Printing color management control and monitoring system and method based on artificial intelligence

Abstract

The invention provides a printing color management control and monitoring system and method based on artificial intelligence, and relates to the technical field of printing color management, and the system comprises an image input system, a characteristic creation system, a color calibration system and an image output system. The color calibration system is used for setting a color characteristic deviation threshold value, determining a color characteristic intervention condition and adjusting color parameters; in the color calibration system, color features in a color space are obtained, and whether editing intervention is conducted on the color features or not is determined according to the relation between the actual color feature deviation and a threshold value; the method is technically characterized in that when a deviation value calculated in the actual printing process is larger than a threshold value, an RGB color space is converted into a CIE Lab color space through a colorimetric method, the amount of printing ink, printing pressure, drying conditions and other factors are adjusted to reduce color difference, color deviation analysis and correction are facilitated, and the color deviation correction efficiency is improved. And continuous color comparison and adjustment work is not needed.

Description

Technical Field

[0001] The present invention relates to the technical field of printing color management, and in particular to a printing color management control and monitoring system and method based on artificial intelligence. Background Art

[0002] In the modern printing industry, ensuring the color quality of printed products is crucial. Color management, a technology that utilizes specialized software and hardware to achieve color control and calibration, ensures consistent color across different output devices, effectively reducing fluctuations in print quality, improving production efficiency, and lowering costs. With the advancement of digitalization, color management technology has become an even more integral part of the printing industry and a key to enhancing corporate competitiveness.

[0003] Color management in the printing industry refers to the process of managing the colors of various media during the printing process to achieve color consistency across them, ensuring accurate color in the final output. This differs significantly from traditional printing. Traditional printing operates as a single unit, requiring no adjustments to color. In the printing industry, however, color is linked to the inherent properties of the object and is defined using color codes. Therefore, accurate color management of media such as paper and ink is essential to ensure the color quality of the final output.

[0004] Artificial intelligence (AI) is a crucial component of the intelligent sciences. It seeks to understand the essence of intelligence and develop new intelligent machines that can respond in ways similar to human intelligence. AI is a broad discipline encompassing robotics, speech recognition, image recognition, natural language processing, expert systems, machine learning, and computer vision. Practical applications of AI are primarily found in machine vision, fingerprint recognition, facial recognition, retinal recognition, iris recognition, palm print recognition, expert systems, automated planning, intelligent search, theorem proving, game theory, automated programming, intelligent control, robotics, language and image understanding, and genetic programming.

[0005] Patent document CN109383152B discloses a method for processing a data manuscript and a digital proofing method using the data manuscript. Based on a standard color space, the method utilizes a color management system for continuous comparison and adjustment, and then continuously adjusts the resolution of the data manuscript to generate a final data manuscript that meets the requirements. This continuous adjustment method generates a data manuscript that meets the requirements, and a digital proofing machine can directly use the data manuscript to print a qualified, high-precision digital sample, thus meeting the requirements of use.

[0006] However, in the process of implementing the above technical solution, it was found that the above technical solution had the following technical problems:

[0007] In the process of printing color management, the data manuscript processing method and the digital proofing method using the data manuscript can generate a data manuscript that meets the requirements by causing the color management system to continuously compare and adjust according to standard colors. However, since the color management system needs to continuously compare and adjust colors, the processing volume is large and the workload is heavy. In addition, the continuous comparison and adjustment processing greatly increases the working pressure of the system. Summary of the Invention

[0008] In order to overcome the shortcomings of the existing data manuscript processing method and the digital proofing method using the data manuscript, which require the color management system to continuously perform color comparison and adjustment, resulting in a large amount of processing and a heavy workload, and the continuous comparison and adjustment processing greatly increases the system working pressure, the embodiment of the present application provides an artificial intelligence-based printing color management control and monitoring system and method. When the deviation value calculated in the actual printing process is greater than the threshold, the RGB color space is converted into the CIE Lab color space using the colorimetry method, and the amount of printing ink, printing pressure, drying conditions and other factors are adjusted to reduce the color difference, thereby facilitating the analysis and correction of color deviations and eliminating the need for continuous color comparison and adjustment.

[0009] The technical solution adopted by the embodiment of the present application to solve the technical problem is:

[0010] An artificial intelligence-based printing color management control and monitoring system and method, including an image input system, a feature creation system, a color calibration system, and an image output system;

[0011] The image input system is used to restore color depth and color type within a dynamic range and capture color information in the original;

[0012] The characteristic creation system is used to generate data by scanning a standard color card, and after analyzing the data using color management software, create a color characteristic file;

[0013] The color calibration system is used to set color characteristic deviation thresholds, determine color characteristic intervention conditions, and adjust color parameters;

[0014] The image output system is used to simulate the final printing effect according to printing requirements, use a colorimeter to measure the actual color value of each color block on the test plate, import the measurement data into the color management software, and generate a color characteristic file for image output;

[0015] The color calibration system acquires color features in a color space and determines whether to perform editing intervention on the color features based on the relationship between the actual color feature deviation and the threshold.

[0016] In a possible implementation, the acquisition of the color feature is based on the RGB color space. On the one hand, the average color value of the image in each color channel (R, G, B) is calculated by the mean, and the formula is as follows:

[0017]

[0018] Where N is the total number of pixels in the image, R i , G i 、B i are the red, green, and blue component values of the i-th pixel respectively;

[0019] On the other hand, the variance formula is used to reflect the discrete degree of color values in each color channel, as follows:

[0020]

[0021] In one possible implementation, in the RGB color space, for a color point C = (R, G, B), the target color point is set to C0 = (R0, G0, B0), and the Euclidean distance is used to measure the color deviation d. The solution formula for d is as follows:

[0022]

[0023] A threshold value T is set according to the above d. When d≤T, the color deviation is considered to be within an acceptable range; when d>T, it is considered that the color has an unacceptable deviation.

[0024] In one possible implementation, in a complex scene of color printing, different weights are assigned to different colors based on the proportion of different colors and considering the sensitivity of human vision to different color channels. R 、ω G and ω B , and adapt the color deviation formula to:

[0025]

[0026] In the process of identifying printed patterns, for the identification of different colors, the sample data continuously recorded during the printing process provides a reference for determining the threshold value of the subsequent printed patterns.

[0027] In a possible implementation, when the color characteristic deviation d is greater than a threshold value T, the printed color is converted from the device-dependent RGB color space to the CIE Lab color space using a colorimetric method. The specific steps are as follows:

[0028] First, convert the RGB value to XYZ value. The conversion formula is related to the standard of the RGB color space used. Taking sRGB as an example, the conversion formula is as follows:

[0029]

[0030] Then, convert the XYZ values to CIE Lab values with the formula:

[0031]

[0032] Among them, X n , Y n , Z n is the tristimulus value under the standard lighting body, and the f(t) function is defined as:

[0033] Finally, color deviation is analyzed and corrected in the CIE Lab color space.

[0034] In one possible implementation, in the CIE Lab color space, color deviation is evaluated by calculating the color difference ΔE between the target color and the actual printed color, and printing parameters are adjusted according to the magnitude and direction of the color difference. The solution formula for ΔE is as follows:

[0035]

[0036] Among them, ΔL', ΔC', and ΔH' are the differences in lightness, chroma, and hue, respectively, and k L 、k C 、k H is a constant related to the measurement conditions, S L 、S C 、S H It is a weighted function that takes visual characteristics into account. RT is a rotation function related to hue. Based on the calculated color difference ΔE, the color difference can be reduced by adjusting factors such as the amount of printing ink, printing pressure, and drying conditions to achieve correction of color deviation.

[0037] A printing color management control and monitoring method based on artificial intelligence, comprising:

[0038] S1: Capture the color information of the original and confirm the color depth;

[0039] S2: Use standard color cards to scan and generate data, and create color profiles after analysis;

[0040] S3: Set the color characteristic deviation threshold and determine whether to perform color characteristic condition intervention based on the deviation situation;

[0041] S4: Convert from device color space to standard RGB color space and edit the color profile;

[0042] S5: Convert the processed image from the RGB color space to the CMYK color space for output.

[0043] In one possible implementation, during the conversion from RGB color space to CMYK color space, the black component K is calculated first, followed by the cyan component C, the magenta component M, and the yellow component Y.

[0044] Where K = 1-max(R, G, B), C = (1-RK) / (1-K), M = (1-GK) / (1-K), and Y = (1-BK) / (1-K); the R, G, and B values are normalized to the range [0, 1].

[0045] The beneficial effects of this application are:

[0046] First, in this solution, color feature information is obtained during the image input and feature creation process, and the deviation of a large amount of data during the printing process is determined by calculating the color feature deviation, thereby determining a threshold. When the deviation value calculated during the actual printing process is less than the threshold, subsequent color feature conversion can be performed and image output can be carried out;

[0047] Secondly, in this solution, when the deviation value calculated during the actual printing process is greater than the threshold, the RGB color space is converted into the CIE Lab color space using the colorimetric method, and the amount of printing ink, printing pressure, drying conditions and other factors are adjusted to reduce the color difference, making it easier to analyze and correct color deviations. There is no need to constantly compare and adjust colors, and the workload is relatively small. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 Schematic diagram of the system flow of the present invention;

[0049] Figure 2 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 3 Schematic diagram of the printing color management control method of the present invention. DETAILED DESCRIPTION

[0051] The technical solution in the embodiments of the present application is to solve the problems of the above-mentioned background technology, and the overall idea is as follows:

[0052] Example 1:

[0053] This embodiment introduces a specific structure of a printing color management control and monitoring system based on artificial intelligence. Figure 1 and Figure 2 As shown, it includes an image input system, a feature creation system, a color calibration system, and an image output system;

[0054] The image input system is used to restore color depth and color type within the dynamic range and capture the color information in the original;

[0055] The characterization creation system is used to generate data by scanning a standard color card, and then create a color characterization file after analyzing the data using color management software;

[0056] The color calibration system is used to set the color characteristic deviation threshold, determine the color characteristic intervention conditions, and adjust the color parameters;

[0057] Among them, the acquisition of color features is based on the RGB color space. On the one hand, the average color value of the image in each color channel (R, G, B) is calculated by the mean, and the formula is as follows:

[0058]

[0059] Where N is the total number of pixels in the image, R i , G i 、B i are the red, green, and blue component values of the i-th pixel respectively; on the other hand, the variance formula is used to reflect the discrete degree of color values in each color channel, as follows:

[0060]

[0061] Color features can be used to perform automatic color correction and contrast enhancement on images (for example, analyzing color features to adjust the color balance of a photo with color cast to restore normal color performance; or performing targeted contrast enhancement on different areas of the image based on the color distribution to highlight image details).

[0062] Secondly, to confirm the color characteristic deviation threshold so that the values obtained in the actual printing process can be compared, in the RGB color space, for a certain color point C = (R, G, B), the target color point is set to C0 = (R0, G0, B0), and the Euclidean distance is used to measure the color deviation d. The solution formula for d is as follows:

[0063]

[0064] A threshold value T is set based on d in the formula. When d≤T, the color deviation is considered to be within the acceptable range; when d>T, the color deviation is considered to be unacceptable and requires intervention and adjustment.

[0065] At the same time, in complex scenes of color printing, different weights are given to different colors based on the proportion of different colors and considering the sensitivity of human vision to different color channels. R 、ω Gand ω B , and adapt the color deviation formula to:

[0066]

[0067] During the recognition process of printed patterns, the sample data continuously recorded during the printing process provides a reference for determining the threshold value of the printed pattern. This can support the color calibration system to obtain the color characteristics in the color space. Based on the relationship between the actual color characteristic deviation and the threshold value, it can determine whether to edit the color characteristics.

[0068] In some examples, when the color characteristic deviation d is greater than a threshold T, the printed color is converted from the device-dependent RGB color space to the CIE Lab color space using a colorimetric method, as follows:

[0069] First, convert the RGB value to XYZ value. The conversion formula is related to the standard of the RGB color space used. Taking sRGB as an example, the conversion formula is as follows:

[0070]

[0071] Then, convert the XYZ values to CIE Lab values with the formula:

[0072]

[0073] Among them, X n , Y n , Z n is the tristimulus value under the standard lighting body, and the f(t) function is defined as:

[0074] Finally, color deviation is analyzed and corrected in the CIE Lab color space.

[0075] In the CIE Lab color space, color deviation is evaluated by calculating the color difference ΔE between the target color and the actual printed color, and the printing parameters are adjusted according to the size and direction of the color difference. The solution formula for ΔE is as follows:

[0076]

[0077] Among them, ΔL', ΔC', and ΔH' are the differences in lightness, chroma, and hue, respectively, and k L 、k C 、k H is a constant related to the measurement conditions, S L 、S C 、S HIt is a weighted function that takes visual characteristics into account. RT is a rotation function related to hue. Based on the calculated color difference ΔE, the color difference can be reduced by adjusting factors such as the amount of printing ink, printing pressure, and drying conditions to achieve color deviation correction.

[0078] Finally, the image output system simulates the final printing effect according to printing requirements, uses a colorimeter to measure the actual color value of each color block on the test plate, imports the measurement data into the color management software, and generates a color characteristic file for the image output.

[0079] Example 2:

[0080] Based on Example 1, this example introduces an artificial intelligence-based printing color management control and monitoring method, including:

[0081] S1: Capture the color information of the original and confirm the color depth;

[0082] S2: Use standard color cards to scan and generate data, and create color profiles after analysis;

[0083] S3: Set the color characteristic deviation threshold and determine whether to perform color characteristic condition intervention based on the deviation situation;

[0084] The color characteristic deviation threshold is set by using the Euclidean distance to measure the color deviation d. A threshold T is set based on the calculated value of the color deviation d. When d≤T, the color deviation is considered to be within the acceptable range; when d>T, the color deviation is considered to be unacceptable. If the color deviation is unacceptable, intervention is selected.

[0085] S4: Convert from device color space to standard RGB color space and edit the color profile;

[0086] When the color characteristic deviation d is greater than the threshold T, the printed color is converted from the device-related RGB color space to the CIE Lab color space using colorimetry methods. The color deviation is evaluated by calculating the color difference ΔE between the target color and the actual printed color, and the printing parameters are adjusted according to the size and direction of the color difference.

[0087] S5: converting the processed image from RGB color space to CMYK color space for output;

[0088] In the process of converting the RGB color space to the CMYK color space, the black component K is calculated first, and then the cyan component C, the magenta component M, and the yellow component Y are calculated;

[0089] Where K = 1-max(R, G, B), C = (1-RK) / (1-K), M = (1-GK) / (1-K), and Y = (1-BK) / (1-K); the R, G, and B values are normalized to the range [0, 1].

[0090] Finally, it should be noted that the above embodiments are merely examples for the purpose of illustrating the present invention and are not intended to limit the embodiments. Those skilled in the art will readily appreciate that other variations or modifications based on the above description are possible. It is not necessary and impossible to provide an exhaustive list of all embodiments. However, obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A printing color management control and monitoring system based on artificial intelligence, characterized in that: Includes image input system, feature creation system, color calibration system and image output system; The image input system is used to restore color depth and color type within a dynamic range and capture color information in the original; The characteristic creation system is used to generate data by scanning a standard color card, and after analyzing the data using color management software, create a color characteristic file; The color calibration system is used to set color characteristic deviation thresholds, determine color characteristic intervention conditions, and adjust color parameters; The image output system is used to simulate the final printing effect according to printing requirements, use a colorimeter to measure the actual color value of each color block on the test plate, import the measurement data into the color management software, and generate a color characteristic file for image output; The color calibration system acquires color features in a color space and determines whether to perform editing intervention on the color features based on the relationship between the actual color feature deviation and the threshold.

2. The artificial intelligence-based printing color management, control, and monitoring system according to claim 1, characterized in that: The acquisition of the color feature is based on the RGB color space. On the one hand, the average color value of the image in each color channel (R, G, B) is calculated by the mean, and the formula is as follows: Where N is the total number of pixels in the image, R i , G i 、B i are the red, green, and blue component values of the i-th pixel respectively; On the other hand, the variance formula is used to reflect the discrete degree of color values in each color channel, as follows:

3. The artificial intelligence-based printing color management, control, and monitoring system according to claim 2, characterized in that: In the RGB color space, for a color point C = (R, G, B), the target color point is set to C0 = (R0, G0, B0), and the Euclidean distance is used to measure the color deviation d. The solution formula for d is as follows: A threshold value T is set according to the above d. When d≤T, the color deviation is considered to be within an acceptable range; when d>T, it is considered that the color has an unacceptable deviation.

4. The artificial intelligence-based printing color management, control, and monitoring system according to claim 3, characterized in that: In complex scenes of color printing, different weights are assigned to different colors based on the proportion of different colors and considering the sensitivity of human vision to different color channels. R 、ω G and ω B , and adapt the color deviation formula to: In the process of identifying printed patterns, for the identification of different colors, the sample data continuously recorded during the printing process provides a reference for determining the threshold value of the subsequent printed patterns.

5. The artificial intelligence-based printing color management, control, and monitoring system according to claim 3, characterized in that: When the color characteristic deviation d is greater than a threshold value T, the printed color is converted from the device-dependent RGB color space to the CIE Lab color space using a colorimetric method. The specific steps are as follows: First, convert the RGB value to XYZ value. The conversion formula is related to the standard of the RGB color space used. Taking sRGB as an example, the conversion formula is as follows: Then, convert the XYZ values to CIE Lab values with the formula: Among them, X n , Y n , Z n is the tristimulus value under the standard lighting body, and the f(t) function is defined as: Finally, color deviation is analyzed and corrected in the CIE Lab color space.

6. The artificial intelligence-based printing color management, control, and monitoring system according to claim 5, characterized in that: In the CIE Lab color space, color deviation is evaluated by calculating the color difference ΔE between the target color and the actual printed color, and printing parameters are adjusted according to the size and direction of the color difference. The solution formula for ΔE is as follows: Among them, ΔL', ΔC', and ΔH' are the differences in lightness, chroma, and hue, respectively, and k L 、k C 、k H is a constant related to the measurement conditions, S L 、S C 、S H It is a weighted function that takes visual characteristics into account. RT is a rotation function related to hue. Based on the calculated color difference ΔE, the color difference can be reduced by adjusting factors such as the amount of printing ink, printing pressure, and drying conditions to achieve correction of color deviation.

7. A printing color management control and monitoring method based on artificial intelligence, which is implemented based on an artificial intelligence-based printing color management control and monitoring system according to any one of claims 1 to 6, characterized in that: include: S1: Capture the color information of the original and confirm the color depth; S2: Use standard color cards to scan and generate data, and create color profiles after analysis; S3: Set the color characteristic deviation threshold and determine whether to perform color characteristic condition intervention based on the deviation situation; S4: Convert from device color space to standard RGB color space and edit the color profile; S5: Convert the processed image from the RGB color space to the CMYK color space for output.

8. The artificial intelligence-based printing color management, control, and monitoring system and method according to claim 7, characterized in that: In the process of converting RGB color space to CMYK color space, the black component K is calculated first, and then the cyan component C, magenta component M, and yellow component Y are calculated; Where K = 1-max(R, G, B), C = (1-RK) / (1-K), M = (1-GK) / (1-K), and Y = (1-BK) / (1-K); the R, G, and B values are normalized to the range [0, 1].

Images