Image semantic-based thermal printing heat load control method and thermal printing device

Abstract

The application provides a thermal load control method and a thermal printing device based on image semantics. The method includes the following steps: performing semantic segmentation on a to-be-printed image to divide a pixel region into a text line area and an image filling area; establishing a virtual thermal load integral model; using the model to predict a thermal load accumulation trend of a print head according to a black pixel proportion of print content line by line; comparing a prediction result of the model with a preset safety threshold; and starting a dynamic control strategy when the prediction result exceeds the safety threshold.

Description

Technical Field

[0001] This invention relates to the field of thermal printing control technology, specifically to a thermal printing heat load control method based on image semantics and a thermal printing device using this method. Background Technology

[0002] Thermal printing technology, with its advantages of simple structure, low noise, and fast response, has been widely used in portable printing devices, especially in the field of education where it has shown significant value in error correction printers.

[0003] Currently, most thermal printers on the market rely on fixed image processing mechanisms, such as using a globally uniform binarization threshold or a preset dithering matrix, to directly convert the input image into print data and drive the printhead heating element. While this open-loop control method can maintain basic functionality when handling routine content, it reveals deeper flaws when faced with complex printing tasks: When printing large areas of black continuously, such as solid shapes in geometry problems or dark shadows in photographs, the heat from the print head cannot dissipate in time and continues to accumulate. This causes subsequent printed content to exhibit thicker lines, blurred details, or even become completely blurred, severely damaging output quality. Furthermore, error-printing scenarios often involve a mix of high-precision fine lines (such as text strokes or geometric outlines) and high-density color blocks (such as image areas or shadow fills). A uniform image processing strategy struggles to balance these two requirements: if parameter settings favor text clarity, image areas are prone to excessive black distortion; if image layering is optimized, broken or missing strokes often appear in the text.

[0004] In existing technologies, some solutions attempt to introduce a closed-loop feedback mechanism of "print-scan-analysis-adjustment" to screen heating strategies through post-printing correction. However, this method can only remedy the situation after printing is complete and cannot predict and intervene in instantaneous heat accumulation in real time during the printing process. As a result, the problem of blurred text cannot be avoided even when printing large areas of black blocks. This highlights the core contradiction in the field of thermal printing: how to proactively prevent physical defects caused by heat accumulation under continuous high-density printing conditions, while meeting the differentiated quality requirements for different areas in mixed text and graphics scenarios. Existing technologies have not yet provided an effective real-time preventive solution. Summary of the Invention

[0005] The purpose of this invention is to provide a thermal printing heat load control method and thermal printing equipment based on image semantics, which has the advantages of effectively preventing the smudged text phenomenon caused by heat accumulation in the print head, while meeting the differentiated quality requirements of different areas in mixed text and image layout.

[0006] This invention provides a thermal load control method for thermal printing based on image semantics, comprising the following steps: Obtain the image to be printed, perform semantic segmentation on the image to be printed, and divide the pixel region into text line area and image fill area; A virtual heat load integral model is established, and the heat load accumulation trend of the print head is predicted line by line based on the proportion of black pixels in the printed content. The prediction results of the model are compared with a preset safety threshold. When the prediction result exceeds the safety threshold, a dynamic control strategy is activated. The dynamic control strategy includes: In the first control mode, the jitter parameters are dynamically adjusted for the image filling area to reduce the density of physical heating points per unit area; and / or, in the second control mode, the transmission rhythm of the printing data is dynamically adjusted according to the prediction result, and a heat dissipation gap is inserted between adjacent printing data blocks to enable the print head to perform passive heat dissipation.

[0007] Furthermore, the virtual heat load integral model is specifically a thermal accumulation bucket model, which calculates the predicted heat load value T of the current print row using a recursive formula. n The recursive formula is: T n =T n 1×α+BPR n ×β; where T n 1 represents the residual heat from the previous printed line, BPR n The percentage of black pixels in the current printed line; α is the thermal decay coefficient, and β is the heating response coefficient.

[0008] Furthermore, the thermal attenuation coefficient α and the heating response coefficient β are obtained through experimental calibration, including: Calibrate β: Print a completely black image continuously, and calculate the average temperature rise per row based on the temperature rise curve of the physical temperature sensor, which is used as the initial β value; Calibrate α: Calculate the temperature retention ratio within a single line printing cycle based on the printhead's natural cooling curve, and use it as the initial α value; Correction: Substitute the initial α value and the initial β value into the model and run it. Compare the prediction error with the high-precision thermocouple measured curve. Fine-tune the coefficients using the least squares method until the prediction error is less than the preset threshold.

[0009] Furthermore, the semantic segmentation is specifically lightweight semantic segmentation, which identifies high-frequency signals and sparse pixel regions as text line regions through connected component analysis or edge detection algorithms; identifies low-frequency signals and dense pixel regions as image filling regions; performs height-ratio binarization processing on the text line regions; and marks the image filling regions as heat load control processing regions.

[0010] Furthermore, the first control mode is specifically dynamic dithering sparsity processing: the default dithering matrix currently used for the image filling area is switched to a preset sparse dithering matrix; wherein, the number of physical heating points corresponding to the sparse dithering matrix is ​​less than that of the default dithering matrix; the sparse dithering matrix includes more than one, each sparse dithering matrix having a different degree of sparsity, and the corresponding matrix is ​​selected from the plurality of sparse dithering matrices for switching based on the closeness of the predicted heat load value to the safety threshold.

[0011] Furthermore, the sparse dithering matrix is ​​a matrix generated by performing logical operations on the default dithering matrix and a preset mask; the preset mask is a checkerboard mask or an interlaced dot matrix mask, used to set the pixels at specific coordinate positions in the default dithering matrix to a non-printing state.

[0012] Furthermore, the second control mode specifically involves microslice cooling frame interpolation: dynamically cutting the transmission length of the printed data packets according to the predicted heat load value, and inserting cooling delay instructions between adjacent data packets; the microslice cooling frame interpolation includes hierarchical adjustment logic: When the predicted heat load value reaches a first preset percentage of the safety threshold, the data packet length is reduced to the first packet length value, and a first delay is inserted; When the predicted heat load value reaches a second preset percentage of the safety threshold, the data packet length is reduced to the second packet length value, and a second delay is inserted; When the predicted heat load value falls below the third preset percentage of the safety threshold, the maximum transmission packet length is restored.

[0013] Furthermore, the dynamic control strategy also includes an edge compensation algorithm: When the first line boundary of a large area of ​​image filling is detected, the heating energy is increased to compensate for insufficient printhead preheating. When the tail boundary of a large area of ​​image filling is detected, heating is stopped in advance, and the residual heat of the print head is used to complete the color development.

[0014] Furthermore, the method also includes a low power protection mode: detecting the battery power of the thermal printer, and if it is lower than a preset threshold, forcibly activating the first control mode or the second control mode.

[0015] Furthermore, the present invention also proposes a thermal printing apparatus comprising: The printhead contains multiple heating elements for heating and developing colors on thermal paper; processor; Memory, which stores computer program instructions; A communication interface for receiving image data to be printed; Paper feed motor, used to drive the thermal paper forward; When the processor executes the program instructions in the memory, it implements the above-mentioned thermal printing thermal load control method based on image semantics.

[0016] As can be seen from the above, the thermal printing heat load control method and thermal printing device based on image semantics provided by the present invention distinguishes between text line areas and image fill areas through semantic segmentation, establishes a heat load prediction model and dynamically activates the control strategy, effectively preventing the blurring phenomenon caused by heat accumulation in the print head, while meeting the differentiated quality requirements for different areas in mixed text and image layout.

[0017] Compared with the prior art, the present invention also has the following beneficial effects: 1. Eliminate the effects of thermal inertia to ensure consistent printing quality of long images. Current thermal printing technology uses a globally uniform driving method. When the print head continuously heats a large area of ​​black material, heat accumulates rapidly on the semiconductor substrate and cannot be dissipated in time, causing subsequent printed lines to become thicker, stick together, or even blur into a mess. This thermal inertia effect is particularly pronounced when printing geometric figures and long passages in error correction notebooks, severely affecting readability.

[0018] This invention establishes a virtual heat load integral model and uses a recursive relationship to predict the cumulative heat load trend of the printhead line by line. When the predicted value exceeds the safety threshold, the system activates a second control mode—micro-slice cooling frame interpolation—dynamically cutting the print data packet according to the heat load level and inserting it into the heat dissipation gap, forcing the printhead to passively dissipate heat in the gaps between large black areas. Simultaneously, the edge compensation algorithm increases heating energy to compensate for insufficient preheating when entering the first line of a large image area and terminates heating early at the last line to utilize residual heat. Through the collaborative mechanism of "prediction-slicing-compensation," this invention suppresses the traditional smoothly rising temperature curve into a sawtooth fluctuation, always keeping the temperature below the safety threshold, completely eliminating the influence of thermal inertia, and ensuring complete consistency of clarity at the beginning and end when printing long images.

[0019] 2. Resolve display conflicts in scenarios involving mixed text and images. Error-prone scenarios typically involve both fine lines (text, geometric shapes) and large blocks of color (images, shadows). Traditional algorithms use a single binarization or dithering threshold, leading to a dilemma: increasing contrast to ensure text clarity results in overly dark image areas and loss of detail; optimizing image detail, however, can cause broken strokes in the text. This contradiction has long plagued the design of image processing algorithms for portable printing devices.

[0020] This invention utilizes lightweight semantic segmentation technology, employing connected component analysis or edge detection algorithms to automatically identify text line areas and image fill areas. For text line areas, high contrast is maintained to ensure clear and sharp strokes. For image fill areas, dynamic dithering sparsity processing is used, switching the default dithering matrix to a sparse dithering matrix (such as a matrix generated based on a checkerboard mask) based on heat load prediction results. While preserving the visual hierarchy of the human eye, the physical heating points in the image fill area are significantly reduced, thus lowering the heat load and avoiding image distortion. Through this partitioning strategy, this invention achieves optimal visual balance in mixed text and image layout scenarios, ensuring that both text and images in error-correction printing achieve ideal results.

[0021] 3. Enhance the power supply robustness of portable devices and eliminate white bar defects. Portable printers are mostly powered by lithium batteries, whose voltage fluctuates drastically with the printing load. When printing heavy content (such as large black areas), the instantaneous current can be too high, causing a drop in system voltage and insufficient heating power. This can result in irregular white streaks or faded text on the paper. This defect is particularly severe when the battery is low, directly affecting the success rate of printing jobs.

[0022] This invention utilizes pre-calculation of thermal load to automatically trigger a dynamic control strategy when a high-load area is detected by the virtual thermal load integral model. The first control mode (dynamic jitter sparsity reduction) lowers the density of heating points per unit area, reducing instantaneous current demand at the source. The second control mode (micro-slice cooling interpolation) disperses continuous high current consumption into multiple small current pulses, preventing voltage drops. In low-battery protection mode, the system forcibly activates a high-sparseness matrix and micro-slice strategy, maintaining stable print density even when the battery voltage is below a preset value, preventing forced shutdown. This invention significantly improves the portable printer's adaptability to power supply fluctuations, fundamentally eliminating white bar defects caused by voltage drops.

[0023] 4. Extends printhead life and is compatible with low-cost consumables. The printhead is the most expensive consumable component in a thermal printer. In current technology, prolonged exposure to extreme high temperatures accelerates printhead aging, leading to issues such as heating element burn-out and needle breakage. Furthermore, high-quality printing places stringent demands on the thermal paper coating; inferior paper is prone to overheating and blackening at high temperatures, resulting in print failures and high user costs.

[0024] This invention uses software algorithms to consistently control the printhead temperature below a safe threshold, avoiding physical overheating damage and significantly extending the printhead's lifespan. Simultaneously, the gentle heating strategy allows the device to be compatible with cheaper, thinner-coated third-party thermal papers. Through the combined effects of sparse shaking and micro-slice cooling, even low-quality paper will not turn black or show through due to overheating. This feature significantly reduces long-term operating costs for users and enhances the product's market competitiveness. Attached Figure Description

[0025] Figure 1 This is a flowchart of a method according to an embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram comparing the heat load control effects of embodiments of the present invention with those of existing technologies.

[0027] in: The red horizontal line represents the safety threshold. The existing technology (gray line) is a continuously rising curve, which leads to blurred characters when it exceeds the threshold; The present invention (orange line) is serrated. Detailed Implementation

[0028] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some, not all, of the embodiments of this invention. The following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0029] Traditional thermal printing technologies typically employ fixed image processing algorithms when handling complex content. This leads to heat buildup in the print head when printing large areas of black continuously, resulting in thicker, blurrier, or even smudged prints. Furthermore, in scenarios involving mixed text and images, a uniform algorithm struggles to balance text clarity with image detail, resulting in less than ideal print quality. Existing thermal management solutions often rely on post-processing correction, failing to proactively prevent instantaneous heat buildup and neglecting the differentiated print quality requirements of different areas in mixed text and image scenarios.

[0030] To address this, the present invention proposes a thermal load control method for thermal printing based on image semantics, comprising the following steps: The image to be printed is obtained, and semantic segmentation is performed on the image to be printed. By analyzing the image features, the pixel area is intelligently divided into text line areas that require high contrast fidelity and image fill areas that allow thermal control optimization. A virtual heat load integral model is established, which can simulate the thermophysical characteristics of the print head and calculate and predict the heat load accumulation trend of the print head in the future based on the proportion of black pixels in the content to be printed. The prediction results of the model are compared with a preset safety threshold, which corresponds to the critical point that ensures that the printing quality does not have thermal defects (such as blurred characters or trailing). When the predicted result exceeds the safety threshold, i.e., when it is determined that the area is about to enter the overheating risk zone, a dynamic control strategy is activated; this strategy includes two co-operating control modes: The first control mode actively adjusts the jitter parameters of the image filling area identified by semantic segmentation (e.g., switching the default dense jitter matrix to a sparse matrix) to reduce the density of physical heating points per unit area. This approach can reduce the activation density of printhead heating elements per unit area at the physical level without significantly affecting human visual perception, fundamentally reducing heat generation. And / or, The second control mode dynamically adjusts the transmission rhythm of the entire printing data according to the predicted heat load value. Specifically, it cuts the large data packets that were originally sent continuously into smaller data blocks and forcibly inserts tiny heat dissipation gaps (delays) between each data block. These gaps can be used to control the paper feed motor to pause or slow down, breaking the continuous heating process of the print head and forcing it to use the gaps for passive heat dissipation, thereby keeping the temperature below the safe red line.

[0031] Through the above-mentioned "prediction-segmentation-dual-mode intervention" technical solution, the present invention achieves active and precise control of the thermal state of the printhead.

[0032] For ease of understanding, the following explains some key terms in this embodiment: The image to be printed refers to the original image data that needs to be output to thermal paper by a thermal printing device. It can contain various visual elements such as text, lines, graphics, and pictures.

[0033] Semantic segmentation refers to classifying each pixel in an image into a predefined semantic category. In this method, it is used to identify and divide the pixel regions of the image to be printed into regions with different printing characteristics, such as text line areas and image fill areas.

[0034] Text line areas refer to pixel regions identified during semantic segmentation as containing high-frequency details such as text, fine lines, or geometric outlines. These areas typically require high printing precision and contrast.

[0035] Image fill regions refer to pixel areas identified during semantic segmentation as containing low-frequency, pixel-dense information such as large areas of color blocks, images, or shadows. These areas are prone to heat accumulation during printing.

[0036] A virtual heat load integral model is a mathematical model used to simulate and predict the heat accumulation state of a printhead during continuous printing. This model assesses the heat load level of the printhead in real time by calculating parameters such as the percentage of black pixels in the printed content.

[0037] Black pixel percentage refers to the proportion of black pixels to the total number of pixels in a specific printed line or area. This proportion is an important parameter for assessing the impact of printed content on the print head's thermal load.

[0038] The heat load accumulation trend refers to the pattern of change in the internal temperature or heat of the printhead over time or during the printing process under continuous operation. Predicting this trend helps to identify potential overheating risks in advance.

[0039] The safety threshold refers to the preset upper limit of printhead heat load. When the predicted cumulative heat load exceeds this threshold, it indicates that the printhead is at risk of overheating, and corresponding control measures need to be initiated.

[0040] Dynamic control strategy refers to a series of measures automatically initiated by the system to adjust printing parameters when the predicted printhead thermal load exceeds a safe threshold. This strategy aims to proactively reduce printhead temperature, prevent overheating damage, and ensure print quality.

[0041] Dithering parameters are parameters used to control the distribution and density of heated dots when converting an image into print data. By adjusting the dithering parameters, the sparsity of the printed dot matrix can be changed.

[0042] Physical heating point density refers to the number of dots that are actually heated and developed in color on a unit area of ​​thermal paper. Reducing this density can effectively reduce the heat output of the printhead in localized areas.

[0043] The transmission rate of print data refers to the speed and frequency at which print data is sent from the controller to the print head. Adjusting this rate controls the activation interval of the print head heating element.

[0044] A heat dissipation gap refers to a non-printing time period artificially inserted between consecutive printed data blocks. During this time period, the printhead heating element is not activated, thus achieving passive heat dissipation.

[0045] Passive cooling refers to the process by which the printhead dissipates heat through natural convection, conduction, and radiation without external active cooling measures.

[0046] This embodiment provides a thermal load control method for thermal printing based on image semantics. First, the image to be printed needs to be acquired, which can be obtained from scanning, photography, or digital files. After acquisition, semantic segmentation processing is performed on the image to divide the pixel regions in the image into regions with different printing characteristics. For example, a simple threshold segmentation method based on pixel grayscale values ​​or color information can be used to roughly divide the image into foreground and background regions. Subsequently, through manual judgment or simple area analysis, regions containing text or thin lines are marked as text line areas, and large areas of color blocks are marked as image fill areas. As another implementation method, the operator can use image editing software to manually select the text and image regions in the image and mark them respectively.

[0047] Furthermore, this method establishes a virtual heat load integral model. This model is used to simulate and predict the heat accumulation state of the printhead during continuous printing. For example, a simple accumulation model can be established, where the black pixel ratio of each printed line is directly multiplied by a fixed coefficient and then accumulated to the current heat load value. When the printhead is not heated, the heat load value decreases at a fixed decay rate. As another implementation, a large number of experiments can be conducted beforehand to record the printhead temperature changes under different black pixel ratios and continuous printing times, and an empirical lookup table can be generated. During actual printing, based on the black pixel ratio of the current line, the corresponding heat load increment is retrieved from the lookup table and accumulated to the current heat load value. This model predicts the heat load accumulation trend of the printhead line by line based on the black pixel ratio of the printed content.

[0048] Subsequently, the model's prediction results are compared with a preset safety threshold. This safety threshold can be a fixed heat load value. During the printing process, the prediction results of the virtual heat load integral model are directly compared with this fixed value. Alternatively, a dynamic safety threshold that changes over time or with the environment can be preset based on factors such as the printing equipment's operating time or ambient temperature.

[0049] The security threshold Defined as the virtual heat product value corresponding to the critical physical temperature for ensuring print quality. It is set based on empirical data. For example, the selected thermal paper will exhibit severe "tailing" or "smearing" when the printhead temperature exceeds 70°C. Therefore, we set 70°C as the safety threshold. If the model directly outputs degrees Celsius, then... = 70℃.

[0050] When the model predicts value When the system detects an overheating risk, it immediately triggers a dynamic control strategy. For example, when the prediction result first exceeds the safety threshold, the system immediately activates the preset dynamic control strategy. Alternatively, to avoid frequent switching of control modes, after the prediction result exceeds the safety threshold, a short confirmation period can be waited, or the dynamic control strategy can be activated only after multiple consecutive prediction results exceed the threshold.

[0051] The dynamic control strategy includes any combination of the first control mode, the second control mode, and the third control mode: The first control mode dynamically adjusts the dithering parameters for the image fill area to reduce the density of physical heating points per unit area. Specifically, two dithering matrices can be preset: a default regular dithering matrix and a sparse dithering matrix. When it is necessary to reduce the density of physical heating points, the system switches the printing data processing of the image fill area from the default dithering matrix to the sparse dithering matrix. The sparse dithering matrix reduces density by decreasing the number of printing points. As another implementation method, random sparsity can be used in the image fill area. For example, after binarizing the image, some black pixels are randomly skipped with a certain probability, preventing them from being printed. This probability can be adjusted based on the heat load prediction results.

[0052] The second control mode dynamically adjusts the transmission rhythm of print data based on the prediction results, inserting heat dissipation gaps between adjacent print data blocks to allow the print head to passively dissipate heat. For example, when the prediction results meet the conditions for activating the second control mode, the system can insert a preset fixed-duration cooling delay after each fixed-size print data block is transmitted. Alternatively, the print data packet can be divided into data blocks of different sizes. When the second control mode needs to be activated, the system divides the print data packet into smaller data blocks and inserts a fixed-duration cooling delay after each data block is transmitted. Smaller data blocks mean more frequent delay insertions.

[0053] The third control mode: This method performs semantic segmentation on the image to distinguish between text line areas and image fill areas, and establishes a virtual heat load integral model to predict the heat load accumulation trend of the printhead, thereby proactively identifying potential overheating risks. When the prediction result exceeds the safety threshold, a dynamic control strategy is activated, including adjusting the jitter parameters to reduce the density of physical heating points, or adjusting the print data transmission rhythm to insert heat dissipation gaps. Therefore, this method effectively prevents physical defects such as blurred or thickened print content caused by heat accumulation during continuous high-density printing of thermal printers, while ensuring the differentiated print quality requirements of different areas in mixed text and image scenarios, improving print quality and equipment reliability.

[0054] The third control mode is the edge compensation algorithm, which includes: increasing heating energy when the first line boundary of a large area of ​​image filling is detected to compensate for insufficient preheating of the print head; and terminating heating in advance when the last line boundary of a large area of ​​image filling is detected, using the residual heat of the print head to complete the color development.

[0055] This invention further proposes that the virtual heat load integral model is specifically a thermal bucket model. The system scans the data line by line, calculates the black pixel ratio (BPR) of each line, and calculates the predicted heat load value T of the current line using a recursive formula. n The recursive formula is: T n =T n 1×α+BPR n ×β; where T n 1 represents the residual heat from the previous printed line, BPR n The percentage of black pixels in the current printed line; α is the thermal decay coefficient, and β is the heating response coefficient.

[0056] Specifically, the thermal bucket model is a physical model that treats the printhead as a "thermal bucket" with heat input and output capabilities. It can simulate the dynamic thermal behavior of the printhead during continuous printing with relatively low computational complexity. This is achieved by employing the recursive formula T... n =T n 1×α+BPR n ×β allows for efficient line-by-line updates of the printhead's predicted heat load, meeting the demands of real-time printing scenarios. The formula logic is: Current line predicted temperature = (Residual heat from the previous line * Attenuation coefficient) + (Current line BPR * Heating coefficient). If the current line predicted temperature exceeds a set safety threshold, dynamic control is triggered.

[0057] In this recursive formula, T n T represents the predicted heat load value after the current printed line is completed, which is also the virtual predicted temperature (unit: dimensionless heat product or mapped degree Celsius) at the end of the nth line printing, reflecting the instantaneous thermal state of the print head. n 1 indicates that heat remains in the print head after the previous line has finished printing and before the current line begins printing, demonstrating the cumulative effect of heat. (BPR) nα is the percentage of black pixels in the current printed line, ranging from [0, 1] (0 for all white, 1 for all black). It directly quantifies the main contribution of the current line's printed content to the heat input. The more black pixels, the higher the heating point density, and the greater the heat input. α is the heat decay coefficient, which characterizes the proportion of heat lost by the printhead through natural heat dissipation in a single printing cycle (e.g., from the end of the previous line to the start of the current line). It characterizes the printhead's natural heat dissipation capacity during the interval between two lines of printing, ranging from (0, 1). Its value is usually determined experimentally or empirically, reflecting the combined influence of printhead materials, structure, and environmental heat dissipation conditions. β is the heating response coefficient, which represents the contribution of the unit black pixel percentage to the printhead's heat load, i.e., the efficiency of the printhead heating element in converting electrical energy into heat energy and transferring it to the thermal paper. It characterizes the temperature rise of the printhead per line when printing an all-black line. It reflects the heating capacity of the printhead heating element and the color sensitivity of the thermal paper. Its value is also determined experimentally or empirically and is an important indicator for measuring the printhead's heating performance.

[0058] By concretizing the virtual heat load integral model into a heat accumulation bucket model and using a recursive formula to calculate the predicted heat load value, this invention can accurately simulate the dynamics of heat accumulation and dissipation of the printhead during continuous printing. Wherein, T n 1 reflects the cumulative effect of heat, BPR n The model directly correlates with the heat input of the current row, while the heat attenuation coefficient α and heating response coefficient β quantify the printhead's heat dissipation capacity and heating efficiency. This model is not only computationally efficient, meeting the needs of real-time prediction, but also has clear physical meaning, accurately capturing the thermal behavior of the printhead. Therefore, when the prediction results are compared with preset safety thresholds, it can more promptly and accurately determine whether the printhead faces overheating risks, thus providing a reliable basis for activating the first or second control mode, effectively preventing printhead damage or print quality degradation, while optimizing printing efficiency.

[0059] This invention further proposes that the thermal attenuation coefficient α and heating response coefficient β be obtained through experimental calibration. This experimental calibration method includes: (1) Calibration steps for β: Under room temperature conditions, control the printer to continuously print N lines of completely black content (BPR=1), ignore heat dissipation, record the temperature rise curve of the physical temperature sensor, and calculate the average temperature rise value per line as the initial value. Values ​​(e.g.: That is, by continuously printing a completely black image, the average temperature rise per line is calculated based on the temperature rise curve of the physical temperature sensor, and this value is used as the initial β value. Specifically, when the printhead continuously outputs a completely black image, all its heating elements are activated, causing the printhead temperature to rise continuously. At this time, the temperature change of the printhead is monitored and recorded in real time by a physical temperature sensor (such as a thermistor or thermocouple) integrated near the printhead, forming a temperature rise curve. By analyzing this curve, especially in the stage after the temperature rise tends to stabilize, the average temperature rise caused by printing one line can be calculated. This average temperature rise per line directly reflects the response characteristics of the printhead under maximum heating load, and is therefore used as the initial estimate of the heating response coefficient β.

[0060] (2) Calibration steps for α: Stop heating and record the cooling curve of the printhead temperature naturally decreasing over time. Calculate the temperature retention ratio within a single line printing cycle time (e.g., 10ms) as... Values ​​(e.g.: = 0.98, meaning 2% heat dissipation per line interval). That is, based on the printhead's natural cooling curve, the temperature retention ratio within a single line printing cycle is calculated as the initial value of α. Specifically, after the printhead stops heating, its temperature gradually decreases due to natural heat dissipation. A physical temperature sensor continuously monitors and records the temperature change of the printhead over time in an unheated state, i.e., the natural cooling curve. Simultaneously, the length of a single line printing cycle is determined. By extracting a time segment from the natural cooling curve for a single line printing cycle, the decrease in printhead temperature during that time segment is calculated, thus yielding the temperature retention ratio. For example, if the temperature at the beginning of a cycle is T1 and at the end is T2, then α can be approximated as T2 / T1. This ratio reflects the degree of heat loss from the printhead within a single printing cycle, thus serving as an initial estimate of the heat attenuation coefficient α.

[0061] (3) Correction steps: Initial , Substitute the data into the formula and run it, then compare the results with the measured data from the high-precision thermocouple mounted on the printhead surface. Fine-tune the coefficients using the least squares method until the error between the virtual temperature curve and the physically measured curve is less than [a certain value]. That is, after substituting the initial α and initial β values ​​into the model and running it, the prediction error is obtained by comparing it with the high-precision thermocouple measured curve. The coefficients are then fine-tuned using the least squares method until the prediction error is less than a preset threshold. Specifically, the initial α and initial β values ​​obtained through the above steps are substituted into the virtual heat load integral model T. n =T n 1×α+BPR nIn the ×β step, during actual printing, high-precision thermocouples and other precision temperature measuring devices are used to measure the actual temperature of the print head in real time, and the measured temperature curve is recorded. The temperature curve predicted by the model is compared with the measured temperature curve obtained by the high-precision thermocouples to calculate the prediction error between the two. To minimize this error, optimization algorithms such as the least squares method are used to iteratively fine-tune α and β. The least squares method optimizes the values ​​of α and β by finding the combination of coefficients that minimizes the sum of the squares of the errors between the predicted and actual values. This correction process continues until the prediction error is reduced to below a preset allowable threshold, ensuring that the model has high prediction accuracy.

[0062] By employing the above technical solution, and combining experimental calibration with high-precision correction, the thermal attenuation coefficient α and heating response coefficient β can be accurately obtained. This calibration method based on actual physical response ensures that the virtual thermal load integral model has extremely high accuracy in predicting the cumulative trend of printhead thermal load. When the prediction results are compared with preset safety thresholds, its reliability is significantly improved, allowing dynamic control strategies (including the first and second control modes) to be activated at the most appropriate time. This effectively avoids the risk of printhead overheating and minimizes unnecessary sacrifices in printing speed or quality due to inaccurate predictions, significantly improving the stability and lifespan of thermal printing equipment.

[0063] In this embodiment, the semantic segmentation is specifically lightweight semantic segmentation. Through connected component analysis or edge detection algorithms, high-frequency signals and sparse pixel regions are identified as text line regions; low-frequency signals and dense pixel regions are identified as image filling regions; the text line regions are subjected to height-ratio binarization processing; and the image filling regions are marked as thermal load control processing regions.

[0064] The lightweight semantic segmentation is an optimized image processing technique designed to achieve pixel-level image classification with low computational resource consumption. Its core lies in employing simplified model structures or efficient algorithms to meet the real-time processing speed and resource constraints of thermal printing devices. This segmentation method can quickly classify each pixel in the image to be printed into a predefined semantic category, such as text line areas or image fill areas, thereby providing accurate region information for subsequent printing control.

[0065] Specifically, connected component analysis is an image processing technique used to identify interconnected regions in an image with the same or similar pixel values. In thermal printed images, text characters or fine lines typically appear as independent regions composed of a series of connected black pixels. By analyzing the geometric features of these connected components (such as area, aspect ratio, density, etc.), they can be effectively separated from the background and identified as text line areas. The edge detection algorithm focuses on identifying boundaries in an image where pixel intensity changes significantly. High-frequency signals typically correspond to areas in an image with drastic changes in brightness or color, such as the stroke edges of text or the detailed contours of an image. By detecting these edges, fine lines and text structures can be distinguished, which are often accompanied by pixel sparseness, meaning that the proportion of effective pixels (such as black pixels) is relatively low in local areas.

[0066] Correspondingly, the low-frequency signals represent areas in the image where pixel intensity changes smoothly or uniformly. These areas typically correspond to large blocks of color or continuous image content. In these areas, pixels tend to be dense, meaning that within localized regions, the proportion of effective pixels (such as black pixels) is relatively high. By identifying these low-frequency signals and pixel-dense areas, they can be accurately classified as image fill areas.

[0067] After identifying the text line area, it is subjected to high-contrast binarization to ensure the clarity and readability of the text and lines. This process converts the pixels in the text line area to pure black or pure white by setting an appropriate threshold, thereby maximizing the contrast between the text and the background and avoiding blurring or unclearness caused by grayscale transitions.

[0068] Simultaneously, the image fill area is marked and designated as a thermal load control processing area. This means the system will focus on the thermal load accumulation in these areas and prepare to apply corresponding dynamic control strategies. This marking mechanism allows for targeted thermal load control, avoiding unnecessary intervention in text line areas, thereby effectively managing the printhead temperature in image areas while ensuring text clarity.

[0069] By employing the above technical solution and using lightweight semantic segmentation combined with connected component analysis or edge detection algorithms, this invention can efficiently and accurately divide the image to be printed into text line areas and image fill areas. This refined distinction avoids the problems of high computational resource consumption and slow processing speed that may arise from traditional general semantic segmentation algorithms, thus meeting the real-time requirements of thermal printing. Specifically, by identifying high-frequency signals and sparse pixel areas as text line areas and performing high-contrast binarization processing, clear and sharp printing results for both text and lines are ensured. At the same time, low-frequency signals and dense pixel areas are identified as image fill areas and marked as thermal load control processing areas, enabling subsequent thermal load control strategies to accurately target the areas most in need of thermal management, effectively reducing the risk of printhead overheating, extending printhead lifespan, and optimizing overall printing efficiency while ensuring print quality.

[0070] The present invention further proposes that the first control mode is specifically dynamic jitter sparsity processing: the default jitter matrix currently used for the image filling area is switched to a preset sparse jitter matrix; wherein, the number of physical heating points corresponding to the sparse jitter matrix is ​​less than that of the default jitter matrix; the sparse jitter matrix includes more than one, each sparse jitter matrix having a different degree of sparsity, and the corresponding matrix is ​​selected from the plurality of sparse jitter matrices for switching according to the closeness of the predicted heat load value to the safety threshold.

[0071] Specifically, the dynamic dithering sparsity processing is a technique that reduces the number of activated heating elements in a thermal printhead by modifying the dithering pattern used to simulate grayscale or continuous tones. Its core lies in intentionally reducing the density of printed dots per unit area when converting image data into binary print data, thereby reducing printhead energy consumption and heat generation. In this embodiment, the dithering matrix is ​​dynamically replaced in the image filling area without changing the original grayscale. For example, a 4x4 dense matrix is ​​used under normal conditions, but automatically switches to a 4x4 sparse matrix (discarding 20% ​​of non-critical black dots) when an overheat warning is triggered. This makes the image appear slightly lighter visually, but physically reduces the number of heating points by 20%, preventing the printhead from overheating and blurring the text.

[0072] The default dithering matrix refers to the standard dithering pattern used by thermal printers under normal operating conditions to achieve optimal visual results (e.g., smooth gradations and minimal artifacts). This matrix typically does not consider the thermal load limitations of the printhead and aims to reproduce image details to the greatest extent possible.

[0073] The sparse dithering matrix is ​​a specially designed or modified dithering matrix that activates significantly fewer physical heating points than the default dithering matrix when processing the same image data. The introduction of this matrix aims to proactively reduce the thermal load on the printhead. To cope with varying degrees of thermal load, this invention can preset more than one sparse dithering matrix with different sparsity levels. For example, a lightly sparsified matrix, a moderately sparsified matrix, and a heavily sparsified matrix can be set. These matrices can be generated in various ways, such as by adjusting the threshold distribution in the default dithering matrix or by applying a specific mask to disable some print points.

[0074] In practice, the system dynamically selects the most suitable matrix from multiple sparse dithering matrices based on how close the predicted heat load value from the virtual heat load integral model is to a preset safety threshold. For example, when the predicted heat load value slightly exceeds the safety threshold, the system can choose a sparse dithering matrix with lower sparsity to moderately reduce the heat load while maintaining a certain level of print quality. Conversely, when the predicted heat load value is significantly higher than the safety threshold, the system switches to a sparse dithering matrix with higher sparsity to reduce the heat load more significantly, thereby quickly and effectively protecting the printhead. This dynamic selection mechanism based on the proximity of heat loads makes the heat load control strategy more flexible and precise.

[0075] Through the above technical solution, this invention provides a refined and adaptive thermal load control mechanism. By introducing a multi-level sparsity jitter matrix and dynamically switching it based on the proximity of the predicted thermal load value to a safety threshold, the printing device can select the most suitable degree of sparsity under different thermal load pressures. This not only effectively reduces the thermal load on the print head and prevents overheating damage, but also maximizes the balance between thermal load control and print quality. When the thermal load pressure is low, selecting a light sparsity matrix can reduce the impact on print quality; when the thermal load pressure is high, selecting a heavy sparsity matrix can rapidly reduce the temperature and ensure safe operation of the device. This hierarchical and dynamic control method significantly improves the stability and reliability of thermal printing devices when processing large-area image filling areas, while also optimizing the user experience.

[0076] In this embodiment, the sparse dithering matrix is ​​a matrix generated by performing logical operations on the default dithering matrix and the preset mask; the preset mask is a checkerboard mask or an interlaced dot matrix mask, which is used to set the pixels at specific coordinate positions in the default dithering matrix to a non-printing state.

[0077] Specifically, the sparse dithering matrix is ​​not generated by simply pre-storing multiple matrices, but rather dynamically or semi-dynamically by performing a logical operation between a default dithering matrix and a preset mask. This logical operation typically uses an AND operation; that is, when the default dithering matrix processes a pixel, if the corresponding preset mask indicates "do not print," then regardless of the original result of the dithering algorithm, that pixel will ultimately be forced to a non-printed state. This generation mechanism makes the sparse dithering matrix generation process more flexible and efficient.

[0078] The preset mask is a key component for achieving sparsity processing, and its specific form can be a checkerboard mask or a spaced dot matrix mask. A checkerboard mask is a mask with a periodic, regular pattern; for example, it can be designed to set every other pixel or every certain number of pixels to a non-printing state, forming a checkerboard-like sparse pattern. A spaced dot matrix mask can set non-printing points at specific intervals (e.g., every N pixels), or force non-printing at fixed positions. Both types of masks can reduce the print point density per unit area in a uniform and controllable manner, thereby effectively reducing the thermal load on the print head. By selecting checkerboard masks of different sizes and sparsity ratios, or adjusting the interval parameters of the spaced dot matrix mask, sparsity dithering matrices with different degrees of sparsity can be easily generated.

[0079] The following explanation uses a 4x4 jitter matrix as an example: 1. Default jitter matrix In normal mode, a standard 4x4 matrix is ​​used, with its threshold distribution uniformly covering gray levels from 0 to 255.

[0080] Feature: When the input pixel is completely black (grayscale value = 0), all 16 pixels in the 4x4 area will be lit up (heated).

[0081] Number of heating points: 16 / 16 (100% duty cycle).

[0082] 2. Sparse jitter matrix In thermal control mode, the system will perform a logical AND operation between the default matrix and a preset "chessboard mask", or directly use the modified high threshold matrix.

[0083] Specific implementation: Force pixels at specific positions in the matrix (such as diagonal positions with indices 0, 5, 10, 15, or interval positions) to be set to "not printed", regardless of the grayscale of the original image.

[0084] For example, for the same "all black" input signal, the sparse matrix forcibly discards 25% of the pixels (only 12 pixels are allowed to be printed per 4x4 block), so that it still appears black on a macroscopic level (the human eye will automatically blend them), but the number of physical heating points is reduced by 25% on a microscopic level.

[0085] Table 1: Comparison of Default Mode and Sparsity Mode Comparison Dimensions Default mode sparse thermal control mode Input grayscale All black All black Physical action 16 points full heating Heating at 12 o'clock, forced cooling at 4 o'clock Heat load 100% 75% (significantly reduced) Visual effects Deep Black A slightly lighter shade of black (but acceptable for printing out incorrect answers). Through the above technical solution, the generation of the sparse dithering matrix no longer relies on pre-storing a large number of matrices with different sparsity levels. Instead, it can be dynamically generated based on the default dithering matrix and easily generated preset masks through logical operations. This significantly reduces the system's storage space requirements and the complexity of matrix management. Simultaneously, by selecting different types or parameterized preset masks, dithering matrices with different sparsity levels can be flexibly generated, thereby more accurately matching the proximity of the current predicted heat load value to the safety threshold, achieving fine-grained heat load control. This generation method ensures the uniformity of the sparsity processing, effectively reducing the density of physical heating points per unit area, while minimizing the negative impact on print quality, enabling the print head to effectively dissipate heat in high-load areas and extending its service life.

[0086] This invention further proposes a second control mode specifically as microslice cooling frame interpolation. This processing method aims to provide the print head with more flexible and efficient heat dissipation opportunities through fine-grained control of print data transmission. Specifically, this method dynamically cuts the transmission length of print data packets according to the predicted heat load value and inserts cooling delay instructions between adjacent data packets. This method of cutting data packets and inserting delays can decompose the continuous printing heating process into multiple short-term heating and short-term cooling cycles, thereby effectively reducing the heat accumulation of the print head under long-term continuous operation. Here, the transmission length of the print data packet refers to the amount of data sent to the print head at one time, which directly affects the continuous heating time of the print head. The cooling delay instruction is an idle time inserted between data packet transmission intervals, allowing the print head to passively dissipate heat and reduce its own temperature. For example, the 1000-line data packet that was originally sent at one time can be dynamically cut according to the heat load curve: between two high-load data packets, an invisible "empty instruction" or "microsecond-level delay" is inserted, forcing the print head to "breathe" between printing large black blocks, utilizing physical passive heat dissipation.

[0087] To achieve smarter and more adaptable control under varying heat load conditions, the microslice cooling interpolation process also includes tiered adjustment logic. This logic employs different levels of control measures based on how close the predicted heat load value is to a preset safety threshold. For example, when the predicted heat load value reaches a first preset percentage of the safety threshold, the system initiates first-level control, reducing the transmission length of the current print data packet to a first packet length value and inserting a first delay. The first packet length value is typically less than the maximum transmission packet length, while the first delay provides a brief passive cooling window for the print head. As the heat load further increases, when the predicted heat load value reaches a second preset percentage of the safety threshold, the system initiates a higher level of control, further reducing the data packet length to a second packet length value and inserting a second delay. Typically, the second packet length value is less than the first packet length value, while the second delay is greater than the first delay to address higher heat load risks. This tiered adjustment mechanism ensures that printing speed is not excessively interfered with when the heat load is low, while more robust cooling measures are implemented promptly when the heat load is high. When the printhead heat load is effectively controlled and the predicted heat load value falls below the third preset percentage of the safety threshold, the system will resume the maximum transmission packet length to ensure that printing efficiency is not unnecessarily limited. The third preset percentage is usually lower than the first and second preset percentages and serves as the basis for judging whether the heat load has returned to normal.

[0088] The dynamic data packet segmentation logic is described in detail in this embodiment as follows: Initial state: When the predicted temperature Far below the safety threshold (e.g.) When the system uses the maximum transmission packet length (e.g., ...), the system will use the maximum transmission packet length. (Lines), to ensure maximum printing speed with no additional delay.

[0089] Dynamic adjustment mechanism: along with Approaching the safety threshold The system dynamically reduces the data packet size and inserts a cooling delay according to the following hierarchical logic: Level 1 alert ( (Approaching 80% of the threshold): Reduce the packet length to 500 lines and insert a 10ms delay between packets.

[0090] Level II Alert ( Approaching 95% of the threshold): drastically reduce the packet length to 50 lines (i.e., "micro-slice"), and insert a 50ms delay between packets.

[0091] The function of slicing: After the small packet is sent, the print head must be forced to stop heating for 50ms after working for 50 lines to wait for data reception (or execute an empty command). During this interval, the heat is allowed to dissipate naturally, thereby forcibly "pressing" the temperature curve into a sawtooth shape to prevent it from exceeding the safety limit.

[0092] Recovery mechanism: Once the predicted temperature is detected to have dropped to a safe range (e.g., below 70% of the threshold), the system automatically resumes large packet length transmission to ensure overall printing efficiency.

[0093] Through the above technical solution, this invention introduces micro-slice cooling frame interpolation processing, combined with graded adjustment logic, to make the thermal load control of the printhead more refined and intelligent. When the predicted thermal load value gradually increases, the system can dynamically reduce the transmission length of the print data packets and insert corresponding cooling delays according to different thermal load levels, thereby providing sufficient passive heat dissipation time for the printhead without significantly affecting printing efficiency. This graded adjustment mechanism avoids excessive or insufficient heat dissipation that may result from a single strategy, ensuring that the printhead remains within a safe temperature range under different thermal load conditions, effectively extending the printhead's lifespan and guaranteeing the stability and quality of print output.

[0094] In some of the embodiments of the present invention described above, a method for managing the thermal load of the print head is proposed through semantic segmentation, a virtual thermal load integral model, and a dynamic control strategy. However, during its implementation, when the print head suddenly enters a large-area image-filling area from a non-image area, there may be insufficient preheating, resulting in a lighter color at the beginning of printing. Conversely, when the print head is about to leave the large-area image-filling area, its temperature may still be high. If heating continues in the conventional manner, the residual heat may cause the color at the end of printing to be too dark or blurry.

[0095] To address this, the present invention further proposes that the dynamic control strategy also includes a third control mode: an edge compensation algorithm. This algorithm specifically includes: when the first line boundary of a large-area image filling region is detected, increasing heating energy to compensate for insufficient printhead preheating; and when the last line boundary of a large-area image filling region is detected, prematurely terminating heating and utilizing the residual heat of the printhead to complete color development.

[0096] The edge compensation algorithm aims to optimize printhead temperature management at the edges of image fill areas. Specifically, when the system identifies an approaching large image fill area through semantic segmentation, it detects the first-line boundary of that area. To prevent print quality degradation due to a low initial printhead temperature, the system actively increases heating energy. This increase can be achieved by extending the heating pulse width, increasing the heating voltage, or activating more heating elements than the image data itself requires, without affecting image details. The goal is to quickly raise the printhead temperature to its optimal operating state when printing the first or first few lines of a large image fill area, ensuring uniform and vibrant color development.

[0097] Accordingly, when the system detects the trailing edge of a large image filling area, indicating that printing of that area is nearing completion, considering the potential for high heat buildup in the print head after prolonged heating, continued heating in the conventional manner could lead to overheating issues such as excessively dark colors, ink dot diffusion, or blurring in the last few lines. Therefore, the edge compensation algorithm prematurely terminates heating for these trailing pixels. At this point, the residual heat stored in the print head is sufficient to complete the color development process of the thermal paper, thus avoiding printing defects caused by overheating and helping to protect the print head from unnecessary overheating stress.

[0098] Through the above technical solution, this invention effectively solves the printing quality problem at the edges of large-area image-filled areas during thermal printing. At the initial boundary of the image-filled area, by increasing heating energy, the print head is ensured to quickly reach the appropriate color development temperature, thus avoiding the phenomenon of pale or uneven color at the beginning of printing due to insufficient preheating, improving the overall consistency and visual effect of the printed image. At the ending boundary of the image-filled area, by prematurely terminating heating and utilizing the residual heat of the print head, excessive heat accumulation at the end of printing is effectively prevented from causing excessively dark or blurry colors or damage to the thermal paper, further improving the stability of print quality. This edge compensation mechanism, combined with existing dynamic thermal load control strategies, forms a more complete and refined thermal management system, enabling thermal printing equipment to output higher quality and more uniform prints when processing documents containing large-area images, while also helping to extend the lifespan of the print head.

[0099] In some embodiments of the present invention, a thermal load control method for thermal printing based on image semantics is proposed. This method manages the thermal load of the print head by dynamically adjusting jitter parameters or print data transmission rhythm to ensure print quality and device safety. However, for battery-powered thermal printing devices, even if the thermal load is within a controllable range, continuous printing operations when the battery is low can still lead to rapid battery depletion, resulting in unexpected device shutdown or print job interruption, affecting user experience and device reliability.

[0100] To address this, the aforementioned method further proposes a low-power protection mode. This mode aims to ensure the continuous and stable operation of the thermal printer when its power supply (usually a battery) is low. Its core function is to prevent the device from unexpectedly shutting down due to depleted power, ensuring the completion of critical printing tasks, and potentially extending the device's usability during low-power conditions.

[0101] This low-power protection mode includes detecting the battery level of the thermal printer. This step is used to obtain the current state of the device's battery in real time. Specifically, thermal printers typically integrate a battery management unit (BMU) or power management integrated circuit (PMIC), which continuously monitors the battery's voltage, current, and estimated remaining power. The processor reads this monitoring data to obtain the battery's real-time power information.

[0102] When the detected battery level falls below a preset threshold, the system will forcibly activate either the first control mode or the second control mode. The preset threshold is a pre-defined battery level; when the detected battery level falls below this threshold, a low-battery protection mode will be triggered. This threshold serves as a key point for initiating energy-saving measures, aiming to intervene before the battery reaches critical depletion. This threshold is typically stored in the printer control system's non-volatile memory and can be a fixed value set at the factory or a user-configurable value within a certain range, such as 20% of the battery capacity or a specific voltage value. When the detected battery level falls below the preset threshold, the printer's control logic will actively intervene and forcibly activate either the first or second control mode. This means that even if these modes are not triggered under normal thermal load management, the system will prioritize energy-saving strategies based on the low-battery state. The first control mode reduces instantaneous power consumption by dynamically adjusting jitter parameters to reduce the number of physical heating points per unit area; the second control mode reduces average power consumption by inserting cooling delay instructions between adjacent print data packets to adjust the transmission rhythm of print data. This forced activation mechanism ensures that in emergency situations where power is low, the device can immediately switch to a low-power operating state to maximize the efficiency of remaining power. The specific mode selected can be intelligently determined and switched based on preset priorities, the current type of print content, or system load.

[0103] By introducing a low-battery protection mode, this invention effectively solves the problems of unstable operation and premature shutdown that thermal printers may face when the battery level is low. When the device's battery level falls below a preset threshold, the system can promptly detect this and forcibly activate either the first or second control mode, thereby proactively reducing power consumption during the printing process. This reduction in power consumption not only significantly extends the device's operating time under low battery conditions, ensuring that users can complete ongoing printing tasks and avoiding data loss or printing interruptions due to battery depletion, but also helps protect the battery and reduce its wear and tear under low-battery, high-load conditions. Therefore, this solution further enhances the overall reliability and user experience of thermal printers while ensuring print quality and printhead safety, making it particularly suitable for mobile or offline printing scenarios.

[0104] To address the technical problems of thermal printing devices easily experiencing heat accumulation effects during continuous high-density printing, leading to blurred printed content, and the difficulty in balancing text clarity and image depth in mixed text and image scenarios, this embodiment provides a thermal printing device. The device includes a printhead containing multiple heating elements for heating and color development on thermal paper; a processor; a memory storing computer program instructions; a communication interface for receiving image data to be printed; and a paper feed motor for driving the thermal paper forward. When the processor executes the program instructions in the memory, it implements the aforementioned image semantic-based thermal printing thermal load control method.

[0105] Specifically, the method first acquires the image to be printed and performs semantic segmentation, dividing the pixel region into text line areas and image fill areas. Then, a virtual heat load integral model is established, which is used to predict the heat load accumulation trend of the print head line by line based on the proportion of black pixels in the printed content. When the prediction result exceeds a preset safety threshold, a dynamic control strategy is activated, including a first control mode and / or a second control mode. The first control mode dynamically adjusts the jitter parameters for the image fill area to reduce the density of physical heating points per unit area; the second control mode dynamically adjusts the transmission rhythm of the printing data based on the prediction result, inserting heat dissipation gaps between adjacent printing data blocks to enable passive heat dissipation of the print head.

[0106] By combining semantic segmentation technology with a virtual heat load integral model, this embodiment achieves proactive prediction and preventative control of heat load trends. Compared to existing post-correction methods, this device can dynamically adjust printing parameters before heat accumulation occurs, effectively avoiding the problem of blurred text when continuously printing large areas of black, while ensuring high contrast in text lines and rich detail in image fill areas. This allows for simultaneous satisfaction of differentiated quality requirements in mixed text and image scenarios, significantly improving the reliability and adaptability of printing results.

[0107] The following example will provide a more detailed explanation of the above technical solution: Imagine user A using a thermal printer to print a learning document containing complex content. The image data of this document includes both small text and geometric lines, as well as large areas of solid fill, such as the shaded part of a geometric shape.

[0108] First, the printing device receives the image data to be printed. The processor performs semantic segmentation on the image. Using lightweight semantic segmentation algorithms, such as combining connected component analysis and edge detection, the system can identify high-frequency signals and sparse pixel regions in the image, accurately identifying them as text line areas. Simultaneously, low-frequency signals and dense pixel regions are identified as image fill areas. For example, the borders of text and geometric shapes are marked as text line areas, while the solid shaded areas inside geometric shapes are marked as image fill areas, and further marked as thermal load control processing areas. This differentiated processing avoids the problem of traditional unified binarization algorithms failing to simultaneously maintain the desired text and image effects in mixed text and image scenarios.

[0109] During the printing process, the system establishes a virtual heat load integral model, specifically using a thermal accumulation barrel model. This model utilizes the recursive formula T. n =T n 1×α+BPR n ×β, predicts the cumulative heat load trend of the printhead line by line. Where T n 1 represents the residual heat in the print head after the previous print line has finished printing; BPR n This represents the percentage of black pixels in the current printed line. The thermal decay coefficient α and heating response coefficient β have been obtained through experimental calibration to ensure the accuracy of the model predictions. For example, when printing to a line containing a large area of ​​solid shadow, BPR... n The value will increase significantly, and the model will predict that the heat load will accumulate rapidly.

[0110] The system compares the model's predictions with preset safety thresholds in real time. When the predicted heat load value approaches or exceeds the safety threshold—for example, when the print head is about to enter or is printing the aforementioned large solid shadow area—the system immediately activates a dynamic control strategy to proactively prevent print quality degradation caused by heat accumulation.

[0111] This dynamic control strategy can include the following modes: One control mode dynamically adjusts the dithering parameters for the image fill area. When the predicted heat load value reaches a first preset percentage of the safety threshold, the system switches the default dithering matrix currently used for the image fill area to a preset sparse dithering matrix. For example, if the predicted heat load value reaches 80% of the safety threshold, the system selects a dithering matrix with medium sparsity for switching. This sparse dithering matrix is ​​generated through logical operations based on the default dithering matrix and a preset checkerboard mask, thereby reducing the number of physical heating points per unit area and lowering heat input. Compared to traditional fixed dithering matrices, this dynamic adjustment can effectively reduce the instantaneous heat load of the print head and avoid smudged text when printing large black areas, while ensuring acceptable visual effects.

[0112] Another control mode dynamically adjusts the transmission rhythm of print data based on the prediction results. When the predicted heat load value continues to rise and reaches a second preset percentage of the safety threshold, such as 90%, the system initiates micro-slice cooling frame interpolation. At this time, the transmission length of the print data packets is dynamically reduced, and cooling delay instructions are inserted between adjacent data packets. For example, the data packet length may be reduced from the maximum transmission packet length to a first packet length value, and a first delay may be inserted. If the heat load increases further, it may be reduced to a second packet length value, and a second delay may be inserted. These inserted heat dissipation gaps provide the print head with time for passive heat dissipation, effectively mitigating heat accumulation. When the predicted heat load value falls back to below a third preset percentage of the safety threshold, the system reverts to the maximum transmission packet length to ensure printing efficiency.

[0113] Furthermore, when the system detects the first line boundary of a large image-filled area, it increases heating energy to compensate for insufficient printhead preheating, ensuring clear color development of the first line. Conversely, when it detects the last line boundary of a large image-filled area, the system prematurely terminates heating, utilizing the residual heat of the printhead to complete color development and preventing overheating at the tail. These edge compensation algorithms further optimize print quality.

[0114] Through the aforementioned dynamic control strategy, this thermal printer can ensure the clarity of text and lines while avoiding blurring or smudging caused by heat accumulation in large solid shadow areas when printing user A's complex learning materials. Compared with the open-loop control or post-correction methods used in existing technologies, this solution can proactively and in real-time perform refined management based on the printing content and printhead status, significantly improving print quality and equipment stability.

[0115] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A thermal printing thermal load control method based on image semantics, characterized in that, Includes the following steps: Obtain the image to be printed, perform semantic segmentation on the image to be printed, and divide the pixel region into text line area and image fill area; A virtual heat load integral model is established, and the heat load accumulation trend of the print head is predicted line by line based on the proportion of black pixels in the printed content. The prediction results of the model are compared with a preset safety threshold. When the prediction result exceeds the safety threshold, a dynamic control strategy is activated. The dynamic control strategy includes: In the first control mode, the jitter parameters are dynamically adjusted for the image filling area to reduce the density of physical heating points per unit area; and / or, in the second control mode, the transmission rhythm of the printing data is dynamically adjusted according to the prediction result, and a heat dissipation gap is inserted between adjacent printing data blocks to enable the print head to perform passive heat dissipation.

2. The method according to claim 1, characterized in that, The virtual heat load integral model calculates the predicted heat load value T of the current printed line using a recursive formula. n The recursive formula is: T n =T n 1×α+BPR n ×β; where T n 1 represents the residual heat from the previous printed line, BPR n The percentage of black pixels in the current printed line; α is the thermal decay coefficient, and β is the heating response coefficient.

3. The method according to claim 2, characterized in that, The thermal attenuation coefficient α and heating response coefficient β were obtained through experimental calibration, including: Calibrate β: Print a completely black image continuously, and calculate the average temperature rise per row based on the temperature rise curve of the physical temperature sensor, which is used as the initial β value; Calibrate α: Calculate the temperature retention ratio within a single line printing cycle based on the printhead's natural cooling curve, and use it as the initial α value; Correction: Substitute the initial α value and the initial β value into the model and run it. Compare the prediction error with the high-precision thermocouple measured curve. Fine-tune the coefficients using the least squares method until the prediction error is less than the preset threshold.

4. The method according to claim 1, characterized in that, The semantic segmentation is specifically lightweight semantic segmentation, which uses connected component analysis or edge detection algorithms to identify high-frequency signals and sparse pixel regions as text line regions; and low-frequency signals and dense pixel regions as image fill regions. The text line regions are subjected to height-ratio binarization processing, and the image fill regions are marked as heat load control processing regions.

5. The method according to claim 1, characterized in that, The first control mode is specifically dynamic dithering sparsity processing: the default dithering matrix currently used for the image filling area is switched to a preset sparse dithering matrix; wherein, the number of physical heating points corresponding to the sparse dithering matrix is ​​less than that of the default dithering matrix; the sparse dithering matrix includes more than one, each sparse dithering matrix has a different degree of sparsity, and the corresponding matrix is ​​selected from the multiple sparse dithering matrices for switching according to the closeness of the predicted heat load value to the safety threshold.

6. The method according to claim 5, characterized in that, The sparse dithering matrix is ​​a matrix generated by performing logical operations on the default dithering matrix and a preset mask; the preset mask is a checkerboard mask or an interlaced dot matrix mask, used to set the pixels at specific coordinate positions in the default dithering matrix to a non-printing state.

7. The method according to claim 1, characterized in that, The second control mode is specifically a micro-slice cooling frame interpolation process: dynamically cutting the transmission length of the printed data packet according to the predicted heat load value, and inserting a cooling delay command between adjacent data packets; the micro-slice cooling frame interpolation process includes hierarchical adjustment logic: When the predicted heat load value reaches a first preset percentage of the safety threshold, the data packet length is reduced to the first packet length value, and a first delay is inserted; When the predicted heat load value reaches a second preset percentage of the safety threshold, the data packet length is reduced to the second packet length value, and a second delay is inserted; When the predicted heat load value falls below the third preset percentage of the safety threshold, the maximum transmission packet length is restored.

8. The method according to any one of claims 1 to 7, characterized in that, The dynamic control strategy also includes an edge compensation algorithm: When the first line boundary of a large area of ​​image filling is detected, the heating energy is increased to compensate for insufficient printhead preheating. When the tail boundary of a large area of ​​image filling is detected, heating is stopped in advance, and the residual heat of the print head is used to complete the color development.

9. The method according to any one of claims 1 to 7, characterized in that, The method also includes a low power protection mode: if the battery power of the thermal printer is detected and it is lower than a preset threshold, the first control mode or the second control mode is forcibly activated.

10. A thermal printing device, characterized in that, include: The printhead contains multiple heating elements for heating and developing colors on thermal paper; processor; Memory, which stores computer program instructions; A communication interface for receiving image data to be printed; Paper feed motor, used to drive the thermal paper forward; When the processor executes the program instructions in the memory, it implements the thermal load control method for image semantics-based thermal printing as described in any one of claims 1 to 9.

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