Method for detecting color performance of thermal paper by fusing multispectral imaging and infrared sensing

Abstract

The application discloses a thermal sensitive paper color developing performance detection method based on multispectral imaging and infrared sensing fusion, relates to the technical field of thermal sensitive paper, and comprises the following steps: obtaining a thermal sensitive heating area; based on the thermal sensitive heating area, using a multi-temperature analysis method to obtain a temperature rising gray scale curve, a temperature rising gray scale array and a stable discrete area of all thermal sensitive papers; and based on the temperature of the thermal sensitive paper heated in actual application, the color developing performance of the thermal sensitive paper is detected; the application is used for solving the problem that in the existing thermal sensitive paper color developing performance detection method, the dynamic change of the color development on the surface of the thermal sensitive paper is not analyzed due to the temperature rising caused by the heating of the thermal sensitive paper and the temperature stability, the reference data in performance detection is limited, the color developing performance detection of the thermal sensitive paper is not comprehensive enough, and the detection result deviates from the actual situation.

Description

Technical Field

[0001] This invention relates to the field of thermal paper technology, specifically a method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing. Background Technology

[0002] Thermal paper is a special type of processed paper coated with a thermal coating. Its core characteristic lies in achieving color development through a thermochemical reaction. When the printhead is heated to 200-300℃, the leuco dye in the coating undergoes an oxidation-reduction reaction with the color developer to generate black or other colored marks. The entire process does not require the participation of ink or ribbon. The testing methods for the color development performance of thermal paper mainly include the detection of density, speed, and uniformity during color development.

[0003] Existing methods for testing the color development performance of thermal paper typically involve improvements to existing color density detection methods. For example, an image of the undeveloped surface of the thermal paper and initial heating parameters are input into a pre-trained model to obtain a predicted optical density distribution image for performance testing. While this improved method can predict the optical density distribution from the undeveloped surface image, improving testing efficiency, it lacks analysis of the dynamic changes in color development on the thermal paper surface due to heating and temperature stabilization. This results in limited reference data for performance testing, an incomplete assessment of the color development performance of thermal paper, and deviating results from reality. For instance, patent application CN120563522A discloses a low basis weight thermal paper... A simplified test method for saturated color development optical density is proposed. This method involves inputting an image of the undeveloped surface and initial heating parameters into a pre-trained generative adversarial network (GAN) model. By combining the GAN with multispectral imaging technology, it enables the direct prediction of the optical density distribution of the saturated color development state from an image of an undeveloped surface. However, other improvements to methods for testing the color development performance of thermal paper typically focus on the color development rate. These methods fail to address the issue of limited reference data and incomplete color development performance testing due to the lack of analysis of the dynamic changes in color development on the thermal paper surface during heating and temperature stabilization. This results in inaccurate test results that deviate from reality. Therefore, it is necessary to improve existing methods for testing the color development performance of thermal paper. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art. By proposing a method for detecting the color development performance of thermal paper that integrates multispectral imaging and infrared sensing, this invention addresses the problem that existing methods for detecting the color development performance of thermal paper fail to analyze the dynamic changes in the color development of the thermal paper surface when the temperature rises due to heating and when the temperature stabilizes. This results in limited reference data during performance testing, an incomplete detection of the color development performance of thermal paper, and detection results that deviate from reality.

[0005] To achieve the above objectives, this application provides a method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing, comprising the following steps:

[0006] Based on the application scenarios of thermal paper, the highest and lowest temperatures of the thermal paper when it is applied are obtained, and the closed interval formed by the highest and lowest temperatures is recorded as the thermal heating interval; based on the thermal heating interval, k thermal papers with the same shape are obtained, and all of them are recorded as thermal paper.

[0007] Based on multispectral imaging and infrared sensors, a multi-temperature analysis method was used to analyze all the test papers, and the heating grayscale curve, heating grayscale array and stable discrete region of each test paper were obtained based on the analysis results.

[0008] Based on the temperature at which the thermal paper is heated in practical applications, the corresponding test paper is obtained, and the color development performance of the thermal paper is tested based on the temperature rise grayscale curve and stable discrete curve of the obtained test paper.

[0009] Furthermore, k thermal papers of the same shape are obtained based on the thermally sensitive heating area, and all are denoted as thermal paper for testing, including:

[0010] Within the thermosensitive heating range, k values ​​containing the highest and lowest temperatures are randomly selected and denoted in ascending order as the testable temperatures KC1 to KC. k Among them, the testable temperature KC1 is the lowest temperature, and the testable temperature KC k This is the highest temperature;

[0011] The thickness and shape of the thermal paper when it is applied are denoted as standard thickness and standard shape, respectively. K thermal papers with standard thickness and standard shape are selected and labeled as test paper CM1 to test paper CM2, respectively. k ; respectively, the testable temperature KC1 to the testable temperature KC k Designated as Sensitivity Test Paper CM1 to Sensitivity Test Paper CM k The analysis temperature.

[0012] Furthermore, multi-temperature analysis methods include:

[0013] The heating time of the thermal paper when it is applied is recorded as t0. For any thermal paper: the thermal paper is uniformly heated, and the surface temperature of the thermal paper is acquired in real time using an infrared sensor. The time when the thermal paper starts to be heated is recorded as t1. When the surface temperature of the thermal paper reaches the analysis temperature of the thermal paper, the time at this time is recorded as t2. The surface temperature of the thermal paper is kept constant until the time is t3, at which point the heating of the thermal paper is stopped. The value of t3 minus t2 is t0.

[0014] When the testing paper is heated, the spectral image of the surface of the testing paper is acquired based on multispectral imaging. The acquisition of the spectral image is stopped at time t3. The obtained spectral image is recorded as the heating characteristic image. The value of t2 minus t1 is recorded as t4, the value of t3 minus t1 is recorded as t5, and the duration of the heating characteristic image is t5.

[0015] Furthermore, multi-temperature analysis also includes:

[0016] The images corresponding to all frames in the heat-affected feature image are acquired sequentially, and the images corresponding to all frames in the heat-affected feature image within the time interval from 0 to t4 are sequentially denoted as heat-increasing analysis images ZF1 to ZF2. q Where q is the number of frames between 0 and t4 in the thermal feature image;

[0017] The images corresponding to all frames within the time interval t4 to t5 in the thermal characteristic image are sequentially denoted as stability analysis images WF1 to WF1. p , where p is the number of frames between t4 and t5 in the heated feature image.

[0018] Furthermore, multi-temperature analysis also includes:

[0019] For any heat gain analysis image: the image after grayscale processing of the heat gain analysis image is denoted as the heat gain grayscale image; the grayscale values ​​of all pixels in the heat gain grayscale image are recorded; a Cartesian coordinate system is established, denoted as the heat gain analysis coordinate system, where the X-axis and Y-axis of the heat gain analysis coordinate system are constant axes;

[0020] Using 0 to 255 as the abscissa and the number of pixels with gray values ​​of 0 to 255 in the heated grayscale image as the ordinate, 255 points are marked in the heated analysis coordinate system, and the curve obtained by fitting the 255 points is recorded as the heated grayscale curve.

[0021] The area of ​​the closed region formed by X=0, X=255, the heating grayscale curve, and the X-axis within the heating analysis coordinate system is denoted as the gray area value of the heating analysis image.

[0022] Furthermore, multi-temperature analysis also includes:

[0023] Obtain the heating grayscale curves and grayscale values ​​of all heating analysis images, and denot the curve obtained by fitting all heating grayscale curves in the same heating analysis coordinate system as the heating grayscale curve.

[0024] The heating analysis image ZF1 is compared with the heating analysis image ZF. q An array [HJ1, HJ2, ..., HJ] consisting of gray values q ] is denoted as the grayscale array for temperature rise.

[0025] Furthermore, multi-temperature analysis also includes:

[0026] For any stable analysis image: the image after grayscale processing of the stable analysis image is recorded as the stable grayscale image; the grayscale values ​​of all pixels in the stable grayscale image are obtained, and the center of the stable grayscale image is recorded as the stable center;

[0027] The distinct gray values ​​corresponding to all pixels within the stable grayscale image are sequentially denoted from smallest to largest as grayscale values ​​TH1 to TH2. r , where r is a positive integer greater than or equal to 0 and less than or equal to 255;

[0028] For any given grayscale value within the image: The distances between all pixels in the stable grayscale image whose grayscale values ​​are within the image and the stability center are sequentially denoted as L1 to L... u , where u is the number of pixels in the stable grayscale image whose grayscale value is the grayscale value in the image;

[0029] The discrete values ​​of grayscale within the image are obtained using a discrete algorithm. The discrete algorithm is as follows: Where F is a discrete value, 1≤i≤u, L i L1 to L u The i-th value in L sq L1 to L u The average value.

[0030] Furthermore, multi-temperature analysis also includes:

[0031] Obtain the discrete values ​​of all grayscale values ​​in the image corresponding to the stable grayscale image; establish a Cartesian coordinate system, denoted as the stability analysis coordinate system, where the X-axis and Y-axis of the stability analysis coordinate system are constant axes; sequentially use all grayscale values ​​in the image corresponding to the stable grayscale image as the abscissa and the discrete value corresponding to each grayscale value as the ordinate, obtain r points in the stability analysis coordinate system, and denot the curve obtained by fitting the r points as the grayscale discrete curve;

[0032] Obtain the gray-level discrete curves of all stable analysis images, place all gray-level discrete curves in the same stable analysis coordinate system, and for any straight line X=X1 parallel to the Y-axis in the stable analysis coordinate system, record the points with the largest and smallest ordinates among the intersection points of X=X1 and all gray-level discrete curves as the high threshold point and the low threshold point, respectively.

[0033] The curve obtained by fitting all high threshold points corresponding to all straight lines parallel to the Y-axis is denoted as the high threshold curve, and the curve obtained by fitting all low threshold points corresponding to all straight lines parallel to the Y-axis is denoted as the low threshold curve. The region between the high threshold curve and the low threshold curve is denoted as the stable discrete region.

[0034] Furthermore, the heating grayscale curves, heating grayscale arrays, and stable discrete regions corresponding to all thermal test papers are obtained. Based on the heating temperature of the thermal paper in actual applications, the corresponding thermal test papers are obtained, and the color development performance of the thermal paper is tested based on the obtained heating grayscale curves and stable discrete curves of the thermal test papers, including:

[0035] When testing the color development performance of thermal paper, the temperature at which the thermal paper is heated during the test is recorded as the test temperature; the temperature rise grayscale curve, temperature rise grayscale array, and stable discrete region corresponding to the thermal paper with the same analysis temperature and test temperature are respectively recorded as the standard grayscale curve, standard grayscale array, and standard discrete region.

[0036] During the process of heating the thermal paper to the test temperature, the thermal enhancement analysis image and the stability analysis image of the thermal paper are obtained based on the multi-temperature analysis method. The heating grayscale curve, heating grayscale array and stable discrete region of the thermal paper are obtained based on the heating analysis image and the stability analysis image, respectively.

[0037] Furthermore, based on the temperature at which the thermal paper is heated in practical applications, the corresponding test paper is obtained, and the color development performance of the thermal paper is tested based on the temperature rise grayscale curve and stable dispersion curve of the obtained test paper. This also includes:

[0038] When the overlap between the heating grayscale curve corresponding to the thermal paper and the standard grayscale curve is less than or equal to the standard overlap, or when the standard grayscale array and the heating grayscale array are not completely the same, the test result of the color development performance of the thermal paper is recorded as uneven heating.

[0039] When the overlap between the heating grayscale curve corresponding to the thermal paper and the standard grayscale curve is greater than the standard overlap, and the standard grayscale array and the heating grayscale array are exactly the same, the test result of the color development performance of the thermal paper is recorded as uniform heating.

[0040] When the stable discrete region corresponding to the thermal paper is completely within the standard discrete region, the test result of the color development performance of the thermal paper is recorded as having good color development performance.

[0041] When the stable discrete region corresponding to the thermal paper is not completely within the standard discrete region, the test result of the thermal paper's color development performance is recorded as poor color development performance.

[0042] The beneficial effects of this invention are as follows: First, this application obtains the thermally sensitive heating zone based on the application scenario of the thermal paper; based on the thermally sensitive heating zone, k thermally sensitive papers of the same shape are obtained and denoted as test papers; then, based on multispectral imaging and infrared sensors, a multi-temperature analysis method is used to analyze all test papers, and based on the analysis results, the heating grayscale curve, heating grayscale array, and stable discrete region of each test paper are obtained; finally, based on the temperature at which the thermal paper is heated in actual applications, the corresponding test paper is obtained, and the color development performance of the thermal paper is detected based on the obtained heating grayscale curve and stable discrete curve of the test paper. The advantage of this is that, through... By acquiring the thermally sensitive heating range and analyzing all the thermally sensitive papers using a multi-temperature analysis method, we can obtain the changes in the color development of the thermally sensitive paper surface under various heating conditions, from heating to temperature stabilization. The characteristics corresponding to temperature changes are converted into heating grayscale curves, heating grayscale arrays, and stable discrete regions. This allows for a more comprehensive detection of the color development performance of the thermally sensitive paper based on the changes in surface color development after heating, using heating grayscale curves, heating grayscale arrays, and stable discrete regions, ensuring that the test results match the actual color development state of the thermally sensitive paper. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the steps of the method of the present invention;

[0044] Figure 2 This is a schematic diagram of the coordinate system for heat enhancement analysis according to the present invention;

[0045] Figure 3 This is a schematic diagram of the stable grayscale image of the present invention;

[0046] Figure 4 This is a schematic diagram illustrating the acquisition of the distance between the pixel whose grayscale value is the grayscale value in the image and the stability center according to the present invention;

[0047] Figure 5 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Example 1, please refer to Figure 1 As shown, this application provides a method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing, including the following steps:

[0050] Step S1: Based on the application scenario of the thermal paper, obtain the highest and lowest temperatures when the thermal paper is applied, and record the closed interval formed by the highest and lowest temperatures as the thermal heating interval; based on the thermal heating interval, obtain k thermal papers with the same shape, and record them as the thermal paper.

[0051] Step S1 includes: Step S101, randomly acquiring k values ​​containing the highest and lowest temperatures within the thermistor heating range, and recording them in ascending order as the testable temperatures KC1 to KC. k Among them, the testable temperature KC1 is the lowest temperature, and the testable temperature KC k This is the highest temperature;

[0052] In the specific implementation process, the value of k can be set according to the actual data analysis capability. In this embodiment, the value of k is set to 5. Since the highest and lowest temperatures in the thermal heating zone when thermal paper is applied are generally the most common heating temperatures, the testable temperature should include the highest and lowest temperatures in the thermal heating zone. In practical applications, if there are multiple preset temperatures for heating thermal paper, the preset temperatures can be recorded as the testable temperatures and subsequent data analysis can be performed.

[0053] Step S102: Record the thickness and shape of the thermal paper when it is applied as standard thickness and standard shape, respectively. Obtain k thermal papers with standard thickness and standard shape, and record them as test paper CM1 to test paper CM2. k ; respectively, the testable temperature KC1 to the testable temperature KC k Designated as Sensitivity Test Paper CM1 to Sensitivity Test Paper CM k The analysis temperature.

[0054] Step S2: Based on multispectral imaging and infrared sensors, use multi-temperature analysis to analyze all the test papers, and obtain the heating grayscale curve, heating grayscale array and stable discrete region of each test paper based on the analysis results.

[0055] The multi-temperature analysis method includes: step S201, obtaining the heating time of the thermal paper when it is applied and recording it as t0; for any thermal paper: uniformly heating the thermal paper, using an infrared sensor to obtain the surface temperature of the thermal paper in real time, and recording the time when the thermal paper starts to be heated as t1; when the surface temperature of the thermal paper is the analysis temperature of the thermal paper, recording the time at this time as t2, and keeping the surface temperature of the thermal paper unchanged until the time is t3, then stopping the heating of the thermal paper, where the value of t3 minus t2 is t0;

[0056] In specific implementation, for example, during a data analysis, the analysis temperature of the thermal paper is 200℃, and the thermal paper is heated for 0.5 seconds. If the thermal paper is heated from 12:00:00, and the time when the surface temperature of the thermal paper reaches 200℃ is 12:00:02, then the heating of the thermal paper should be stopped at 12:00:02.5. Here, t0 is 0.5 seconds, t1 is 12:00:00, t2 is 12:00:02, t3 is 12:00:02.5, t4 is 2 seconds, and t5 is 2.5 seconds.

[0057] Step S202: When the test paper is heated, the spectral image of the test paper surface is acquired based on multispectral imaging, and the acquisition of the spectral image is stopped at time t3. The obtained spectral image is recorded as the heat-affected feature image. The value of t2 minus t1 is recorded as t4, the value of t3 minus t1 is recorded as t5, and the duration of the heat-affected feature image is t5.

[0058] The multi-temperature analysis method further includes: step S203, sequentially acquiring the images corresponding to all frames in the thermal characteristic image, and sequentially recording the images corresponding to all frames in the image with a time interval between 0 and t4 as thermal analysis images ZF1 to thermal analysis images ZF1. q Where q is the number of frames between 0 and t4 in the thermal feature image;

[0059] In the specific implementation process, by acquiring the heat gain analysis image when the surface temperature of the thermal paper rises and the stability analysis image when the surface temperature of the thermal paper stabilizes, the color change of the thermal paper surface when the thermal paper is heated to a stable temperature can be analyzed, thereby enabling a more comprehensive color development test when testing the color development performance of the thermal paper.

[0060] Step S204: Record the images corresponding to all frames within the time interval t4 to t5 of the thermal characteristic image as stable analysis images WF1 to WF1, respectively. p , where p is the number of frames between t4 and t5 in the heated feature image.

[0061] The multi-temperature analysis method also includes: step S205, for any heating analysis image: the image after grayscale processing of the heating analysis image is recorded as the heating grayscale image; the grayscale values ​​of all pixels in the heating grayscale image are recorded; a plane rectangular coordinate system is established, which is recorded as the heating analysis coordinate system, wherein the X-axis and Y-axis of the heating analysis coordinate system are constant axes;

[0062] Step S206: Mark 255 points in the heating analysis coordinate system with 0 to 255 as the abscissa and the number of pixels with gray values ​​of 0 to 255 in the heating grayscale image as the ordinate. Record the curve obtained by fitting the 255 points as the heating grayscale curve.

[0063] In specific implementation processes, such as during a data analysis, the obtained heat gain analysis coordinate system is as follows: Figure 2 As shown, curve ZH is the heat-increasing grayscale curve fitted by 255 points marked in the heat-increasing analysis coordinate system, and the areas of regions ZM1 and ZM2 are the grayscale values ​​of the heat-increasing analysis image. By acquiring the heat-increasing grayscale curves and grayscale values ​​of all heat-increasing analysis images, the dynamic change characteristics of the surface color of the thermal paper under heating can be obtained. This allows for a more comprehensive detection of the color development state of the thermal paper under heating, based on the heating grayscale curves and grayscale values.

[0064] Step S207: The area of ​​the closed region formed by X=0, X=255, the heating grayscale curve and the X-axis in the heating analysis coordinate system is recorded as the gray area value of the heating analysis image.

[0065] The multi-temperature analysis method also includes: step S208, obtaining the heating grayscale curves and gray accumulation values ​​of all heating analysis images, and recording the curve obtained by fitting all heating grayscale curves in the same heating analysis coordinate system as the heating grayscale curve.

[0066] Step S209: Transfer the heating analysis image ZF1 to the heating analysis image ZF q An array [HJ1, HJ2, ..., HJ] consisting of gray values q Let this be the grayscale array for temperature increase;

[0067] In the specific implementation process, for example, during a data analysis, the gray values ​​of all the heat-generating analysis images obtained are 200, 34, 453, 123, 534, 32, 12 and 234 respectively. Then, [200, 34, 453, 123, 534, 32, 12, 234] can be recorded as the heat-generating gray value array.

[0068] The multi-temperature analysis method also includes: step S210, for any stable analysis image: the image after grayscale processing of the stable analysis image is recorded as a stable grayscale image; the grayscale values ​​of all pixels in the stable grayscale image are obtained, and the center of the stable grayscale image is recorded as the stable center;

[0069] Step S211: Record the distinct gray values ​​corresponding to all pixels in the stable grayscale image in ascending order as grayscale values ​​TH1 to TH2. rWhere r is a positive integer greater than or equal to 0 and less than or equal to 255; 0.0324 0.0484 0.1024 0.1764 0.3364

[0070] Step S212, for any in-image grayscale value: Record the distances between all pixels in the stable grayscale image whose grayscale values ​​are in-image grayscale values ​​and the stability center as L1 to L2. u Where u is the number of pixels in the stable grayscale image with a grayscale value equal to the grayscale value in the image; 1.18

[0071] In specific implementation processes, such as during a data analysis, the obtained stable grayscale image is as follows: Figure 3 As shown, Figure 3 The center of the triangle is the stable center. When the grayscale value in the image is 100, the position of the pixel with a grayscale value of 100 is... Figure 3 The center of all □ in the equation can be obtained through analysis, which means that... Figure 4 The lengths of all dashed lines within the range are denoted as L1 to L6, and subsequent discrete values ​​are obtained.

[0072] Step S213: Use a discrete algorithm to obtain the discrete values ​​of grayscale values ​​within the image. The discrete algorithm is as follows: Where F is a discrete value, 1≤i≤u, L i L1 to L u The i-th value in L sq L1 to L u The average value;

[0073] In the specific implementation process, for example, during a data analysis, by Figure 3 as well as Figure 4 The L1 to L6 values ​​obtained when the gray value in the image is 100 are 1cm, 1.4cm, 1.5cm, 1.6cm, 0.6cm and 1cm respectively. Therefore, it can be calculated that the discrete value corresponding to the gray value in the image is approximately 0.0202.

[0074] The multi-temperature analysis method also includes: step S214, obtaining the discrete values ​​of all gray values ​​in the image corresponding to the stable gray-scale image; establishing a Cartesian coordinate system, denoted as the stable analysis coordinate system, wherein the X-axis and Y-axis of the stable analysis coordinate system are constant axes; sequentially using all gray values ​​in the image corresponding to the stable gray-scale image as the abscissa and the discrete value corresponding to each gray value in the image as the ordinate, obtaining r points in the stable analysis coordinate system, and recording the curve obtained by fitting the r points as the gray-scale discrete curve;

[0075] In the specific implementation process, by obtaining the discrete value of each grayscale value and the corresponding grayscale discrete curve, the distribution characteristics of pixels in the grayscale stable image can be effectively quantified. This allows for the integration of all grayscale discrete curves into a stable discrete region after obtaining the grayscale discrete curves corresponding to all stable analysis images. This enables the acquisition of the region corresponding to the characteristics of the grayscale image of the thermal paper with good performance when the surface temperature is stable. Thus, when testing the color development performance of the thermal paper, the color development state of the thermal paper with a stable surface temperature can be effectively detected based on the stable discrete region.

[0076] Step S215: Obtain the gray-level discrete curves of all stable analysis images, place all gray-level discrete curves in the same stable analysis coordinate system, and for any straight line X=X1 parallel to the Y-axis in the stable analysis coordinate system, record the points with the largest and smallest ordinates among the intersection points of X=X1 and all gray-level discrete curves as the high threshold point and the low threshold point, respectively.

[0077] Step S216: Fit the curves corresponding to the high threshold points of all lines parallel to the Y-axis and record them as high threshold curves; fit the curves corresponding to the low threshold points of all lines parallel to the Y-axis and record them as low threshold curves; and record the region between the high threshold curves and the low threshold curves as stable discrete regions.

[0078] Step S3: Based on the temperature at which the thermal paper is heated in actual application, obtain the corresponding test paper, and test the color development performance of the thermal paper based on the temperature rise grayscale curve and stable discrete curve of the obtained test paper.

[0079] Obtain the heating grayscale curves, heating grayscale arrays, and stable discrete regions corresponding to all thermal paper samples. Step S3 includes: Step S301, when performing a color development performance test on thermal paper, the temperature at which the thermal paper is heated during the test is recorded as the test temperature; the heating grayscale curves, heating grayscale arrays, and stable discrete regions corresponding to thermal paper samples whose analysis temperature is equal to the test temperature are respectively recorded as the standard grayscale curve, standard grayscale array, and standard discrete region.

[0080] In step S302, during the process of heating the thermal paper to the test temperature, the thermal enhancement analysis image and the stability analysis image corresponding to the thermal paper are obtained based on the multi-temperature analysis method, and the heating grayscale curve, heating grayscale array and stable discrete region corresponding to the thermal paper are obtained based on the heating analysis image and the stability analysis image, respectively.

[0081] Step S3 also includes: Step S303, when the overlap between the heating grayscale curve corresponding to the thermal paper and the standard grayscale curve is less than or equal to the standard overlap, or the standard grayscale array and the heating grayscale array are not completely the same, the test result of the color development performance of the thermal paper is recorded as uneven heating.

[0082] In the specific implementation process, the standard overlap can be determined according to the actual judgment criteria. In this embodiment, the standard fusion degree is set to 90%. For example, if the overlap between the heating grayscale curve and the standard grayscale curve obtained in a data analysis is 80%, and the standard grayscale array and the heating grayscale array are exactly the same, then through analysis, it can be found that the overlap between the heating grayscale curve and the standard grayscale curve is small. This indicates that the dynamic change of the surface color of the thermal paper when heated is different from that of the thermal paper with good performance. That is, the color change of the thermal paper when heated is abnormal, and there may be a lack of a certain chemical element. Therefore, the test result of the color development performance of the thermal paper should be recorded as uneven heating.

[0083] Step S304: When the overlap between the heating grayscale curve corresponding to the thermal paper and the standard grayscale curve is greater than the standard overlap, and the standard grayscale array is exactly the same as the heating grayscale array, the test result of the color development performance of the thermal paper is recorded as uniform heating.

[0084] Step S305: When the stable discrete region corresponding to the thermal paper is completely within the standard discrete region, the color development performance test result of the thermal paper is recorded as having good color development performance.

[0085] Step S306: When the stable discrete region corresponding to the thermal paper is not completely within the standard discrete region, the test result of the color development performance of the thermal paper is recorded as poor color development performance.

[0086] Example 2, please refer to Figure 5 As shown, Figure 5 The example illustrates the structure of an electronic device, which may include a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in the thermal paper color development performance detection method, such as the multispectral imaging and infrared sensing fusion method, are performed to achieve the following functions: First, based on the application scenario of the thermal paper, the highest and lowest temperatures of the thermal paper when it is applied are obtained, and the closed interval formed by the highest and lowest temperatures is recorded as the thermal heating interval; based on the thermal heating interval, k thermal papers of the same shape are obtained, and all are recorded as test papers; then, based on multispectral imaging and infrared sensors, a multi-temperature analysis method is used to analyze all test papers, and based on the analysis results, the temperature rise grayscale curve, temperature rise grayscale array, and stable discrete region of each test paper are obtained; finally, based on the temperature at which the thermal paper is heated in actual application, the corresponding test paper is obtained, and the color development performance of the thermal paper is detected based on the obtained temperature rise grayscale curve and stable discrete curve of the test paper.

[0087] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0088] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by the computer, the computer can execute the multispectral imaging and infrared sensing fusion thermal paper color development performance detection method provided by the above methods. The method includes: first, based on the application scenario of the thermal paper, obtaining the highest and lowest temperatures of the thermal paper when it is applied, and recording the closed interval formed by the highest and lowest temperatures as the thermal heating interval; obtaining k thermal papers of the same shape based on the thermal heating interval, and recording them as test papers; then analyzing all test papers using a multi-temperature analysis method based on multispectral imaging and infrared sensors, and obtaining the temperature rise grayscale curve, temperature rise grayscale array, and stable discrete region of each test paper based on the analysis results; finally, based on the temperature at which the thermal paper is heated in actual application, obtaining the corresponding test paper, and detecting the color development performance of the thermal paper based on the obtained temperature rise grayscale curve and stable discrete curve of the test paper.

[0089] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it runs the steps of the above-described method for detecting the color development performance of thermal paper using multispectral imaging and infrared sensing fusion, to achieve the following functions: First, based on the application scenario of the thermal paper, the highest and lowest temperatures of the thermal paper when it is applied are obtained, and the closed interval formed by the highest and lowest temperatures is recorded as the thermal heating interval; based on the thermal heating interval, k thermal papers of the same shape are obtained, and all are recorded as test papers; then, based on multispectral imaging and infrared sensors, a multi-temperature analysis method is used to analyze all test papers, and based on the analysis results, the heating grayscale curve, heating grayscale array, and stable discrete region of each test paper are obtained; finally, based on the temperature at which the thermal paper is heated in actual application, the corresponding test paper is obtained, and the color development performance of the thermal paper is detected based on the obtained heating grayscale curve and stable discrete curve of the test paper.

[0090] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0091] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing, characterized in that, Includes the following steps: Based on the application scenarios of thermal paper, the highest and lowest temperatures of the thermal paper when it is applied are obtained, and the closed interval formed by the highest and lowest temperatures is recorded as the thermal heating interval; based on the thermal heating interval, k thermal papers with the same shape are obtained, and all of them are recorded as thermal paper. Based on multispectral imaging and infrared sensors, a multi-temperature analysis method was used to analyze all the test papers, and the heating grayscale curve, heating grayscale array and stable discrete region of each test paper were obtained based on the analysis results. Based on the temperature at which the thermal paper is heated in practical applications, the corresponding test paper is obtained, and the color development performance of the thermal paper is tested based on the temperature rise grayscale curve and the stable discrete curve of the obtained test paper. Multi-temperature analysis methods include: The heating time of the thermal paper when it is applied is recorded as t0. For any thermal paper: the thermal paper is uniformly heated, and the surface temperature of the thermal paper is acquired in real time using an infrared sensor. The time when the thermal paper starts to be heated is recorded as t1. When the surface temperature of the thermal paper reaches the analysis temperature of the thermal paper, the time at this time is recorded as t2. The surface temperature of the thermal paper is kept constant until the time is t3, at which point the heating of the thermal paper is stopped. The value of t3 minus t2 is t0. When the testing paper is heated, the spectral image of the surface of the testing paper is acquired based on multispectral imaging, and the acquisition of the spectral image is stopped at time t3. The obtained spectral image is recorded as the heating characteristic image. The value of t2 minus t1 is recorded as t4, the value of t3 minus t1 is recorded as t5, and the duration of the heating characteristic image is t5. The images corresponding to all frames in the heat-affected feature image are acquired sequentially, and the images corresponding to all frames in the heat-affected feature image within the time interval from 0 to t4 are sequentially denoted as heat-increasing analysis images ZF1 to ZF2. q Where q is the number of frames between 0 and t4 in the thermal feature image; The images corresponding to all frames within the time interval t4 to t5 in the thermal characteristic image are sequentially denoted as stability analysis images WF1 to WF1. p , where p is the number of frames between t4 and t5 in the heated feature image.

2. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 1, characterized in that, Based on the heat-sensitive heating zone, k thermal papers of the same shape are obtained and denoted as thermal paper for testing, including: Within the thermosensitive heating range, k values ​​containing the highest and lowest temperatures are randomly selected and denoted in ascending order as the testable temperatures KC1 to KC. k Among them, the testable temperature KC1 is the lowest temperature, and the testable temperature KC k This is the highest temperature; The thickness and shape of the thermal paper when it is applied are denoted as standard thickness and standard shape, respectively. K thermal papers with standard thickness and standard shape are selected and labeled as test paper CM1 to test paper CM2, respectively. k ; respectively, the testable temperature KC1 to the testable temperature KC k Designated as Sensitivity Test Paper CM1 to Sensitivity Test Paper CM k The analysis temperature.

3. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 2, characterized in that, Multi-temperature analysis methods also include: For any heat gain analysis image: the image after grayscale processing of the heat gain analysis image is denoted as the heat gain grayscale image; the grayscale values ​​of all pixels in the heat gain grayscale image are recorded; a Cartesian coordinate system is established, denoted as the heat gain analysis coordinate system, where the X-axis and Y-axis of the heat gain analysis coordinate system are constant axes; Using 0 to 255 as the abscissa and the number of pixels with gray values ​​of 0 to 255 in the heated grayscale image as the ordinate, 255 points are marked in the heated analysis coordinate system, and the curve obtained by fitting the 255 points is recorded as the heated grayscale curve. The area of ​​the closed region formed by X=0, X=255, the heating grayscale curve, and the X-axis within the heating analysis coordinate system is denoted as the gray area value of the heating analysis image.

4. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 3, characterized in that, Multi-temperature analysis methods also include: Obtain the heating grayscale curves and grayscale values ​​of all heating analysis images, and denot the curve obtained by fitting all heating grayscale curves in the same heating analysis coordinate system as the heating grayscale curve. The heating analysis image ZF1 is compared with the heating analysis image ZF. q An array [HJ1, HJ2, ..., HJ] consisting of gray values q ] is denoted as the grayscale array for temperature rise.

5. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 4, characterized in that, Multi-temperature analysis methods also include: For any stable analysis image: the image after grayscale processing of the stable analysis image is recorded as the stable grayscale image; the grayscale values ​​of all pixels in the stable grayscale image are obtained, and the center of the stable grayscale image is recorded as the stable center; The distinct gray values ​​corresponding to all pixels within the stable grayscale image are sequentially denoted from smallest to largest as grayscale values ​​TH1 to TH2. r , where r is a positive integer greater than or equal to 0 and less than or equal to 255; For any given grayscale value within the image: The distances between all pixels in the stable grayscale image whose grayscale values ​​are within the image and the stability center are sequentially denoted as L1 to L... u , where u is the number of pixels in the stable grayscale image whose grayscale value is the grayscale value in the image; The discrete values ​​of grayscale within the image are obtained using a discrete algorithm. The discrete algorithm is as follows: Where F is a discrete value, 1≤i≤u, L i L1 to L u The i-th value in L sq L1 to L u The average value.

6. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 5, characterized in that, Multi-temperature analysis methods also include: Obtain the discrete values ​​of all grayscale values ​​in the image corresponding to the stable grayscale image; establish a Cartesian coordinate system, denoted as the stability analysis coordinate system, where the X-axis and Y-axis of the stability analysis coordinate system are constant axes; sequentially use all grayscale values ​​in the image corresponding to the stable grayscale image as the abscissa and the discrete value corresponding to each grayscale value as the ordinate, obtain r points in the stability analysis coordinate system, and denot the curve obtained by fitting the r points as the grayscale discrete curve; Obtain the gray-level discrete curves of all stable analysis images, place all gray-level discrete curves in the same stable analysis coordinate system, and for any straight line X=X1 parallel to the Y-axis in the stable analysis coordinate system, record the points with the largest and smallest ordinates among the intersection points of X=X1 and all gray-level discrete curves as the high threshold point and the low threshold point, respectively. The curve obtained by fitting all high threshold points corresponding to all straight lines parallel to the Y-axis is denoted as the high threshold curve, and the curve obtained by fitting all low threshold points corresponding to all straight lines parallel to the Y-axis is denoted as the low threshold curve. The region between the high threshold curve and the low threshold curve is denoted as the stable discrete region.

7. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 6, characterized in that, Acquire the temperature rise grayscale curves, temperature rise grayscale arrays, and stable discrete regions corresponding to all thermal paper test sheets. Based on the heating temperature of the thermal paper in actual applications, acquire the corresponding thermal paper test sheets. Then, based on the acquired temperature rise grayscale curves and stable discrete curves of the thermal paper test sheets, test the color development performance of the thermal paper, including: When testing the color development performance of thermal paper, the temperature at which the thermal paper is heated during the test is recorded as the test temperature; the temperature rise grayscale curve, temperature rise grayscale array, and stable discrete region corresponding to the thermal paper with the same analysis temperature and test temperature are respectively recorded as the standard grayscale curve, standard grayscale array, and standard discrete region. During the process of heating the thermal paper to the test temperature, the thermal enhancement analysis image and the stability analysis image of the thermal paper are obtained based on the multi-temperature analysis method. The heating grayscale curve, heating grayscale array and stable discrete region of the thermal paper are obtained based on the heating analysis image and the stability analysis image, respectively.

8. The method for detecting the color development performance of thermal paper by fusing multispectral imaging and infrared sensing according to claim 7, characterized in that, Based on the heating temperature of the thermal paper in practical applications, the corresponding test paper is obtained. The color development performance of the thermal paper is then tested based on the heating grayscale curve and stable dispersion curve of the obtained test paper. This process also includes: When the overlap between the heating grayscale curve corresponding to the thermal paper and the standard grayscale curve is less than or equal to the standard overlap, or when the standard grayscale array and the heating grayscale array are not completely the same, the test result of the color development performance of the thermal paper is recorded as uneven heating. When the overlap between the heating grayscale curve corresponding to the thermal paper and the standard grayscale curve is greater than the standard overlap, and the standard grayscale array and the heating grayscale array are exactly the same, the test result of the color development performance of the thermal paper is recorded as uniform heating. When the stable discrete region corresponding to the thermal paper is completely within the standard discrete region, the test result of the color development performance of the thermal paper is recorded as having good color development performance. When the stable discrete region corresponding to the thermal paper is not completely within the standard discrete region, the test result of the thermal paper's color development performance is recorded as poor color development performance.

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