetra- insertion watermark after with original image
10 times of difference results it is as shown in Figure 2.
Embodiment of the present invention invisibility（Y-PSNR）It is as shown in Figure 3 with quantization step relational result.
Embodiment of the present invention robustness test result is as shown in Figure 4.
Claims (1)
1. it is a kind of based on phase singularity value correction image watermark method, it is characterised in that follow the steps below：
Agreement：I refers to host image；X, y represent the line number and columns of image respectively；W refers to binary bitmap, and size is；
LL represents watermark coefficient to be embedded；It is quantization step；Represent and contain watermarking images；Represent it is corrected after containing watermark
Image；EW represents the watermark information for extracting；
A. initial setting up
Obtain host image and Initialize installation；
B. watermark insertion
B.1 original image I carries out the double tree anisotropic filter group conversion of two grades of pyramids；
B.2 the low frequency sub-band coefficient to PDTDFB conversion carries out piecemeal treatment, is per block size；
B.3 watermark coefficient to be embedded in each sub-block is changed according to following formula, the insertion of watermark information is carried out using quantization method：
B.4 low frequency sub-band merges with all high-frequency sub-bands after changing, and carries out inverse PDTDFB conversion and obtains containing watermarking images；
C. geometric correction
C.1 choose altimetric image to be checked rotated, scaled, X-axis translation, Y-axis translation attack after each 50 width image, as instruction
Practice sample set；
C.2 quaternary number two-dimensional wavelet transformation is carried out to every width training sample image and obtains phasing matrix, phasing matrix is carried out very
Different value is decomposed；
C.3 preceding 4 characteristic vectors as training sample image in principal singular value are chosen, LS-SVR training patterns are obtained；
C.4 calculate to be detected containing watermarking imagesThe Mathematical Modeling of geometric correction, is determined using the LS-SVR training patterns for obtaining
Model parameter；
C.5 using model parameter to imageGeometric correction is carried out, obtains corrected containing watermarking images；
D. watermark extracting
D.1 to corrected containing watermarking imagesCarry out two grades of PDTDFB conversion；
D.2 the low frequency sub-band coefficient to PDTDFB conversion carries out piecemeal treatment, is per block size；
D.3 the extraction of watermark is carried out using quantization method in each sub-block, extraction process is expressed as：
D.4 it is right according to watermarking images correspondence positionBeing chosen selected, you can obtain the watermarking images for finally extracting more.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107945097A (en) * | 2017-12-18 | 2018-04-20 | 辽宁师范大学 | Robust image watermark method based on joint statistical model correction |
| CN108053360A (en) * | 2017-12-18 | 2018-05-18 | 辽宁师范大学 | The digital image watermark detection method of HMT models is closed based on multiphase |
| CN108090864A (en) * | 2017-12-18 | 2018-05-29 | 辽宁师范大学 | Quaternion wavelet area image method of detecting watermarks based on super-pixel |
| CN109727178A (en) * | 2018-12-27 | 2019-05-07 | 辽宁师范大学 | The domain NSST robust image watermark method based on polynary BKF parameter correction |
| CN110793472A (en) * | 2019-11-11 | 2020-02-14 | 桂林理工大学 | Grinding surface roughness detection method based on quaternion singular value entropy index |
| CN113393360A (en) * | 2021-06-08 | 2021-09-14 | 陕西科技大学 | Correction method for printing and scanning resistant digital watermark image |
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107945097A (en) * | 2017-12-18 | 2018-04-20 | 辽宁师范大学 | Robust image watermark method based on joint statistical model correction |
| CN108053360A (en) * | 2017-12-18 | 2018-05-18 | 辽宁师范大学 | The digital image watermark detection method of HMT models is closed based on multiphase |
| CN108090864A (en) * | 2017-12-18 | 2018-05-29 | 辽宁师范大学 | Quaternion wavelet area image method of detecting watermarks based on super-pixel |
| CN107945097B (en) * | 2017-12-18 | 2021-02-19 | 辽宁师范大学 | Lu-lolly image watermarking method based on joint statistical model correction |
| CN108090864B (en) * | 2017-12-18 | 2021-06-11 | 辽宁师范大学 | Quaternion wavelet domain image watermark detection method based on super pixels |
| CN108053360B (en) * | 2017-12-18 | 2021-06-15 | 辽宁师范大学 | Digital image watermark detection method based on multi-correlation HMT model |
| CN109727178A (en) * | 2018-12-27 | 2019-05-07 | 辽宁师范大学 | The domain NSST robust image watermark method based on polynary BKF parameter correction |
| CN109727178B (en) * | 2018-12-27 | 2023-05-09 | 辽宁师范大学 | NSST domain robust image watermarking method based on multivariate BKF parameter correction |
| CN110793472A (en) * | 2019-11-11 | 2020-02-14 | 桂林理工大学 | Grinding surface roughness detection method based on quaternion singular value entropy index |
| CN110793472B (en) * | 2019-11-11 | 2021-07-27 | 桂林理工大学 | Grinding surface roughness detection method based on quaternion singular value entropy index |
| CN113393360A (en) * | 2021-06-08 | 2021-09-14 | 陕西科技大学 | Correction method for printing and scanning resistant digital watermark image |
| CN113393360B (en) * | 2021-06-08 | 2022-10-21 | 陕西科技大学 | Correction method for printing and scanning resistant digital watermark image |
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Application publication date: 20170606 |