A digital printing quality detection method based on image analysis

Abstract

The present invention discloses a digital printing quality detection method based on image analysis, belonging to the technical field of quality control. Specifically, it includes: monitoring the voltage value of a preset light source and generating a fluctuation curve of the voltage value changing with time; collecting in real time the fluorescence images of the same printed matter under the irradiation of the preset light source within a detection period to generate an observed fluorescence image sequence; analyzing the observed fluorescence image sequence to obtain the quality scores of all the observed fluorescence images; extracting the voltage values at the corresponding time nodes from the voltage fluctuation image, using the voltage value as the abscissa and the quality score as the ordinate to construct a point graph; fitting the point graph to obtain a fitting function, and correcting the quality score according to the fitting function. If the corrected image quality score is greater than or equal to a preset threshold, it is determined that the printed matter is qualified; the present invention reduces misjudgment and missed judgment caused by voltage fluctuation factors, and improves the accuracy and reliability of quality detection.

Description

Technical Field

[0001] The present invention relates to the technical field of quality control, and particularly relates to a digital printing quality detection method based on image analysis. Background Art

[0002] The printing industry is one of the largest industries globally and also an important channel for a large amount of data transmission and interpretation. The social contribution of the printing industry is increasing continuously and has become an important factor in the social economy. Printing is a technology that transfers the original content such as text, pictures, photos, anti-counterfeiting, etc. to the surfaces of materials such as paper, textiles, plastics, leather, PVC, PC, etc. through processes such as plate making, ink application, and pressurization. Printing is the process of transferring an approved printing plate to a printing substrate through a printing machine and special ink. The definition of printing in international standards is: a replication process of transferring a colorant / colorant (such as ink) to a printing substrate using an analog or digital image carrier.

[0003] In the prior art, the quality of printed products is usually controlled by machine vision, that is, by comparing the image of the printed product after being irradiated by a preset light source with a template image to achieve efficient and accurate printing quality control. However, in the actual process, the voltage fluctuation of the power supply will affect the intensity and stability of the light source. The voltage fluctuation will change the brightness and color temperature of the light source. The changes in brightness and color temperature will affect the color performance of the image, and further affect the accuracy of subsequent image matching and defect detection, resulting in inconsistent acquisition effects of each actual printed product image, thus leading to errors in the actual printing quality evaluation and affecting the quality control results. Summary of the Invention

[0004] The purpose of the present invention is to provide a digital printing quality detection method based on image analysis to solve the following technical problems:

[0005] In the prior art, the quality of printed products is usually controlled by machine vision, that is, by comparing the image of the printed product after being irradiated by a preset light source with a template image to achieve efficient and accurate printing quality control. However, in the actual process, the voltage fluctuation of the power supply will affect the intensity and stability of the light source. The voltage fluctuation will change the brightness and color temperature of the light source. The changes in brightness and color temperature will affect the color performance of the image, and further affect the accuracy of subsequent image matching and defect detection, resulting in inconsistent acquisition effects of each actual printed product image, thus leading to errors in the actual printing quality evaluation and affecting the quality control results.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A digital printing quality detection method based on image analysis. S1, within a preset detection period, monitor the voltage value of a preset light source and generate a fluctuation curve of the voltage value changing with time; collect in real time the fluorescence images of the same printed matter under the irradiation of the preset light source within the detection period to generate an observed fluorescence image sequence.

[0008] S2, analyze the observed fluorescence image sequence to obtain the quality scores of all observed fluorescence images; obtain the corresponding time node of any observed fluorescence image, extract the voltage value at the corresponding time node from the voltage fluctuation image, use the voltage value as the abscissa and the quality score as the ordinate to construct a point graph; fit the point graph to obtain a fitting function, and the fitting function is used to fit the relationship between the quality score and the voltage value.

[0009] S3, obtain the quality score and voltage value of the fluorescence image corresponding to the current printed matter, correct the quality score of the fluorescence image of the printed matter according to the fitting function. If the corrected image quality score is greater than or equal to a preset threshold, it is determined that the printed matter is qualified; if the corrected image quality score is less than the preset threshold, it is determined that the printed matter is unqualified.

[0010] As a further solution of the present invention: in S2, the calculation process of the quality score is as follows:

[0011] Perform grayscale processing on the observed fluorescence image to obtain a grayscale image. Establish a rectangular coordinate system with the central pixel point of the grayscale image as the origin, generate the coordinates (x, y) of all pixel points in the grayscale image, and identify the grayscale value P(x, y) of all pixel points in the grayscale image. For the corresponding pixel points in the template image, record its grayscale value P′(x′, y′). Calculate the grayscale difference D between the pixel points at the same position in the grayscale image and the template image through the grayscale difference formula D = |Pi(x, y) - Pi'(x', y')|, accumulate the grayscale differences of all pixel points to obtain the total grayscale difference M.

[0012] Convert the fluorescence image and the template image to the HIS color space respectively to obtain the corresponding HSV color matrices. Apply the Haar transform to the HSV color matrices, and perform normalization processing on the matrix after the Haar transform to obtain the fluorescence head image color feature vector a and the template image color feature vector b; calculate the vector cosine value N of the color feature vector a and the color feature vector b.

[0013] Calculate the quality score of any fluorescence image according to the calculation formula W = b * M + d * N; where b and d are preset coefficients.

[0014] As a further solution of the present invention: in S2, if there are two or more mass fractions corresponding to any voltage value, calculate the average value of these mass fractions, and use this average value as the unique mass fraction corresponding to this voltage value, and construct a point position diagram according to the unique mass fraction.

[0015] As a further solution of the present invention: extract the abscissa of the corresponding point of the maximum mass fraction from the point position diagram, and set this abscissa as the reference voltage value.

[0016] As a further solution of the present invention: if there are two or more points with the same and maximum mass fractions, then mark these points as pending points, obtain the coordinate positions of all points in the point position diagram and calculate the Euclidean distances between all points to generate a set U of Euclidean distances, set a clustering control radius R, take any pending point as the center, calculate the point density P within the control radius R, select the pending point with the maximum point density as the corresponding abscissa, and mark this abscissa as the reference voltage value.

[0017] As a further solution of the present invention: the specific calculation process of the point density is as follows:

[0018]

[0019] P = i / (πR 2 );

[0020] where u is the sum of the Euclidean distance data values of all points, I is the Euclidean distance between any two points, and i is the number of points within the control radius R.

[0021] As a further solution of the present invention: in S2, the specific expression formula of the fitting function is:

[0022] Perform fitting on the point position diagram by the least squares method to obtain the fitting straight line equation: W = k×X + b, where k represents the slope of the fitting straight line, b represents the intercept of the fitting straight line, and k and b are constants.

[0023] As a further solution of the present invention: in S3, the specific process of correction is as follows:

[0024] Calculate the difference between the reference voltage value and the voltage value corresponding to the current printed matter, substitute this difference into the fitting function, calculate the correction fraction, and sum the fluorescence image quality fraction corresponding to the current printed matter and the correction fraction to obtain the corrected image quality fraction of this printed matter.

[0025] Advantages of the present invention:

[0026] The present invention first sets a detection period. During this period, the same printed matter is continuously detected, and a fitting function of the relationship between the power supply voltage value and the image quality score of the printed matter is constructed by monitoring the power supply voltage. It can be understood that through the fitting function, the influence on the image quality under different voltage values can be quantified, thereby providing a more accurate reference for quality control, more precisely evaluating the quality of the printed matter, and improving the accuracy of quality control. Traditional methods for quality control of printed matter often rely on fixed image matching algorithms and defect detection algorithms, and do not consider being easily affected by light source changes. As a result, when the printed quality is good but affected by light source changes, there are deviations during color calibration, which are misjudged as poor effects, leading to misjudgments or missed judgments. By introducing a voltage monitoring and quality score correction mechanism, the present invention can dynamically adjust the image quality evaluation standard, reduce misjudgments and missed judgments caused by factors such as voltage fluctuations. Through real-time monitoring and dynamic adjustment, problems in the printing process can be promptly discovered and adjusted, avoiding the generation of a large number of defective products. At the same time, since the possibility of misjudgments and missed judgments is reduced, the workload of manual re-inspection is also reduced, thus overall improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below with reference to the accompanying drawings.

[0028] Figure 1 It is a schematic flowchart of a digital printing quality detection method based on image analysis according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] Please refer to Figure 1 As shown, the present invention is a digital printing quality detection method based on image analysis, including the following steps:

[0031] S1. During a preset detection period, monitor the voltage value of a preset light source and generate a fluctuation curve of the voltage value changing with time; collect in real time the fluorescence images of the same printed matter under the illumination of the preset light source during the detection period to generate an observed fluorescence image sequence;

[0032] S2. Analyze the observed fluorescence image sequence to obtain the quality scores of all observed fluorescence images; obtain the corresponding time node of any observed fluorescence image, extract the voltage value at the corresponding time node from the voltage fluctuation image, use the voltage value as the abscissa and the quality score as the ordinate to construct a point graph; fit the point graph to obtain a fitting function, and the fitting function is used to fit the relationship between the quality score and the voltage value.

[0033] S3. Obtain the quality score and voltage value of the fluorescence image corresponding to the current printed matter, correct the fluorescence image quality score of the printed matter according to the fitting function. If the corrected image quality score is greater than or equal to the preset threshold, it is determined that the printed matter is qualified; if the corrected image quality score is less than the preset threshold, it is determined that the printed matter is unqualified.

[0034] The present invention first sets a detection period, continuously detects the same printed matter within the detection period, and constructs a fitting function of the relationship between the power supply voltage value and the quality score of the printed flat image by monitoring the power supply voltage. It can be understood that through the fitting function, the influence of different voltage values on the image quality can be quantified, so as to provide a more accurate reference for quality control, more accurately evaluate the quality of printed matter, and thus improve the accuracy of quality control. Traditional printed matter quality control methods often rely on fixed image matching algorithms and defect detection algorithms, and do not consider being easily affected by light source changes, resulting in a situation where the printed quality is good, but affected by light source changes, there are deviations during color calibration, and it is misjudged as a bad effect, leading to misjudgment or missed judgment. The present invention can dynamically adjust the image quality evaluation standard by introducing a voltage monitoring and quality score correction mechanism, reduce misjudgment and missed judgment caused by factors such as voltage fluctuation. Through real-time monitoring and dynamic adjustment, problems in the printing process can be discovered and adjusted in time, avoiding the generation of a large number of defective products. At the same time, since the possibility of misjudgment and missed judgment is reduced, the workload of manual re-inspection is also reduced, thus overall improving the production efficiency.

[0035] It should be noted that the voltage fluctuation of the light source will cause dynamic changes in the brightness and color temperature of the light. The change in color temperature will directly affect the hue of the image, and the hue difference usually leads to the change in the brightness distribution of the image, which in turn affects the calculation of the pixel brightness value. This difference will cause the pixel values at the same position to change under the illumination of light sources with different color temperatures, resulting in errors during the comparison or matching process. It can be understood that the hue is the key factor determining the color of the image, and the hue difference will directly affect the color value of each pixel, causing the pixel colors in the image to change. At the same time, the change in hue is usually accompanied by a change in saturation. Saturation reflects the concentration or purity of the color. When the saturation is high, the color appears more vivid, while when the saturation is low, the color appears darker. Therefore, the differences in hue and saturation will not only change the color performance of the pixels, but also affect the overall visual effect and pixel values of the image, thus affecting the accuracy and contrast of the image, resulting in differences in the quality scores of the same printed matter in actual situations.

[0036] In a preferred case of this embodiment, in S2, the calculation process of the quality score is as follows:

[0037] Perform grayscale processing on the observed fluorescence image to obtain a grayscale image. Establish a rectangular coordinate system with the central pixel point of the grayscale image as the origin, generate the coordinates (x, y) of all pixel points in the grayscale image, and identify the grayscale value P(x, y) of all pixel points in the grayscale image. For the corresponding pixel points in the template image, record its grayscale value P′(x′, y′). Calculate the grayscale difference D between the pixel points at the same position in the grayscale image and the template image through the grayscale difference formula D = |Pi(x, y) - Pi'(x', y')|, and accumulate the grayscale differences of all pixel points to obtain the total grayscale difference sum M;

[0038] Convert the fluorescence image and the template image to the HIS color space respectively to obtain the corresponding HSV color matrices. Apply the Haar transform to the HSV color matrices, and perform normalization processing on the matrix after the Haar transform to obtain the fluorescence head image color feature vector a and the template image color feature vector b; calculate the vector cosine value N of the color feature vector a and the color feature vector b;

[0039] Calculate the quality score of any fluorescence image according to the calculation formula W = b * M + d * N; where b and d are preset coefficients.

[0040] In another preferred case of this embodiment, in S2, it further includes that if there are two or more quality scores corresponding to any voltage value, calculate the mean value of these quality scores, and use this mean value as the unique quality score corresponding to this voltage value. Construct a point map according to the unique quality score.

[0041] In another preferred case of this embodiment, the abscissa of the corresponding point of the maximum mass fraction is extracted from the dot map, and this abscissa is set as the reference voltage value.

[0042] By using the voltage value corresponding to the maximum mass fraction as the reference voltage, it can ensure that the evaluation is carried out under the condition of the best image quality, which helps to reduce the influence of the image quality change caused by voltage fluctuation on the evaluation result, thereby improving the accuracy of the overall evaluation.

[0043] In another preferred case of this embodiment, if there are two or more points with the same mass fraction and all are the maximum values, then these points are marked as pending points. Obtain the coordinate positions of all points in the dot map and calculate the Euclidean distance between all points to generate a set U of Euclidean distances. Set the clustering control radius R. Taking any pending point as the center, calculate the point density P within the control radius R, select the abscissa corresponding to the pending point with the maximum point density, and mark this abscissa as the reference voltage value.

[0044] In another preferred case of this embodiment, the specific calculation process of the point density is as follows:

[0045]

[0046] P = i / (πR 2 ) ;

[0047] Where, u is the sum of the Euclidean distance data values of all points, I is the Euclidean distance between any two points, and i is the number of points within the control radius R.

[0048] In another preferred case of this embodiment, in the S2, the specific expression formula of the fitting function is:

[0049] By fitting the dot map by the least squares method, the fitting straight line equation is obtained: W = k×X + b, where k represents the slope of the fitting straight line, b represents the intercept of the fitting straight line, and k and b are constant values.

[0050] In another preferred case of this embodiment, in the S3, the specific process of correction is as follows:

[0051] Calculate the difference between the reference voltage value and the voltage value corresponding to the current printed matter, substitute this difference into the fitting function, calculate the correction score, and sum the fluorescence image quality score corresponding to the current printed matter and the correction score to obtain the corrected image quality score of this printed matter.

[0052] The above has described in detail an embodiment of the present invention, but the above content is only a preferred embodiment of the present invention and cannot be considered as defining the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention shall still fall within the scope covered by the patent of the present invention.

Claims

1. A digital printing quality detection method based on image analysis, characterized in that: The following steps are involved: S1, within a preset detection period, monitoring the voltage value of a preset light source and generating a fluctuation curve of the voltage value over time; collecting in real time the fluorescence image of the same printed matter under the irradiation of the preset light source within the detection period, generating an observed fluorescence image sequence; S2, analyzing the observed fluorescence image sequence to obtain the quality scores of all observed fluorescence images; obtaining the corresponding time node of any observed fluorescence image, extracting the voltage value of the corresponding time node from the voltage fluctuation image, and constructing a point map with the voltage value as the horizontal coordinate and the quality score as the vertical coordinate; Fitting the point map to obtain a fitting function, wherein the fitting function is used to fit the relationship between the mass fraction and the voltage value; S3, obtaining the quality score of the fluorescent image corresponding to the current printed product, and correcting the quality score of the fluorescent image of the printed product according to the fitting function, if the corrected image quality score is greater than or equal to a preset threshold, the printed product is judged to be qualified; if the corrected image quality score is less than the preset threshold, the printed product is judged to be unqualified; In S2, the calculation process of the mass fraction is: The observed fluorescence image is gray-processed to obtain a gray-scale image. A rectangular coordinate system is established with the central pixel of the gray-scale image as the origin to generate the coordinates (x, y) of all pixels in the gray-scale image. The gray-scale values ​​P(x, y) of all pixels in the gray-scale image are identified. For the corresponding pixels in the template image, their gray-scale values ​​P′(x′, y′) are recorded. The gray-scale difference formula is used to calculate the gray-scale value P′(x′, y′). Calculate the grayscale difference D of the pixel at the same position between the grayscale image and the template image, accumulate the grayscale differences of all pixels, and obtain the total grayscale difference M; The fluorescent image and the template image are respectively converted into the HIS color space to obtain the corresponding HSV color matrix, the Haar transform is applied to the HSV color matrix, and the matrix after the Haar transform is normalized to obtain the color feature vector a of the fluorescent head image and the color feature vector b of the template image; the vector cosine value N of the color feature vector a and the color feature vector b is calculated; The quality score of any fluorescent image is calculated according to the calculation formula W=b*M+d*N; wherein b and d are preset coefficients.

2. The digital printing quality detection method based on image analysis according to claim 1, characterized in that: In the S2, if there are two or more mass scores corresponding to any voltage value, the average of these mass scores is calculated, and the average is used as the unique mass score corresponding to the voltage value, and a point map is constructed according to the unique mass score.

3. The digital printing quality detection method based on image analysis according to claim 2, characterized in that: The horizontal coordinate of the point corresponding to the maximum mass fraction is extracted from the point map, and the horizontal coordinate is set as the reference voltage value.

4. The digital printing quality detection method based on image analysis according to claim 3 is characterized in that: If there are two or more points with the same quality score and both are maximum values, the points are calibrated as pending points, the coordinate positions of all points in the point map are obtained, and the Euclidean distances between all points are calculated to generate the Euclidean distance set U, set the clustering control radius R, and take any pending point as the center to calculate the point density P within the control radius R, select the horizontal coordinate corresponding to the pending point with the largest point density, and calibrate the horizontal coordinate as the reference voltage value.

5. The digital printing quality detection method based on image analysis according to claim 4 is characterized in that: The specific calculation process of point density is: ; Among them, u is the sum of the Euclidean distance data values ​​of all points, I is the Euclidean distance between any points, and i is the number of points within the control radius R.

6. The digital printing quality detection method based on image analysis according to claim 1, characterized in that: In S2, the specific expression formula of the fitting function is: The point map is fitted by the least square method to obtain the fitting line equation: W=k×X+b, where k represents the slope of the fitting line, b represents the intercept of the fitting line, and k and b are constants.

7. The digital printing quality detection method based on image analysis according to claim 1 is characterized in that: In S3, the specific process of correction is: The difference between the reference voltage value and the voltage value corresponding to the current print is calculated, and the difference is substituted into the fitting function to calculate the correction score. The fluorescent image quality score corresponding to the current print is summed with the correction score to obtain the corrected image quality score of the print.

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