CN112199689B - Halftone information hiding and identifying method based on mobile terminal - Google Patents
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Abstract
The invention discloses a halftone information hiding and identifying method based on a mobile terminal, which specifically comprises the following steps: manufacturing a printing carrier image and anti-counterfeiting information; scrambling the anti-counterfeiting information to generate printing quantum information; manufacturing a halftone hidden image to obtain a hidden image containing printing quantum information, and judging visual effects of the hidden image and the printing quantum information; printing a carrier image, namely a half-tone unencrypted image and a manufactured hidden image containing printing quantum information, namely a half-tone encrypted image by using a digital printer and a high-precision scanner, performing analog printing and scanning to respectively obtain an unencrypted and encrypted scanned image containing printing quantum information, and performing geometric correction and gray histogram equalization correction; comparing the characteristic values of the gray level co-occurrence matrix of the encrypted scanned image and the unencrypted scanned image, and identifying whether the image contains hidden information according to the difference of the characteristic values of the encrypted scanned image and the unencrypted scanned image. The method solves the problem that the mobile terminal equipment in the prior art cannot acquire the dot information of the printed image.
Description
Technical Field
The invention belongs to the technical field of anti-counterfeiting of printed images, and relates to a halftone information hiding and identifying method based on a mobile terminal.
Background
With the development of social economy, the living standard of people is greatly improved. Pirates began to gain illegal benefits by copying various goods. The halftone information hiding technology is rapidly developed and applied due to the advantages of low cost, simplicity in operation and the like, and information hiding and extraction are achieved through changing the properties of the halftone dots. But is limited by the inability of the mobile terminal device to collect dot information of the printed image, which hinders the development of the technology at the mobile terminal.
Disclosure of Invention
The invention aims to provide a halftone information hiding and identifying method based on a mobile terminal, which solves the problem that the mobile terminal equipment in the prior art cannot collect the dot information of a printing image.
The technical scheme adopted by the invention is that the halftone information hiding and identifying method based on the mobile terminal is implemented according to the following steps:
Step 1, making a printing carrier image, and processing anti-counterfeiting images and text information in different formats to form anti-counterfeiting information in a standard gray mode;
Step 2, scrambling the anti-counterfeiting information processed in the step 1 according to a scrambling algorithm to generate printing quantum information, and completing modulation of the printing quantum information;
Step 3, a halftone hidden image is manufactured by utilizing halftone image anti-counterfeiting technology based on a halftone grating, then the manufactured halftone hidden image is subjected to secondary Haar wavelet decomposition, and the printing quantum information generated in the step 2 is embedded into the LL 2 part of the secondary Haar wavelet decomposition to obtain a hidden image containing the printing quantum information;
Step 4, comparing the structural similarity of the hidden image containing the printing quantum information manufactured in the step 3 with the halftone hidden image manufactured by the halftone image anti-counterfeiting technology based on the halftone grating, and judging the visual effect of the hidden image and the halftone hidden image;
step 5, using a digital printer and a high-precision scanner to perform analog printing and scanning on the printing carrier image manufactured in the step 1, namely the half-tone unencrypted image and the hidden image containing printing quantum information manufactured in the step 3, namely the half-tone encrypted image, so as to respectively obtain an unencrypted and encrypted scanning image containing printing quantum information;
step 6, carrying out geometric correction and gray histogram equalization correction on the unencrypted and encrypted scanned image containing printing quantum information obtained in the step 5;
and 7, comparing the gray level co-occurrence matrix characteristic values of the encrypted scanned image corrected in the step 6 with the gray level co-occurrence matrix characteristic values of the unencrypted scanned image, and identifying whether the image contains hidden information according to the difference of the characteristic values of the encrypted scanned image and the unencrypted scanned image.
The present invention is also characterized in that,
The step 2 is specifically as follows:
Constructing two logistic systems in MATLAB software, setting system parameters as u 1, u 2,u1 and u 2 as any positive integer, respectively setting system initial values as x 1, x 2,x1 and x 2 as [0,1], reading the anti-counterfeiting information processed in the step 1, calculating the sum of all pixels of the anti-counterfeiting information, performing residual operation on the sum of the pixels, dividing the remainder by 256 to obtain an auxiliary key, constructing two logistic chaotic sequences, modifying the logistic chaotic sequences into a replacement value encryption sequence y 1、y2 by using the auxiliary key, sequentially replacing the pixels of the original image by using the y 1、y2 sequence, outputting the image after replacing the pixels, and finishing the modulation of the printing quantum information.
In the step 2, the anti-counterfeiting information is read in MATLAB software, the sum of all pixels of the anti-counterfeiting information is calculated, the sum of the pixels is subjected to remainder operation, and then the remainder is divided by 255 to obtain an auxiliary key, and the auxiliary key is realized by the following steps:
Reading the anti-counterfeiting information, obtaining the size of the anti-counterfeiting information, and utilizing Calculating the sum of all pixels of the anti-counterfeiting information, and calculating/>, by calculating the remainderObtaining an auxiliary key, wherein% is a remainder operation,Representing the sum of all pixels of the security information,/>The auxiliary key is represented by i, the ith pixel point is represented by X i, the pixel number of the ith pixel point is represented by X, and n is the total pixel number.
In the step2, two logistic chaotic sequences are constructed by the following modes:
The first logistic chaotic sequence is calculated by the following formula:
the second logistic chaotic sequence is calculated by the following formula:
wherein u 1、u2 is a system parameter, x 1、x2 is a system initial value, the value range is [0,1], i is the ith pixel point, The ith sub-element in the first chaotic sequence and the ith sub-element in the second chaotic sequence are respectively adopted.
The transformation of the logistic chaotic sequence into the alternative value encryption sequence y 1、y2 by using the auxiliary key is realized by the following steps:
Wherein the method comprises the steps of The ith subelement in the sequence of respectively y 1、y2, key is the key,/>The (i+1) th subelement in the first chaotic sequence and the second chaotic sequence constructed in the step (2) respectively, wherein i is the ith pixel point;
The pixels of the original image are replaced in sequence by using the y1 and y2 sequences, and the image after the replaced pixels are output is realized by the following modes:
firstly, carrying out bit logic operation on an image, judging whether each pixel value is prime or not according to the sequence from top to bottom and from left to right, and if the pixel value is prime, carrying out the following replacement calculation on the point by using a y l sequence:
Wherein, [ ] is a rounding operation,% is a remainder operation;
otherwise, the following substitution calculation is performed on the point by using the y 2 sequence:
wherein, [ ] is a rounding operation,% is a remainder operation/> I-th subelement in the sequence of y 1、y2,/>, respectivelyThe corresponding pixel values after replacement with the y l、y2 sequence, respectively.
The LL 2 part of the second-level Haar wavelet decomposition in step 3 is specifically:
the wavelet basis function is designated as Haar using dwt2 () function in MATLAB software, and then a halftone hidden image based on the halftone dot raster technique is subjected to a secondary Haar wavelet decomposition.
In the step 4, the hidden image containing the printing quantum information manufactured in the step 3 is compared with the halftone hidden image manufactured by the halftone image anti-counterfeiting technology based on the halftone grating in terms of structural similarity, and the visual effects of the hidden image and the halftone hidden image are judged specifically according to the following mode:
image structure similarity calculation formula:
Wherein, 、/>、/>、/>、/>、、/>；
Wherein x is the halftone hidden image manufactured in the step 3, y is the hidden image containing printing quantum information,Hiding image pixel mean for halftoning,/>For the hidden image pixel mean value containing printing quantity information,/>Concealing the variance of an image for halftoning,/>Variance of hidden image containing printing amount information,/>Is covariance,/>Is constant, L is the dynamic range of pixel values,/>N is the total number of pixels, i is the ith pixel,/>The pixel value is the pixel point of the ith pixel point of the two diagrams respectively;
through the calculated image structural similarity, the structural similarity ranges from [0,1], if the structural similarity is closer to 1, the visual effects of the two images are closer, and otherwise, the visual effects of the two images are not closer.
The step 6 is specifically as follows:
Respectively reading a scanning image of an unencrypted image and a hidden image containing printing quantum information in MATLAB, changing the type of the scanning image into 8 bits by utilizing a Uint8 function, geometrically correcting the scanning image by utilizing a polynomial fitting function Isqcurvefit (f, a, x and y), wherein f is a sign function handle, a is an estimated value of a pre-fitted unknown parameter, x is a known value of x, y is a known value of y corresponding to x, then taking the upper left point of a cut-out area according to a data cursor, resampling the image by utilizing a bilinear interpolation method to finish geometrical correction, and carrying out gray histogram equalization correction processing on the scanning image after the geometrical correction of the scanning image, wherein the method specifically comprises the following steps:
respectively reading a geometrically corrected scanned image and an original image of an unencrypted image and a hidden image containing printed quantum information in MATLAB to enable And respectively carrying out histogram equalization processing on the original image according to gray probability density functions of the scanned image subjected to geometric correction and the original image, wherein the histogram equalization processing is as follows:
Wherein the method comprises the steps of 、/>Different gray levels of geometrically corrected scanned image and original image, respectively,/>To solve the equilibrium transformation function, n is the total pixel number,/>The pixel value of the ith pixel point is i, and i is the ith pixel.
The step 7 is specifically as follows:
Respectively reading the encrypted scanning image and the unencrypted scanning image corrected by the step 6 in MATLAB software, respectively calculating gray level co-occurrence matrix characteristic values at intervals of a unit and b unit in the transverse and longitudinal directions according to the directions of 45 degrees, 90 degrees and 135 degrees, wherein the values of a and b are 0 and 3, and comparing the differences of the characteristic values of the two types of images so as to judge whether the images carry anti-counterfeiting information, wherein the judgment on whether the images carry the anti-counterfeiting information is specifically as follows: the entropy and the differential entropy of the encrypted image are both larger than those of the unencrypted image, and the angular second moment is smaller than that of the unencrypted image.
The invention has the beneficial effects that
Compared with halftone image anti-counterfeiting technology based on halftone gratings, the anti-counterfeiting method increases anti-counterfeiting performance of products, solves the problem that the conventional halftone hiding technology cannot be applied to a mobile terminal, and provides a thought for realizing the mobile terminal of the halftone hiding technology.
Detailed Description
The present invention will be described in detail with reference to the following embodiments.
The invention discloses a halftone information hiding and identifying method based on a mobile terminal, which is implemented according to the following steps:
Step 1, making a printing carrier image, and processing anti-counterfeiting images and text information in different formats to form anti-counterfeiting information in a standard gray mode;
Step 2, scrambling the anti-counterfeiting information processed in the step 1 according to a scrambling algorithm to generate printing quantum information, and completing modulation of the printing quantum information; the method comprises the following steps:
constructing two logistic systems in MATLAB software, setting system parameters as u 1, u 2,u1 and u 2 as any positive integer, respectively setting system initial values as x 1, x 2,x1 and x 2 as [0,1], reading the anti-counterfeiting information processed in the step 1, calculating the sum of all pixels of the anti-counterfeiting information, performing residual operation on the sum of the pixels, dividing the remainder by 255 to obtain an auxiliary key, constructing two logistic chaotic sequences, modifying the logistic chaotic sequences into a replacement value encryption sequence y 1、y2 by using the auxiliary key, sequentially replacing the pixels of the original image by using the y 1、y2 sequence, outputting the image after replacing the pixels, and finishing the modulation of the printing quantum information.
Wherein, read the anti-fake information in MATLAB software, calculate the sum of all picture elements of anti-fake information, and carry on the operation of taking the remainder to the picture element sum, then the remainder divides 255 to get the auxiliary key and realize through the following modes:
Reading the anti-counterfeiting information, obtaining the size of the anti-counterfeiting information, and utilizing Calculating the sum of all pixels of the anti-counterfeiting information, and calculating/>, by calculating the remainderObtaining an auxiliary key, wherein% is a remainder operation,Representing the sum of all pixels of the security information,/>Representing an auxiliary key, i representing an ith pixel point, X i representing the pixel number of the ith pixel point, and n being the total pixel number;
constructing two logistic chaotic sequences is achieved by:
The first logistic chaotic sequence is calculated by the following formula:
the second logistic chaotic sequence is calculated by the following formula:
wherein u 1、u2 is a system parameter, x 1、x2 is a system initial value, the value range is [0,1], i is the ith pixel point, The ith subelement in the first chaotic sequence and the ith subelement in the second chaotic sequence respectively;
The transformation of the logistic chaotic sequence into the alternative value encryption sequence y 1、y2 by using the auxiliary key is realized by the following steps:
Wherein the method comprises the steps of The ith subelement in the sequence of respectively y 1、y2, key is the key,/>The (i+1) th subelement in the first chaotic sequence and the second chaotic sequence constructed in the step (2) respectively, wherein i is the ith pixel point;
The pixels of the original image are replaced in sequence by using the y1 and y2 sequences, and the image after the replaced pixels are output is realized by the following modes:
firstly, carrying out bit logic operation on an image, judging whether each pixel value is prime or not according to the sequence from top to bottom and from left to right, and if the pixel value is prime, carrying out the following replacement calculation on the point by using a y l sequence:
Wherein, [ ] is a rounding operation,% is a remainder operation;
otherwise, the following substitution calculation is performed on the point by using the y 2 sequence:
wherein, [ ] is a rounding operation,% is a remainder operation/> I-th subelement in the sequence of y 1、y2,/>, respectivelyThe corresponding pixel values after replacement with the y l、y2 sequence, respectively;
Step 3, a halftone hidden image is manufactured by utilizing halftone image anti-counterfeiting technology based on a halftone grating, then secondary Haar wavelet decomposition is carried out on the manufactured halftone hidden image, the printing quantum information generated in the step 2 is embedded into the LL 2 part of the secondary Haar wavelet decomposition, and a hidden image containing the printing quantum information is obtained, wherein the LL 2 part of the secondary Haar wavelet decomposition specifically comprises:
Designating a wavelet basis function as Haar by using a dwt2 () function in MATLAB software, and then performing secondary Haar wavelet decomposition on a halftone hidden image based on a halftone dot type grating technology;
and 4, comparing the structural similarity of the hidden image containing the printing quantum information manufactured in the step 3 with the halftone hidden image manufactured by the halftone image anti-counterfeiting technology based on the halftone grating, and judging the visual effect of the hidden image and the halftone hidden image according to the following specific mode:
image structure similarity calculation formula:
Wherein, 、/>、/>、/>、/>、、/>；
Wherein x is the halftone hidden image manufactured in the step 3, y is the hidden image containing printing quantum information,Hiding image pixel mean for halftoning,/>For the hidden image pixel mean value containing printing quantity information,/>Concealing the variance of an image for halftoning,/>Variance of hidden image containing printing amount information,/>Is covariance,/>Is constant, L is the dynamic range of pixel values,/>N is the total number of pixels, i is the ith pixel,/>The pixel value is the pixel point of the ith pixel point of the two diagrams respectively;
Through the calculated image structural similarity, the structural similarity range is [0,1], if the structural similarity is closer to 1, the visual effects of the two images are closer to each other, otherwise, the visual effects of the two images are less close to each other;
step 5, using a digital printer and a high-precision scanner to perform analog printing and scanning on the printing carrier image manufactured in the step 1, namely the half-tone unencrypted image and the hidden image containing printing quantum information manufactured in the step 3, namely the half-tone encrypted image, so as to respectively obtain an unencrypted and encrypted scanning image containing printing quantum information;
Step 6, carrying out geometric correction and gray histogram equalization correction on the unencrypted and encrypted scanned image containing printing quantum information obtained in the step 5; the method comprises the following steps:
Respectively reading a scanning image of an unencrypted image and a hidden image containing printing quantum information in MATLAB, changing the type of the scanning image into 8 bits by utilizing a Uint8 function, geometrically correcting the scanning image by utilizing a polynomial fitting function Isqcurvefit (f, a, x and y), wherein f is a sign function handle, a is an estimated value of a pre-fitted unknown parameter, x is a known value of x, y is a known value of y corresponding to x, then taking the upper left point of a cut-out area according to a data cursor, resampling the image by utilizing a bilinear interpolation method to finish geometrical correction, and carrying out gray histogram equalization correction processing on the scanning image after the geometrical correction of the scanning image, wherein the method specifically comprises the following steps:
respectively reading a geometrically corrected scanned image and an original image of an unencrypted image and a hidden image containing printed quantum information in MATLAB to enable And respectively carrying out histogram equalization processing on the original image according to gray probability density functions of the scanned image subjected to geometric correction and the original image, wherein the histogram equalization processing is as follows:
Wherein the method comprises the steps of 、/>Different gray levels of geometrically corrected scanned image and original image, respectively,/>To solve the equilibrium transformation function, n is the total pixel number,/>The pixel value of the ith pixel point is i, and i is the ith pixel;
Step 7, comparing the gray level co-occurrence matrix eigenvalues of the encrypted scanned image corrected in the step 6 with those of the unencrypted scanned image, and identifying whether the image contains hidden information according to the difference of the eigenvalues of the encrypted scanned image and the unencrypted scanned image, wherein the method specifically comprises the following steps:
Respectively reading the encrypted scanning image and the unencrypted scanning image corrected by the step 6 in MATLAB software, respectively calculating gray level co-occurrence matrix characteristic values at intervals of a unit and b unit in the transverse and longitudinal directions according to the directions of 45 degrees, 90 degrees and 135 degrees, wherein the values of a and b are 0 and 3, and comparing the differences of the characteristic values of the two types of images so as to judge whether the images carry anti-counterfeiting information, wherein the judgment on whether the images carry the anti-counterfeiting information is specifically as follows: the entropy and the differential entropy of the encrypted image are both larger than those of the unencrypted image, and the angular second moment is smaller than that of the unencrypted image.
Examples
Photoshop and MATLAB as tools
(1) Processing the anti-counterfeiting images and text information in different formats to make the anti-counterfeiting images and text information become the standard gray-scale anti-counterfeiting information: storing images in photoshop as grayscale mode sizes；
(2) The anti-counterfeiting information is subjected to logistic chaotic scrambling to obtain two chaotic sequences, pixel values of an original image are replaced by the two chaotic sequences, and modulation of printing quantum information is finished specifically according to the following steps: two logistic systems are constructed, system parameters u 1 =4 and u 2 =4 are set, system initial values x 1 =0.2 and x 2 =0.7, anti-fake information is read in MATLAB software, the sum of all pixels of the anti-fake information is calculated, the sum of the pixels is subjected to residual operation, 255 is divided by the remainder to obtain auxiliary keys, two logistic chaotic sequences are constructed, the auxiliary keys are utilized to transform the logistic chaotic sequences into alternative value encryption sequences y 1,y2, the pixels of an original image are replaced in sequence by utilizing y 1 and y 2 sequences, the images after the pixels are replaced are output, and modulation of printing quantum information is completed.
Wherein, read the anti-fake information in MATLAB software, calculate the sum of all picture elements of anti-fake information, and carry on the operation of taking the remainder to the picture element sum, then the remainder divides 255 to get the auxiliary key and realize through the following modes:
Reading the anti-counterfeiting information, obtaining the size of the anti-counterfeiting information, and utilizing Calculating the sum of all pixels of the anti-counterfeiting information, and calculating/>, by calculating the remainderObtaining an auxiliary key, wherein% is a remainder operation,Representing the sum of all pixels of the security information,/>Representing an auxiliary key, i representing an ith pixel point, X i representing the pixel number of the ith pixel point, and n being the total pixel number;
constructing two logistic chaotic sequences is achieved by:
The first logistic chaotic sequence is calculated by the following formula:
the second logistic chaotic sequence is calculated by the following formula:
wherein u 1、u2 is a system parameter, x 1、x2 is a system initial value, the value range is [0,1], i is the ith pixel point, The ith subelement in the first chaotic sequence and the ith subelement in the second chaotic sequence respectively;
The transformation of the logistic chaotic sequence into the alternative value encryption sequence y 1、y2 by using the auxiliary key is realized by the following steps:
Wherein the method comprises the steps of The ith subelement in the sequence of respectively y 1、y2, key is the key,/>The (i+1) th subelement in the first chaotic sequence and the second chaotic sequence constructed in the step (2) respectively, wherein i is the ith pixel point;
The pixels of the original image are replaced in sequence by using the y1 and y2 sequences, and the image after the replaced pixels are output is realized by the following modes:
firstly, carrying out bit logic operation on an image, judging whether each pixel value is prime or not according to the sequence from top to bottom and from left to right, and if the pixel value is prime, carrying out the following replacement calculation on the point by using a y l sequence:
Wherein, [ ] is a rounding operation,% is a remainder operation;
otherwise, the following substitution calculation is performed on the point by using the y 2 sequence:
wherein, [ ] is a rounding operation,% is a remainder operation/> I-th subelement in the sequence of y 1、y2,/>, respectivelyThe corresponding pixel values after replacement with the y l、y2 sequence, respectively;
(3) Halftone hidden images are manufactured by halftone image anti-counterfeiting technology based on halftone gratings, such as: halftone image anti-counterfeiting technical research based on halftone dot type grating (Shaanxi university of science and technology report, authors: guo Linghua, chen Yan, liu Guodong, xing Tiedou, [ J ].2015 (35): 33-36), then performing secondary Haar wavelet decomposition on the manufactured halftone hidden image, and embedding the printing quantum information generated in the step 2 into LL 2 part of the secondary Haar wavelet decomposition to obtain a hidden image containing the printing quantum information, wherein the LL 2 part of the secondary Haar wavelet decomposition is specifically:
Designating a wavelet basis function as Haar by using a dwt2 () function in MATLAB software, and then performing secondary Haar wavelet decomposition on a halftone hidden image based on a halftone dot type grating technology;
(4) Comparing the structural similarity of the hidden image containing the printing quantum information manufactured in the step 3 with the halftone hidden image manufactured by the halftone hidden calculation technology, and judging the visual effect of the hidden image and the halftone hidden image; wherein, the hidden image containing printing quantum information manufactured in the step 3 is compared with the half-tone hidden image manufactured by the half-tone image anti-counterfeiting technology based on the dot type grating in terms of structural similarity, and the visual effects of the hidden image and the half-tone hidden image are judged specifically according to the following modes:
image structure similarity calculation formula:
Wherein, 、/>、/>、/>、/>、、/>；
Wherein x is the halftone hidden image manufactured in the step 3, y is the hidden image containing printing quantum information,Hiding image pixel mean for halftoning,/>For the hidden image pixel mean value containing printing quantity information,/>Concealing the variance of an image for halftoning,/>Variance of hidden image containing printing amount information,/>Is covariance,/>Is constant, L is the dynamic range of pixel values,/>N is the total number of pixels, i is the ith pixel,/>The pixel value is the pixel point of the ith pixel point of the two diagrams respectively;
Through the calculated image structural similarity, the structural similarity range is [0,1], if the structural similarity is closer to 1, the visual effects of the two images are closer to each other, otherwise, the visual effects of the two images are less close to each other;
in order to further verify the correctness of the method, whether the halftone hidden image manufactured by the invention can achieve the same visual effect as the traditional halftone hidden image or not is verified in MATLAB, specifically shown in table 1, and the structural similarity index SSIM is obtained.
TABLE 1
(5) And (3) performing analog printing and scanning on the printing carrier image manufactured in the step (1), namely the half-tone unencrypted image and the hidden image containing the printing quantum information manufactured in the step (3), namely the half-tone encrypted image by using a digital printer and a high-precision scanner to respectively obtain an unencrypted and encrypted scanning image containing the printing quantum information.
The printing image is simulated by using EPSONStylus pro 9910,9910 digital printer, and the Maiteya DRS 750DCS platform scanner scans the printing image, wherein the scanning resolution is respectively 1200dpi, 1400dpi, 1600dpi and 1800dpi.
(6) Performing geometric correction and gray histogram equalization correction on the unencrypted and encrypted scanned image containing printing quantum information obtained in the step 5;
Respectively reading a scanning image of an unencrypted image and a hidden image containing printing quantum information in MATLAB, changing the type of the scanning image into 8 bits by utilizing a Uint8 function, geometrically correcting the scanning image by utilizing a polynomial fitting function Isqcurvefit (f, a, x and y), wherein f is a sign function handle, a is an estimated value of a pre-fitted unknown parameter, x is a known value of x, y is a known value of y corresponding to x, then taking the upper left point of a cut-out area according to a data cursor, resampling the image by utilizing a bilinear interpolation method to finish geometrical correction, and carrying out gray histogram equalization correction processing on the scanning image after the geometrical correction of the scanning image, wherein the method specifically comprises the following steps:
respectively reading a geometrically corrected scanned image and an original image of an unencrypted image and a hidden image containing printed quantum information in MATLAB to enable And respectively carrying out histogram equalization processing on the original image according to gray probability density functions of the scanned image subjected to geometric correction and the original image, wherein the histogram equalization processing is as follows:
Wherein the method comprises the steps of 、/>Different gray levels of geometrically corrected scanned image and original image, respectively,/>To solve the equilibrium transformation function, n is the total pixel number,/>The pixel value of the ith pixel point is i, and i is the ith pixel;
(7) And (3) comparing the gray level co-occurrence matrix eigenvalues of the encrypted scanned image corrected in the step (6) with the gray level co-occurrence matrix eigenvalues of the unencrypted scanned image, and identifying whether the image contains hidden information according to the difference of the eigenvalues of the encrypted scanned image and the unencrypted scanned image.
And (3) respectively reading the encrypted scanning image and the unencrypted scanning image corrected in the step (6) in MATLAB software, respectively calculating the characteristic value of the gray level co-occurrence matrix at intervals of 1 unit in the transverse and longitudinal directions according to the 45-degree direction, and then comparing the difference of the characteristic values of the two types of images, thereby judging whether the images carry anti-counterfeiting information. In order to further check the correctness of the method, whether the image carries anti-counterfeiting information can be judged by utilizing the characteristic value of the gray level co-occurrence matrix, the image manufactured by the method is verified in MATLAB, specifically shown in table 2, and whether the image carries anti-counterfeiting information is judged: the entropy and the differential entropy of the encrypted image are both larger than those of the unencrypted image, and the angular second moment is smaller than that of the unencrypted image.
The data in table 2 represent the average difference percentage of eight characteristic values of the encrypted image and the unencrypted image in terms of angular second moment, contrast, correlation, homogeneity, entropy, differential contrast, and differential mean. The verification result shows that whether the image carries the anti-counterfeiting information can be judged by utilizing the difference of the characteristic values of the gray level co-occurrence matrix
TABLE 2
Claims (5)
1. The halftone information hiding and identifying method based on the mobile terminal is characterized by comprising the following steps:
Step 1, making a printing carrier image, and processing anti-counterfeiting images and text information in different formats to form anti-counterfeiting information in a standard gray mode;
Step 2, scrambling the anti-counterfeiting information processed in the step 1 according to a scrambling algorithm to generate printing quantum information, and completing modulation of the printing quantum information; the method comprises the following steps:
Constructing two logistic systems in MATLAB software, setting system parameters as u 1, u 2,u1 and u 2 as any positive integer, respectively setting system initial values as x 1, x 2,x1 and x 2 as [0,1], reading the anti-counterfeiting information processed in the step 1, calculating the sum of all pixels of the anti-counterfeiting information, performing residual operation on the sum of the pixels, dividing the remainder by 256 to obtain an auxiliary key, constructing two logistic chaotic sequences, modifying the logistic chaotic sequences into a replacement value encryption sequence y 1、y2 by using the auxiliary key, sequentially replacing the pixels of the original image by using the y 1、y2 sequence, outputting the image after replacing the pixels, and finishing the modulation of printing quantum information;
the anti-fake information is read in MATLAB software, the sum of all pixels of the anti-fake information is calculated, the sum of the pixels is subjected to remainder operation, and then the remainder is divided by 255 to obtain an auxiliary key, and the auxiliary key is realized by the following steps:
Reading the anti-counterfeiting information, obtaining the size of the anti-counterfeiting information, and utilizing Calculating the sum of all pixels of the anti-counterfeiting information, and calculating/>, by calculating the remainderObtaining an auxiliary key, wherein% is a remainder operation,Representing the sum of all pixels of the security information,/>Representing an auxiliary key, i representing an ith pixel point, X i representing the pixel number of the ith pixel point, and n being the total pixel number;
constructing two logistic chaotic sequences is achieved by:
The first logistic chaotic sequence is calculated by the following formula:
the second logistic chaotic sequence is calculated by the following formula:
wherein u 1、u2 is a system parameter, x 1、x2 is a system initial value, the value range is [0,1], i is the ith pixel point, The ith subelement in the first chaotic sequence and the ith subelement in the second chaotic sequence respectively;
The transformation of the logistic chaotic sequence into the alternative value encryption sequence y 1、y2 by using the auxiliary key is realized by the following steps:
Wherein the method comprises the steps of The ith subelement in the sequence of respectively y 1、y2, key is the key,/>The (i+1) th subelement in the first chaotic sequence and the second chaotic sequence constructed in the step (2) respectively, wherein i is the ith pixel point;
The pixels of the original image are replaced in sequence by using the y1 and y2 sequences, and the image after the replaced pixels are output is realized by the following modes:
firstly, carrying out bit logic operation on an image, judging whether each pixel value is prime or not according to the sequence from top to bottom and from left to right, and if the pixel value is prime, carrying out the following replacement calculation on the point by using a y l sequence:
Wherein, [ ] is a rounding operation,% is a remainder operation;
otherwise, the following substitution calculation is performed on the point by using the y 2 sequence:
wherein, [ ] is a rounding operation,% is a remainder operation/> I-th subelement in the sequence of y 1、y2,/>, respectivelyThe corresponding pixel values after replacement with the y l、y2 sequence, respectively;
Step 3, a halftone hidden image is manufactured by utilizing halftone image anti-counterfeiting technology based on a halftone grating, then the manufactured halftone hidden image is subjected to secondary Haar wavelet decomposition, and the printing quantum information generated in the step 2 is embedded into the LL 2 part of the secondary Haar wavelet decomposition to obtain a hidden image containing the printing quantum information;
Step 4, comparing the structural similarity of the hidden image containing the printing quantum information manufactured in the step 3 with the halftone hidden image manufactured by the halftone image anti-counterfeiting technology based on the halftone grating, and judging the visual effect of the hidden image and the halftone hidden image;
step 5, using a digital printer and a high-precision scanner to perform analog printing and scanning on the printing carrier image manufactured in the step 1, namely the half-tone unencrypted image and the hidden image containing printing quantum information manufactured in the step 3, namely the half-tone encrypted image, so as to respectively obtain an unencrypted and encrypted scanning image containing printing quantum information;
step 6, carrying out geometric correction and gray histogram equalization correction on the unencrypted and encrypted scanned image containing printing quantum information obtained in the step 5;
and 7, comparing the gray level co-occurrence matrix characteristic values of the encrypted scanned image corrected in the step 6 with the gray level co-occurrence matrix characteristic values of the unencrypted scanned image, and identifying whether the image contains hidden information according to the difference of the characteristic values of the encrypted scanned image and the unencrypted scanned image.
2. The mobile-end-based halftone information hiding and identifying method according to claim 1, wherein the LL 2 portion of the two-level Haar wavelet decomposition in the step 3 is specifically:
the wavelet basis function is designated as Haar using dwt2 () function in MATLAB software, and then a halftone hidden image based on the halftone dot raster technique is subjected to a secondary Haar wavelet decomposition.
3. The method for hiding and identifying halftone information based on mobile terminal according to claim 1, wherein in step 4, the hidden image containing the printing quantum information manufactured in step 3 is compared with the halftone hidden image manufactured by halftone image anti-counterfeiting technology based on halftone grating in terms of structural similarity, and the visual effects of the hidden image and the halftone hidden image are determined specifically according to the following modes:
image structure similarity calculation formula:
Wherein, 、/>、/>、/>、、/>、/>；
Wherein x is the halftone hidden image manufactured in the step 3, y is the hidden image containing printing quantum information,Hiding image pixel mean for halftoning,/>For the hidden image pixel mean value containing printing quantity information,/>Concealing the variance of an image for halftoning,/>Variance of hidden image containing printing amount information,/>Is covariance,/>Is constant, L is the dynamic range of pixel values,/>N is the total number of pixels, i is the ith pixel,/>The pixel value is the pixel point of the ith pixel point of the two diagrams respectively;
through the calculated image structural similarity, the structural similarity ranges from [0,1], if the structural similarity is closer to 1, the visual effects of the two images are closer, and otherwise, the visual effects of the two images are not closer.
4. The method for hiding and identifying halftone information based on mobile terminal according to claim 1, wherein the step 6 specifically comprises:
Respectively reading a scanning image of an unencrypted image and a hidden image containing printing quantum information in MATLAB, changing the type of the scanning image into 8 bits by utilizing a Uint8 function, geometrically correcting the scanning image by utilizing a polynomial fitting function Isqcurvefit (f, a, x and y), wherein f is a sign function handle, a is an estimated value of a pre-fitted unknown parameter, x is a known value of x, y is a known value of y corresponding to x, then taking the upper left point of a cut-out area according to a data cursor, resampling the image by utilizing a bilinear interpolation method to finish geometrical correction, and carrying out gray histogram equalization correction processing on the scanning image after the geometrical correction of the scanning image, wherein the method specifically comprises the following steps:
respectively reading a geometrically corrected scanned image and an original image of an unencrypted image and a hidden image containing printed quantum information in MATLAB to enable And respectively carrying out histogram equalization processing on the original image according to gray probability density functions of the scanned image subjected to geometric correction and the original image, wherein the histogram equalization processing is as follows:
Wherein the method comprises the steps of 、/>Different gray levels of geometrically corrected scanned image and original image, respectively,/>To solve the equilibrium transformation function, n is the total pixel number,/>The pixel value of the ith pixel point is i, and i is the ith pixel.
5. The method for hiding and identifying halftone information based on mobile terminal according to claim 1, wherein the step 7 specifically comprises:
Respectively reading the encrypted scanning image and the unencrypted scanning image corrected by the step 6 in MATLAB software, respectively calculating gray level co-occurrence matrix characteristic values at intervals of a unit and b unit in the transverse and longitudinal directions according to the directions of 45 degrees, 90 degrees and 135 degrees, wherein the values of a and b are 0 and 3, and comparing the differences of the characteristic values of the two types of images so as to judge whether the images carry anti-counterfeiting information, wherein the judgment on whether the images carry the anti-counterfeiting information is specifically as follows: the entropy and the differential entropy of the encrypted image are both larger than those of the unencrypted image, and the angular second moment is smaller than that of the unencrypted image.
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