CN108986008A - Image processing method, device and equipment - Google Patents
Image processing method, device and equipment Download PDFInfo
- Publication number
- CN108986008A CN108986008A CN201710404269.XA CN201710404269A CN108986008A CN 108986008 A CN108986008 A CN 108986008A CN 201710404269 A CN201710404269 A CN 201710404269A CN 108986008 A CN108986008 A CN 108986008A
- Authority
- CN
- China
- Prior art keywords
- measured value
- image
- image data
- data
- restored
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
-
- 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
- G06T1/005—Robust watermarking, e.g. average attack or collusion attack resistant
- G06T1/0057—Compression invariant watermarking
Abstract
The embodiment of the invention discloses a kind of image processing method, device and equipment.A kind of image processing method may include: rarefaction raw image data.Image data and calculation matrix based on rarefaction obtain the first measured value of raw image data by compression sensing method.Coding is carried out to the first measured value and obtains perception cryptographic Hash, using perceptual hash value as the second measured value of raw image data.Second measured value is embedded into raw image data by reversible water mark method.Above-mentioned image processing method, device and equipment can generate the image authentication watermark convenient for the recovery after the recovery of watermarking images and distorted image.
Description
Technical field
The invention belongs to technical field of image processing more particularly to a kind of image processing methods, device and equipment.
Background technique
With being constantly progressive for network technology, paperless office is more and more gradually instead of traditional working way
People by network transmission multimedia resource, but there is also certain to distort risk while offering convenience for network transmission,
Therefore, the integrality for verifying multimedia resource content seems extremely important.
But because distorted image is easy but verification is very difficult, so that photo is in application scenarios such as evidence obtaining, archives
In can not play a significant role always, so needing the authenticity for guaranteeing image by the technological means of image authentication.
Currently, carrying out the certification of image's authenticity there are mainly two types of method, one is digital signature, and one is fragile water
Print.And fragile watermark is one of digital watermarking algorithm, digital watermark technology is recognized due to not needing additional space to store
Information is demonstrate,proved, therefore is more suitable the certification demand of image's authenticity than digital signature.
Fragile watermark Verification System is similar with general watermaking system, is divided into watermark insertion and watermark extracting authenticates two steps
Suddenly.By a key, original watermark is generated according to certain generating algorithm, it may include the copyright information of original image, or
Itself is a visual copyright marking or a string of certification symbols for person's own.According to watermarking algorithm, will give birth to
At original watermark be embedded into original image, then obtained watermarking images.
The authentication information of the embedded picture hash function traditional often through SHA-1 or MD5 etc. in Fragile Watermark Algorithm
It generates, and traditional hash function processing text information no doubt facilitates, but opposite with complicated and safety is calculated for image
Lower defect.
After Fragile Watermark Algorithm embeds a watermark into image, more or less change can be generated to the pixel of image, it can not
Reach military affairs, medicine, law or enterprise etc. to the standard in the higher field of the integrity demands of data content.
After the authentication information of image is embedded in carrier image as watermark by Fragile Watermark Algorithm, being able to validate only image mostly is
It is no to be tampered.If after image authentication is tampered, Fragile Watermark Algorithm is helpless for carrying out tamper recovery after distorting.
Also, Fragile Watermark Algorithm certification is generally basede on statistical theory, needs according to previously given priori statistical property
Threshold value is authenticated, and the accuracy of verifying depends on given threshold value, and usually there is different images difference to be suitble to
Judgment threshold, so can not find a perfect threshold value is suitable for each image.If fragile watermark certificate scheme does not use threshold
Value technology, then when receiving end is extracted watermark and authenticated, it will usually need to provide original watermark, can not achieve blind Detecting.
To sum up, existing image authentication watermark generation method is high, poor for applicability with complexity and can be to original image
The shortcomings that pixel impacts.
Summary of the invention
The embodiment of the invention provides a kind of image processing method, device and equipment, can generate convenient for watermark figure
The image authentication watermark of recovery and the recovery after distorted image of picture.
In a first aspect, providing a kind of image processing method, may include:
Rarefaction raw image data.
Image data and calculation matrix based on rarefaction obtain the first of raw image data by compression sensing method
Measured value.
Coding is carried out to the first measured value and obtains perception cryptographic Hash, using perceptual hash value as the second of raw image data
Measured value.
Second measured value is embedded into raw image data by reversible water mark method.
Second aspect provides a kind of image data processing system, may include: Thinning Unit, the life of the first measured value
At unit, the second measured value generation unit and measured value embedded unit.
The Thinning Unit can be used for rarefaction raw image data.
The first measured value generation unit can be used for image data based on rarefaction and calculation matrix and pass through compression sense
First measured value of perception method acquisition raw image data.
The second measured value generation unit can be used for carrying out the first measured value coding and obtain perception cryptographic Hash, will perceive
Second measured value of the cryptographic Hash as raw image data.
The measured value embedded unit can be used for the second measured value being embedded into original image number by reversible water mark method
In.
The third aspect provides a kind of image-data processing apparatus, may include memory and processor.
The memory can be used for storing executable program code.
The processor can be used for reading the executable program code stored in the memory to execute above-mentioned image
Data processing method.
Image processing method, device and the equipment provided according to embodiments of the present invention.It is obtained by compression sensing method
The first measured value and the second measured value for obtaining raw image data, as the authenticating water-mark of raw image data, and will be used for original
Second measured value of beginning image data certification is embedded into raw image data in a manner of reversible water mark.At this image data
Reason method, apparatus and equipment have the advantages that be simple and efficient, are widely applicable, and can generate convenient for watermarking images recovery and
The image authentication watermark that watermarking images can restore after being tampered.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, will make below to required in the embodiment of the present invention
Attached drawing is briefly described, it should be apparent that, drawings described below is only some embodiments of the present invention, for
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is the schematic flow chart of the image processing method of an embodiment of the present invention；
Fig. 2 is the schematic flow chart of the image processing method of another embodiment of the invention；
Fig. 3 is the schematic flow chart of the image processing method of another embodiment of the invention；
Fig. 4 is the schematic flow chart of the image processing method of another embodiment of the present invention；
Fig. 5 is the schematic block diagram of the image data processing system of an embodiment of the present invention；
Fig. 6 is the schematic block diagram of the image data processing system of another embodiment of the invention；
Fig. 7 is the schematic block diagram of the image data processing system of another embodiment of the invention；
Fig. 8 is the schematic block diagram of the image-data processing apparatus of an embodiment of the present invention；
Fig. 9 is the example effect figure of the image processing method of an embodiment of the present invention.
Specific embodiment
The feature and exemplary embodiment of various aspects of the invention is described more fully below.In following detailed description
In, many details are proposed, in order to provide complete understanding of the present invention.But to those skilled in the art
It will be apparent that the present invention can be implemented in the case where not needing some details in these details.Below to implementation
The description of example is used for the purpose of providing by showing example of the invention and better understanding of the invention.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.Embodiment is described in detail below with reference to the accompanying drawings.
Fig. 1 is the schematic flow chart of the image processing method of an embodiment of the present invention.As shown in Figure 1, a kind of
Image processing method may include: S110~S140.
S110, rarefaction raw image data.
In one example, in compression sensing method, it is assumed that a natural sign x ∈ Rn, pass through a calculation matrix A ∈
Rm×nThe linear random projection for carrying out y=Ax, obtains one measured value y, wherein y ∈ Rm, m < < n.If signal s is on ψ
Sparse, then y=Ax may be expressed as:
Y=Ax=A Ψ s=Θ s (1)
In formula (1), ψ is sparse matrix, Θ=A ψ, Θ ∈ Rm×n, R is natural number, matrix A can be meet it is limited equidistant
The calculation matrix of property (Restricted Isometry Property, RIP) condition, such as: gaussian random matrix, shellfish effort
Matrix and the chaos matrix etc. generated by chaology.It can be obtained by the inverse problem of solution formula (1) by above-mentioned calculation matrix
To signal s, signal x is obtained by x=ψ s.When restoring to raw image data, the reconstruction of signal s can use l1Most
Optimization problem solves under small norm, is expressed as the mathematical model of formula (2):
min||s||L1Subjectto y=Θ s (2)
So it is not difficult to find out that, before the measured value for obtaining raw image data using compressed sensing, need to original graph
As data progress rarefaction, to meet the requirement of compression sensing method.
In some instances, the S110 Zig-zag mode that can be sorted using the Z row of quantization parameter be scanned to allow original graph
As adjacent pixel diffusion in data, thus rarefaction raw image data.
S120, image data and calculation matrix based on rarefaction obtain raw image data by compression sensing method
First measured value.
In some instances, compressed sensing calculation matrix A can be obtained by above-mentioned formula.
For example, it is assumed that carrying out compression measurement to image using chaos matrix A, chaos matrix A is by following Logistic-sine
Chaotic maps model generates:
zn+1=Fr(zn)=(ryn(1-yn))+(4-r)sin(πyn/4)mod1,r∈(0,4],yn∈(0,1] (3)
xk=1-2zn+kd (4)
xk∈X(d,k,y0), d=15, k ∈ Z+ (5)
Wherein, k indicates positive integer, and d indicates to take a data every how many, for example, d=15.y0It indicates to give first
Initial value, r indicate chaotic parameter.In order to generate chaos matrix A ∈ Rm×n, can be by chaotic parameter r and initial value y0As key, by
Formula (3)~(5) generate random sequence X (d, k, the y that length is m × n0), final chaotic measurement matrix such as formula (6):
S130 carries out coding to the first measured value and obtains perception cryptographic Hash, using perceptual hash value as raw image data
The second measured value.
In some instances, in S130, coding can be carried out to the first measured value according to chaotic maps method and is perceived
Cryptographic Hash, using perceptual hash value as the second measured value of raw image data.For example, being iterated chaos to the second measured value
Mapping obtains the second measured value of raw image data.
Second measured value is embedded into raw image data by S140 by reversible water mark method.
In some instances, in S140, the second measured value can be used as the short watermark of raw image data, using can be against the current
Impression method is embedded into raw image data.It can restore when needed to being embedded in short watermark raw image data.
In some instances, in S140, the number of the corresponding pixel of each gray level in raw image data can be counted,
And draw histogram, wherein abscissa indicates each gray level of image, and ordinate indicates the corresponding pixel of the gray level
Number.
H (p)=[h (0), h (1) ..., h (255)] (7)
H (i) indicates that pixel value is i, i ∈ [0,255] in formula (8).
Number of pixels is most in formula (8) the gray level gray level most as peak point and number of pixels is found out as zero
Point remembers it for P and Z respectively.Peak point is pairs of with Matching zeros, by the edge histogram Bin between peak point and zero point
0:00 direction translates one, if zero point adds 1 on the right of peak point, by all gray levels between peak point and zero point, instead
Subtract 1, at this point, former zero point exchanges to by peak point.
Raw image data can be scanned, when meeting peak point gray level, is embedded in second measured value an of storage unit, example
Such as, 1bit, if the value of insertion is " 0 ", gray level is remained unchanged；If the value of insertion is " 1 ", gray level becomes adjacent zero
Point, for example, gray level is made to add deduct 1.
Since above-mentioned embedded mode is reversible, so after removing short watermark, it can be by image to be detected data of acquisition
It restores.
The image processing method provided according to embodiments of the present invention.Original image number is obtained by compression sensing method
According to the first measured value and the second measured value, as the authenticating water-mark of raw image data, and raw image data will be used for and recognized
Second measured value of card is embedded into raw image data in a manner of reversible water mark.This image processing method has letter
Single efficient, widely applicable advantage, and can generate be tampered convenient for the recovery of watermarking images and watermarking images after can be extensive
Multiple image authentication watermark.
In some instances, the above-mentioned raw image data for being embedded in short watermark can be uploaded in network, Huo Zhetong
Other modes are crossed to store in the storage system that can be obtained to other terminals.For example, the original image number that short watermark will be embedded in
According to sharing to cloud.
In some instances, network can be uploaded directly into using the first measured value as the long watermark of raw image data
In, or stored in the storage system that can be obtained to other terminals by other means.For example, long watermark cloud is shared to
Cloud.
Fig. 2 is the schematic flow chart of the image processing method of another embodiment of the invention.As shown in Fig. 2, should
Image processing method may include:
S210 obtains image to be detected data for being embedded with the second measured value.It can be embedded in several ways
Image to be detected data of second measured value.Such as it can be obtained from network cloud.
S220 is restored the second measured value extracted in image to be detected data by reversible water mark method and obtains restored image
Data.
S230, rarefaction restored image data.
S240, restored image data and calculation matrix based on rarefaction obtain restored image number by compression sensing method
According to third measured value.
S250 carries out coding to third measured value and obtains perception cryptographic Hash, will carry out coding acquisition to third measured value
Fourth measured value of the perceptual hash value as raw image data.
S260 judges whether the 4th measured value is identical as the second measured value of image to be detected data, if the 4th measured value
It is identical as the second measured value of image to be detected data, then S270a is entered step, if the 4th measured value and image to be detected data
The second measured value it is identical, then enter step S270b.
S270a determines that image to be detected data are not tampered with.
S270b determines that image to be detected data are tampered.
Fig. 3 is the schematic flow chart of the image processing method of another embodiment of the invention.As shown in figure 3, if
Determine that image to be detected data are tampered, which can also include:
S310 restores restored image data by compressed sensing reconstructing method.It in some instances, can be to
Three measured values restore the image being tampered by the sparse restructing algorithm of l1-svd.
In some instances, can also include: before rarefaction restored image data in S230
Piecemeal processing is carried out to restored image data.
So, if it is determined that image to be detected data are tampered, which can also include shown in Fig. 4
Step.Fig. 4 is the schematic flow chart of the image processing method of another embodiment of the present invention.As shown in figure 4, the image
Data processing method can also include:
S410 obtains the second measured value of image to be detected data, wherein the second measured value of image to be detected data is
It is obtained based on piecemeal treated image to be detected data.
S420, block-by-block compare the second measured value of third measured value and image to be detected data.
S430, restored image number corresponding to the third measured value block different with the second measured value of image to be detected data
Restored according to by compressed sensing reconstructing method.
Since image processing method shown in Fig. 4 only needs to reconstruct the image block data for restoring to be tampered, so fortune
Calculate speed quickly, and the picture quality restored is higher.
According to some embodiments, first raw image data can be carried out before the S110 in the image processing method
Piecemeal processing.
In some instances, it is assumed that raw image data is that size is N × N (2n×2n) gray level image, then can will scheme
As data are divided into S non overlapping blocks, every block size is B × B (2b×2b), then S=N2/B2=2n-b×2n-b。
In some instances, S110 may include that each image block that will be obtained is scanned with Zig-zag mode, will be every
A image block is transformed into one-dimensional vector
It in some instances, can be by formula (3)~(6) and in two preset-key K in S1201(r01,y01) and K2
(r02,y02) guidance under generate perception calculation matrix A1 and A2,λ is whole manifold, and with A1, A2 is right respectivelyIt carries out perception sampling and obtains measured value g1i,g2i∈Rλ, i ∈ (1,2 ..., S), and will survey
The corresponding addition summation of magnitude obtains Gi=g1i+g2i,i∈(1,2,...,λ×S)。
In some instances, in S120, dct transform can be carried out to S non overlapping blocks, respectively the DCT coefficient to every piece
It is scanned with Zig-zag mode and is converted into one-dimensional vectorUsing formula (3)~
(6) in preset-key K4(r04,y04) guidance under generate perception calculation matrix A3,With the calculation matrix of generation
A3 carries out perception sampling to S one-dimensional vector respectively and obtains compression measured value fi=A3 × βi, fi∈Rλ,i∈(1,2,...,S)。
The the first measured value F={ f that will be obtained1,f2,...,fLUpload cloud in a manner of zero watermarking as long watermark and saved.
In some instances, in S130, using formula (3) Logistic-sine chaotic maps to measured value GiIt is compiled
Code.In some instances, due to chaotic maps parameter request r ∈ (0,4], yn∈ (0,1], therefore can be first by measured value GiWith public affairs
Formula (7) is quantified.
Wherein Max=max (G1,G2,...,Gλ×s), Min=min (G1,G2,...,Gλ×s).After the completion of quantization preset it is close
Key K3(r03,y03) guidance is iterated chaotic maps, such as can carry out 4 wheel iterative chaotic maps, it is as follows: assuming that every wheel
Chaotic maps need to calculate n times, enable N=λ × S:
The first round: forward iteration chaotic maps
1th:r1=(G1+r03)/2∈(0,4],Y1=Fr1(y03)∈(0,1]
2~Nth:ri=(Gi+ri-1)/2∈(0,4],Yi=Fri(Yi-1)∈(0,1]
Second wheel: inverse iteration chaotic maps
N+1th:rN+1=(GN+rN)/2∈(0,4],YN+1=Fr(N+1)(YN)∈(0,1]
N+2~2Nth:ri=(G2N-i+1+ri-1)/2∈(0,4],Yi=Fri(Yi-1)∈(0,1]
Third round: forward iteration chaotic maps
2N+1th:r2N+1=(G1+r2N)/2∈(0,4],Y2N+1=Fr(2N+1)(Y2N)∈(0,1]
2N+2~3Nth:ri=(Gi-2N+ri-1)/2∈(0,4],Yi=Fri(Yi-1)∈(0,1]
Fourth round: inverse iteration chaotic maps
3N+1th:r3N+1=(GN+r3N)/2∈(0,4],Y3N+1=Fr(3N+1)(Y3N)∈(0,1]
3N+2~4Nth:ri=(G4N-i+1+ri-1)/2∈(0,4],Yi=Fri(Yi-1)∈(0,1]
It in some instances, can be by Y in S130N,Y2N,Y3N,Y4N4 numbers are converted into binary format respectively, for example,
40bit cascade after every number decimal point can be taken is spliced into 160bit, the perceptual hash value as generated, as original image
Second measured value of data, that is, the short watermark of raw image data.The figure obtained using above-mentioned image processing method
As safety not only Dependent Algorithm in Precision of authenticating water-mark itself, key is also relied on, compared to traditional hash function SHA-1 and MD5,
Image data is more suitable for generating authenticating water-mark by calculating perceptual hash value, and improves the safety of watermark authentication method
Property.
In some instances, in S140, short watermark can be embedded in raw image data by the method for reversible water mark,
And cloud is uploaded to the long watermark being calculated and is stored.
In some instances, it in S210, after obtaining a testing image data, can be restored by reversible water mark method
The second measured value extracted in image to be detected data obtains restored image data.If image is not tampered with, restored image number
It is consistent with the second measured value of raw image data according to the 4th measured value answered, and restored image data and raw image data phase
Together, image 100% can recover to reset condition.
In some instances, in S410, if image is tampered, the image of recovery can be re-started piecemeal processing,
Sparse processing obtains third measured value by compression sensing method.
In some instances, in S420, by image block be unit by the first measured value of the testing image data of acquisition with
The third measured value of restored image data is compared, and finds different image block, realizes tampering location.
In some instances, in S430, by image block be unit by the first measured value of the testing image data of acquisition with
The third measured value of restored image data is compared, and different image block is judged to distorting block, using compressed sensing weight
Structure algorithm restores the image block that replacement is tampered.Since this method only needs to reconstruct the image block for restoring to be tampered, so operation
Speed quickly, and restore picture quality it is higher.
Above in conjunction with Fig. 1 to Fig. 4, image processing method according to an embodiment of the present invention is described in detail, below
Image data processing system according to an embodiment of the present invention and equipment will be described in detail in conjunction with Fig. 5 to Fig. 8.
Fig. 5 is the schematic block diagram of the image data processing system of an embodiment of the present invention.As shown in figure 5, one
Kind image data processing system 500, may include: Thinning Unit 510, the first measured value generation unit 520, the second measured value
Generation unit 530 and measured value embedded unit 540.
Thinning Unit 510 can be used for rarefaction raw image data.
First measured value generation unit 520 can be used for image data based on rarefaction and calculation matrix and pass through compression sense
First measured value of perception method acquisition raw image data.
Second measured value generation unit 530 can be used for carrying out the first measured value coding and obtain perception cryptographic Hash, will feel
Know second measured value of the cryptographic Hash as raw image data.
Measured value embedded unit 540 can be used for the second measured value being embedded into original image number by reversible water mark method
In.
Image data processing system 500 according to an embodiment of the present invention can correspond to picture number according to an embodiment of the present invention
According to the executing subject in processing method, and the function of each unit in image data processing system 500 is respectively in order to realize
The corresponding process of each method in Fig. 1, for sake of simplicity, details are not described herein.
Therefore, the image data processing system provided according to embodiments of the present invention.It is obtained by compression sensing method original
The first measured value and the second measured value of image data, as the authenticating water-mark of raw image data, and will be used for original image
Second measured value of data authentication is embedded into raw image data in a manner of reversible water mark.This image data processing system
Have the advantages that be simple and efficient, is widely applicable, and after capable of generating and being tampered convenient for the recovery of watermarking images and watermarking images
The image authentication watermark that can restore.
In some instances, the second measured value generation unit 530 is also used to:
Coding is carried out to the first measured value according to chaotic maps method and obtains perception cryptographic Hash, using perceptual hash value as original
Second measured value of beginning image data.
Fig. 6 is the schematic block diagram of the image data processing system of another embodiment of the invention.As shown in fig. 6,
Image data processing system 600 may include: Thinning Unit 610, the first measured value generation unit 620, the life of the second measured value
At unit 630, measured value embedded unit 640 and judging unit 650.
In some instances, image data processing system 600 therein, can be raw with Thinning Unit 610, the first measured value
At Thinning Unit 510 shown in unit 620, the second measured value generation unit 630 and measured value embedded unit 640 and Fig. 5,
First measured value generation unit 520, the second measured value generation unit 530 are similar with the function of measured value embedded unit 540.
In some instances, judging unit 650 can be used for:
Obtain image to be detected data for being embedded with the second measured value.
The second measured value extracted in image to be detected data is restored by reversible water mark method obtains restored image data.
Rarefaction restored image data.
Restored image data and calculation matrix based on rarefaction obtain restored image data by compression sensing method
Third measured value.
Coding is carried out to third measured value and obtains perception cryptographic Hash, the perception for carrying out coding acquisition to third measured value is breathed out
Fourth measured value of the uncommon value as raw image data.
4th measured value is identical as the second measured value of image to be detected data, determines that image to be detected data are not usurped
Change.
4th measured value is not identical as the second measured value of image to be detected data, determines that image to be detected data are usurped
Change.
Fig. 7 is the schematic block diagram of the image data processing system of another embodiment of the invention.As shown in Figure 7.
Image data processing system 700 may include: Thinning Unit 710, the first measured value generation unit 720, the life of the second measured value
At unit 730, measured value embedded unit 740, judging unit 750 and recovery unit 760.
In some instances, Thinning Unit 710 therein, the first measured value generation unit 720, the second measured value generate
Unit 730, measured value embedded unit 740, judging unit 750 and recovery unit 760 can in Fig. 6 Thinning Unit 610,
First measured value generation unit 620,650 function of the second measured value generation unit 630, measured value embedded unit 640 and judging unit
It can be similar.
Recovery unit 760 can be used for restoring by image data of the compressed sensing reconstructing method to recovery.
In some instances, above-mentioned judging unit can be also used for carrying out piecemeal processing to restored image data.
In some instances, above-mentioned recovery unit can be also used for:
Obtain the second measured value of image to be detected data, wherein the second measured value of image to be detected data is to be based on
What piecemeal treated image to be detected data obtained.
Block-by-block compares the second measured value of third measured value and image to be detected data.
It is logical to the corresponding restored image data of the third measured value block different with the second measured value of image to be detected data
Overcompression sensing reconstructing method is restored.
Fig. 8 is the schematic block diagram of the image-data processing apparatus of an embodiment of the present invention.As shown in figure 8, knot
At least part for closing the image processing method and image data processing system stated can be real by computer equipment 800
It is existing.The equipment 800 may include processor 803 and memory 804.
Memory 804 can be used for storing executable program code.
Processor 803 can be used for reading the executable program code stored in memory 804 to execute above-mentioned image
Data processing method.
Therefore, the image-data processing apparatus provided according to embodiments of the present invention.It is obtained by compression sensing method original
The first measured value and the second measured value of image data, as the authenticating water-mark of raw image data, and will be used for original image
Second measured value of data authentication is embedded into raw image data in a manner of reversible water mark.This image-data processing apparatus
Have the advantages that be simple and efficient, is widely applicable, and after capable of generating and being tampered convenient for the recovery of watermarking images and watermarking images
The image authentication watermark that can restore.
In some illustrated examples, accelerating the equipment 800 that cursor is mobile in network view can also include input equipment
801, input port 802, output port 805 and output equipment 806.Wherein, input port 802, processor 803, memory
804 and output port 805 be connected with each other by bus 810, input equipment 801 and output equipment 806 pass through input terminal respectively
Mouth 802 and output port 805 are connect with bus 810, and then are connect with the other assemblies of equipment 800.
In some instances, here output interface and input interface can also be indicated with I/O interface.Specifically, it inputs
Equipment 801 is received from external input information, and is transmitted to processor 803 for information is inputted by input port 802.Example
Such as, input information is raw image data.
In some instances, processor 803 is based on the computer executable program code or instruction stored in memory 804
Input information is handled to generate output information, for example, processor 804 executes following steps: rarefaction original image number
According to.Image data and calculation matrix based on rarefaction obtain the first measurement of raw image data by compression sensing method
Value.Coding is carried out to the first measured value and obtains perception cryptographic Hash, using perceptual hash value as the second measurement of raw image data
Value.Second measured value is embedded into raw image data by reversible water mark method.Temporarily or permanently by output information
It is stored in memory 804, output information is then transmitted to output equipment 806 via output port 805 when needed.Output
Output information is output to the outside of equipment 800 by equipment 806.For example, uploading to cloud.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.Some or all of unit therein can be selected to realize the embodiment of the present invention according to the actual needs
Purpose.
Fig. 9 is the example effect figure of the image processing method of an embodiment of the present invention.As shown in figure 9, with 512
For the portrait image of × 512 sizes, for pixel value between 0~255, piecemeal size is all made of 16 × 16.
Fig. 9 (a) indicates raw image data.Fig. 9 (b) indicates the raw image data after water mark inlaying.Fig. 9 (c) indicates Fig. 9
(b) image data after content is tampered, can also Fig. 9 (c) be referred to as image to be detected data.Fig. 9 (d) indicates to use above-mentioned figure
Image data tampering location figure after being authenticated as processing method is wherein unauthenticated in white rectangle frame and is passed through
Region after distorting.Fig. 9 (e) indicates that finally obtained recovery is schemed after carrying out tamper recovery using above-mentioned image processing method
As data.
It can be seen that the recovery image data in Fig. 9 (e) is identical with the raw image data in Fig. 9 (a).
Claims (13)
1. a kind of image processing method, which is characterized in that the described method includes:
Rarefaction raw image data；
Image data and calculation matrix based on rarefaction obtain the first of the raw image data by compression sensing method
Measured value；
Coding is carried out to first measured value and obtains perception cryptographic Hash, using the perceptual hash value as the original image number
According to the second measured value；
Second measured value is embedded into the raw image data by reversible water mark method.
2. image processing method according to claim 1, which is characterized in that described to be carried out to first measured value
Coding obtains perception cryptographic Hash, using the perceptual hash value as the second measured value of the raw image data, comprising:
Coding is carried out to first measured value according to chaotic maps method and obtains perception cryptographic Hash, the perceptual hash value is made
For the second measured value of the raw image data.
3. image processing method according to claim 1, which is characterized in that further include:
Obtain image to be detected data for being embedded with the second measured value；
The second measured value extracted in image to be detected data is restored by reversible water mark method obtains restored image data；
Restored image data described in rarefaction；
Restored image data and calculation matrix based on rarefaction obtain the restored image data by compression sensing method
Third measured value；
Coding is carried out to the third measured value and obtains perception cryptographic Hash, the sense of coding acquisition will be carried out to the third measured value
Know fourth measured value of the cryptographic Hash as the raw image data；
4th measured value is identical as the second measured value of image to be detected data, determines image to be detected data
It is not tampered with；
4th measured value is not identical as the second measured value of image to be detected data, determines image to be detected number
According to being tampered.
4. image processing method according to claim 3, which is characterized in that if it is determined that image to be detected data
It is tampered, the method also includes:
The restored image data are restored by compressed sensing reconstructing method.
5. image processing method according to claim 4, which is characterized in that restored image number described in the rarefaction
According to before, further includes:
Piecemeal processing is carried out to the restored image data.
6. image processing method according to claim 5, which is characterized in that if it is determined that image to be detected data
It is tampered, the method also includes:
Obtain the second measured value of image to be detected data, wherein the second measured value of image to be detected data is
It is obtained based on piecemeal treated image to be detected data；
Second measured value of block-by-block the third measured value and image to be detected data；
To the corresponding restored image number of block that the second measured value of the third measured value with image to be detected data is different
Restored according to by compressed sensing reconstructing method.
7. a kind of image data processing system, which is characterized in that described device includes:
Thinning Unit is used for rarefaction raw image data；
First measured value generation unit, for based on rarefaction image data and calculation matrix pass through compression sensing method obtain
First measured value of the raw image data；
Second measured value generation unit obtains perception cryptographic Hash for carrying out coding to first measured value, by the perception
Second measured value of the cryptographic Hash as the raw image data；
Measured value embedded unit, for second measured value to be embedded into the raw image data by reversible water mark method
In.
8. image data processing system according to claim 7, which is characterized in that the second measured value generation unit is also
For:
Coding is carried out to first measured value according to chaotic maps method and obtains perception cryptographic Hash, the perceptual hash value is made
For the second measured value of the raw image data.
9. image data processing system according to claim 7, which is characterized in that further include judging unit, be used for:
Obtain image to be detected data for being embedded with the second measured value；
The second measured value extracted in image to be detected data is restored by reversible water mark method obtains restored image data；
Restored image data described in rarefaction；
Restored image data and calculation matrix based on rarefaction obtain the restored image data by compression sensing method
Third measured value；
Coding is carried out to the third measured value and obtains perception cryptographic Hash, the sense of coding acquisition will be carried out to the third measured value
Know fourth measured value of the cryptographic Hash as the raw image data；
4th measured value is identical as the second measured value of image to be detected data, determines image to be detected data
It is not tampered with；
4th measured value is not identical as the second measured value of image to be detected data, determines image to be detected number
According to being tampered.
10. image data processing system according to claim 9, which is characterized in that further include recovery unit, be used for:
Restored by image data of the compressed sensing reconstructing method to the recovery.
11. image data processing system according to claim 10, which is characterized in that the judging unit is also used to:
Piecemeal processing is carried out to the restored image data.
12. image data processing system according to claim 11, which is characterized in that the recovery unit is also used to:
Obtain the second measured value of image to be detected data, wherein the second measured value of image to be detected data is
It is obtained based on piecemeal treated image to be detected data；
Second measured value of block-by-block the third measured value and image to be detected data；
To the corresponding restored image number of block that the second measured value of the third measured value with image to be detected data is different
Restored according to by compressed sensing reconstructing method.
13. a kind of image-data processing apparatus, which is characterized in that including memory and processor；
The memory is for storing executable program code；
It is any with perform claim requirement 1 to 6 that the processor is used to read the executable program code stored in the memory
Image processing method described in.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710404269.XA CN108986008A (en) | 2017-06-01 | 2017-06-01 | Image processing method, device and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710404269.XA CN108986008A (en) | 2017-06-01 | 2017-06-01 | Image processing method, device and equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108986008A true CN108986008A (en) | 2018-12-11 |
Family
ID=64501737
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710404269.XA Pending CN108986008A (en) | 2017-06-01 | 2017-06-01 | Image processing method, device and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108986008A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109756740A (en) * | 2019-01-18 | 2019-05-14 | 北京邮电大学 | Semi-tensor method for compressing image and image recovery method based on optimal calculation matrix |
| CN111127288A (en) * | 2019-12-16 | 2020-05-08 | 中移（杭州）信息技术有限公司 | Reversible image watermarking method and device and computer readable storage medium |
| CN112910656A (en) * | 2021-01-29 | 2021-06-04 | 北京邮电大学 | Compressed sensing data transmission method based on digital signcryption |
| CN116339899A (en) * | 2023-05-29 | 2023-06-27 | 内江师范学院 | Desktop icon management method and device based on artificial intelligence |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7352877B2 (en) * | 2003-02-04 | 2008-04-01 | Hitachi, Ltd. | Digital-watermark-embedding and picture compression unit |
| US20130039588A1 (en) * | 2011-08-12 | 2013-02-14 | Sony Corporation | Image processing method and apparatus for tamper proofing |
| CN103700061A (en) * | 2013-12-30 | 2014-04-02 | 东北大学 | Compressive-sensing-based digital image watermark embedding and extraction method |
| CN103971322A (en) * | 2014-05-13 | 2014-08-06 | 安徽师范大学 | Watermark embedding method for host image and watermark extracting method for image including watermark |
-
2017
- 2017-06-01 CN CN201710404269.XA patent/CN108986008A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7352877B2 (en) * | 2003-02-04 | 2008-04-01 | Hitachi, Ltd. | Digital-watermark-embedding and picture compression unit |
| US20130039588A1 (en) * | 2011-08-12 | 2013-02-14 | Sony Corporation | Image processing method and apparatus for tamper proofing |
| CN103700061A (en) * | 2013-12-30 | 2014-04-02 | 东北大学 | Compressive-sensing-based digital image watermark embedding and extraction method |
| CN103971322A (en) * | 2014-05-13 | 2014-08-06 | 安徽师范大学 | Watermark embedding method for host image and watermark extracting method for image including watermark |
Non-Patent Citations (1)
| Title |
|---|
| 邓秘密: "压缩感知在图像水印算法中的应用研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109756740A (en) * | 2019-01-18 | 2019-05-14 | 北京邮电大学 | Semi-tensor method for compressing image and image recovery method based on optimal calculation matrix |
| CN109756740B (en) * | 2019-01-18 | 2020-02-18 | 北京邮电大学 | Half tensor image compression method and image recovery method based on optimal measurement matrix |
| CN111127288A (en) * | 2019-12-16 | 2020-05-08 | 中移（杭州）信息技术有限公司 | Reversible image watermarking method and device and computer readable storage medium |
| CN111127288B (en) * | 2019-12-16 | 2023-07-04 | 中移（杭州）信息技术有限公司 | Reversible image watermarking method, reversible image watermarking device and computer readable storage medium |
| CN112910656A (en) * | 2021-01-29 | 2021-06-04 | 北京邮电大学 | Compressed sensing data transmission method based on digital signcryption |
| CN116339899A (en) * | 2023-05-29 | 2023-06-27 | 内江师范学院 | Desktop icon management method and device based on artificial intelligence |
| CN116339899B (en) * | 2023-05-29 | 2023-08-01 | 内江师范学院 | Desktop icon management method and device based on artificial intelligence |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Naveh et al. | Photoproof: Cryptographic image authentication for any set of permissible transformations | |
| Fridrich et al. | Statistically undetectable jpeg steganography: dead ends challenges, and opportunities | |
| Sun et al. | A robust and secure media signature scheme for JPEG images | |
| Butora et al. | Reverse JPEG compatibility attack | |
| US7656559B2 (en) | System and method for generating a signed hardcopy document and authentication thereof | |
| CN108986008A (en) | Image processing method, device and equipment | |
| Murali et al. | Comparision and analysis of photo image forgery detection techniques | |
| WO2022095312A1 (en) | Electronic seal adding and verifying method and system | |
| CN108416724B (en) | Reversible information hiding method based on multiple predictors | |
| CN112632475B (en) | Picture copyright protection system and method based on national password and picture steganography | |
| Zhang et al. | Improving the robustness of JPEG steganography with robustness cost | |
| US9239966B2 (en) | Method and device for watermarking a sequence of images, method and device for authenticating a sequence of watermarked images and corresponding computer program | |
| Sengupta et al. | Authentication through Hough transformation generated signature on G-Let D3 Domain (AHSG) | |
| US20160189015A1 (en) | Data exchange methods, systems and apparatus using color images | |
| Hong et al. | A recoverable AMBTC authentication scheme using similarity embedding strategy | |
| Raj et al. | Security analysis of hash based fragile watermarking scheme for image integrity | |
| Lou et al. | Digital signature-based image authentication | |
| Chen et al. | Image authentication for permissible cropping | |
| Murali et al. | Detection Of digital photo image forgery | |
| Alam et al. | An investigation into image hiding steganography with digital signature framework | |
| Chinniyan et al. | Image Steganography Using Deep Neural Networks. | |
| RU2739936C1 (en) | Method of adding digital labels to digital image and apparatus for realizing method | |
| Jothimani et al. | Image authentication using global and local features | |
| WO2023172268A1 (en) | Image difference generation | |
| KR100440085B1 (en) | Apparatus for inserting watermarks using bitplane informations and method thereof, and apparatus for detecting whether the watermarked digital data was modulated and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181211 |
|
| RJ01 | Rejection of invention patent application after publication |