Method and system for detecting and identifying anti-counterfeiting effect of packaging paper

Abstract

The invention discloses a packaging paper anti-counterfeiting effect detection and identification method and system, and relates to the technical field of packaging paper anti-counterfeiting printing, the packaging paper anti-counterfeiting effect detection and identification system comprises an ultraviolet irradiation module, a feature extraction module, a data optimization module and a sample inspection module, each standard sample group uses the same irradiation condition, and different standard sample groups use different irradiation conditions. The method has the beneficial effects that the dispersion degree of the key features of the standard sample under different irradiation conditions is quantitatively analyzed, the superior irradiation condition with the highest key feature data stability is screened out, the dispersion degree of the key features of the standard sample is reduced, and the reference value is representative; the key feature comparison error during the detection of the sample to be detected is reduced, and the anti-counterfeiting identification accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-counterfeiting printing of packaging paper, and in particular to a method and system for detecting and identifying the anti-counterfeiting effect of packaging paper. Background Art

[0002] In the production system of high-value commodities such as cigarettes, packaging paper printing anti-counterfeiting technology is a core link in building a product safety barrier. In the printing process, ink anti-counterfeiting, pattern anti-counterfeiting and other technologies are often used. Anti-counterfeiting inks include optical color-changing, fluorescent, thermosensitive and other inks, which achieve differentiated anti-counterfeiting functions through microstructure design or chemical response mechanism. Fluorescent ink is a functional ink that can emit bright visible light (such as red, green, blue, yellow, etc.) under ultraviolet light. Its principle is that the fluorescent pigment in the ink absorbs ultraviolet light energy and then releases it in the form of visible light, thereby presenting a fluorescent effect visible to the naked eye. Under natural light, fluorescent ink is usually colorless or light-colored, with strong concealment. Under ultraviolet light, it presents a clear and bright fluorescent pattern, which is a relatively commonly used anti-counterfeiting technology.

[0003] In the existing technology for anti-counterfeiting detection of cigarette packaging paper, the selection of ultraviolet light irradiation conditions (such as irradiation intensity and wavelength) is arbitrary, and there is a lack of systematic analysis of the detection effects under different irradiation conditions. As a result, the detection results of different batches are not comparable, making it difficult to establish a unified anti-counterfeiting detection standard. Summary of the Invention

[0004] The purpose of this section is to provide a method and system for detecting and identifying the anti-counterfeiting effect of packaging paper, which can improve the accuracy of detecting the anti-counterfeiting effect of cigarette packaging paper.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: A method for detecting and identifying the anti-counterfeiting effect of packaging paper, comprising the following steps: S100, subjecting a plurality of standard sample groups of packaging paper to ultraviolet light irradiation, wherein each standard sample group uses the same irradiation conditions, and different standard sample groups use different irradiation conditions; S200, extracting key features from the fluorescence images of the standard samples after ultraviolet light irradiation, and analyzing the degree of discreteness of all key features in each group of standard samples; S300, screening out irradiation conditions whose degree of discreteness meets preset requirements as excellent irradiation conditions, and calculating the baseline values ​​of the key features of the standard samples under the excellent irradiation conditions; S400, irradiating the sample to be tested using the excellent irradiation conditions, extracting key features and comparing them with the corresponding baseline values, and displaying the comparison data.

[0006] As a preferred embodiment of the method for detecting and identifying the anti-counterfeiting effect of packaging paper described in the present invention, the same irradiation conditions refer to the same irradiation intensity of ultraviolet light and the same wavelength of ultraviolet light, and the key features refer to the grayscale value and brightness value extracted from the fluorescent image after ultraviolet light irradiation.

[0007] As a preferred embodiment of the method for detecting and identifying the anti-counterfeiting effect of packaging paper described in the present invention, in S200, the specific steps are as follows: S201, extracting the grayscale value G and brightness value L in the fluorescent image; S202, calculating the comprehensive index R of each standard sample in turn, the calculation formula is: R = w1G + w2L, where w1 and w2 are weight coefficients, w1 + w2 = 1; S203, calculating the average value R of the comprehensive index of each group of standard samples t ; S204, calculate the standard deviation S of the comprehensive index of each group of standard samples, the calculation formula is:

[0008]

[0009] Where m represents the total number of standard samples, and m ≥ 10.

[0010] As a preferred embodiment of the method for detecting and identifying the anti-counterfeiting effect of packaging paper described in the present invention, in S300, the specific steps are as follows: S301, setting a standard deviation threshold U, and comparing the standard deviation S of the comprehensive index of each group of standard samples with the standard deviation threshold U; S302, screening out n sample groups with S less than U, and using the irradiation conditions corresponding to the n sample groups as the optimal irradiation conditions; S303, using the average value R of the comprehensive index of the sample groups corresponding to the optimal irradiation conditions t , as the benchmark value of the key feature.

[0011] As a preferred embodiment of the method for detecting and identifying the anti-counterfeiting effect of packaging paper according to the present invention, wherein: the method of irradiating the sample to be tested using the optimal irradiation conditions, extracting the key features and comparing them with the corresponding reference values, comprises sorting n sample groups in descending order of standard deviation, and the irradiation conditions corresponding to the n sample groups are A1, A2, A3...A n , use the first i irradiation conditions to irradiate the sample to be tested in sequence, extract the gray value G and brightness value L respectively, calculate the comprehensive index R and the comprehensive index R and the corresponding reference value R t The difference D1, D2...D i , the difference between the comprehensive index and the benchmark value under different irradiation conditions is displayed on a visual screen.

[0012] As a preferred solution of the packaging paper anti-counterfeiting effect detection and identification system described in the present invention, it includes: an ultraviolet light irradiation module, a feature extraction module, a data optimization module, and a sample inspection module.

[0013] As a preferred solution of the packaging paper anti-counterfeiting effect detection and identification system described in the present invention, the ultraviolet light irradiation module is used to perform ultraviolet light irradiation on multiple standard sample groups of packaging paper, each standard sample group uses the same irradiation conditions, and different standard sample groups use different irradiation conditions.

[0014] As a preferred solution of the packaging paper anti-counterfeiting effect detection and identification system described in the present invention, the feature extraction module is used to extract key features from the fluorescence image of the standard sample after ultraviolet light irradiation, analyze the discrete degree of all key features in each group of standard samples, extract the grayscale value and brightness value in the fluorescence image, calculate the comprehensive index of each standard sample in turn, calculate the average value of the comprehensive index of each group of standard samples, and calculate the standard deviation of the comprehensive index of each group of standard samples.

[0015] As a preferred solution of the packaging paper anti-counterfeiting effect detection and identification system described in the present invention, the data optimization module is used to screen out irradiation conditions whose discreteness meets the preset requirements as excellent irradiation conditions, calculate the baseline values ​​of key features of standard samples under excellent irradiation conditions, set the standard deviation threshold, compare the standard deviation of the comprehensive index of each group of standard samples with the standard deviation threshold, screen multiple sample groups that meet the preset conditions, and use the irradiation conditions corresponding to the multiple sample groups as excellent irradiation conditions. The average value of the comprehensive index of the sample groups corresponding to the excellent irradiation conditions is used as the baseline value of the key features.

[0016] As a preferred solution of the packaging paper anti-counterfeiting effect detection and identification system described in the present invention, the sample inspection module is used to illuminate the sample to be tested using excellent illumination conditions, extract key features and compare them with corresponding benchmark values, display comparison data, sort multiple sample groups in descending order according to standard deviation, and multiple sample groups correspond to multiple illumination conditions in turn. The first several illumination conditions are used to illuminate the sample to be tested in turn, and the grayscale value and brightness value are extracted respectively. The comprehensive index and the difference between the comprehensive index and the corresponding benchmark value are calculated, and the difference between the comprehensive index and the benchmark value under different illumination conditions is displayed on a visual screen.

[0017] Beneficial effects of the present invention:

[0018] 1. By quantitatively analyzing the degree of discreteness of key features of standard samples under different irradiation conditions, the optimal irradiation conditions with the highest stability of key feature data are screened out, reducing the discreteness of key features of standard samples, ensuring the representativeness of benchmark values, reducing the key feature comparison error when testing samples to be tested, and improving the accuracy of anti-counterfeiting identification.

[0019] 2. By clarifying the screening rules for conditions such as UV light intensity and wavelength, extracting the grayscale and brightness values ​​of the fluorescence image, and constructing a comprehensive index calculation model, combined with the quantitative analysis method of the comprehensive index and standard deviation, a repeatable and standardized detection process is formed, which is suitable for large-scale production scenarios.

[0020] 3. By sorting and displaying the difference between the comprehensive index and the benchmark value under different illumination conditions, users can quickly judge the degree of deviation between the tested sample and the standard characteristics through the visual screen, lowering the technical threshold for anti-counterfeiting identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without inventiveness or labor. Among them:

[0022] Figure 1 The figure is a flow chart of the method for detecting and identifying the anti-counterfeiting effect of packaging paper of the present invention. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from this description. The "embodiment" referred to here refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention.

[0025] Example 1

[0026] Reference Figure 1 This embodiment provides a method for detecting and identifying the anti-counterfeiting effect of packaging paper, which specifically includes the following steps: S100, subjecting multiple standard sample groups of packaging paper to ultraviolet light irradiation, using the same irradiation conditions for each standard sample group, and using different irradiation conditions for different standard sample groups; S200, extracting key features from the fluorescence images of the standard samples after ultraviolet light irradiation, and analyzing the degree of dispersion of all key features in each group of standard samples; S300, screening out irradiation conditions whose degree of dispersion meets preset requirements as excellent irradiation conditions, and calculating the benchmark values ​​of the key features of the standard samples under the excellent irradiation conditions; S400, irradiating the sample to be tested using the excellent irradiation conditions, extracting key features and comparing them with the corresponding benchmark values, and displaying the comparison data.

[0027] The same irradiation conditions refer to the same irradiation intensity and wavelength of the ultraviolet light, and the key features refer to the grayscale value and brightness value extracted from the fluorescence image after ultraviolet light irradiation.

[0028] Grayscale value refers to the digital quantification result used to represent the brightness and darkness of the pixels in the fluorescence image, and brightness value refers to the physical quantity used to represent the physical light intensity in the fluorescence image.

[0029] In S200, the specific steps are as follows: S201, extract the gray value G and brightness value L in the fluorescence image; S202, calculate the comprehensive index R of each standard sample in turn, the calculation formula is: R = w1G + w2L, where w1 and w2 are weight coefficients, w1 + w2 = 1; S203, calculate the average value R of the comprehensive index of each group of standard samples t ; S204, calculate the standard deviation S of the comprehensive index of each group of standard samples, the calculation formula is:

[0030]

[0031] Where m represents the total number of standard samples, and m ≥ 10.

[0032] In S300, the specific steps are as follows: S301, set the standard deviation threshold U, and compare the standard deviation S of the comprehensive index of each group of standard samples with the standard deviation threshold U; S302, filter out n sample groups with S less than U, and use the irradiation conditions corresponding to the n sample groups as the optimal irradiation conditions; S303, use the average value R of the comprehensive index corresponding to the sample group under the optimal irradiation conditions t , as the benchmark value of the key feature.

[0033] Irradiate the sample under test using optimal irradiation conditions, extract key features and compare them with corresponding benchmark values, including sorting n sample groups in descending order of standard deviation. The irradiation conditions corresponding to n sample groups are A1, A2, A3...A n , use the first i irradiation conditions to irradiate the sample to be tested in sequence, extract the gray value G and brightness value L respectively, calculate the comprehensive index R and the comprehensive index R and the corresponding reference value R t The difference D1, D2...D i , the difference between the comprehensive index and the benchmark value under different irradiation conditions is displayed on a visual screen.

[0034] Fluorescence images were collected using an industrial camera equipped with an ultraviolet filter. The camera resolution was not less than 1920 × 1080. A median filter algorithm was used to remove salt and pepper noise and reduce ambient light interference. Histogram equalization was used to enhance image contrast and highlight the characteristics of the fluorescent area.

[0035] Grayscale value G extraction method: Extract the grayscale value of each pixel from the preprocessed grayscale image (8-bit grayscale, 0-255 value range). The grayscale mean of all pixels within the ROI (region of interest) is taken as the grayscale feature value G of the sample. ROI delineation rule: With the packaging paper anti-counterfeiting mark area as the center, automatically identify the edge contour and expand it by 10% as the extraction range.

[0036] Method for extracting the brightness value L: convert the color fluorescence image from RGB color space to HSV color space, extract the V component (brightness channel), perform Gaussian blur smoothing on the V component image, and take the brightness mean of all pixels in the ROI as the brightness eigenvalue L.

[0037] In S100, the UV wavelength is 200-400nm (such as 254nm, 365nm), and the irradiation intensity range is 5-50mW / cm 2 Different groups of standard samples are separated by 50nm wavelength and 10mW / cm 2 Set the gradient conditions to ensure that the excitation bands of common anti-counterfeiting inks are covered.

[0038] The values ​​of weight coefficients w1 and w2 can be adjusted according to the characteristics of anti-counterfeiting ink. For example, for ink sensitive to fluorescence intensity, w1=0.4 and w2=0.6 can be set to highlight the influence of brightness value. For ink sensitive to pattern clarity, w1=0.6 and w2=0.4 can be set.

[0039] In S301 , the value of U may refer to industry standards or historical test data, for example, taking 1 / 2 of the average value of the standard deviations of all sample groups, or setting it according to the anti-counterfeiting level requirements of the packaging paper.

[0040] When m ≥ 10, the statistical validity of the standard deviation calculation can be ensured, and increasing the sample size can improve the reliability of the dispersion assessment.

[0041] In S400, the visualization screen can use a dynamic bar graph or heat map, with the horizontal axis being the irradiation condition number and the vertical axis being the difference. The absolute value of the difference is marked with different colors to intuitively display the degree of anti-counterfeiting deviation of the sample to be tested.

[0042] Example 2

[0043] This embodiment provides a packaging paper anti-counterfeiting effect detection and identification system, which specifically includes an ultraviolet light irradiation module, a feature extraction module, a data optimization module, and a sample inspection module.

[0044] The ultraviolet irradiation module is used to perform ultraviolet irradiation on multiple standard sample groups of packaging paper. Each standard sample group uses the same irradiation conditions, and different standard sample groups use different irradiation conditions.

[0045] The feature extraction module is used to extract key features from the fluorescence images of standard samples after ultraviolet light irradiation, analyze the discrete degree of all key features in each group of standard samples, extract the grayscale value and brightness value in the fluorescence image, calculate the comprehensive index of each standard sample in turn, calculate the average value of the comprehensive index of each group of standard samples, and calculate the standard deviation of the comprehensive index of each group of standard samples.

[0046] The data optimization module is used to screen out irradiation conditions whose discreteness meets the preset requirements as excellent irradiation conditions, calculate the baseline values ​​of key characteristics of standard samples under excellent irradiation conditions, set the standard deviation threshold, compare the standard deviation of the comprehensive index of each group of standard samples with the standard deviation threshold, screen multiple sample groups that meet the preset conditions, and use the irradiation conditions corresponding to the multiple sample groups as excellent irradiation conditions. The average value of the comprehensive index of the sample groups corresponding to the excellent irradiation conditions is used as the baseline value of the key characteristics.

[0047] The sample inspection module is used to irradiate the sample to be tested using optimal irradiation conditions, extract key features and compare them with corresponding benchmark values, display the comparison data, sort multiple sample groups in descending order according to standard deviation, and multiple sample groups correspond to multiple irradiation conditions in turn. The first several irradiation conditions are used to irradiate the sample to be tested in turn, and the grayscale value and brightness value are extracted respectively. The comprehensive index and the difference between the comprehensive index and the corresponding benchmark value are calculated, and the difference between the comprehensive index and the benchmark value under different irradiation conditions is displayed on a visual screen.

[0048] Importantly, although only a few embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible without departing substantially from the subject matter described in this application, such as the size, structure, shape and proportion of the various elements, as well as temperature, pressure, mounting arrangements, use of materials, color, orientation changes, etc.; for example, an element shown as integrally formed may be composed of multiple parts or elements, and the position of the elements may be inverted or otherwise changed; therefore, all such modifications should be included within the scope of the present invention, and other substitutions, modifications, changes and omissions may be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present invention.

Claims

1. A method for detecting and identifying the anti-counterfeiting effect of packaging paper, characterized in that: The following steps are involved: S100, irradiating multiple standard sample groups of wrapping paper with ultraviolet light, using the same irradiation conditions for each standard sample group and different irradiation conditions for different standard sample groups; S200, extracting key features from the fluorescence images of the standard samples after ultraviolet light irradiation, and analyzing the degree of dispersion of all key features in each group of standard samples; S300, screening out irradiation conditions whose discreteness meets preset requirements as excellent irradiation conditions, and calculating the reference values ​​of key characteristics of the standard sample under the excellent irradiation conditions; S400: Irradiate the sample under test using optimal irradiation conditions, extract key features, compare them with corresponding benchmark values, and display the comparison data.

2. The method for detecting and identifying the anti-counterfeiting effect of packaging paper according to claim 1, wherein: The same irradiation conditions refer to the same irradiation intensity of the ultraviolet light and the same wavelength of the ultraviolet light, and the key features refer to the grayscale value and brightness value extracted from the fluorescence image after ultraviolet light irradiation.

3. The method for detecting and identifying the anti-counterfeiting effect of packaging paper according to claim 1, wherein: In S200, the specific steps are as follows: S201, extracting the gray value G and brightness value L in the fluorescence image; S202, calculating the comprehensive index R of each standard sample in turn, using the following formula: R = w1G + w2L, where w1 and w2 are weight coefficients, w1 + w2 = 1; S203, calculate the average value R of the comprehensive index of each group of standard samples t ; S204. Calculate the standard deviation S of the comprehensive index of each group of standard samples. The calculation formula is: Where m represents the total number of standard samples, and m ≥ 10.

4. The method for detecting and identifying the anti-counterfeiting effect of packaging paper according to claim 2, wherein: In S300, the specific steps are as follows: S301, setting a standard deviation threshold U, and comparing the standard deviation S of the comprehensive index of each group of standard samples with the standard deviation threshold U; S302, screening out n sample groups whose S is less than U, and using the irradiation conditions corresponding to the n sample groups as the optimal irradiation conditions; S303, using the average value R of the comprehensive index of the sample group corresponding to the optimal irradiation condition t , as the benchmark value of the key feature.

5. The method for detecting and identifying the anti-counterfeiting effect of packaging paper according to claim 3, characterized in that: The method uses the optimal irradiation conditions to irradiate the sample to be tested, extracts key features and compares them with corresponding benchmark values, including sorting n sample groups in descending order of standard deviation, and the irradiation conditions corresponding to the n sample groups are A1, A2, A3...A n , use the first i irradiation conditions to irradiate the sample to be tested in sequence, extract the gray value G and brightness value L respectively, calculate the comprehensive index R and the comprehensive index R and the corresponding reference value R t The difference D1, D2...D i , the difference between the comprehensive index and the benchmark value under different irradiation conditions is displayed on a visual screen.

6. A packaging paper anti-counterfeiting effect detection and identification system, using the packaging paper anti-counterfeiting effect detection and identification method according to claim 1, characterized in that: It includes ultraviolet light irradiation module, feature extraction module, data optimization module and sample inspection module.

7. The packaging paper anti-counterfeiting effect detection and identification system according to claim 6, characterized in that: The ultraviolet irradiation module is used to perform ultraviolet irradiation on multiple standard sample groups of packaging paper. Each standard sample group uses the same irradiation conditions, and different standard sample groups use different irradiation conditions.

8. The packaging paper anti-counterfeiting effect detection and identification system according to claim 6, characterized in that: The feature extraction module is used to extract key features from the fluorescence images of the standard samples after ultraviolet light irradiation, analyze the discrete degree of all key features in each group of standard samples, extract the grayscale value and brightness value in the fluorescence image, calculate the comprehensive index of each standard sample in turn, calculate the average value of the comprehensive index of each group of standard samples, and calculate the standard deviation of the comprehensive index of each group of standard samples.

9. The packaging paper anti-counterfeiting effect detection and identification system according to claim 6, characterized in that: The data optimization module is used to screen out irradiation conditions whose degree of dispersion meets preset requirements as excellent irradiation conditions, calculate the baseline values ​​of key features of standard samples under excellent irradiation conditions, set standard deviation thresholds, compare the standard deviation of the comprehensive index of each group of standard samples with the standard deviation thresholds, screen multiple sample groups that meet the preset conditions, and use the irradiation conditions corresponding to the multiple sample groups as excellent irradiation conditions. The average value of the comprehensive index of the sample groups corresponding to the excellent irradiation conditions is used as the baseline value of the key features.

10. The packaging paper anti-counterfeiting effect detection and identification system according to claim 6, characterized in that: The sample inspection module is used to irradiate the sample to be tested using optimal irradiation conditions, extract key features and compare them with corresponding benchmark values, display comparison data, sort multiple sample groups in descending order according to standard deviation, and multiple sample groups correspond to multiple irradiation conditions in turn. The first several irradiation conditions are used to irradiate the sample to be tested in turn, and the grayscale value and brightness value are extracted respectively. The comprehensive index and the difference between the comprehensive index and the corresponding benchmark value are calculated, and the difference between the comprehensive index and the benchmark value under different irradiation conditions is displayed on a visual screen.

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