CN110570210B - Double-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficient - Google Patents

Double-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficient Download PDF

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CN110570210B
CN110570210B CN201910797852.0A CN201910797852A CN110570210B CN 110570210 B CN110570210 B CN 110570210B CN 201910797852 A CN201910797852 A CN 201910797852A CN 110570210 B CN110570210 B CN 110570210B
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dimensional code
texture
order
texture pattern
correlation coefficient
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CN110570210A (en
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谭洪舟
钟沈君
谢舜道
陈荣军
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Sun Yat Sen University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
    • G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
    • G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
    • G06K7/1404—Methods for optical code recognition
    • G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
    • G06K7/1417—2D bar codes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
    • G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
    • G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
    • G06K7/1404—Methods for optical code recognition
    • G06K7/1439—Methods for optical code recognition including a method step for retrieval of the optical code
    • G06K7/1443—Methods for optical code recognition including a method step for retrieval of the optical code locating of the code in an image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
    • G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
    • G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
    • G06K7/1404—Methods for optical code recognition
    • G06K7/146—Methods for optical code recognition the method including quality enhancement steps
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/018—Certifying business or products
    • G06Q30/0185—Product, service or business identity fraud
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G06T7/41—Analysis of texture based on statistical description of texture

Abstract

The invention provides a double-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficients, which comprises the following steps of: selecting a two-order two-dimensional code scanning version for inputting; performing texture classification on the input two-order two-dimensional code; matching the patterns with the same texture into texture pattern pairs according to the classification result; calculating an enhanced correlation coefficient by using the texture pattern pair; and comparing the enhanced correlation coefficient with an authentication threshold value to finish the anti-counterfeiting authentication of the two-order two-dimensional code. The invention provides a double-order two-dimensional code anti-counterfeiting authentication method, which classifies texture patterns in an input second-order two-dimensional code and forms two different texture pattern pairs, calculates the mean value of enhanced correlation coefficients of the double-order two-dimensional code according to the enhanced correlation coefficients, and finally judges the authenticity of the double-order two-dimensional code according to the mean value.

Description

Double-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficient
Technical Field
The invention relates to the technical field of multimedia image security anti-counterfeiting, in particular to a dual-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficients.
Background
The protection of important printed matters is always a popular research subject in the field of multimedia security, and methods such as texture two-dimensional codes based on text hash hiding, information loss in a printing and scanning process, sensitivity in a copying and scanning (P & S) process and the like are used for anti-counterfeiting of the printed matters before, but a set of solution for preventing the printed matters from being copied in a physical channel cannot be obtained; meanwhile, with the improvement of printing and scanning equipment technology, the number of anti-counterfeiting printed matters increases day by day, and the detection of important and valuable printed matters such as false invoices, diplomas, certificates and the like becomes a challenge of research nowadays.
Disclosure of Invention
The invention provides a double-order two-dimensional code anti-counterfeiting authentication method based on an enhanced correlation coefficient, aiming at overcoming the technical defect that the existing printed matter protection technology lacks a scheme for preventing a printed matter from being copied in a physical channel.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a double-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficients comprises the following steps:
s101: selecting a two-order two-dimensional code scanning version for inputting;
s102: performing texture classification on the input two-order two-dimensional code;
s103: matching the patterns with the same texture into texture pattern pairs according to the classification result;
s104: calculating an enhanced correlation coefficient by using the texture pattern pair;
s105: and comparing the enhanced correlation coefficient with an authentication threshold value to finish the anti-counterfeiting authentication of the two-order two-dimensional code.
In step S101, the specific process of generating the two-level two-dimensional code is as follows:
stage 1: sequentially replacing all dark modules in the common matrix type two-dimensional code data area by using the texture pattern set S1 to obtain a texture two-dimensional code; and (2) stage: and replacing a part of dark modules in the texture two-dimensional code data area by using the texture pattern set S2, thereby obtaining the two-order two-dimensional code.
Wherein, the stage 1 specifically comprises:
selecting related information of the two-dimensional code, including but not limited to version, error correction registration and module size, to generate a common two-dimensional code I ″ 0 (ii) a Selecting S1 texture pattern set
Figure GDA0003972128300000011
Progressive sequential scanning of common two-dimensional code I ″) 0 Dark module for coding regionsd 0 ，d 1 ，d 2 ，d 3 …; collection of patterns using S1 texture>
Figure GDA0003972128300000021
According to +>
Figure GDA0003972128300000022
Replace the common two-dimensional code I ″' one by one in the sequence of 0 All dark modules in the data area to obtain a final texture two-dimensional code I' 0 ；
The stage 2 is specifically: texture two-dimensional code I 'is selected' 0 And selecting S2 texture pattern set
Figure GDA0003972128300000023
Figure GDA0003972128300000024
The S2 texture pattern set is formed by passing the S1 texture pattern set through P once&The texture pattern set after S; line-by-line scanning texture two-dimensional code I' 0 The embedded texture pattern in the coding region is collected with the S2 texture pattern->
Figure GDA0003972128300000025
According to the following
Figure GDA0003972128300000026
The texture two-dimensional code I 'is replaced alternately in groups' 0 Obtaining the double-order two-dimension code I finally by the part of the texture patterns 0 。/>
In step S102, the texture classification specifically includes: to-be-input two-order two-dimensional code I k Is classified as an S1 texture pattern
Figure GDA0003972128300000027
Figure GDA0003972128300000028
And S2 texture pattern>
Figure GDA0003972128300000029
Figure GDA00039721283000000210
Wherein m and n are constants, and when k =1, I k Representing a scanned version of the real two-dimensional code; when k =2, I k It is indicated that the input is a scanned version of a forged two-dimensional code.
In step S103, the texture pattern pair matching process specifically includes: and classifying the S1 texture pattern set and the S2 texture pattern set, and matching the same texture pattern into two different texture pattern pairs of T1 and T2 by combining the S1 texture pattern set in the original two-order two-dimensional code.
Wherein the T1 texture pattern pair is expressed as
Figure GDA00039721283000000211
Figure GDA00039721283000000212
Wherein the texture pattern->
Figure GDA00039721283000000213
Is an input two-order two-dimensional code I k On the classified S1 grain pattern, the grain pattern>
Figure GDA00039721283000000214
Is I 0 S1 texture pattern of (1);
the T2 texture pattern pair is expressed as
Figure GDA00039721283000000215
Figure GDA00039721283000000216
Wherein the texture pattern->
Figure GDA00039721283000000217
Is an input two-order two-dimensional code I k On the classified S2 grain pattern, the grain pattern->
Figure GDA00039721283000000218
Is an input two-order two-dimensional code I k And (5) classifying the S1 texture patterns.
Wherein, in the step S104, specifically: and calculating the mean value of the enhanced correlation coefficient according to the traditional correlation coefficient of the texture pattern pair, namely the authentication enhanced correlation coefficient of the two-order two-dimensional code.
The process of calculating the enhanced correlation coefficient mean specifically comprises the following steps:
let two random vectors X = (X) 1 ，x 2 ，...，x n ) And Y = (Y) 1 ，y 2 ，...，y n ) Wherein the random vector X is an S1 texture pattern, and the random vector Y is an S2 texture pattern;
the corresponding components of X and Y form a set of pairs XY of elements comprising (X) i ，y i ) (i =1,2,.., n), the set of element pairs XY is divided into three classes, respectively:
the first type: the two element pairs are in agreement with each other,
Figure GDA0003972128300000031
i.e. any two elements (x) of the set XY i ，y i ) And (x) j ，y j ) The rows are the same;
the second type: the two element pairs are not in agreement with each other,
Figure GDA0003972128300000032
the ranks of any two elements (xi, yi) and (xj, yj) in the set XY are different;
the third type: the two element pairs are not in the certainty,
Figure GDA0003972128300000033
any two elements (x) in the set XY i ，y i ) And (x) j ，y j ) Is uncertain;
calculating the correlation coefficient of a single texture pattern, wherein the specific formula is as follows:
Figure GDA0003972128300000034
/>
wherein C represents a first type of element pair in the set XY and D represents a second type of element pair in XY; therefore, the specific formula of the mean value of the enhanced correlation coefficients obtained by all texture pattern pairs is as follows:
Figure GDA0003972128300000035
where Corr (,) represents the Kendel correlation coefficient of the texture pattern pair, k =1,2 represents the scanned version of the true two-dimensional code and the scanned version of the forged two-dimensional code, and both coefficients α and β are 0.1, R adv2S Is the average of the enhanced correlation coefficients of all pairs of texture patterns.
Wherein, the step S105 specifically includes: according to the correlation coefficient R adv2s Comparing with a comparison authentication threshold TH; if the authentication threshold value is greater than the authentication threshold value TH, the input I is judged k K =1, namely the scanned version of the real two-order two-dimensional code is obtained; otherwise, input I is determined k K =2, which is the scanned version of the forged two-level two-dimensional code; wherein: the authentication threshold TH is obtained by an experiment.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
according to the anti-counterfeiting authentication method for the double-order two-dimensional code based on the enhanced correlation coefficient, provided by the invention, the texture patterns in the input second-order two-dimensional code are classified to form two different texture pattern pairs, the mean value of the enhanced correlation coefficient of the double-order two-dimensional code is calculated according to the enhanced correlation coefficient, and finally the authenticity of the double-order two-dimensional code is judged according to the mean value.
Drawings
FIG. 1 is a schematic flow chart of a two-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficients;
FIG. 2 is a set of embedded S1 texture patterns;
FIG. 3 is a screenshot of the upper left corner of a common two-dimensional code;
FIG. 4 is a screenshot of the upper left corner of a texture two-dimensional code;
FIG. 5 is a screenshot of the upper left corner of a two-level two-dimensional code;
fig. 6 is a schematic diagram of a process in which two-dimensional codes may be copied and counterfeited.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described with reference to the drawings and the embodiments.
Example 1
As shown in fig. 1, taking a QR code as an example, a two-order two-dimensional code anti-counterfeiting authentication method based on an enhanced correlation coefficient includes the following steps:
s101: selecting a two-order two-dimensional code scanning version for inputting;
s102: performing texture classification on the input two-order two-dimensional code;
s103: matching the patterns with the same texture into texture pattern pairs according to the classification result;
s104: calculating an enhanced correlation coefficient by using the texture pattern pair;
s105: and comparing the enhanced correlation coefficient with an authentication threshold value to complete the anti-counterfeiting authentication of the two-order two-dimensional code.
More specifically, as shown in fig. 2, in step S101, the specific process of generating the two-level two-dimensional code is as follows:
stage 1: sequentially replacing all dark modules in the common matrix type two-dimensional code data area by using the texture pattern set S1 to obtain a texture two-dimensional code; and (2) stage: and replacing a part of dark modules in the texture two-dimensional code data area by using the texture pattern set S2, thereby obtaining the two-order two-dimensional code.
More specifically, as shown in fig. 3 and 4, the phase 1 specifically includes:
selecting related information of the two-dimensional code, including but not limited to version, error correction registration and module size, to generate a common two-dimensional code I ″ 0 (ii) a Selecting S1 texture pattern set
Figure GDA0003972128300000051
Progressive sequential scanning of common two-dimensional code I ″) 0 Dark module d of the coding region 0 ，d 1 ，d 2 ，d 3 …; collection of patterns using S1 texture>
Figure GDA0003972128300000052
According to>
Figure GDA0003972128300000053
Replace the common two-dimensional code I ″' one by one in the sequence of 0 All dark modules in the data area to obtain the final texture two-dimensional code I' 0 ；
As shown in fig. 5, the stage 2 specifically includes: texture two-dimensional code I 'is selected' 0 And selecting S2 texture pattern set
Figure GDA0003972128300000054
The S2 texture pattern set is formed by passing the S1 texture pattern set through P once&The texture pattern set after S; texture two-dimensional code I 'is scanned line by line' 0 The embedded texture pattern in the coding region is collected with the S2 texture pattern->
Figure GDA0003972128300000055
According to
Figure GDA0003972128300000056
The texture two-dimensional code I 'is replaced alternately in groups' 0 Obtaining the double-order two-dimensional code I finally by using partial texture patterns 0 。
In the concrete implementation process, as shown in fig. 6, there may be a process of copy-forgery-inhibited for a two-level two-dimensional code, and today, copying a printed matter by printing and scanning is one of the main means, so two cases of obtaining a real two-level two-dimensional code and obtaining a two-level two-dimensional code with copy-forgery-inhibited are explained:
acquiring a real two-order two-dimensional code: the digital format double-order two-dimension code is the original double-order two-dimension code, and the definition symbol is I 0 ；I 0 The two-level two-dimensional code is printed on a document and is called as a real two-level two-dimensional code, and the definition symbol is I P0 ；I P0 The two-dimensional code scanned into digital format is called print-scan two-order two-dimensional code, and the defined symbol is I 1 Then I 1 The scanning format is a real two-order two-dimension code.
Acquisition of a copy-forged two-order two-dimensional code: the digital format double-order two-dimension code is the original double-order two-dimension code, and the definition symbol is I 0 ；I 0 The two-level two-dimensional code is printed on a document and is called as a real two-level two-dimensional code, and the definition symbol is I P0 ；I P0 The two-dimensional code scanned into a digital format is called a print-scan dual-order two-dimensional code, and a defined symbol is I 1 ；I 1 Printing the two-dimensional code to a document to form a forged two-dimensional code, wherein the symbol is defined as I P1 Wherein is selected from I P0 To I P1 This process is a process in which there is copy-forgery; i is P1 Then the two-dimensional code which is scanned into a digital format is called as a forged two-dimensional code of a scanning format, and the defined symbol is I 2 Then I 2 The two-order two-dimensional code is a forged two-order two-dimensional code in a scanning format.
More specifically, in step S102, the texture classification specifically includes: to-be-input two-order two-dimensional code I k Is classified as an S1 texture pattern
Figure GDA0003972128300000057
Figure GDA0003972128300000058
And S2 texture pattern->
Figure GDA0003972128300000059
Figure GDA00039721283000000510
Wherein m and n are constants, and when k =1, I k Representing a scanned version of the real two-dimensional code; when k =2, I k The representation input is a scanned version of a forged two-dimensional code.
More specifically, in the step S103, the matching process of the texture pattern pair specifically includes: and classifying the S1 texture pattern set and the S2 texture pattern set, and matching the same texture pattern into two different texture pattern pairs of T1 and T2 by combining the S1 texture pattern set in the original two-order two-dimensional code.
More specifically, the T1 texture pattern pair is represented as
Figure GDA0003972128300000061
Figure GDA0003972128300000062
Wherein the texture pattern->
Figure GDA0003972128300000063
Is an input two-order two-dimensional code I k On the classified S1 grain pattern, the grain pattern->
Figure GDA0003972128300000064
Is a 1 0 S1 texture pattern of (1);
the T2 texture pattern pair is expressed as
Figure GDA0003972128300000065
Figure GDA0003972128300000066
Wherein the texture pattern->
Figure GDA0003972128300000067
Is an input two-order two-dimensional code I k On the classified S2 grain pattern, the grain pattern->
Figure GDA0003972128300000068
Is an input two-order two-dimensional code I k And (5) classifying the S1 texture patterns.
More specifically, in the step S104, specifically: and calculating the mean value of the enhanced correlation coefficient according to the traditional correlation coefficient of the texture pattern pair, namely the authentication enhanced correlation coefficient of the two-order two-dimensional code.
More specifically, the process of calculating the enhanced correlation coefficient mean specifically includes:
let two random vectors X = (X) 1 ，x 2 ，...，x n ) And Y = (Y) 1 ，y 2 ，...，y n ) Wherein the random vector X is an S1 texture pattern, and the random vector Y is an S2 texture pattern;
the corresponding components of X and Y form a set of pairs XY of elements, which include the elements (X) i Yi) (i =1,2,.. N), the set of element pairs XY is divided into three categories, respectively:
the first type is: the two element pairs are in agreement with each other,
Figure GDA0003972128300000069
i.e. any two elements (x) in the set XY i ，y i ) And (x) j ，y j ) The rows are the same;
the second type: the two element pairs are not in agreement with each other,
Figure GDA00039721283000000610
any two elements (x) in the set XY i ，y i ) And (x) j ，y j ) The rows are different;
in the third category: the two element pairs are not determined to be in the same position,
Figure GDA00039721283000000611
any two elements (x) in the set XY i ，y i ) And (x) j ，y j ) Is uncertain;
calculating the correlation coefficient of a single texture pattern, wherein the specific formula is as follows:
Figure GDA0003972128300000071
wherein C represents a first type of element pair in XY of the set, and D represents a second type of element pair in XY; therefore, the specific formula of the mean value of the enhanced correlation coefficients obtained by all texture pattern pairs is as follows:
Figure GDA0003972128300000072
wherein, C o rr (,) denotes the Kendel correlation coefficient of the texture pattern pair, k =1,2 denotes a scanned version of the real two-dimensional code and a scanned version of the forged two-dimensional code, coefficients α and β are both 0.1, adv2S is the average of the enhanced correlation coefficients of all pairs of texture patterns.
More specifically, step S105 specifically includes: according to the correlation coefficient R adv2S Comparing with a comparison authentication threshold TH; if the authentication threshold value is greater than the authentication threshold value TH, the input I is judged k K =1, which is the scanning version of the real two-order two-dimensional code; otherwise, input I is determined k K =2, namely, the scanning version of the forged two-order two-dimensional code is obtained; wherein: the authentication threshold TH is obtained by an experiment.
In the specific implementation process, the method classifies texture patterns in the input second-order two-dimensional code and forms two different texture pattern pairs, then calculates the mean value of the enhanced correlation coefficient of the double-order two-dimensional code according to the enhanced correlation coefficient, and finally judges the authenticity of the double-order two-dimensional code according to the mean value.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. This need not be, nor should it be exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

Claims (7)

1. A two-order two-dimensional code anti-counterfeiting authentication method based on enhanced correlation coefficient is characterized in that: the method comprises the following steps:
s101: selecting a two-order two-dimensional code scanning version for inputting;
s102: performing texture classification on the input two-order two-dimensional code;
s103: matching the patterns with the same texture into texture pattern pairs according to the classification result;
s104: calculating an enhanced correlation coefficient by using the texture pattern pair; the method specifically comprises the following steps:
calculating the mean value of the enhanced correlation coefficient according to the traditional correlation coefficient of the texture pattern pair, namely the authentication enhanced correlation coefficient of the two-order two-dimensional code;
the process of calculating the enhanced correlation coefficient mean specifically comprises the following steps:
let two random vectors X = (X) 1 ，x 2 ，...，x n ) And Y = (Y) 1 ，y 2 ，...，y n ) Wherein the random vector X is an S1 texture pattern, and the random vector Y is an S2 texture pattern;
the corresponding components of X and Y form a set of pairs XY of elements comprising (X) i ，y i ) (i =1,2,.., n), the set of element pairs XY is divided into three classes, respectively:
the first type: the two element pairs are in agreement with each other,
Figure FDA0003972128290000011
i.e. any two elements (x) of the set XY i ，y i ) And (x) j ，y j ) The rows of (A) are the same;
the second type: the two element pairs are not in agreement with each other,
Figure FDA0003972128290000012
any two elements (x) in the set XY i ，y i ) And (x) j ，y j ) The rows are different;
in the third category: the two element pairs are not determined to be in the same position,
Figure FDA0003972128290000013
any two elements (x) in the set XY i ，y i ) And (x) j ，y j ) Is uncertain;
calculating the correlation coefficient of a single texture pattern, wherein the specific formula is as follows:
Figure FDA0003972128290000014
wherein C represents a first type of element pair in the set XY and D represents a second type of element pair in XY; therefore, the specific formula of the mean value of the enhanced correlation coefficients obtained by all texture pattern pairs is as follows:
Figure FDA0003972128290000021
where Corr (,) represents the kendell correlation coefficient of the texture pattern pair, k =1,2 represents the scanned version of the genuine two-dimensional code and the scanned version of the counterfeit two-dimensional code, and both coefficients α and β are 0.1, r adv2S Is the mean of the enhanced correlation coefficients of all pairs of texture patterns;
s105: and comparing the enhanced correlation coefficient with an authentication threshold value to finish the anti-counterfeiting authentication of the two-order two-dimensional code.
2. The double-order two-dimensional code anti-counterfeiting authentication method based on the enhanced correlation coefficient according to claim 1, characterized in that: in the step S101, the specific process of generating the two-level two-dimensional code is as follows:
stage 1: using the texture pattern set S1 to sequentially replace all dark modules in the common matrix type two-dimensional code data area to obtain texture two-dimensional codes; and (2) stage: and replacing a part of dark modules in the texture two-dimensional code data area by using the texture pattern set S2, thereby obtaining the two-order two-dimensional code.
3. The double-order two-dimensional code anti-counterfeiting authentication method based on the enhanced correlation coefficient according to claim 2, characterized in that: the stage 1 is specifically:
selecting related information of the two-dimensional code, including but not limited to version, error correction registration and module size, to generate a common two-dimensional code I ″ 0 (ii) a Selecting S1 texture pattern set
Figure FDA0003972128290000022
Progressive sequential scanning of common two-dimensional code I ″) 0 Dark module d of the coding region 0 ，d 1 ，d 2 ，d 3 …; collection of patterns using S1 texture>
Figure FDA0003972128290000023
According to>
Figure FDA0003972128290000024
Replace the common two-dimensional code I ″' one by one in the sequence of 0 All dark modules in the data area to obtain the final texture two-dimensional code I' 0 ；
The stage 2 is specifically: texture two-dimensional code I 'is selected' 0 And selecting S2 texture pattern set
Figure FDA0003972128290000025
Figure FDA0003972128290000026
The S2 texture pattern set is formed by passing the S1 texture pattern set through P once&The texture pattern set after S; line-by-line scanning texture two-dimensional code I' 0 The embedded texture pattern in the coding region is collected with the S2 texture pattern->
Figure FDA0003972128290000027
According to
Figure FDA0003972128290000028
In sequence, the texture two-dimensional code I 'is replaced alternately in groups' 0 Obtaining the double-order two-dimensional code I finally by using partial texture patterns 0 。
4. The double-order two-dimensional code anti-counterfeiting authentication method based on the enhanced correlation coefficient according to claim 3, characterized in that: in step S102, the texture classification specifically includes: to-be-input two-order two-dimensional code I k Is classified as an S1 texture pattern
Figure FDA0003972128290000029
Figure FDA00039721282900000210
And S2 texture pattern
Figure FDA00039721282900000211
Figure FDA00039721282900000212
Wherein m and n are constants, and when k =1, I k Representing a scanned version of the real two-dimensional code; when k =2, I k The representation input is a scanned version of a forged two-dimensional code.
5. The enhanced correlation coefficient-based dual-order two-dimensional code anti-counterfeiting authentication method according to claim 4, characterized in that: in step S103, the texture pattern pair matching process specifically includes: and classifying the S1 texture pattern set and the S2 texture pattern set, and matching the same texture pattern into two different texture pattern pairs of T1 and T2 by combining the S1 texture pattern set in the original two-order two-dimensional code.
6. The enhanced correlation coefficient-based dual-order two-dimensional code anti-counterfeiting authentication method according to claim 5, characterized in that:the T1 texture pattern pair is expressed as
Figure FDA0003972128290000031
Figure FDA0003972128290000032
Wherein the texture pattern->
Figure FDA0003972128290000033
Is an input two-order two-dimensional code I k On the classified S1 grain pattern, the grain pattern>
Figure FDA0003972128290000034
Is I 0 S1 texture pattern of (1);
the T2 texture pattern pair is expressed as
Figure FDA0003972128290000035
Figure FDA0003972128290000036
Wherein the texture pattern->
Figure FDA0003972128290000037
Is an input two-order two-dimensional code I k On the classified S2 grain pattern, the grain pattern->
Figure FDA0003972128290000038
Is an input two-order two-dimensional code I k And (5) classifying the S1 texture patterns.
7. The double-order two-dimensional code anti-counterfeiting authentication method based on the enhanced correlation coefficient according to claim 6, characterized in that: the step S105 specifically includes: according to the correlation coefficient R adv2S Comparing with a comparison authentication threshold TH; if the authentication threshold value is greater than the authentication threshold value TH, the input I is judged k K =1, which is the scanning version of the real two-order two-dimensional code; otherwise, input I is determined k K =2, which is the scanned version of the forged two-level two-dimensional code; wherein: the authentication threshold TH is obtained by an experiment.
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