Printing quality control method and device

Abstract

The present disclosure provides a printing quality control method and device, belonging to the field of detection parameter control, the method comprising: determining the adjustment level of the target printed product based on multiple feature data of the target printed product; adjusting the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain the target quality detection algorithm; performing quality detection on the target printed product based on the target quality detection algorithm to obtain the quality detection result of the target printed product; and performing quality control on the target printed product based on the quality detection result. The printing quality control method and device provided by the present disclosure can improve the accuracy and reliability of printing quality control.

Description

Technical Field

[0001] The present invention relates to the field of detection parameter control, and more specifically, to a printing quality control method and device. Background Art

[0002] In today's printing industry, as the market's requirements for printed product quality continue to increase, all types of printed products, such as commercial advertisements, exquisite brochures, and high-end packaging, need to meet precise and stable quality standards. The quality of printed products covers many aspects, including brightness, chroma, and hue. The good presentation of these factors directly affects the visual effect and use value of printed products.

[0003] In today's printing quality control process, since the detection parameters of the detection process are fixed and cannot be adjusted according to actual conditions, the printing quality detection is inaccurate, which in turn leads to unsatisfactory printing quality control.

[0004] Therefore, an accurate and reliable printing quality control method is urgently needed. Summary of the invention

[0005] The purpose of the present disclosure is to provide a printing quality control method and device to improve the accuracy and reliability of printing quality control.

[0006] A first aspect of the embodiments of the present disclosure provides a printing quality control method, comprising:

[0007] determining an adjustment level of the target printed product based on a plurality of characteristic data of the target printed product;

[0008] Adjusting the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain a target quality detection algorithm;

[0009] Performing quality inspection on the target printed product based on the target quality inspection algorithm to obtain a quality inspection result of the target printed product;

[0010] The target printed product is subjected to quality control based on the quality detection result.

[0011] A second aspect of the embodiments of the present disclosure provides a printing quality control device, comprising:

[0012] A level determination module, configured to determine an adjustment level of a target printed product based on a plurality of characteristic data of the target printed product;

[0013] A parameter adjustment module, used to adjust the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain a target quality detection algorithm;

[0014] A quality detection module, used to perform quality detection on the target printed product based on the target quality detection algorithm to obtain a quality detection result of the target printed product;

[0015] A quality control module is used to perform quality control on the target printed product based on the quality detection result.

[0016] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned printing quality control method when executing the computer program.

[0017] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned printing quality control method are implemented.

[0018] The beneficial effects of a printing quality control method and device provided by the embodiments of the present disclosure are:

[0019] The present disclosure determines the adjustment level based on multiple characteristic data of the target printed product, and can conduct personalized quality inspection and control for printed products of different batches, different types or different requirements according to their uniqueness. The present disclosure can obtain a target quality inspection algorithm that is more suitable for specific printed products by adjusting the inspection parameters in the standard quality inspection algorithm according to the adjustment level, thereby improving the pertinence and accuracy of quality inspection, reducing unnecessary inspection steps, thereby improving the overall inspection efficiency, and improving the accuracy and reliability of printing quality control. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A flow chart of a printing quality control method provided by an embodiment of the present disclosure;

[0022] Figure 2 A structural block diagram of a printing quality control device provided by an embodiment of the present disclosure;

[0023] Figure 3 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0025] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0026] Please refer to Figure 1 , Figure 1 A flow chart of a printing quality control method provided in one embodiment of the present disclosure, the method comprising:

[0027] S101: Determine an adjustment level of a target printed product based on a plurality of feature data of the target printed product.

[0028] In this embodiment, the target printed product refers to a specific printed product that needs to be quality inspected, such as a picture album, a poster, or a product package.

[0029] The plurality of feature data may be application features, printing features, color gamut features, etc. of the target printed product.

[0030] In this embodiment, the adjustment level of the target printed product is determined based on a plurality of feature data of the target printed product, including:

[0031] Determine weights corresponding to a plurality of feature data of a target printed product respectively;

[0032] A weighted calculation is performed on multiple feature data to obtain an adjustment level of the target printed product.

[0033] In this embodiment, different feature data can be assigned different weights for weighted calculation to obtain the adjustment level of the target printed product. The application features of the target printed product can be obtained from the printing data input by the printer before printing, or can be obtained by inputting the image of the target printed product into the first neural network model and according to the output of the first neural network model, and the first neural network model is trained with a training set consisting of a large number of printed product images and corresponding application features.

[0034] The printing characteristics of the target printed product can be obtained by detecting the paper and ink of the target printed product, and the color gamut characteristics of the target printed product can be obtained by image recognition.

[0035] For example, set the weight corresponding to the application feature to , the weight corresponding to the printing feature is , the weight corresponding to the color gamut feature is , then score the application features, material features and color gamut features respectively to get the score of application features , scoring of material characteristics and color gamut feature scoring .

[0036] The score of application characteristics can be determined according to the application purpose and requirements of the target printed product. For example, a picture album used for high-end art exhibitions can be scored 8 points; the simple packaging of ordinary products can be scored 4 points. The scoring criteria can be determined according to specific industry standards or internal regulations of the enterprise.

[0037] The score of material characteristics can be determined by considering factors such as the quality and characteristics of the printed material and the suitability of the target printed product. For example, a print using high-quality art paper and durable ink can be scored 9 points; while a print using ordinary newsprint can be scored 3 points.

[0038] The color gamut characteristics can be evaluated by evaluating the breadth of the color range of the printed product, the color accuracy requirements, etc. For example, a poster with rich colors and extremely high color reproduction requirements can be scored 9 points; a book with only black and white can be scored 2 points.

[0039] The adjustment level can be calculated according to the first adjustment level calculation formula. The first adjustment level calculation formula is:

[0040] .

[0041] In this embodiment, determining the adjustment level of the target printed product based on a plurality of feature data of the target printed product further includes:

[0042] respectively determining weights of a plurality of sub-feature data of a plurality of feature data;

[0043] Determine scores for multiple feature data respectively;

[0044] Constructing a weight matrix based on multiple sub-feature data;

[0045] Determining feature vectors of the plurality of feature data based on the scores of the plurality of feature data;

[0046] The adjustment level is calculated based on the weight matrix and the eigenvector.

[0047] The multiple feature data may be application features, material features, and color gamut features. The application features may include multiple sub-application features, such as visual communication features, expected features, and usage environment features.

[0048] The material feature may include multiple sub-material features, for example, a paper type feature, an ink type feature, a surface treatment feature, and the like.

[0049] The color gamut feature may include multiple sub-color gamut features, for example, a color gamut width feature and a color gamut accuracy requirement feature.

[0050] The scores and weights of multiple sub-features can be determined separately to calculate the total score A of the corresponding feature. For example, the application scenario can be further subdivided into three sub-factors: visual communication feature (A1), expectation feature (A2) and usage environment feature (A3).

[0051] For visual communication characteristics, if the printed material requires strong visual impact and color expression (such as fashion advertising posters), 8 points will be given; if it only needs to clearly convey information, 4 points will be given.

[0052] In terms of expected characteristics, if there are extremely high requirements for color accuracy and printing quality (such as art connoisseurs for art albums), 9 points can be given; for general consumer product packaging, the audience has relatively loose requirements for color, so 5 points can be given.

[0053] In terms of usage environment characteristics, if the printed material is often displayed under strong light or special lighting conditions (such as outdoor billboards) and has high requirements for color stability and brightness, it will be rated 8 points; for printed materials used in ordinary indoor environments (such as books), it will be rated 5 points.

[0054] The above-mentioned visual communication features, expected features and usage environment features are assigned corresponding weights, which can be determined based on actual experience. For example, the weights corresponding to the visual communication features, expected features and usage environment features are 0.4, 0.4 and 0.2 respectively, and the application scenario comprehensive score A=A1×0.4+A2×0.4+A3×0.2.

[0055] Similarly, the total score B of the material feature and the total score C of the color gamut feature can be calculated by determining the scores and weights of their sub-features. The weights of the sub-features of the application feature, the sub-features of the material feature, and the sub-features of the color gamut feature are constructed into a weight matrix. For example, the weights of the visual communication feature, the expected feature, and the use environment feature are 0.4, 0.4, and 0.2, respectively; the weights of the paper type feature, the ink type feature, and the surface treatment feature are 0.3, 0.4, and 0.3, respectively; the weights of the color gamut width feature and the color gamut accuracy requirement feature are 0.5 and 0.5, respectively. The weight matrix can be .

[0056] Based on the total integral of the application features, the total integral of the material features and the total integral of the color gamut features calculated above, a feature vector is constructed. ,For example, , the adjustment level can be calculated using the second adjustment level formula, which can be: ,in for The transposed vector of .

[0057] In this embodiment, determining the adjustment level of the target printed product based on a plurality of feature data of the target printed product further includes:

[0058] In response to the application feature satisfying a first condition, adjusting the level to a first level;

[0059] In response to the color gamut feature satisfying a second condition, adjusting the level to a second level;

[0060] In response to the material characteristic satisfying a third condition, the level is adjusted to a third level.

[0061] For example, the first condition is that the target printed product is used in the outside world, in which case the adjustment level can be 1; the second condition can be that the number of colors of the target printed product is greater than the first number, in which case the adjustment level can be 2; the third condition can be that the material of the target printed product is newsprint, in which case the adjustment level can be 3.

[0062] S102: adjusting detection parameters in the standard quality detection algorithm based on the adjustment level to obtain a target quality detection algorithm.

[0063] In this embodiment, the standard quality detection algorithm may be the CIE94 algorithm, and the detection parameters may be the three correction coefficients in CIE94, which are: The number of adjustment coefficients can be determined by the calculated adjustment level. The higher the adjustment level, the more adjustments are required.

[0064] Or a pre-set correspondence table between an adjustment level and the number of parameters that need to be adjusted, for example, when the adjustment level is 1, the corresponding number of parameters that need to be adjusted is 1, when the adjustment level is 2, the corresponding number of parameters that need to be adjusted is 2, and when the adjustment level is 3, the corresponding number of parameters that need to be adjusted is 3.

[0065] It should be noted that the number of adjustment parameters corresponding to the adjustment level calculated by different calculation formulas for the adjustment level is different. For example, the adjustment level calculated by the above weighted calculation is 1, and the adjustment level determined by the above conditions is also 1. However, the adjustment level calculated by the weighted calculation is 1, and the corresponding number of parameter adjustments may be 2, while the adjustment level obtained by conditional determination is 1, and the corresponding number of parameter adjustments may be 1. That is, different calculation methods have corresponding determination methods. The number of adjustment parameters can be obtained in the form of the above corresponding table, or the number of adjustment parameters can be determined by setting the adjustment level threshold.

[0066] S103: Performing quality inspection on the target printed product based on the target quality inspection algorithm to obtain a quality inspection result of the target printed product.

[0067] In this embodiment, the formula of CIE94 is: ,in, is the difference in brightness between two colors, is the difference between the chromaticities of two colors, Is the difference between the hues of two colors. is the correction parameter, is the weight coefficient.

[0068] in, , , , , , , .

[0069] Represents the brightness of two colors, Indicates the chroma of two colors on the red-green axis, Indicates the chroma of two colors on the yellow-blue axis, Indicates the total color difference between two colors.

[0070] The CIE94 algorithm is calculated in the CIELAB color space. The CIELAB color space is designed based on the visual characteristics of the human eye. Its three coordinate axes represent brightness ( )、Red-Green Axis( ) and the yellow-blue axis ( ). The quality inspection of the target printed product can include three parts, namely brightness inspection, chroma inspection and hue inspection.

[0071] The brightness parameter part of the target quality detection algorithm is used to detect the brightness of the target print. Professional optical equipment, such as a spectrophotometer, can be used to measure the brightness values ​​of different areas of the print.

[0072] For example, for an oil painting print, the brightness is measured in multiple key color areas (such as the sky part, the character skin color part, etc.) to obtain the actual brightness value of each area. At the same time, according to the standard color model or the color standard in the original design draft, determine the standard brightness value standards corresponding to these areas. The brightness difference is calculated by the target quality detection algorithm. Under the CIE94 algorithm framework, the brightness difference is calculated based on the corrected brightness parameters. .

[0073] Similarly, the difference in chroma and hue of the target print can be calculated.

[0074] S104: Perform quality control on the target printed product based on the quality inspection result

[0075] In one embodiment of the present disclosure, quality control of a target printed product is performed based on a quality detection result, including:

[0076] Controlling the brightness quality of the target printed product based on the brightness detection result;

[0077] Control the chroma quality of the target printed product based on the chroma detection result;

[0078] The color tone quality of the target printed product is controlled based on the color tone detection result.

[0079] In this embodiment, if the brightness detection result shows that some areas of the target printed product are not bright enough, that is, When the brightness difference exceeds the preset value, for offset printing, when the brightness value is lower than the standard brightness, the printing pressure can be appropriately increased to transfer the ink to the paper better, thereby improving the brightness of the printed product. This is because increasing the printing pressure can make the ink layer thicker and reflect more light, thereby increasing the brightness. At the same time, you can also consider adjusting the ink formula and using ink with higher glossiness to enhance the light reflection effect.

[0080] If the color saturation test finds that the color saturation of the printed product is lower than the standard requirement, When the color difference exceeds the preset value, the color ink supply can be increased when the color is insufficient. At the same time, the quality of the ink can be checked to ensure that the color of the ink itself meets the standard. If the ink deteriorates during storage or use, the color may decrease, and it is necessary to replace the qualified ink.

[0081] If the color tone detection result indicates that the color tone of the printed product is deviated, When the chroma difference exceeds the preset value, it may be that an error occurred during plate making, which can prompt relevant personnel to check whether the plate making meets the standards.

[0082] It can be concluded from the above that the present disclosure determines the adjustment level based on multiple characteristic data of the target printed product, and can perform personalized quality inspection and control on printed products of different batches, different types or different requirements according to their uniqueness. The present disclosure can obtain a target quality inspection algorithm that is more suitable for a specific printed product by adjusting the inspection parameters in the standard quality inspection algorithm according to the adjustment level, thereby improving the pertinence and accuracy of quality inspection, reducing unnecessary inspection steps, thereby improving the overall inspection efficiency, and improving the accuracy and reliability of printing quality control.

[0083] In one embodiment of the present disclosure, before determining the adjustment level of the target printed product based on a plurality of feature data of the target printed product, the method further includes:

[0084] Acquiring a first printed product image;

[0085] Dividing the first printed matter image into regions to obtain a plurality of printed image regions;

[0086] Determining an image enhancement factor corresponding to each printed image area;

[0087] Based on the image enhancement coefficients corresponding to the respective printed image regions, the corresponding printed image regions are enhanced to obtain an image of a target printed product.

[0088] In this embodiment, the first printed product is a printed product to be detected, and the image of the target printed product is an image obtained after image enhancement is performed on the image of the first printed product.

[0089] The image of the first printed product can be distinguished according to the image features of the regions, for example:

[0090] defining an area of ​​the image characterized by text and / or lines as a first area;

[0091] An area of ​​the image characterized by being neither text nor line is defined as the second area.

[0092] In this embodiment, the image features within the area can be determined based on image recognition or a neural network model.

[0093] Alternatively, the image of the first print can be differentiated according to the noise level of the area, for example:

[0094] defining an area where the noise is greater than the first noise threshold as a third area;

[0095] A region where noise is less than or equal to the second noise threshold is defined as a fourth region.

[0096] In this embodiment, the size of the noise in the area can be identified by a neural network model. The first noise threshold and the second noise threshold are both determined according to actual conditions.

[0097] The image enhancement coefficient can be the coefficient in the Laplace operator formula According to the formula of the Laplace operator algorithm, we can get the image after image enhancement ,in is the image processed by the Laplacian operator algorithm, is the original image.

[0098] When the image features in the area are text or lines, clear and sharp edges are required, and the image enhancement factor It can be increased according to the preset step size. On the contrary, when the image features in the area are non-text and non-line, to prevent over-sharpening, the image enhancement coefficient Can be decreased by another preset step size. For example:

[0099] In response to the region being the first region, increasing the image enhancement coefficient according to a first coefficient step size;

[0100] In response to the region being the second region, the image enhancement coefficient is reduced according to a second coefficient step size.

[0101] In this embodiment, the image enhancement coefficient is a preset constant value, for example, 1. The first ordinal step and the second coefficient step can be determined based on experiments. For example, the first coefficient step is 0.5 and the second coefficient step can be 0.6. Then, when the image area is the first area, the image enhancement coefficient is 1.5, and when the image area is the second area, the image enhancement coefficient is 0.4.

[0102] For areas with lower noise in the region, the image enhancement factor It can be increased according to the preset step size. Conversely, for areas with high noise in the area, to prevent excessive amplification of noise, the image enhancement factor Can be decreased by another preset step size. For example:

[0103] In response to the region being a third region, increasing the image enhancement coefficient according to a third coefficient step size;

[0104] In response to the region being the fourth region, the image enhancement coefficient is reduced according to a fourth coefficient step size.

[0105] In this embodiment, the image enhancement coefficient is a preset constant value, for example, 1. The first ordinal step and the second coefficient step can be determined based on experiments. For example, the first coefficient step is 0.4 and the second coefficient step can be 0.5. Then, when the image area is the third area, the image enhancement coefficient is 1.4, and when the image area is the fourth area, the image enhancement coefficient is 0.5.

[0106] By dividing the first printed product into different areas and setting different image enhancement coefficients, the edge of the enhanced image can be made clearer, which is convenient for subsequent quality inspection and can also make the result of quality inspection more accurate.

[0107] It can be concluded from the above that the present disclosure achieves refined preprocessing of the printed image by dividing the first printed image into regions and setting different image enhancement coefficients for different regions, fully considering the impact of different image features and noise levels on image quality, thereby being able to more effectively improve image quality. The edges of the printed image after image enhancement processing are clearer and the details are more prominent, which helps the quality detection algorithm to more accurately identify printing quality problems and improves the accuracy and reliability of printing quality control.

[0108] In one embodiment of the present disclosure, the detection parameters in the standard quality detection algorithm are adjusted based on the adjustment level to obtain the target quality detection algorithm, including:

[0109] In response to the adjustment level being less than or equal to the first level, adjusting a first number of detection parameters;

[0110] In response to the adjustment level being greater than the first level and less than or equal to the second level, adjusting a second number of detection parameters;

[0111] In response to the adjustment level being greater than the second level and less than or equal to the third level, adjusting a third number of detection parameters;

[0112] The first quantity, the second quantity, and the third quantity are each different.

[0113] In this embodiment, the hierarchical adjustment method is to adjust the quality detection algorithm in a targeted manner according to the different complexity or quality requirements of the target printed products. By dividing the adjustment level range into different ranges, suitable detection accuracy and parameter adjustment can be provided for printed products with different quality requirements.

[0114] When the adjustment level is at a low level, it means that the quality requirements of the target printed product are relatively low or its characteristic data show that it does not have high requirements for color accuracy and other aspects. At this time, only the first number of detection parameters need to be adjusted, which is relatively small. In this case, only the most critical or most problematic parameters of the quality detection algorithm are adjusted to avoid overly complicated detection processes while meeting basic quality control.

[0115] When the adjustment level is in the middle range, the quality requirements of the target printed product are increased. This may be because the application scenario of the printed product is more important, the printing material has a greater impact on the color rendering, or the color gamut characteristics are more complex. At this time, the second number of detection parameters needs to be adjusted. This number is more than the number of parameters adjusted at the first level, which means that more factors will be considered in the quality inspection process to more finely detect the quality of the printed product.

[0116] When the adjustment level is high, it indicates that the target printed product has very high quality requirements, which may be used for high-end art printing, high-precision brand image display, etc. At this time, the third number of detection parameters needs to be adjusted. This number is the largest among the three levels, and multiple parameters in the quality detection algorithm will be fully adjusted to ensure the most stringent detection of printed product quality.

[0117] For example, for the printing of high-end art albums, the accuracy of brightness, chroma and tone needs to be fully considered. Adjust to 1.5, Adjusted to 1.4, Adjust to 1.3. Because in high-end art printing, every attribute of color is crucial, and any slight difference in brightness, chroma or hue may affect the restoration and appreciation value of the artwork. By adjusting these three detection parameters, the target quality detection algorithm can more accurately detect the color difference between the print and the original artwork, thus ensuring that the printing quality reaches the highest standards.

[0118] In this embodiment, the first level, the second level and the third level are all determined through experiments. It should be noted that different adjustment level calculation methods correspond to different first levels, second levels and third levels.

[0119] From the above, it can be concluded that the present disclosure can accurately match the quality inspection requirements of different printed products by corresponding the adjustment level of the target printed product with different numbers of detection parameter adjustments, thereby ensuring the flexibility and adaptability of the quality inspection algorithm, so that both daily printed products with low quality requirements and artworks with high quality requirements can be properly and effectively inspected. In this embodiment, when the adjustment level is low, only a small number of key parameters need to be adjusted, which not only meets the basic quality control requirements, but also avoids unnecessary complex inspection processes, thereby improving inspection efficiency and reducing costs. When the adjustment level is high, this embodiment can more comprehensively evaluate the quality of the printed product by adjusting more inspection parameters, which helps to discover potential subtle quality defects and improves the accuracy and reliability of inspection.

[0120] The detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter;

[0121] Multiple feature data, including: application features, material features and color gamut features;

[0122] Adjusting a first number of detection parameters includes:

[0123] In response to the application characteristic satisfying the first application condition, increasing the brightness parameter according to the first brightness step;

[0124] In response to the color gamut feature satisfying the first color gamut condition, increasing the brightness parameter according to the second brightness step;

[0125] In response to the color gamut feature satisfying the second color gamut condition, the target printed product is divided into a first saturation region and a second saturation region according to a color standard; and a brightness parameter when detecting the first saturation region is increased according to a third brightness step.

[0126] In this embodiment, the brightness parameter refers to the brightness correction coefficient in the CIE94 algorithm formula. . Application characteristics refer to the application scenarios of the target printed products.

[0127] For example, for posters used outdoors, or books and magazines used indoors, the first application condition may be that the product is used outdoors. Different lighting environments will affect the human eye's perception of color. Under bright lighting conditions, the human eye is relatively more sensitive to changes in brightness. Therefore, when the target printed product is used outdoors, the brightness parameter may be increased according to the first brightness step. The application feature may be manually set before printing.

[0128] When the color range of the target print is narrow and concentrated in a specific area, such as prints with mainly blue or red tones, or application scenarios with special requirements for a certain color attribute, the brightness parameter also needs to be adjusted. The width or narrowness of the color range can be determined by identifying the type of color. A color type threshold can be pre-set. When the number of color types is less than this value, it is determined that the color range is narrow, otherwise it is determined that the color range is wide. The first color gamut condition can be that the color range of the target print is narrow.

[0129] For example, when printing ocean-themed promotional posters, there are only three types of colors, and the pre-set color type threshold is 6. The first condition is met, and the color accuracy of the blue tone is crucial. At this time, the brightness parameters when detecting the blue area can be increased according to the second brightness step based on the color characteristics of the blue area and the sensitivity of the human eye to changes in blue tones.

[0130] When the color range of the target printed product is relatively wide, such as a children's picture book containing various bright colors, the characteristics of different color areas are quite different. In this case, the parameters need to be adjusted according to the specific color distribution and importance. Therefore, the second color gamut condition can be that the color range of the target printed product is relatively wide. At this time, the target printed product can be divided into a low saturation area (first saturation area) and a high saturation area (second saturation area) according to the color standard. For the high saturation area, the change of chroma and hue has a more significant impact on the visual effect, while for the darker or low saturation color area, the brightness difference is an important factor affecting the visual effect, so when the quality inspection of the first area is performed, the brightness parameter can be increased according to the third brightness step.

[0131] The degree of saturation can be determined by comparing whether the color belongs to a preset saturated color. If it does, it is a high-saturation area, and if it does not, it is a low-saturation area.

[0132] In this embodiment, the first brightness step size, the second brightness step size, and the third brightness step size are all determined based on experiments.

[0133] It can be concluded from the above that this embodiment can compensate for the difference in color perception under different lighting environments by adjusting the brightness parameter according to the application characteristics, thereby improving the color accuracy of the printed product. This embodiment can enhance the visual effect of the darker or low-saturation color area by dividing the target printed product into low-saturation areas and high-saturation areas according to the color standard, and adding the brightness parameter to the low-saturation area, which is more in line with actual detection needs and improves the accuracy and reliability of quality control.

[0134] In one embodiment of the present disclosure, the detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter;

[0135] Multiple feature data, including: application features, material features and color gamut features;

[0136] Adjusting a second number of detection parameters includes:

[0137] In response to the material characteristic satisfying the first material condition, increasing the chroma parameter according to a first chroma step; and increasing the hue parameter according to a first hue step;

[0138] In response to the color gamut feature satisfying the second color gamut condition, the target print is divided into a first saturation area and a second saturation area according to a color standard; the chroma parameter when detecting the second saturation area is increased according to a second chroma step; and the hue parameter when detecting the second saturation area is increased according to a second hue step.

[0139] In this embodiment, the material characteristic refers to the characteristic of the substrate of the target printed product. The first material condition may be that the substrate of the target printed product has high glossiness. The chroma parameter is , the hue parameter is The level of glossiness can be determined by judging whether the printing material belongs to the preset list of high-gloss materials. If it does, it is a high-gloss material, otherwise, it is a low-gloss material.

[0140] When the printing material of the target printed product is glossy coated paper, the glossiness is high, and the color vividness and contrast will be more obvious. At this time, the changes in saturation and hue will stimulate the human eye more strongly. The saturation parameter can be increased according to the first saturation step; and the hue parameter can be increased according to the first hue step.

[0141] As mentioned above, when the color range of the target printed product is relatively wide, the characteristics of different color areas are quite different. The second color gamut condition can be that the color range of the target printed product is relatively wide. At this time, the target printed product can be divided into a low saturation area (first saturation area) and a high saturation area (second saturation area) according to the color standard. For the high saturation area, the change of chroma and hue has a more significant impact on the visual effect. Therefore, when the second saturation area is quality tested, the chroma parameter when testing the second saturation area can be increased according to the second chroma step; and the hue parameter when testing the second saturation area can be increased according to the second hue step.

[0142] In this embodiment, the first chroma step, the second chroma step, the first hue step, and the second hue step are all determined according to actual conditions.

[0143] From the above, it can be concluded that the present invention adjusts the chroma parameters and hue parameters according to the material characteristics, so that the test results are more in line with reality. The chroma parameters and hue parameters can be adjusted in a targeted manner according to the width of the color range and the importance of a specific color area, thereby improving the accuracy and reliability of quality detection, thereby providing accurate data for subsequent quality control, and further improving the accuracy and reliability of printing quality control.

[0144] In one embodiment of the present disclosure, the detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter;

[0145] Multiple feature data, including: application features, material features and color gamut features;

[0146] Adjust a third number of detection parameters, including:

[0147] In response to the material characteristic satisfying the second material condition, the brightness parameter is increased according to a fourth brightness step; and the chroma parameter is decreased according to a third chroma step; and the hue parameter is decreased according to a third hue step.

[0148] In this embodiment, the material characteristic refers to the printing material of the target printed product, and the second material condition may be that the printing material has low glossiness. The level of glossiness can be determined by judging whether the printing material belongs to a preset list of materials with high glossiness. If it does, it is a material with high glossiness, otherwise, it is a material with low glossiness.

[0149] For example, when the printing material is newsprint, which has strong ink absorption, a rough surface, and low glossiness, the color brightness may be more affected, and the requirements for saturation and hue are not high. Therefore, at this time, the brightness parameter can be increased according to the fourth brightness step; and the saturation parameter can be reduced according to the third saturation step; and the hue parameter can be reduced according to the third hue step.

[0150] In this embodiment, the fourth brightness step, the third chroma step, and the third hue step are all determined through experiments.

[0151] From the above, it can be concluded that the present invention takes into account the influence of the printing material on the printed color, thereby adjusting the brightness parameters, chroma parameters and hue parameters in the detection method, so that the detected color is more in line with reality, improving the accuracy and reliability of quality detection, thereby improving the accuracy and reliability of printing quality control.

[0152] In one embodiment of the present disclosure, quality detection of a target printed product is performed based on a target quality detection algorithm to obtain a quality detection result of the target printed product, including:

[0153] Performing brightness detection on the target printed product based on the target quality detection algorithm to obtain a brightness detection result of the target printed product;

[0154] Performing chroma detection on the target printed product based on the target quality detection algorithm to obtain the chroma detection result of the target printed product;

[0155] Performing color tone detection on the target printed product based on the target quality detection algorithm to obtain the color tone detection result of the target printed product;

[0156] The quality detection result of the target printed product is obtained based on the brightness detection result, the chroma detection result and the hue detection result.

[0157] In this embodiment, the brightness, chroma and hue can be detected respectively by the formula of CIE94 algorithm, and the detection result of brightness can be reflected as brightness difference The brightness difference refers to the brightness difference between the target printed product and the standard printed sample. The color saturation test result can be reflected as the color saturation difference. , the hue detection result can be reflected as the hue difference .

[0158] The final quality inspection result can be calculated according to the adjusted CIE94 algorithm formula.

[0159] It can be concluded from the above that the present disclosure can provide more accurate brightness difference, chroma difference and hue difference detection results by using the adjusted CIE94 algorithm to detect the quality of the target printed product. These precise numerical differences help to quantify the degree of color deviation and provide a reliable basis for subsequent quality control and improvement, thereby improving the accuracy and reliability of printing quality control.

[0160] A printing quality control method corresponding to the above embodiment, Figure 2 This is a structural block diagram of a printing quality control device provided by an embodiment of the present disclosure. For ease of explanation, only the parts related to the embodiment of the present disclosure are shown. Figure 2 The printing quality control device 20 includes: a grade determination module 21, a parameter adjustment module 22, a quality detection module 23 and a quality control module 24.

[0161] The level determination module 21 is used to determine the adjustment level of the target printed product based on a plurality of characteristic data of the target printed product;

[0162] A parameter adjustment module 22, used to adjust the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain a target quality detection algorithm;

[0163] The quality detection module 23 is used to perform quality detection on the target printed product based on the target quality detection algorithm to obtain the quality detection result of the target printed product;

[0164] The quality control module 24 is used to perform quality control on the target printed product based on the quality detection result.

[0165] In one embodiment of the present disclosure, the level determination module 21 is specifically used to respectively determine the weights corresponding to the plurality of feature data of the target printed product;

[0166] A weighted calculation is performed on multiple feature data to obtain an adjustment level of the target printed product.

[0167] In one embodiment of the present disclosure, the parameter adjustment module 22 is specifically configured to adjust a first number of detection parameters in response to the adjustment level being less than or equal to the first level;

[0168] In response to the adjustment level being greater than the first level and less than or equal to the second level, adjusting a second number of detection parameters;

[0169] In response to the adjustment level being greater than the second level and less than or equal to the third level, adjusting a third number of detection parameters;

[0170] The first quantity, the second quantity, and the third quantity are each different.

[0171] In one embodiment of the present disclosure, the detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter;

[0172] Multiple feature data, including: application features, material features and color gamut features;

[0173] The parameter adjustment module 22 is further configured to increase the brightness parameter according to the first brightness step in response to the application characteristic satisfying the first application condition;

[0174] In response to the color gamut feature satisfying the first color gamut condition, increasing the brightness parameter according to the second brightness step;

[0175] In response to the color gamut feature satisfying the second color gamut condition, the target printed product is divided into a first saturation region and a second saturation region according to a color standard; and a brightness parameter when detecting the first saturation region is increased according to a third brightness step.

[0176] In one embodiment of the present disclosure, the detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter;

[0177] Multiple feature data, including: application features, material features and color gamut features;

[0178] The parameter adjustment module 22 is further configured to, in response to the material characteristic satisfying the first material condition, increase the chroma parameter according to the first chroma step length; and increase the hue parameter according to the first hue step length;

[0179] In response to the color gamut feature satisfying the second color gamut condition, the target print is divided into a first saturation area and a second saturation area according to a color standard; the chroma parameter when detecting the second saturation area is increased according to a second chroma step; and the hue parameter when detecting the second saturation area is increased according to a second hue step.

[0180] In one embodiment of the present disclosure, the detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter;

[0181] Multiple feature data, including: application features, material features and color gamut features;

[0182] The parameter adjustment module 22 is further configured to, in response to the material characteristic satisfying the second material condition, increase the brightness parameter according to the fourth brightness step; and, reduce the chroma parameter according to the third chroma step; and, reduce the hue parameter according to the third hue step.

[0183] In one embodiment of the present disclosure, the quality detection module 23 is specifically used to perform brightness detection on the target printed product based on the target quality detection algorithm to obtain a brightness detection result of the target printed product;

[0184] Performing chroma detection on the target printed product based on the target quality detection algorithm to obtain the chroma detection result of the target printed product;

[0185] Performing color tone detection on the target printed product based on the target quality detection algorithm to obtain the color tone detection result of the target printed product;

[0186] The quality detection result of the target printed product is obtained based on the brightness detection result, the chroma detection result and the hue detection result.

[0187] In one embodiment of the present disclosure, the quality control module 24 is specifically configured to control the brightness quality of the target printed product based on the brightness detection result;

[0188] Control the chroma quality of the target printed product based on the chroma detection result;

[0189] The color tone quality of the target printed product is controlled based on the color tone detection result.

[0190] In one embodiment of the present disclosure, a printing quality control device 20 further includes: an image enhancement module;

[0191] An image enhancement module, used for acquiring a first printed product image;

[0192] Dividing the first printed matter image into regions to obtain a plurality of printed image regions;

[0193] Determining an image enhancement factor corresponding to each printed image area;

[0194] Based on the image enhancement coefficients corresponding to the respective printed image regions, the corresponding printed image regions are enhanced to obtain an image of a target printed product.

[0195] See also Figure 3 , Figure 3 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. Figure 3 The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303 and one or more memories 304. The processors 301, input devices 302, output devices 303 and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of each module / unit in the above-mentioned device embodiments, such as Figure 2 The functions of modules 21 to 24 are shown.

[0196] It should be understood that in the embodiment of the present disclosure, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0197] The input device 302 may include a touch panel, a fingerprint collection sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.

[0198] The memory 304 may include a read-only memory and a random access memory, and provide instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0199] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of a printing quality control method provided in the embodiments of the present disclosure, and can also execute the implementation methods of the electronic device described in the embodiments of the present disclosure, which will not be repeated here.

[0200] In another embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by the processor, all or part of the processes in the above-mentioned embodiment method are implemented, and the computer program can also be completed by instructing the relevant hardware through the computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0201] The computer-readable storage medium may be an internal storage unit of the electronic device of any of the aforementioned embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0202] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0203] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the electronic devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0204] In the several embodiments provided in the present application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0205] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present disclosure.

[0206] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0207] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A printing quality control method, characterized in that: include: determining an adjustment level of the target printed product based on a plurality of characteristic data of the target printed product; Adjusting the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain a target quality detection algorithm; Performing quality inspection on the target printed product based on the target quality inspection algorithm to obtain a quality inspection result of the target printed product; The target printed product is subjected to quality control based on the quality detection result.

2. A printing quality control method as claimed in claim 1, characterized in that: The step of determining the adjustment level of the target printed product based on a plurality of feature data of the target printed product comprises: respectively determining weights corresponding to a plurality of feature data of the target printed product; A weighted calculation is performed on the plurality of feature data to obtain an adjustment level of the target printed product.

3. A printing quality control method as claimed in claim 1, characterized in that: The step of adjusting the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain the target quality detection algorithm includes: In response to the adjustment level being less than or equal to the first level, adjusting a first number of detection parameters; In response to the adjustment level being greater than the first level and less than or equal to a second level, adjusting a second number of detection parameters; In response to the adjustment level being greater than the second level and less than or equal to a third level, adjusting a third number of detection parameters; The first number, the second number, and the third number are different.

4. A printing quality control method as claimed in claim 3, characterized in that: The detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter; The plurality of feature data include: application features, material features and color gamut features; The adjusting the first number of detection parameters comprises: In response to the application characteristic satisfying a first application condition, increasing the brightness parameter according to a first brightness step; In response to the color gamut feature satisfying a first color gamut condition, increasing the brightness parameter according to a second brightness step; In response to the color gamut feature satisfying a second color gamut condition, the target printed product is divided into a first saturation region and a second saturation region according to a color standard; and the brightness parameter when detecting the first saturation region is increased according to a third brightness step.

5. A printing quality control method as claimed in claim 3, characterized in that: The detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter; The plurality of feature data include: application features, material features and color gamut features; The adjusting the second number of detection parameters comprises: In response to the material characteristic satisfying a first material condition, increasing the chroma parameter according to a first chroma step; and increasing the hue parameter according to a first hue step; In response to the color gamut feature satisfying the second color gamut condition, the target print is divided into a first saturation area and a second saturation area according to a color standard; the chroma parameter when detecting the second saturation area is increased according to a second chroma step; and the hue parameter when detecting the second saturation area is increased according to a second hue step.

6. A printing quality control method as claimed in claim 3, characterized in that: The detection parameters in the standard quality detection algorithm include: brightness parameter, chroma parameter and hue parameter; The plurality of feature data include: application features, material features and color gamut features; The adjusting the third number of detection parameters comprises: In response to the material characteristic satisfying the second material condition, the brightness parameter is increased according to a fourth brightness step; and the chroma parameter is decreased according to a third chroma step; and the hue parameter is decreased according to a third hue step.

7. A printing quality control method as claimed in claim 1, characterized in that: The step of performing quality detection on the target printed product based on the target quality detection algorithm to obtain a quality detection result of the target printed product includes: Performing brightness detection on the target printed product based on the target quality detection algorithm to obtain a brightness detection result of the target printed product; Performing chroma detection on the target printed product based on the target quality detection algorithm to obtain a chroma detection result of the target printed product; Performing tone detection on the target printed product based on the target quality detection algorithm to obtain a tone detection result of the target printed product; A quality detection result of the target printed product is obtained based on the brightness detection result, the chroma detection result and the hue detection result.

8. A printing quality control method as claimed in claim 1, characterized in that: The performing quality control on the target printed product based on the quality detection result includes: Controlling the brightness quality of the target printed product based on the brightness detection result; Controlling the chroma quality of the target printed product based on the chroma detection result; The color tone quality of the target printed product is controlled based on the color tone detection result.

9. A printing quality control device, characterized in that: include: A level determination module, configured to determine an adjustment level of a target printed product based on a plurality of characteristic data of the target printed product; A parameter adjustment module, used to adjust the detection parameters in the standard quality detection algorithm based on the adjustment level to obtain a target quality detection algorithm; A quality detection module, used to perform quality detection on the target printed product based on the target quality detection algorithm to obtain a quality detection result of the target printed product; A quality control module is used to perform quality control on the target printed product based on the quality detection result.

10. A printing quality control device as claimed in claim 9, characterized in that: The level determination module is specifically used for: respectively determining weights corresponding to application characteristics of the target printed product, material characteristics of the target printed product, and color gamut characteristics of the target printed product; The application feature, the material feature and the color gamut feature are weightedly calculated to obtain an adjustment level of the target printed product.

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