A method and system for adjusting intelligent printing parameters based on AI.

Abstract

This invention proposes an AI-assisted intelligent printing parameter adjustment method and system. The intelligent printing parameter adjustment method includes: identifying printing feature vectors based on the text to be printed to obtain the corresponding printing feature vectors; retrieving historical printing records from the printer control terminal corresponding to the text, and obtaining the printing consumable index corresponding to the printer control terminal based on the historical printing records; obtaining the printing consumable correlation degree between the current text to be printed and the printer control terminal based on the printing feature vector and the printing consumable index; and dynamically adjusting the printing parameters of the text to be printed based on the printing consumable correlation degree and the remaining ink volume of the printing device. The system includes modules corresponding to the steps of the method.

Description

Technical Field

[0001] This invention proposes an AI-assisted intelligent printing parameter adjustment method and system, belonging to the field of intelligent equipment parameter control technology. Background Technology

[0002] With the deepening of office automation and digitalization, printing equipment has become an indispensable output tool in daily office, education and scientific research and family life. Users' demand for a balance between printing efficiency, output quality and consumable costs is becoming increasingly prominent.

[0003] Existing methods for adjusting printing parameters have significant limitations: On the one hand, traditional manual adjustment relies on users subjectively setting parameters such as print density, paper type, and resolution. This not only increases the user's workload but also, due to users' insufficient understanding of the correlation between printing parameters and consumable consumption, easily leads to unreasonable parameter settings—for example, using excessively high print density for documents with high text density results in ink waste, or using excessively low resolution for important documents affects readability. On the other hand, although some devices have simple automatic adjustment functions, they often adjust based solely on the remaining ink volume of the printer (such as directly reducing print density when the remaining ink volume is low), without considering the specific characteristics of the text to be printed (such as text font size, line spacing, image proportion, etc.) or the consumable usage preferences reflected in the user's historical printing habits (such as a specific user's preference for conventional printing parameters for similar documents). As a result, the adjusted parameters are difficult to balance the personalized needs of print quality and consumable conservation, lacking adaptability and intelligence.

[0004] Therefore, how to combine the characteristics of the text to be printed, the user's historical consumable usage patterns, and the real-time status of the equipment to achieve intelligent and dynamic adjustment of printing parameters has become a key technical issue for improving the printing experience and optimizing consumable management. Summary of the Invention

[0005] This invention provides an AI-assisted intelligent printing parameter adjustment method and system to solve the aforementioned technical problems in the prior art. The technical solution adopted is as follows:

[0006] An AI-assisted intelligent printing parameter adjustment method, the intelligent printing parameter adjustment method comprising:

[0007] Based on the text to be printed, the printing feature vector is identified to obtain the printing feature vector corresponding to the text to be printed.

[0008] The system retrieves historical printing records from the printer control terminal corresponding to the printed text from the cloud platform, and obtains the printing consumable index corresponding to the printer control terminal based on the historical printing records. A data connection is established between the cloud platform and the printer control terminal, and the cloud platform is used to store the historical printing records of the printer control terminal.

[0009] Based on the printing feature vector corresponding to the current text to be printed and the printing consumable index corresponding to the printer control terminal, obtain the correlation degree between the current text to be printed and the printing consumable of the printer control terminal.

[0010] The printing parameters of the text to be printed are dynamically adjusted based on the correlation between the text to be printed and the printing consumables on the printer control terminal, as well as the remaining ink on the printing device.

[0011] Furthermore, based on the text to be printed, print feature vector recognition is performed to obtain the print feature vector corresponding to the text to be printed, including:

[0012] The text to be printed is scanned page by page, and text paragraph recognition is performed on each text page to obtain the text ratio of each text page. At the same time, it is determined whether there is an image area on each text page.

[0013] When an image region exists on the text page, obtain the resolution and edge complexity of the image contained within that region.

[0014] Based on the proportion of text on each text page and the resolution and edge complexity of the included images, obtain the printing feature vector corresponding to the text to be printed.

[0015] Furthermore, the edge complexity of the image contained within the image region is obtained, including:

[0016] Extract the percentage of edge pixels in eight directions within the image region;

[0017] Multiple target directions are determined based on a direction filtering strategy;

[0018] The directional entropy of the image region is obtained by utilizing the proportion of edge pixels in multiple target directions of the image contained within the image region;

[0019] Select the edge chain codes corresponding to the three directions with the largest edge pixel proportion, and use the corresponding curvature fluctuation coefficients of the images contained in the obtained image region;

[0020] The edge complexity of the image contained within the image region is obtained by combining the directional entropy corresponding to the image region with the curvature fluctuation coefficient corresponding to each edge chain code.

[0021] Furthermore, based on the text proportion of each text page and the resolution and edge complexity of the included images, the printing feature vector corresponding to the text to be printed is obtained, including:

[0022] Retrieve the resolution and edge complexity of the image regions contained in each text page;

[0023] The overall resolution and overall edge complexity of the text to be printed are obtained based on the resolution and edge complexity of the image regions contained in each text page.

[0024] Retrieve the text percentage corresponding to each text page, and obtain the average text percentage of the text to be printed based on the text percentage corresponding to each text page;

[0025] The average text ratio, overall resolution, and overall edge complexity of the text to be printed are used as feature elements to generate a printing feature vector corresponding to the text to be printed.

[0026] Further, retrieve the historical printing records of the printer control terminal corresponding to the printed text, and obtain the printing consumable index corresponding to the printer control terminal based on the historical printing records, including:

[0027] Retrieve the printing parameters of the historical printing records of the printer control terminal corresponding to the printed text, wherein the printing parameters include the overall resolution, overall edge complexity and ink consumption for each print.

[0028] Normalize the overall resolution and overall edge complexity corresponding to each print, and then multiply the normalized overall resolution and overall edge complexity to obtain the print complexity factor corresponding to each print.

[0029] The ink consumption for each print is normalized using the full ink level of the ink cartridge, and the normalized ink consumption value for each print is obtained.

[0030] The printing consumable index corresponding to the printer control terminal is obtained by using the printing complexity factor corresponding to each print and the normalized ink consumption value.

[0031] Furthermore, based on the printing feature vector corresponding to the current text to be printed and the printing consumable index corresponding to the printer control terminal, the correlation degree between the current text to be printed and the printing consumables of the printer control terminal is obtained, including:

[0032] Retrieve the print feature vector corresponding to each print in the historical print record;

[0033] Based on the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print, obtain the cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print;

[0034] By combining the cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print, and the printing consumable index corresponding to the printer control terminal, the correlation degree between the current text to be printed and the printing consumable of the printer control terminal is obtained.

[0035] Furthermore, by combining the cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print, and the printing consumable index corresponding to the printer control terminal, the correlation degree between the current text to be printed and the printing consumables of the printer control terminal is obtained, including:

[0036] The cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print is normalized to obtain the normalized cosine similarity.

[0037] The normalized cosine similarity is compared with the preset similarity reference value;

[0038] The print feature vector corresponding to each print operation with a normalized cosine similarity value not lower than the preset similarity reference value is used as the first vector dataset.

[0039] The printed feature vectors corresponding to each print that are lower than the preset similarity reference value after normalization are used as the second vector dataset.

[0040] Retrieve the average text ratio, overall resolution, and overall edge complexity of each printed feature vector in the first vector dataset, and the average text ratio, overall resolution, and overall edge complexity of each printed feature vector in the second vector dataset;

[0041] Retrieve the average character proportion, overall resolution, and overall edge complexity from the printing feature vector corresponding to the text to be printed;

[0042] By combining the average text proportion, overall resolution, and overall edge complexity in the print feature vector corresponding to the text to be printed with the average text proportion, overall resolution, and overall edge complexity in each print feature vector in the first vector dataset and the average text proportion, overall resolution, and overall edge complexity in each print feature vector in the second vector dataset, and the printing consumable index corresponding to the printer control terminal, the correlation degree between the current text to be printed and the printing consumables of the printer control terminal is obtained.

[0043] Furthermore, the printing parameters of the text to be printed are dynamically adjusted based on the correlation between the current text to be printed and the printing consumables on the printer control terminal, and the remaining ink volume of the current printing device, including:

[0044] Retrieve the remaining ink level of the current printing device;

[0045] The text to be printed is simulated for printing according to the printing resolution set on the printer control terminal to obtain the simulated ink volume;

[0046] Compare the simulated ink volume with the remaining ink volume of the current printing device;

[0047] The printing parameters of the text to be printed are dynamically adjusted based on the comparison between the simulated ink volume and the remaining ink volume of the current printing device, combined with the correlation between the current text to be printed and the printing consumables of the printer control terminal.

[0048] Furthermore, based on the comparison between the simulated ink volume and the remaining ink volume of the current printing device, and in conjunction with the correlation between the current text to be printed and the printing consumables of the printer control terminal, the printing parameters of the text to be printed are dynamically adjusted, including:

[0049] When the simulated ink volume exceeds the remaining ink volume of the current printing device, an insufficient ink volume prompt is sent to the printer control terminal, and the printing operation is not started.

[0050] When the simulated ink volume does not exceed the remaining ink volume of the current printing device, but exceeds the ink volume corresponding to a preset percentage of the remaining ink volume, the printing resolution of the text to be printed and the black density corresponding to the image portion are dynamically adjusted based on the printing resolution set on the printer control terminal and the correlation between the text to be printed and the printing consumables on the printer control terminal; wherein, the preset percentage ranges from 67% to 58%;

[0051] When the simulated ink volume does not exceed the preset percentage of the remaining ink volume of the current printing device, the printing parameters of the document to be printed will not be adjusted, and the printing will be performed according to the printing resolution set by the printer control terminal and the original image black density of the printing device.

[0052] An AI-assisted intelligent printing parameter adjustment system, the intelligent printing parameter adjustment system comprising:

[0053] The vector acquisition module is used to identify the printing feature vector based on the text to be printed and obtain the printing feature vector corresponding to the text to be printed.

[0054] The printing consumables index acquisition module is used to retrieve the historical printing records of the printer control terminal corresponding to the printed text from the cloud platform, and obtain the printing consumables index corresponding to the printer control terminal based on the historical printing records; wherein, the cloud platform establishes a data connection with the printer control terminal, and the cloud platform is used to store the historical printing records of the printer control terminal;

[0055] The correlation degree acquisition module is used to obtain the correlation degree between the current text to be printed and the printing consumables of the printer control terminal based on the printing feature vector corresponding to the current text to be printed and the printing consumables index corresponding to the printer control terminal.

[0056] The dynamic adjustment module is used to dynamically adjust the printing parameters of the text to be printed based on the correlation between the current text to be printed and the printing consumables of the printer control terminal and the remaining ink of the current printing device.

[0057] Beneficial effects of this invention:

[0058] This invention proposes an AI-assisted intelligent printing parameter adjustment method and system. By integrating the characteristics of the text to be printed, the user's historical consumable patterns, and the real-time status of the equipment, it overcomes the subjectivity of traditional manual adjustments and the limitations of simple automatic adjustments, making parameter settings more closely aligned with the attributes of the printed content and the actual situation of the equipment. Based on consumable correlation analysis, it can avoid ink waste or insufficient quality caused by unreasonable parameter settings while ensuring that the printing effect meets the user's expectations, thus optimizing consumable utilization. By incorporating consumable indices extracted from historical records into the adjustment logic, the printing parameters are made more consistent with the user's long-established usage habits, reducing the frequency of manual intervention and improving operational convenience. Leveraging AI's ability to process multi-dimensional data, it can handle printing needs for different types of text (such as plain text, mixed text and images, etc.) and different ink volume states, ensuring that reasonable parameters are output in diverse scenarios. Attached Figure Description

[0059] Figure 1 This is a flowchart of the method described in this invention;

[0060] Figure 2 This is a system block diagram of the system described in this invention. Detailed Implementation

[0061] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0062] This invention proposes an AI-assisted intelligent printing parameter adjustment method, such as... Figure 1 As shown, the intelligent printing parameter adjustment method includes:

[0063] Based on the text to be printed, the printing feature vector is identified to obtain the printing feature vector corresponding to the text to be printed.

[0064] The system retrieves historical printing records from the printer control terminal corresponding to the printed text from the cloud platform, and obtains the printing consumable index corresponding to the printer control terminal based on the historical printing records. A data connection is established between the cloud platform and the printer control terminal, and the cloud platform is used to store the historical printing records of the printer control terminal.

[0065] Based on the printing feature vector corresponding to the current text to be printed and the printing consumable index corresponding to the printer control terminal, obtain the correlation degree between the current text to be printed and the printing consumable of the printer control terminal.

[0066] The printing parameters of the text to be printed are dynamically adjusted based on the correlation between the text to be printed and the printing consumables on the printer control terminal, as well as the remaining ink on the printing device.

[0067] The working principle of the above technical solution is as follows: First, AI algorithms are used to extract features from the text to be printed, generating a printing feature vector containing key information such as text density, font size, and image proportion, quantifying the attributes of the content to be printed; Second, based on the historical printing records of the printer control terminal, data analysis is used to mine the user's consumable usage habits, forming a corresponding printing consumable index that reflects the user's preference for consumable consumption and printing effect; Then, the feature vector of the text to be printed is correlated with the user's consumable index to calculate the consumable correlation between the two, clarifying the matching relationship between the current printing task and the user's consumable habits; Finally, combining this correlation and the real-time remaining ink volume of the printing device, the AI ​​model dynamically optimizes parameters such as printing density and resolution to achieve intelligent parameter adaptation.

[0068] The above technical solution achieves the following results: By integrating the characteristics of the text to be printed, the user's historical consumable patterns, and the real-time status of the device, it overcomes the subjectivity of traditional manual adjustments and the limitations of simple automatic adjustments, making parameter settings more closely match the attributes of the printed content and the actual situation of the device. Based on the analysis of consumable correlation, it can avoid ink waste or insufficient quality caused by unreasonable parameter settings while ensuring that the printing effect meets the user's expectations, thus optimizing consumable utilization. By incorporating consumable indices extracted from historical records into the adjustment logic, the printing parameters are made more in line with the user's long-established usage habits, reducing the frequency of manual intervention and improving operational convenience. Leveraging AI's ability to process multi-dimensional data, it can handle printing needs for different types of text (such as plain text, mixed text and images, etc.) and different ink volume states, ensuring that reasonable parameters are output in various scenarios.

[0069] One embodiment of the present invention involves identifying printing feature vectors based on the text to be printed, and obtaining the printing feature vectors corresponding to the text to be printed, including:

[0070] The text to be printed is scanned page by page, and text paragraph recognition is performed on each text page to obtain the text ratio of each text page. At the same time, it is determined whether there is an image area on each text page.

[0071] When an image region exists on the text page, obtain the resolution and edge complexity of the image contained within that region.

[0072] Based on the proportion of text on each text page and the resolution and edge complexity of the included images, obtain the printing feature vector corresponding to the text to be printed.

[0073] The working principle of the above technical solution is as follows: First, the text is scanned page by page to cover all content. The proportion of text on each page is extracted through text paragraph recognition to quantify the weight of text information on the page. At the same time, it is determined whether there are image areas on each page. If so, the resolution (reflecting the image clarity requirements) and edge complexity (reflecting the richness of image details) of the image are further extracted. Finally, the key indicators such as the proportion of text on each page, image resolution, and edge complexity are integrated to form a printing feature vector that can comprehensively characterize the attributes of the text content to be printed.

[0074] The above technical solution achieves the following results: by fusing multiple dimensions such as text proportion, image resolution, and edge complexity, it avoids the one-sided representation of text attributes by a single feature, and more accurately captures the content features of the text (such as text-intensive or image-dominated text). For documents containing mixed content (text and images coexisting), it effectively extracts features of different types of content through multi-dimensional analysis, ensuring that the feature vectors can adapt to diverse text structures. Accurate feature vectors can improve the accuracy of correlation analysis with user consumable indexes, making the adjustment of printing parameters based on correlation more closely match the actual printing needs of the text (such as higher precision parameters corresponding to high-resolution images). Through a process of page-by-page scanning, element-by-element recognition, and multi-indicator integration, the feature vector generation process has a clear hierarchy and logic, improving the stability and interpretability of the recognition results.

[0075] One embodiment of the present invention involves obtaining the edge complexity of an image contained within an image region, including:

[0076] Extract the percentage of edge pixels in eight directions within the image region;

[0077] Multiple target directions are determined based on a direction filtering strategy;

[0078] The directional entropy of the image region is obtained by utilizing the proportion of edge pixels in multiple target directions of the image contained within the image region;

[0079] The directional entropy is obtained by the following formula:

[0080]

[0081] in, f This represents the directional entropy corresponding to an image region. n Indicates the number of orientations of the image; p i Indicates the first i The percentage of edge pixels in each direction;

[0082] Select the edge chain codes corresponding to the three directions with the largest edge pixel proportion, and use the corresponding curvature fluctuation coefficients of the images contained in the obtained image region;

[0083] The curvature fluctuation coefficient of the image contained within the image region is obtained by the following formula:

[0084]

[0085] in, S This represents the curvature fluctuation coefficient of the image contained within the image region; m Indicates the number of edge chain codes; k i Indicates the first i The curvature corresponding to the chain code points of each edge chain code; k This represents the average curvature of the chain code points corresponding to the eight directions; d i Indicates the first i The straight-line distance between the chain code points of each edge chain code and the center point of the image region; p si Indicates the first i The percentage of edge pixels corresponding to each chain code point of an edge chain code; L This indicates the length of the edges of the image contained within the image region;

[0086] The edge complexity of the image contained within the image region is obtained by combining the directional entropy corresponding to the image region with the curvature fluctuation coefficient corresponding to each edge chain code.

[0087] The edge complexity of the image contained within the image region is obtained by the following formula:

[0088]

[0089] in, G This indicates the edge complexity of the image contained within an image region; S This represents the curvature fluctuation coefficient of the image contained within the image region; f This represents the directional entropy corresponding to the image region.

[0090] Meanwhile, the direction filtering strategy is as follows:

[0091] Retrieve the edge pixel percentages corresponding to the eight directions;

[0092] The maximum and minimum percentages of edge pixels are retrieved, and the difference between the maximum and minimum percentages of edge pixels is processed to obtain the absolute difference in percentage between the maximum and minimum percentages of edge pixels.

[0093] The standard deviation of the edge pixel ratio is obtained by using the edge pixel ratios corresponding to the eight directions.

[0094] The ratio parameter of the proportion is obtained by processing the ratio between the standard deviation of the proportion of edge pixels and the absolute difference of the proportion.

[0095] Compare the minimum percentage of edge pixels with the percentage ratio parameter;

[0096] When the minimum proportion of edge pixels is not lower than the proportion ratio parameter, all eight directions are taken as target directions;

[0097] When the minimum edge pixel percentage is lower than the percentage ratio parameter, the difference between the minimum edge pixel percentage and the second smallest edge pixel percentage is retrieved.

[0098] If the ratio of the difference between the minimum edge pixel percentage and the second minimum edge pixel percentage to the minimum edge pixel percentage is higher than the percentage ratio parameter, then the direction other than the direction corresponding to the minimum edge pixel percentage will be taken as the target direction.

[0099] If the ratio of the difference between the minimum and the second minimum edge pixel percentage to the minimum edge pixel percentage is not higher than the percentage ratio parameter, then all directions other than those corresponding to the minimum and second minimum edge pixel percentages will be taken as the target directions.

[0100] The working principle of the above technical solution is as follows: First, the target direction is determined by directional filtering, and the proportion of edge pixels in multiple target directions of the image region is extracted. Based on this, the directional entropy is calculated to quantify the disorder of the edge direction distribution. Second, the edge chain codes corresponding to the three directions with the largest proportion of edge pixels are selected. By calculating the deviation of the curvature of these chain code points from the average curvature, the distance from the chain code point to the image center, the corresponding edge pixel proportion, and the total edge length, the curvature fluctuation coefficient is obtained, which characterizes the severity of the local curvature change and the spatial distribution characteristics of the edge. Finally, the directional entropy and the curvature fluctuation coefficient are fused by a formula to comprehensively reflect the characteristics of the image edge in terms of both directional distribution uniformity and local morphological fluctuation, forming a quantitative result of edge complexity.

[0101] On the other hand, the direction selection strategy analyzes the multi-dimensional statistical characteristics of edge pixel proportions in eight directions. This analysis includes extreme values ​​(maximum and minimum), extreme value differences, standard deviation, and proportional relationships. This analysis determines the distribution characteristics of edge pixel proportions, identifying whether they are uniformly distributed or exhibit significantly low-proportion "abnormal directions." This allows for the precise selection of target directions representative of edge information. Specifically, the strategy uses the "proportion ratio parameter (generated by the ratio of the standard deviation to the absolute difference of the extreme values)" as the core criterion, combined with the "difference ratio between the minimum and second-minimum edge pixel proportions," to dynamically determine which directions should be included in subsequent calculations. This ensures that no valid edge directions are missed, while directions with minimal contribution to edge features are excluded.

[0102] The above technical solution achieves the following effects: by capturing the overall disorder of edge direction distribution through directional entropy and combining it with the curvature fluctuation coefficient to reflect the spatial characteristics of local curvature changes, it realizes a multi-dimensional characterization from macroscopic distribution to microscopic morphology, avoiding the limitations of a single index in describing complexity. In the calculation of the curvature fluctuation coefficient, distance weight, edge pixel proportion weight, and edge length normalization are introduced to make the measurement of local curvature fluctuations more closely match the spatial distribution law of the edge, improving the ability to distinguish complex edge morphologies (such as irregular curves and multi-directional turning edges). The analysis selects the three directional chain codes with the largest proportions, reducing redundant calculations while retaining the main edge features, balancing efficiency and representation accuracy. Accurate edge complexity quantification results can more accurately reflect the detail richness of the image, allowing subsequent printing parameters (such as resolution and density) to be adjusted more closely to the actual output requirements of the image, avoiding excessive consumption or insufficient quality.

[0103] Meanwhile, the directional filtering strategy described in this embodiment achieves adaptive dynamic filtering of target directions, overcoming the limitations of fixed-direction filtering: when the edge pixel proportion distribution is uniform, all eight directions are retained to ensure that the directional entropy can fully integrate the edge information of all directions; when there are "invalid / weak contribution directions" with a significantly low proportion, these directions are selectively excluded, so that the target direction focuses on directions with richer and more representative edge information. Therefore, a more accurate set of basic directions is provided for subsequent "directional entropy calculation" and "edge complexity assessment," significantly improving the accuracy and reliability of edge complexity calculation, while enhancing the adaptability to images with different edge structures (such as uniform edge distribution, local strong edge distribution, etc.), allowing the "edge complexity" index to more realistically and objectively characterize the complexity of image edges.

[0104] In one embodiment of the present invention, a printing feature vector corresponding to the text to be printed is obtained based on the text ratio of each text page and the resolution and edge complexity of the included images, including:

[0105] Retrieve the resolution and edge complexity of the image regions contained in each text page;

[0106] The overall resolution and overall edge complexity of the text to be printed are obtained based on the resolution and edge complexity of the image regions contained in each text page.

[0107] The overall resolution is obtained using the following formula:

[0108]

[0109] in, Z b Indicates the overall resolution; x Indicates the page number of the text to be printed; P ai Indicates the first i The percentage of the page area occupied by the image region contained in the page text; B i Indicates the first i The resolution of the image region contained in the page text;

[0110] Furthermore, the overall edge complexity is obtained using the following formula:

[0111]

[0112] in, Z f Indicates the overall marginal complexity of the text to be printed; y Indicates the number of image regions contained in the text to be printed; G i Indicates the first i The edge complexity corresponding to each image region;

[0113] Retrieve the text percentage corresponding to each text page, and obtain the average text percentage of the text to be printed based on the text percentage corresponding to each text page;

[0114] The average text ratio, overall resolution, and overall edge complexity of the text to be printed are used as feature elements to generate a printing feature vector corresponding to the text to be printed.

[0115] The working principle of the above technical solution is as follows: First, the resolution and edge complexity of the image regions contained in each text page are retrieved; for the overall resolution, a comprehensive value reflecting the overall level of clarity of the entire text image is obtained by combining the area ratio of each page's image region with its corresponding resolution through weighted calculation; for the overall edge complexity, the edge complexity of all image regions is integrated and calculated to characterize the overall complexity of image details in the text; at the same time, the average text ratio of each text page is calculated to reflect the overall text density; finally, the average text ratio, overall resolution, and overall edge complexity are used as core feature elements and combined to form a printing feature vector that can comprehensively reflect the attributes of the text to be printed.

[0116] The above technical solution achieves the following effects: by integrating three core indicators—text proportion, image resolution, and image edge complexity—it fully covers the text and image features within the text, avoiding the one-sided representation of text attributes by a single-dimensional feature. Comprehensive resolution is weighted by area proportion, making the impact of images with a higher proportion on the page more significant on the overall resolution; comprehensive edge complexity integrates features from all image regions, and the text proportion is averaged, all of which more accurately reflect the overall characteristics of the text. The standardized feature vector format facilitates correlation analysis with the printer control terminal's printing consumable index, improving the accuracy of correlation calculations and providing a scientific basis for the dynamic adjustment of printing parameters. Whether the text is primarily text-based, primarily image-based, or a mixture of text and images, its attributes can be accurately captured through corresponding feature elements, improving the solution's adaptability to different text types.

[0117] In one embodiment of the present invention, retrieving the historical printing records of the printer control terminal corresponding to the printed text, and obtaining the printing consumable index corresponding to the printer control terminal based on the historical printing records, includes:

[0118] Retrieve the printing parameters of the historical printing records of the printer control terminal corresponding to the printed text, wherein the printing parameters include the overall resolution, overall edge complexity and ink consumption for each print.

[0119] Normalize the overall resolution and overall edge complexity corresponding to each print, and then multiply the normalized overall resolution and overall edge complexity to obtain the print complexity factor corresponding to each print.

[0120] The ink consumption for each print is normalized using the full ink level of the ink cartridge, and the normalized ink consumption value for each print is obtained.

[0121] The printing consumable index corresponding to the printer control terminal is obtained by using the printing complexity factor corresponding to each print and the normalized ink consumption value.

[0122] The printing consumable index corresponding to the printer control terminal is obtained by the following formula:

[0123]

[0124] in, H This indicates the printing consumables index corresponding to the printer control terminal; z This indicates the number of prints included in the historical print records of the printer control terminal; M i Indicates the first i The normalized ink consumption value corresponding to each print; D i Indicates the first i The printing complexity factor corresponding to each print.

[0125] The working principle of the above technical solution is as follows: First, key parameters from historical printing records are retrieved, including the overall resolution, overall edge complexity, and ink consumption for each print. The overall resolution and overall edge complexity are normalized to eliminate dimensional differences, and then a printing complexity factor reflecting the complexity of each print is obtained through multiplication. At the same time, the ink consumption for each print is normalized based on the full ink level of the ink cartridge to obtain a standardized ink consumption value. Finally, using the number of prints as the base, the product of the printing complexity factor and the normalized ink consumption value for each print is accumulated and averaged to calculate the printing consumables index, which characterizes the consumables usage habits of the printer control terminal.

[0126] The above technical solution achieves the following effects: By integrating the complexity of the printed content (printing complexity factor) with actual ink consumption, the index more accurately reflects the user's consumable consumption characteristics in different printing scenarios, avoiding the bias caused by a single parameter (such as ink consumption alone). Normalization eliminates differences in the absolute values ​​of parameters across different printing tasks, ensuring that overall resolution, edge complexity, and ink consumption participate in the calculation on a unified scale, improving the comparability between multiple printing records and the stability of the calculation results. By averaging multiple historical records, the impact of a single, accidental printing action on the results is weakened, making the consumable index more representative of the user's long-term consumable usage preferences, providing a stable benchmark for subsequent correlation analysis. The calculation logic of the consumable index echoes the printing feature vector (including overall resolution and edge complexity), facilitating efficient correlation analysis between the two and providing accurate user habit basis for subsequent personalized adjustments to printing parameters.

[0127] On the other hand, existing technologies mostly calculate ink consumption or printing parameters separately, while this solution combines printing complexity factors with ink consumption in a coupled calculation. This allows the consumable index to reflect both the user's actual ink usage habits and the impact of content complexity on consumable consumption. This solves the problem in traditional methods where "the same amount of ink cannot distinguish consumable usage efficiency when corresponding to different content," achieving a deep binding between consumable characteristics and content characteristics. Simultaneously, normalization eliminates interference from differences in ink cartridge capacity and printing task parameter scales, allowing historical records of the same user on different devices and at different times to be directly used in the calculation. This overcomes the limitation that "historical data cannot be reused due to scenario differences," achieving the universality of the consumable index across diverse printing scenarios.

[0128] In one embodiment of the present invention, the correlation degree between the current text to be printed and the printing consumables of the printer control terminal is obtained based on the printing feature vector corresponding to the current text to be printed and the printing consumables index corresponding to the printer control terminal, including:

[0129] Retrieve the print feature vector corresponding to each print in the historical print record;

[0130] Based on the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print, obtain the cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print;

[0131] By combining the cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print, and the printing consumable index corresponding to the printer control terminal, the correlation degree between the current text to be printed and the printing consumable of the printer control terminal is obtained.

[0132] The working principle of the above technical solution is as follows: First, retrieve the printing feature vector corresponding to each print in the historical print record as a comparison benchmark; calculate the cosine similarity value between the printing feature vector of the current text to be printed and each historical printing feature vector to quantify the similarity between the current printing task and the historical tasks in terms of content features; finally, combine the cosine similarity value with the printing consumable index corresponding to the printer control terminal for analysis, and combine the two information to obtain the correlation between the current text to be printed and the printer control terminal at the level of consumable usage, so as to characterize the degree of matching between the current task and the user's historical consumable usage habits.

[0133] The above technical solution achieves the following results: By quantifying the feature matching degree between the current and historical printing tasks using cosine similarity, and combining it with a printing consumables index that reflects the user's long-term consumables habits, the correlation degree not only reflects the similarity of content features but also incorporates the user's consumables usage patterns, avoiding biases caused by single-dimensional analysis. The correlation degree calculation logic directly links the user's historical printing features and consumables data, making the results more closely match the user's consumables usage preferences in similar printing scenarios, providing a basis for subsequent parameter adjustments that align with user habits. Accurate correlation degree effectively bridges the characteristics of the current printing task with the user's consumables habits, making correlation-based parameter adjustments more targeted and reducing randomness. As historical data accumulates, by continuously incorporating new historical printing feature vectors, the correlation degree calculation can dynamically reflect changes in user habits, ensuring the effectiveness of the correlation degree in long-term use.

[0134] In one embodiment of the present invention, the cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print job is combined with the printing consumable index corresponding to the printer control terminal to obtain the correlation degree between the current text to be printed and the printing consumables of the printer control terminal, including:

[0135] The cosine similarity value between the printing feature vector corresponding to the text to be printed and the printing feature vector corresponding to each print is normalized to obtain the normalized cosine similarity.

[0136] The normalized cosine similarity is compared with the preset similarity reference value;

[0137] The print feature vector corresponding to each print operation with a normalized cosine similarity value not lower than the preset similarity reference value is used as the first vector dataset.

[0138] The printed feature vectors corresponding to each print that are lower than the preset similarity reference value after normalization are used as the second vector dataset.

[0139] Retrieve the average text ratio, overall resolution, and overall edge complexity of each printed feature vector in the first vector dataset, and the average text ratio, overall resolution, and overall edge complexity of each printed feature vector in the second vector dataset;

[0140] Retrieve the average character proportion, overall resolution, and overall edge complexity from the printing feature vector corresponding to the text to be printed;

[0141] By combining the average text proportion, overall resolution, and overall edge complexity in the print feature vector corresponding to the text to be printed, along with the average text proportion, overall resolution, and overall edge complexity in each print feature vector of the first vector dataset and the average text proportion, overall resolution, and overall edge complexity in each print feature vector of the second vector dataset, and the printing consumable index corresponding to the printer control terminal, the correlation degree between the current text to be printed and the printing consumables of the printer control terminal is obtained. The printing consumables correlation degree comprehensively considers the relationship between the text to be printed and the historical printing of the printer control terminal in terms of text proportion, consumables correlation, and similarity, reflecting the degree of fit between the consumables consumption pattern of the text to be printed and the historical situation and printing habits of the printer control terminal.

[0142] The correlation between the current text to be printed and the printing consumables of the printer control terminal is obtained by the following formula:

[0143]

[0144] in, J This indicates the correlation between the text to be printed and the printing consumables on the printer control terminal; a This indicates the number of printed feature vectors contained in the first vector dataset; b This indicates the number of printed feature vectors contained in the second vector dataset; R This represents the average percentage of text in the text to be printed. R i Represents the first vector dataset. i The average percentage of text in each printed feature vector; H This indicates the printing consumables index corresponding to the printer control terminal; Sim i Represents the first vector dataset. i The normalized cosine similarity between the printed feature vector and the printed feature vector of the text to be printed; R j Represents the second vector dataset. j The average percentage of text in each printed feature vector; Sim j Represents the second vector dataset. j The normalized cosine similarity between the printed feature vector and the printed feature vector of the text to be printed.

[0145] in, Used to quantify the "text ratio of the text to be printed" R ) × Consumables Index ( H ", and "normalized similarity of the first vector dataset with high similarity to historical printouts ()", and "normalized similarity of the first vector dataset with high similarity to historical printouts () Sim i The relationship between ")" and "the proportion of historically similar printed text" is relative to "the proportion of historically similar printed text". R i The degree of difference between ")"; then divide by a (Number of vectors in the first vector set) yields the "average difference under similar scenarios". This is used to reflect the close correlation between consumable consumption patterns and the current text in scenarios with historically similar printing features.

[0146] at the same time, Used to quantify the "text ratio of the text to be printed" R ) × Consumables Index ( H ", and "normalized similarity of the second vector dataset with lower similarity to historical prints ()", Sim j The relationship between ")" and "the proportion of text printed in different historical periods" is relative to "the proportion of text printed in different historical periods". R j The degree of difference between ")"; then divide by b (The number of vectors in the second vector set) yields the "average value of differences under different scenarios." This reflects the reference value of consumable consumption patterns to the current text in scenarios with historically different printing characteristics (i.e., changes in consumable associations caused by differences). Finally, the square root of the product of the "average value of differences in similar scenarios" and the "average value of differences in different scenarios" is used to synthesize the influence of the two types of scenarios—considering both the "continuity of consumable patterns in similar printing" and the "reference and constraint of differences in consumable patterns in different printing" on the current context. In this embodiment, in Later and Performing a product involves introducing dissimilar tasks as "boundary constraints." When the features of the dissimilar tasks differ significantly from the current task, this constraint is applied. S imj The value is relatively small. At this point, the average percentage of text corresponding to the current text to be printed is compared with the percentage of text printed in different historical periods. R j The ratio of the two values ​​is used to determine whether the proportion of text is the main factor causing the low cosine similarity. That is, when the average proportion of text corresponding to the current text to be printed is different from the proportion of text printed in the past ( R j When the ratio of the two values ​​approaches 1, it indicates that the average proportion of text corresponding to the current text to be printed is different from the proportion of text printed in the past. R j The similarity is higher, but the corresponding factor leading to lower cosine similarity is not due to a large difference in the average proportion of text. In this case, through... This method extracts the influence of text proportion elements in this case, thereby avoiding the exclusion of cases where the cosine similarity is low but the text proportion is extremely similar due to large differences in images in historical files and large printing resolutions, which would lead to inaccurate correlation of printing consumables.

[0147] The final result is a quantitative assessment that comprehensively reflects the correlation between the current text and consumable consumption. This embodiment is applicable to various types of documents to be printed, both with high and low text ratios. For example, when the text to be printed is a combination of high text ratio and high resolution or complex edge images, such as technical manuals or academic papers, where the text is dense and contains detailed engineering drawings, the historical prints of the first vector set should be similar documents with "lots of text and fine images" (such as past technical manual prints). These types of prints require more toner due to the large amount of text, and the high-resolution images also increase consumable usage, ultimately leading to higher consumable consumption. In this case, the "difference calculation of the first vector set" in the formula reflects the consistency between the current text and similar historical prints in the 'text-image-consumable' correlation, while the "difference calculation of the second vector set" reflects the difference from low-consumable scenarios such as 'few texts and simple images' (such as posters or simple tables). The final correlation is higher, corresponding to "high consumable demand," consistent with reality (high text + fine image printing consumes more consumables). Meanwhile, when the text to be printed consists of a low proportion of text combined with low-resolution or simple edge images, such as brief notices or memos containing only simple icons, the historical prints of the first vector set should be similar documents with "few texts and simple images" (such as past notice prints). These types of prints consume less consumables. In this case, the "difference calculation of the first vector set" in the formula will reflect the consistency between the current text and historically similar prints in the 'text-image-consumable' association, and the "difference calculation of the second vector set" will reflect the difference from high-consumable scenarios such as 'more text and more detailed images'. Ultimately, the correlation is lower, corresponding to "low consumable demand," which is consistent with reality (simple text printing consumes less consumables).

[0148] The working principle of the above technical solution is as follows: First, the cosine similarity between the current text to be printed and the historical printing feature vectors is normalized to eliminate the difference in dimensions; the normalized cosine similarity is compared with a preset reference value to divide it into a first vector dataset with high similarity and a second vector dataset with low similarity; then, the average text proportion of each printing feature vector in the two datasets and the average text proportion of the text to be printed itself are retrieved; finally, based on the dataset classification results, combined with the printing consumable index of the printer control terminal, the normalized cosine similarity between each vector and the text to be printed, the text proportion difference, similarity and consumable index are integrated to quantify the correlation between the current printing task and the user's consumable habits.

[0149] The above technical solution achieves the following effects: By dividing the dataset according to a preset similarity threshold, high-similarity historical tasks dominate the correlation calculation, while low-similarity tasks serve as auxiliary references, avoiding interference from irrelevant historical data and enhancing the correlation's ability to capture core similarity features. Introducing the average text proportion as a key parameter, combined with cosine similarity and consumable index, ensures that the correlation not only reflects overall feature similarity but also the matching degree of specific content attributes (such as text density), improving the granularity of correlation analysis. Through hierarchical processing and multi-parameter fusion, even when faced with uneven similarity in historical data, the above methods can effectively distinguish between key and secondary information, ensuring the stability and effectiveness of the correlation in diverse printing scenarios.

[0150] On the other hand, existing technologies often assume that "high similarity leads to completely identical consumable consumption patterns." However, in reality, even if text features are similar, subtle differences such as resolution and edge complexity can still result in significantly different consumable consumption. This embodiment accurately captures the non-linear relationship between similarity and consumable consumption through multi-feature fusion and hierarchical weighting. This makes the correlation calculation more nuanced in high-similarity scenarios and can uncover potential patterns even in low-similarity scenarios, which is something that traditional "single similarity + single feature" methods cannot achieve. Furthermore, existing technologies typically treat consumable evaluation as an "inherent attribute of the text" (e.g., a fixed number of pages corresponds to a fixed amount of consumables), ignoring individual differences in terminal devices. This embodiment introduces a consumable index H, creating a dynamic coupling between text features and terminal characteristics. That is, the correlation of the same text on different devices will vary depending on the value of H. This "text-terminal" bidirectional adaptation capability solves the pain point of traditional evaluation methods being "highly general but weakly specific," making it particularly suitable for multi-device sharing scenarios (e.g., enterprise offices, multiple printers in the home). Furthermore, by incorporating features such as edge complexity, it can capture hidden consumable consumption points that traditional methods overlook (such as the need for higher ink volumes for printing edges of complex graphics, and the higher consumable consumption for fine text at high resolutions). These factors are easily masked in single-feature evaluations, but they are made explicit within the multi-dimensional framework of this embodiment, enabling the correlation results to reflect the "hidden consumable costs" of the text and helping users identify printing tasks that "seem simple but are actually high-consumption."

[0151] In one embodiment of the present invention, the printing parameters of the text to be printed are dynamically adjusted based on the correlation between the current text to be printed and the printing consumables of the printer control terminal and the remaining ink volume of the current printing device, including:

[0152] Retrieve the remaining ink level of the current printing device;

[0153] The text to be printed is simulated for printing according to the printing resolution set on the printer control terminal to obtain the simulated ink volume;

[0154] Compare the simulated ink volume with the remaining ink volume of the current printing device;

[0155] The printing parameters of the text to be printed are dynamically adjusted based on the comparison between the simulated ink volume and the remaining ink volume of the current printing device, combined with the correlation between the current text to be printed and the printing consumables of the printer control terminal.

[0156] Specifically, the printing parameters of the text to be printed are dynamically adjusted based on the comparison between the simulated ink volume and the remaining ink volume of the current printing device, combined with the correlation between the text to be printed and the printing consumables of the printer control terminal. This includes:

[0157] When the simulated ink volume exceeds the remaining ink volume of the current printing device, an insufficient ink volume prompt is sent to the printer control terminal, and the printing operation is not started.

[0158] When the simulated ink volume does not exceed the remaining ink volume of the current printing device, but exceeds the ink volume corresponding to a preset percentage of the remaining ink volume, the printing resolution of the text to be printed and the black density corresponding to the image portion are dynamically adjusted based on the printing resolution set on the printer control terminal and the correlation between the text to be printed and the printing consumables on the printer control terminal; wherein, the preset percentage ranges from 67% to 58%;

[0159] The adjusted print resolution is obtained using the following formula:

[0160]

[0161] in, Z d This indicates the adjusted print resolution; Z 0 indicates the print resolution set on the printer control terminal; E p This represents the absolute difference between the simulated ink volume and the remaining ink volume (preset percentage), and the percentage of ink volume relative to the full ink volume of the ink cartridge. J This indicates the correlation between the text to be printed and the printing consumables on the printer control terminal;

[0162] Furthermore, the black concentration of the adjusted image portion is obtained using the following formula:

[0163]

[0164] in, D d This indicates the black concentration of a portion of the image after adjustment. D 0 indicates the original black level of the printed image; Z d This indicates the adjusted print resolution; Z0 indicates the print resolution set on the printer control terminal; J This indicates the correlation between the text to be printed and the printing consumables on the printer control terminal;

[0165] When the simulated ink volume does not exceed the preset percentage of the remaining ink volume of the current printing device, the printing parameters of the document to be printed will not be adjusted, and the printing will be performed according to the printing resolution set by the printer control terminal and the original image black density of the printing device.

[0166] The working principle of the above technical solution is as follows: First, the remaining ink volume of the current printing device is retrieved; simultaneously, the text to be printed is simulated for printing according to the initial print resolution set by the printer control terminal, and the simulated ink volume required to complete the printing of the text is calculated. The simulated ink volume is compared with the remaining ink volume of the current printing device, and three scenarios are handled: If the simulated ink volume exceeds the remaining ink volume, a "low ink volume" prompt is sent to the printer control terminal, and printing is not started. If the simulated ink volume does not exceed the remaining ink volume, but exceeds the ink volume corresponding to a preset percentage (58%-67%) of the remaining ink volume, the print resolution and the black density of the image are dynamically adjusted based on the "correlation degree J between the text to be printed and the printing consumables of the printer control terminal". If the simulated ink volume does not exceed the ink volume corresponding to the preset percentage of the remaining ink volume, the original print resolution set by the printer control terminal and the original black density of the print device are maintained, and printing proceeds normally.

[0167] The above technical solution achieves the following effects: By combining "printing simulation and ink volume comparison," it proactively identifies the risk of insufficient ink, avoiding "printing interruptions and wasted consumables." When ink is scarce, it dynamically adjusts parameters to achieve refined ink utilization. Instead of simply and crudely reducing resolution or density, it quantifies the coupling relationship between correlation, remaining ink volume, resolution, and black density through formulas. Even with limited ink, it ensures the visual quality of images / text through "resolution-density coordinated adjustment," balancing user experience and cost. It proactively alerts users when ink is low, allowing for timely decision-making; when ink is scarce but printing is still possible, it automatically optimizes parameters without requiring manual adjustments, enhancing the intelligence and convenience of the printing process. It reduces unnecessary high ink consumption, indirectly extending the lifespan of consumables such as ink cartridges and lowering long-term printing costs. Simultaneously, the printing consumable correlation J comprehensively considers the relationship between the text to be printed and the printer control terminal's historical printing in terms of text proportion, consumable correlation, and similarity, reflecting the degree of fit between the consumable consumption pattern of the text to be printed and the historical situation of the printer control terminal. When adjusting print resolution and image black density, a higher J indicates a close correlation between the consumable consumption pattern of the text to be printed and the printer control terminal's history (especially similar tasks). Adjusting print parameters based on the consumable patterns of similar historical tasks allows for more accurate adaptation. A lower J means the text to be printed differs significantly from historical patterns, requiring more caution in adjustments. Combining J with the actual consumable consumption pattern ensures adjustments better align with expected consumable needs, preventing consumable waste or poor print quality due to improper parameter adjustments. Adjusting print parameters solely based on the relationship between simulated ink volume and remaining ink volume without considering J ignores the consumable consumption characteristics of the text itself and its correlation with the printer control terminal's historical printing data. For example, even if different texts have the same simulated ink volume and remaining ink volume relationship, the required resolution and black density adjustments will differ due to variations in their correlation with the printer control terminal's historical printing data. Combining J with the actual printing data makes adjustments more targeted and reasonable, fully utilizing the reference value of historical printing data to optimize print parameters and balance print quality with consumable usage.

[0168] On the other hand, existing technologies often trigger single parameter adjustments (such as reducing resolution only) based on a single threshold (e.g., ink level below 20%), lacking a coupled consideration of the text's inherent consumable properties and the degree of ink scarcity. This solution, through the synergy of the text's inherent consumable properties and the degree of ink scarcity, can precisely customize the resolution reduction for texts with different consumable consumption potentials and at different stages of ink scarcity. This achieves deep linkage between text characteristics, ink status, and parameter adjustment, resulting in control precision and adaptability far exceeding traditional single-factor methods. In existing technologies, resolution and black density adjustments are often independent operations, easily leading to problems such as "density mismatch after resolution reduction (e.g., blurry image)" or "resolution redundancy after density reduction (e.g., wasted ink)." This solution uses a formula to make the black density of the adjusted image portion dependent on the adjusted print resolution, allowing both to change synergistically. This naturally adapts to the "ink volume requirements under the new resolution," saving ink while maintaining maximum print quality consistency. This synergistic effect surpasses the print quality of conventional independent adjustments.

[0169] In one embodiment of the present invention, the intelligent printing parameter adjustment method further includes:

[0170] When printing a document in color, determine whether the remaining ink level is sufficient to meet the printing requirements of the document.

[0171] When the remaining amount of color ink is insufficient to meet the printing requirements of the document to be printed, retrieve the corresponding number of times color printing was converted to black and white and the historical print files of color-to-black and white printing from the user's historical printing records.

[0172] The similarity between the historical print files of the color-to-black and white printing and the current print file to be printed is compared to obtain the similarity value between each historical print file of the color-to-black and white printing and the current print file to be printed.

[0173] The feasibility assessment parameters for color-to-black printing are obtained by combining the similarity values ​​between each historical print file and the current print file to be printed with the comprehensive edge complexity of each print text.

[0174] The feasibility assessment parameters for color-to-black printing are obtained using the following formula:

[0175]

[0176] in, S a This represents the parameters for feasibility assessment of color-to-black and white printing; g represents the number of historical printouts of documents converted from color to black and white. S mj Indicates the first j The similarity score between historical print files and the current file to be printed when converting from color to black and white;Z fj Indicates the first j The overall edge complexity corresponding to the historical print files of color-to-black printing; Z f Indicates the overall marginal complexity of the text to be printed;

[0177] When the feasibility assessment parameters for color-to-black printing exceed the preset parameter threshold, it is determined that the conversion printing can be carried out, and the color-to-black printing determination result is sent to the user for confirmation.

[0178] If the user refuses to print from color to black and white, the user will be prompted to refill the color ink.

[0179] If the feasibility assessment parameters for color-to-black printing do not exceed the preset parameter threshold, the user will be prompted to replenish the color ink.

[0180] The working principle of the above technical solution is as follows: Before performing a color printing task on the document to be printed, the system first checks the remaining ink level and compares it with the ink level required for the document to be printed to determine whether the ink level meets the printing requirements, which serves as the trigger condition for subsequent processes; when the ink level is insufficient, the system automatically retrieves relevant data on "color-to-black printing" from the user's historical printing records, including the number of historical color-to-black printings and the corresponding historical printed documents, to establish a basis for comparing the current document with historical documents; the system calculates the similarity value between each historical color-to-black printing file and the current document to be printed through an algorithm, while introducing "comprehensive edge complexity" (…). Z fj , Z f — This indicator reflects the impact of the complexity of visual elements in a document (such as image edges and text layout) on the visual effect after color-to-black and white conversion. Substituting similarity and complexity into a preset formula yields parameters for evaluating the feasibility of color-to-black and white printing. S a );

[0181] Multi-branch decision execution:

[0182] like S a If the threshold is exceeded, the system determines that converting the current file from color to black and white is feasible. The system will then send the result to the user and wait for the user's confirmation before proceeding with the conversion.

[0183] If the user refuses to switch from color to black and white, the system will prompt the user to replenish the color ink;

[0184] like S a If the threshold is not exceeded (meaning the visual effect may be poor after color to black), the system will directly prompt the user to add color ink and terminate the conversion evaluation process.

[0185] The technical advantages of the above solution are as follows: Traditional color-to-black and white conversion decisions often rely solely on "file type similarity," easily overlooking the impact of "visual complexity on conversion results" (e.g., high-complexity color images may lose key information after conversion to black and white). This solution uses a formula to integrate "similarity (reflecting file content matching)" and "comprehensive edge complexity (reflecting visual conversion adaptability)" to calculate Sa. This ensures the reuse of historical effective experience while also taking into account the visual characteristics of the current file, effectively avoiding the problem of "misjudging feasibility / infeasibility due to a single factor," making the feasibility assessment more closely aligned with actual printing effect requirements. Users do not need to manually query historical records or judge the feasibility of color-to-black and white conversion; the system automatically completes data retrieval, calculation, and preliminary judgment, reducing unnecessary user operations. A "user confirmation step" is added, respecting the user's wishes when feasibility is determined (rather than forcing conversion), and clearly prompting "replenish color ink" when the user refuses or feasibility is determined. The process branches are clear, avoiding printing task delays caused by "insufficient ink + no guidance," improving operational autonomy and process smoothness. Traditional solutions abruptly terminate printing when color ink is insufficient, requiring the user to refill ink before restarting, resulting in wasted time. This solution employs a "color-to-matrix" alternative path, allowing printing to continue when feasible, avoiding interruptions due to temporary ink shortages. Furthermore, precise evaluation based on historical data reduces resource waste caused by "blind conversion leading to poor print quality (requiring reprints)," balancing efficiency and print quality. This embodiment uses "user's historical printing data" as its core basis, combined with objective indicators of document visual characteristics (integrating edge complexity), and calculates through a quantitative formula. S a This transforms the determination of "whether color can be converted to black and white" from "subjective experience judgment" to "data-driven objective calculation", reducing human intervention error, improving the scientificity and reliability of decision-making logic, and adapting to the different color-to-black and white conversion needs of different types of files (such as documents, images, and mixed text and graphics).

[0186] In one embodiment of the present invention, the intelligent printing parameter adjustment method further includes:

[0187] When the print instruction corresponding to the current print text is detected to be color print, all image areas in the print text are scanned to determine whether the image contained in the image area is a black and white image;

[0188] When the image contained in the image area is detected to be a black and white image, an early warning is issued for the current printed text in color printing, and the printing mode corresponding to the current printed document is automatically adjusted from color printing to black and white printing;

[0189] After automatically switching the printing mode of the current document from color printing to black and white printing, a print mode conversion notification is sent to the printer control terminal.

[0190] The working principle of the above technical solution is as follows: The system first determines the type of the current print instruction. When the instruction is detected as "color print," the image area scanning process is initiated. All image areas in the printed text are scanned and analyzed, with the core determination being whether the image within that area is a black and white image. If the determination result is "black and white image," the system will simultaneously perform two operations: first, issue a warning for the current color print settings; second, automatically switch the print mode from "color print" to "black and white print." After completing the automatic print mode adjustment, the system will send a "print mode conversion notification" to the printer control terminal, synchronizing the current print mode change status.

[0191] The technical benefits of the above solution are as follows: It avoids the use of color ink when only black and white images need to be printed, reducing unnecessary consumption of color ink and directly lowering the cost of consumables procurement and usage, especially suitable for high-frequency printing scenarios. It eliminates the need for manual page-by-page checking of image types in printed text and manual switching of print modes, reducing manual intervention steps, shortening print preparation time, and improving overall printing efficiency. Through "Color Printing Situation Warning," users are promptly informed of any mismatch between the actual image type and the initial print command. "Mode Conversion Notification" ensures that users or administrators are aware of the printing status in real time, preventing printing errors or information omissions due to incorrect mode settings. It reduces unnecessary color ink consumption and the generation of consumable waste, aligning with the resource conservation and environmental protection concepts of green office practices. The printer control terminal can obtain print mode conversion information in real time, facilitating unified monitoring, recording, and traceability of print tasks, improving the standardization and traceability of print management.

[0192] This invention proposes an AI-assisted intelligent printing parameter adjustment system, such as... Figure 2 As shown, the intelligent printing parameter adjustment system includes:

[0193] The vector acquisition module is used to identify the printing feature vector based on the text to be printed and obtain the printing feature vector corresponding to the text to be printed.

[0194] The printing consumables index acquisition module is used to retrieve the historical printing records of the printer control terminal corresponding to the printed text from the cloud platform, and obtain the printing consumables index corresponding to the printer control terminal based on the historical printing records; wherein, the cloud platform establishes a data connection with the printer control terminal, and the cloud platform is used to store the historical printing records of the printer control terminal;

[0195] The correlation degree acquisition module is used to obtain the correlation degree between the current text to be printed and the printing consumables of the printer control terminal based on the printing feature vector corresponding to the current text to be printed and the printing consumables index corresponding to the printer control terminal.

[0196] The dynamic adjustment module is used to dynamically adjust the printing parameters of the text to be printed based on the correlation between the current text to be printed and the printing consumables of the printer control terminal and the remaining ink of the current printing device.

[0197] The working principle of the above technical solution is as follows: First, AI algorithms are used to extract features from the text to be printed, generating a printing feature vector containing key information such as text density, font size, and image proportion, quantifying the attributes of the content to be printed; Second, based on the historical printing records of the printer control terminal, data analysis is used to mine the user's consumable usage habits, forming a corresponding printing consumable index that reflects the user's preference for consumable consumption and printing effect; Then, the feature vector of the text to be printed is correlated with the user's consumable index to calculate the consumable correlation between the two, clarifying the matching relationship between the current printing task and the user's consumable habits; Finally, combining this correlation and the real-time remaining ink volume of the printing device, the AI ​​model dynamically optimizes parameters such as printing density and resolution to achieve intelligent parameter adaptation.

[0198] The above technical solution achieves the following results: By integrating the characteristics of the text to be printed, the user's historical consumable patterns, and the real-time status of the device, it overcomes the subjectivity of traditional manual adjustments and the limitations of simple automatic adjustments, making parameter settings more closely match the attributes of the printed content and the actual situation of the device. Based on the analysis of consumable correlation, it can avoid ink waste or insufficient quality caused by unreasonable parameter settings while ensuring that the printing effect meets the user's expectations, thus optimizing consumable utilization. By incorporating consumable indices extracted from historical records into the adjustment logic, the printing parameters are made more in line with the user's long-established usage habits, reducing the frequency of manual intervention and improving operational convenience. Leveraging AI's ability to process multi-dimensional data, it can handle printing needs for different types of text (such as plain text, mixed text and images, etc.) and different ink volume states, ensuring that reasonable parameters are output in various scenarios.

[0199] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An AI-assisted-based intelligent printing parameter adjustment method, characterized in that, The intelligent printing parameter adjustment method comprises: According to the to-be-printed text, a printing feature vector is identified, and a printing feature vector corresponding to the to-be-printed text is obtained; The historical printing records of the printer control terminal corresponding to the printing text are called from the cloud platform, and a printing consumable index corresponding to the printer control terminal is obtained according to the historical printing records; wherein, the cloud platform and the printer control terminal are connected by data, and the cloud platform is used to store the historical printing records of the printer control terminal; According to the printing feature vector corresponding to the current to-be-printed text and the printing consumable index corresponding to the printer control terminal, a printing consumable correlation degree between the current to-be-printed text and the printer control terminal is obtained; According to the printing consumable correlation degree between the current to-be-printed text and the printer control terminal and the remaining ink amount of the current printing device, the printing parameters of the to-be-printed text are dynamically adjusted.

2. The method of claim 1, wherein, According to the to-be-printed text, a printing feature vector is identified, and a printing feature vector corresponding to the to-be-printed text is obtained, comprising: The to-be-printed text is scanned page by page, and text paragraph recognition is performed on each text page to obtain the text proportion corresponding to each text page, and it is judged whether each text page has an image area; When the text page has an image area, the resolution and edge complexity of the image contained in the image area are obtained; According to the text proportion corresponding to each text page and the resolution and edge complexity of the contained image, a printing feature vector corresponding to the to-be-printed text is obtained.

3. The method of claim 2, wherein, The edge complexity of the image contained in the image area is obtained, comprising: The edge pixel proportion in eight directions of the image contained in the image area is extracted; A plurality of target directions are determined according to a direction filtering strategy; The direction entropy corresponding to the image area is obtained by using the edge pixel proportion in the plurality of target directions of the image contained in the image area; The edge chain codes corresponding to the three directions with the largest edge pixel proportion are selected, and the curvature fluctuation coefficient of the image contained in the image area is obtained by calculating the deviation of the curvature and the average curvature of the chain code points, the distance from the chain code points to the image center, the corresponding edge pixel proportion and the total length of the edge. The edge complexity of the image contained in the image area is obtained by using the direction entropy corresponding to the image area and the curvature fluctuation coefficient corresponding to each edge chain code.

4. The method of claim 2, wherein the print parameter is adjusted based on the print parameter adjustment information. According to the text proportion corresponding to each text page and the resolution and edge complexity of the contained image, a printing feature vector corresponding to the to-be-printed text is obtained, comprising: The resolution and edge complexity of the image area contained in each text page are called; The comprehensive resolution and comprehensive edge complexity corresponding to the to-be-printed text are obtained according to the resolution and edge complexity of the image area contained in each text page; The text proportion corresponding to each text page is called, and the average value of the text proportion corresponding to the to-be-printed text is obtained according to the text proportion corresponding to each text page; The average value of the text proportion, the comprehensive resolution and the comprehensive edge complexity corresponding to the to-be-printed text are taken as feature elements to generate a printing feature vector corresponding to the to-be-printed text.

5. The method of claim 1, wherein, The history printing record of the printer control terminal corresponding to the printing text is called, and a printing consumable index corresponding to the printer control terminal is obtained according to the history printing record, including: The printing parameter of the history printing record of the printer control terminal corresponding to the printing text is called, wherein the printing parameter includes a corresponding comprehensive resolution, a comprehensive edge complexity and an ink consumption of each printing; The corresponding comprehensive resolution and comprehensive edge complexity of each printing are normalized, and the normalized comprehensive resolution and comprehensive edge complexity are multiplied to obtain a printing complexity factor corresponding to each printing; The ink consumption of each printing is normalized by using the full ink amount of the ink cartridge to obtain a normalized ink consumption value corresponding to each printing; The printing complexity factor corresponding to each printing and the normalized ink consumption value are used to obtain the printing consumable index corresponding to the printer control terminal.

6. The method of claim 1, wherein, According to the printing feature vector corresponding to the current to-be-printed text and the printing consumable index corresponding to the printer control terminal, the printing consumable correlation degree between the current to-be-printed text and the printer control terminal is obtained, including: The printing feature vector corresponding to each printing in the history printing record is called; According to the printing feature vector corresponding to the to-be-printed text and the printing feature vector corresponding to each printing, a cosine similarity value between the printing feature vector corresponding to the to-be-printed text and the printing feature vector corresponding to each printing is obtained; The cosine similarity value between the printing feature vector corresponding to the to-be-printed text and the printing feature vector corresponding to each printing is combined with the printing consumable index corresponding to the printer control terminal to obtain the printing consumable correlation degree between the current to-be-printed text and the printer control terminal.

7. The method of claim 6, wherein the step of adjusting the printing parameters is performed by a user. The cosine similarity value between the printing feature vector corresponding to the to-be-printed text and the printing feature vector corresponding to each printing is combined with the printing consumable index corresponding to the printer control terminal to obtain the printing consumable correlation degree between the current to-be-printed text and the printer control terminal, including: The cosine similarity value between the printing feature vector corresponding to the to-be-printed text and the printing feature vector corresponding to each printing is normalized to obtain a normalized cosine similarity; The normalized cosine similarity is compared with a preset similarity reference value; The printing feature vector corresponding to each printing corresponding to the normalized cosine similarity value not lower than the preset similarity reference value is taken as a first vector data set; The printing feature vector corresponding to each printing corresponding to the normalized cosine similarity value lower than the preset similarity reference value is taken as a second vector data set; The average value of the text proportion, the comprehensive resolution and the comprehensive edge complexity in each printing feature vector in the first vector data set and the average value of the text proportion, the comprehensive resolution and the comprehensive edge complexity in each printing feature vector in the second vector data set are called; The average value of the text proportion, the comprehensive resolution and the comprehensive edge complexity in the printing feature vector corresponding to the to-be-printed text are called; The average proportion of characters, the comprehensive resolution, and the comprehensive edge complexity in the printing feature vector corresponding to the text to be printed are combined with the average proportion of characters, the comprehensive resolution, and the comprehensive edge complexity in each printing feature vector in the first vector data set and the average proportion of characters, the comprehensive resolution, and the comprehensive edge complexity in each printing feature vector in the second vector data set, and the printing consumable index corresponding to the printer control terminal to obtain the printing consumable correlation degree of the current text to be printed and the printer control terminal.

8. The method of claim 1, wherein, The printing parameters of the text to be printed are dynamically adjusted according to the printing consumable correlation degree of the current text to be printed and the printer control terminal and the remaining ink amount of the current printing device, including: The remaining ink amount of the current printing device is called; The text to be printed is simulated according to the printing resolution set by the printer control terminal to obtain a simulated ink amount; The simulated ink amount is compared with the remaining ink amount of the current printing device; The printing parameters of the text to be printed are dynamically adjusted according to the comparison result between the simulated ink amount and the remaining ink amount of the current printing device and the printing consumable correlation degree of the current text to be printed and the printer control terminal.

9. The method of claim 8, wherein, The printing parameters of the text to be printed are dynamically adjusted according to the comparison result between the simulated ink amount and the remaining ink amount of the current printing device and the printing consumable correlation degree of the current text to be printed and the printer control terminal, including: When the simulated ink amount exceeds the remaining ink amount of the current printing device, an insufficient ink amount prompt is sent to the printer control terminal, and the printing operation is not started; When the simulated ink amount does not exceed the remaining ink amount of the current printing device but exceeds the ink amount corresponding to a preset percentage of the remaining ink amount, the printing resolution set by the printer control terminal and the printing consumable correlation degree of the text to be printed and the printer control terminal are combined to dynamically adjust the printing resolution of the text to be printed and the black density corresponding to the image part; wherein the preset percentage is 67%-58%; When the simulated ink amount does not exceed the ink amount corresponding to the preset percentage of the remaining ink amount of the current printing device, the printing parameters of the text to be printed are not adjusted, and the printing is performed according to the printing resolution set by the printer control terminal and the original image black density of the printing device.

10. An AI-assisted based intelligent printing parameter adjustment system, characterized in that, The intelligent printing parameter adjustment system includes: A vector acquisition module is configured to identify a printing feature vector of a text to be printed and acquire a printing feature vector corresponding to the text to be printed; A printing consumable index acquisition module is configured to call historical printing records of a printer control terminal corresponding to a printing text from a cloud platform, and acquire a printing consumable index corresponding to the printer control terminal according to the historical printing records; wherein the cloud platform is connected with the printer control terminal, and the cloud platform is configured to store the historical printing records of the printer control terminal; An association degree acquisition module is configured to acquire a printing consumable association degree of a current text to be printed and a printer control terminal according to a printing feature vector corresponding to the current text to be printed and a printing consumable index corresponding to the printer control terminal. The dynamic adjustment module is configured to dynamically adjust the printing parameter of the text to be printed according to the current text to be printed, the printing consumable association degree of the printer control terminal, and the remaining ink amount of the current printing device.

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