Method for generating composite label paper based on graphic and text information and composite label paper

Abstract

This invention relates to the field of image processing, specifically to a method for generating composite label paper based on image and text information, and the composite label paper itself. The method includes: S1, acquiring a standard information surface image and a standard back surface image in advance, and acquiring the information surface image and the back surface image during the generation process. S2, comparing the standard information surface image and the back surface image to identify several problematic parts in the information surface image. S3, comparing the standard back surface image and the back surface image to identify several problematic parts in the back surface image. S4, based on the comparison results corresponding to the information surface image and the back surface image, determining the causes of each problematic part in the information surface image, and controlling the generation process according to the causes of the problems. This invention enables the identification of the causes of problems on the composite label paper, facilitating the optimization and control of the composite label paper generation process.

Description

Technical Field

[0001] This invention relates to the field of image processing, and more particularly to a method for generating composite label paper based on graphic and textual information, and the composite label paper itself. Background Technology

[0002] Composite label paper is widely used in manufacturing and other fields, so quality control during the production process of composite label paper is essential.

[0003] Chinese patent application CN109934809A discloses a method for detecting character defects on paper labels, including the following steps: S1: Classify labels and obtain all label types and corresponding label templates; S2: Set ROI, obtain the ROI image in the current complete image, and obtain the current label type and corresponding label template; S3: Match the ROI image and the current label template to obtain a registration image; S4: Obtain an AND-OR graph, set a dynamic threshold, and highlight the defective areas of the AND-OR graph according to the dynamic threshold; S5: Calculate the area of ​​the defective area and determine whether the current defective area exceeds the preset defective area threshold for the current label type. However, the above patent application can only detect defects from the label paper and cannot determine the cause of the defects. Therefore, this invention proposes a method for generating composite label paper based on graphic and textual information. Summary of the Invention

[0004] This invention identifies several problematic areas in the information surface image by comparing two standard information surface images. It also identifies several problematic areas in the rear surface image by comparing two standard rear surface images. Based on the comparison results for the information surface images and the rear surface images, the invention determines the cause of each problematic area in the information surface image. This invention aims to intelligently identify the causes of problems on composite label paper.

[0005] This invention provides a method for generating composite label paper based on graphic and textual information, comprising the following steps:

[0006] S1. Obtain in advance the standard information surface image corresponding to the information surface of the composite label paper and the standard back surface image corresponding to the back surface of the composite label paper. During the generation process, obtain the information surface image corresponding to the information surface of the composite label paper and the back surface image corresponding to the back surface of the composite label paper.

[0007] S2. Compare the standard information surface image with the information surface image to identify several problematic parts in the information surface image;

[0008] S3. Compare the standard rear surface image with the rear surface image to identify several problematic parts in the rear surface image;

[0009] S4. Based on the comparison results of the information surface image and the comparison results of the back surface image, determine the cause of the problem corresponding to each problem part in the information surface image, and control the generation process according to the cause of the problem.

[0010] As a preferred embodiment of the present invention, a comparative processing of a standard information surface image and an information surface image is performed to identify several problematic portions in the information surface image, including the following steps:

[0011] S21. Establish an image coordinate system on the standard information surface image with the image element in the upper left corner as the origin, the horizontal direction to the right as the positive x-axis, and the vertical direction downward as the positive y-axis. Establish an image coordinate system on the information surface image using the same method. Divide the standard information surface image and the information surface image into several image blocks, each containing the same number of image elements.

[0012] S22. For image blocks in the information plane image, identify image blocks in the standard information plane image with the same address, calculate the sum of the image element values ​​of all image elements contained in the image block in the information plane image, calculate the sum of the image element values ​​of all image elements contained in the image block in the standard information plane image, calculate the difference between the two, and if the difference is greater than a certain value, determine that the image block in the information plane image is a problem image block.

[0013] S23. In the information surface image, use several adjacent problem image blocks to form a problem section, and record the address of the problem section.

[0014] As a preferred embodiment of the present invention, a comparative processing of a standard rear surface image and a rear surface image is performed to identify several problematic portions in the rear surface image, including the following steps:

[0015] S31. Establish an image coordinate system on the standard back surface image with the image element in the upper right corner as the origin, the horizontal leftward direction as the positive x-axis, and the vertical downward direction as the positive y-axis. Establish an image coordinate system on the back surface image using the same method. Divide the standard back surface image and the back surface image into several image blocks by dividing the information surface image.

[0016] S32. For image blocks in the rear surface image, determine the image blocks in the standard rear surface image with the same address, calculate the sum of the image element values ​​of all image elements contained in the image block in the rear surface image, calculate the sum of the image element values ​​of all image elements contained in the image block in the standard rear surface image, and if the difference between the two is greater than a preset value, determine that the image block in the rear surface image is a problem image block.

[0017] S33. In the back surface image, use several adjacent problem image blocks to form a problem section, and record the address of the problem section.

[0018] As a preferred embodiment of the present invention, a specific value is set through the following steps:

[0019] S221. Generate test images of different problem levels, and compare the standard information surface image with the test images of each problem level to obtain the specific values ​​to be selected for each test image of each problem level.

[0020] S222. Set the problem level range, determine several candidate specific values ​​corresponding to the problem level range, and take the smallest candidate specific value among the several candidate specific values ​​as the specific value.

[0021] S223. Determine whether a specific value needs to be reset. If yes, proceed to S221. If no, end all steps.

[0022] As a preferred technical solution of the present invention, generating test images with different problem levels includes: setting several problem types, generating problem images of different problem levels for each problem type, with the problem images taking image blocks as the basic unit, and adding several problem images of the same problem level to a standard information surface image to obtain test images of the corresponding problem levels.

[0023] As a preferred technical solution of the present invention, the standard information surface image is compared with the test images of each problem level to obtain the specific values ​​to be selected for each problem level test image, including the following steps:

[0024] S2211. Set initial specific values ​​and select the test image of the highest problem level;

[0025] S2212. Compare the standard information surface image with the selected test image to identify several problem parts in the selected test image. Determine whether the several problem parts include all the problem images in the selected test image. If yes, use the preliminary specific value as the candidate specific value and continue to the next step. If no, continue to S2214.

[0026] S2213. Determine whether the specific values ​​corresponding to the test images of each problem level have been obtained. If yes, end all steps; otherwise, continue to the next step.

[0027] S2214. Select the test image with the highest problem level from all test images that have not yet obtained the candidate specific value, reduce the initial specific value by one step, and jump to S2212.

[0028] As a preferred embodiment of the present invention, reducing the initial specific value by one step includes the following steps:

[0029] S22141. Determine the experimental image for which a specific value was obtained in the previous test, compare the standard information surface image with the determined experimental image, obtain several differences corresponding to each image block in the determined experimental image, and establish a first distribution histogram of several differences.

[0030] S22142. Compare the standard information surface image with the selected test image to obtain several differences corresponding to each image block in the selected test image, and establish a second distribution histogram of several differences.

[0031] S22143. Find the difference between the candidate specific value and the determined test image in the first distribution histogram, and determine the difference corresponding to the first trough in the second distribution histogram. If the difference between the two is greater than the preset first threshold, increase the value represented by the step size to reduce the initial specific value by one step size. If the difference between the two is less than the preset second threshold, decrease the value represented by the step size to reduce the initial specific value by one step size.

[0032] As a preferred embodiment of the present invention, based on the comparison results corresponding to the information surface image and the comparison results corresponding to the rear surface image, the cause of the problem corresponding to each problematic part in the information surface image is determined, including the following steps:

[0033] S41. For the problematic part in the information surface image, determine whether there is a problematic part with the same address in the rear surface image. If not, determine that the problematic part in the information surface image is caused by printing issues. If yes, continue to the next step.

[0034] S42. Determine whether the size of the problematic part in the information surface image is greater than a preset threshold. If not, remove the problematic part from the information surface image. If yes, determine that the problematic part in the information surface image is caused by the composite label paper itself.

[0035] The present invention also provides a composite label paper, comprising an information surface and a back surface, wherein the composite label paper is produced using the method described in any one of the above-mentioned methods.

[0036] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0037] In the technical solution provided by this invention, firstly, a standard information surface image corresponding to the information surface of the composite label paper and a standard back surface image corresponding to the back surface of the composite label paper are acquired in advance. During the generation process, the information surface image corresponding to the information surface of the composite label paper and the back surface image corresponding to the back surface of the composite label paper are also acquired. Secondly, the standard information surface image and the information surface image are compared to identify several problematic parts in the information surface image. Thirdly, the standard back surface image and the back surface image are compared to identify several problematic parts in the back surface image. Finally, based on the comparison results of the information surface image and the back surface image, the causes of each problematic part in the information surface image are determined, and the generation process is controlled according to the causes. Through this invention, not only can problems on the composite label paper be detected, but the causes of these problems can also be automatically identified, thereby facilitating the optimization and control of the composite label paper generation process. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating the method for generating composite label paper based on graphic and textual information provided by the present invention. Detailed Implementation

[0039] 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.

[0040] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0041] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0042] like Figure 1 As shown in the figure, this invention provides a method for generating composite label paper based on graphic and textual information. The method mainly includes the following steps:

[0043] S1. Obtain in advance the standard information surface image corresponding to the information surface of the composite label paper and the standard back surface image corresponding to the back surface of the composite label paper. During the generation process, obtain the information surface image corresponding to the information surface of the composite label paper and the back surface image corresponding to the back surface of the composite label paper.

[0044] S2. Compare the standard information surface image with the information surface image to identify several problematic parts in the information surface image;

[0045] S3. Compare the standard rear surface image with the rear surface image to identify several problematic parts in the rear surface image;

[0046] S4. Based on the comparison results of the information surface image and the comparison results of the back surface image, determine the cause of the problem corresponding to each problem part in the information surface image, and control the generation process according to the cause of the problem.

[0047] Specifically, to identify the causes of problems while detecting issues with the composite label paper, steps S1 to S4 are proposed. In S1, a standard information face image corresponding to the information side of the composite label paper and a standard back surface image corresponding to the back surface are acquired in advance. The information side of the composite label paper is the front side where the graphic information has already been printed, and the back surface is the back side of the composite label paper. The back side of the composite label paper does not have any graphic information printed on it. It is important to note that the standard information face image and the standard back surface image will not have any problems. During the process of repeatedly printing graphic information to continuously generate various composite labels, when a composite label paper is generated, the information face image corresponding to the information side and the back surface image corresponding to the back surface are acquired. It is important to note that the information face image and the back surface image may have problems. In S2, the standard information face image and the information face image are compared to identify several problematic parts in the information face image. These problematic parts may correspond to stains, foreign objects, ripples, unevenness, etc. In step S3, a comparison is performed between the standard back surface image and the back surface image to identify several problematic areas in the back surface image. These problematic areas may correspond to issues such as foreign objects, unevenness, etc., all of which are inherent problems with the composite label paper itself. It's important to note that in this embodiment, foreign objects refer to those penetrating the composite label paper. In step S4, based on the comparison results between the information surface image and the back surface image—that is, the several problematic areas in the information surface image and the several problematic areas in the back surface image—the cause of each problematic area in the information surface image is determined. The causes include printing-related issues and issues inherent to the composite label paper itself. Therefore, while discarding the generated problematic composite label paper, the generation process can be controlled according to the cause of the problem. For example, if the issue is related to printing, the printing equipment can be inspected and maintained; if the issue is related to the composite label paper itself, the material quality of the composite label paper can be improved.

[0048] Furthermore, a comparison process is performed between the standard information surface image and the information surface image to identify several problematic parts in the information surface image, including the following steps:

[0049] S21. Establish an image coordinate system on the standard information surface image with the image element in the upper left corner as the origin, the horizontal direction to the right as the positive x-axis, and the vertical direction downward as the positive y-axis. Establish an image coordinate system on the information surface image using the same method. Divide the standard information surface image and the information surface image into several image blocks, each containing the same number of image elements.

[0050] S22. For image blocks in the information plane image, identify image blocks in the standard information plane image with the same address, calculate the sum of the image element values ​​of all image elements contained in the image block in the information plane image, calculate the sum of the image element values ​​of all image elements contained in the image block in the standard information plane image, calculate the difference between the two, and if the difference is greater than a certain value, determine that the image block in the information plane image is a problem image block.

[0051] S23. In the information surface image, use several adjacent problem image blocks to form a problem section, and record the address of the problem section.

[0052] Specifically, the process of comparing the standard information surface image and the information surface image to identify several problematic parts in the information surface image is described. In S21, the image element at the top left corner of the standard information surface image is taken as the origin. The image element, i.e., the pixel, is used to establish an image coordinate system with the horizontal rightward direction as the positive x-axis and the vertical downward direction as the positive y-axis. At the same time, an image coordinate system is also established on the information surface image using the same method. Then, the standard information surface image and the information surface image are divided into several image blocks using the same method. Each image block contains the same number of image elements. In S22, for image blocks in the information plane image, image blocks in the standard information plane image with the same address are identified. The address refers to the coordinates in the coordinate system. The sum of the image element values ​​of all image elements contained in the image block in the information plane image and the sum of the image element values ​​of all image elements contained in the image block in the standard information plane image are calculated. When the image element value is an RGB value, that is, the sum of the r, g, and b values ​​of all image elements are calculated separately, and the difference between the two is calculated. Specifically, the Euclidean distance formula can be used for calculation. If the difference is greater than a certain value, the image block in the information plane image is determined to be a problem image block. Problem image blocks may correspond to blemishes, foreign objects, ripples, bumps, etc. In S23, several problem image blocks with adjacent coordinates in the information plane image are grouped into a problem section, and the address of the problem section is recorded.

[0053] Furthermore, a comparative process is performed between the standard rear surface image and the rear surface image to identify several problematic portions in the rear surface image, including the following steps:

[0054] S31. Establish an image coordinate system on the standard back surface image with the image element in the upper right corner as the origin, the horizontal leftward direction as the positive x-axis, and the vertical downward direction as the positive y-axis. Establish an image coordinate system on the back surface image using the same method. Divide the standard back surface image and the back surface image into several image blocks by dividing the information surface image.

[0055] S32. For image blocks in the rear surface image, determine the image blocks in the standard rear surface image with the same address, calculate the sum of the image element values ​​of all image elements contained in the image block in the rear surface image, calculate the sum of the image element values ​​of all image elements contained in the image block in the standard rear surface image, and if the difference between the two is greater than a preset value, determine that the image block in the rear surface image is a problem image block.

[0056] S33. In the back surface image, use several adjacent problem image blocks to form a problem section, and record the address of the problem section.

[0057] Specifically, this section describes the process of comparing a standard rear surface image with another rear surface image to identify several problematic parts in the rear surface image. This process is similar to the process of comparing a standard information surface image with another information surface image to identify several problematic parts in the information surface image. In S31, an image coordinate system is established with the image element at the upper right corner of the standard rear surface image as the origin, the horizontal direction to the left as the positive x-axis, and the vertical direction downward as the positive y-axis. An image coordinate system is also established on the rear surface image using the same method. Based on this, the standard rear surface image and the rear surface image are divided into several image blocks using the same method as for dividing the information surface image. In S32, regarding the image blocks in the rear surface image, image blocks in the standard rear surface image with the same address are identified. The sum of the image element values ​​of all image elements contained in the image block in the rear surface image and the sum of the image element values ​​of all image elements contained in the image block in the standard rear surface image are calculated. If the difference between the two is greater than a preset value, the image block in the rear surface image is determined to be a problematic image block. Problematic image blocks may correspond to foreign objects, unevenness, or other problems. In S33, several adjacent problem image blocks in the rear surface image are combined to form a problem section, and the address of the problem section is recorded.

[0058] Furthermore, based on the comparison results corresponding to the information surface image and the corresponding rear surface image, the causes of problems corresponding to each problematic part in the information surface image are determined, including the following steps:

[0059] S41. For the problematic part in the information surface image, determine whether there is a problematic part with the same address in the rear surface image. If not, determine that the problematic part in the information surface image is caused by printing issues. If yes, continue to the next step.

[0060] S42. Determine whether the size of the problematic part in the information surface image is greater than a preset threshold. If not, remove the problematic part from the information surface image. If yes, determine that the problematic part in the information surface image is caused by the composite label paper itself.

[0061] Specifically, this section describes the process of determining the cause of each problematic portion in the information surface image based on the comparison results of the corresponding information surface image and the corresponding back surface image. In S41, for each problematic portion in the information surface image, it is determined whether there is a problematic portion with the same address in the back surface image. If not, the problematic portion in the information surface image can be considered to be caused by printing issues. If it exists, proceed to S42. In S42, it is determined whether the size, i.e., the area, of the problematic portion in the information surface image is greater than a preset threshold. The preset threshold is determined based on the actual application scenario. If it is not greater than the threshold, the problematic portion in the information surface image is removed, meaning that the negative impact of the problematic portion in the information surface image is considered small and can be disregarded as a problematic portion, thereby reducing the number of discarded composite label sheets to some extent. If it is greater than or equal to the threshold, the problematic portion in the information surface image can be considered to be caused by the composite label sheet itself.

[0062] Furthermore, set specific values ​​through the following steps:

[0063] S221. Generate test images of different problem levels, and compare the standard information surface image with the test images of each problem level to obtain the specific values ​​to be selected for each test image of each problem level.

[0064] S222. Set the problem level range, determine several candidate specific values ​​corresponding to the problem level range, and take the smallest candidate specific value among the several candidate specific values ​​as the specific value.

[0065] S223. Determine whether a specific value needs to be reset. If yes, jump to S221; otherwise, end all steps.

[0066] Furthermore, generating test images with different problem levels includes: setting several problem types, generating problem images of different problem levels for each problem type, with the problem images based on image blocks as the basic unit, and adding several problem images of the same problem level to the standard information surface image to obtain test images of the corresponding problem levels.

[0067] Specifically, the process of setting specific values ​​will be introduced first. As you can imagine, the process of setting preset values ​​is similar to setting specific values, so it will not be repeated here; you can also directly use the specific values. In S221, test images of different problem levels are generated. The standard information surface image and the test images of each problem level are compared separately. The purpose is to obtain the candidate specific values ​​corresponding to each problem level's test image. The specific method for generating test images of different problem levels is as follows: Several problem types are set, such as blemishes, bumps, ripples, and foreign objects. For each problem type, a problem image of a different problem level is generated. For example, for blemishes, a higher problem level blemish image has a darker color. The problem image is based on image blocks, and the size of these image blocks is the same as the size mentioned above. Several problem images of the same problem level are added to the standard information surface image to obtain the corresponding problem level test image. For example, if there are four problem types, each with high, medium, and low problem level problem images, then adding high-problem-level problem images of all four problem types to the standard information surface image simultaneously will yield a high-problem-level test image. In step S222, the problem level range is set. This range can be determined based on the tolerance level for problems occurring with the composite label paper. For example, the problem level range could be high or medium. Several candidate specific values ​​corresponding to the problem level range are then identified, and the smallest candidate specific value is selected as the specified value. In step S223, it is determined whether the specific value needs to be reset. If so, for example, when adding a problem type or problem level, execution jumps to step S221 to continue, thus dynamically changing the specific value according to application requirements. If not, all steps end.

[0068] Furthermore, the standard information surface image and the test images for each problem level are compared and processed separately to obtain the specific candidate values ​​corresponding to the test images for each problem level, including the following steps:

[0069] S2211. Set initial specific values ​​and select the test image of the highest problem level;

[0070] S2212. Compare the standard information surface image with the selected test image to identify several problem parts in the selected test image. Determine whether the several problem parts include all the problem images in the selected test image. If yes, use the preliminary specific value as the candidate specific value and continue to the next step. If no, continue to S2214.

[0071] S2213. Determine whether the specific values ​​corresponding to the test images of each problem level have been obtained. If yes, end all steps; otherwise, continue to the next step.

[0072] S2214. Select the test image with the highest problem level from all test images that have not yet obtained the candidate specific value, reduce the initial specific value by one step, and jump to S2212.

[0073] Specifically, the process of comparing the standard information surface image with test images at each problem level to obtain the candidate specific values ​​corresponding to each problem level's test images is described. In S2211, an initial specific value is set, initially set to a maximum value. The test image with the highest problem level is selected from the test images at different problem levels. In S2212, the standard information surface image is compared with the selected test image to identify several problem parts in the selected test image. The comparison process here is the same as the comparison process between the standard information surface image and the information surface image, so it will not be repeated. It is determined whether the several problem parts include all problem images in the selected test image. If so, the initial specific value is used as the candidate specific value, and the process continues to the next step. If not, the process continues to S2214. In S2213, it is determined whether the candidate specific values ​​corresponding to the test images at all problem levels have been obtained. If so, the process ends. If not, the process continues to S2214. In S2214, among all the test images for which the candidate specific value has not yet been obtained, the test image with the highest problem level is selected, and the initial specific value is reduced by one step. Then, the process jumps to S2212. It should be noted that before starting to execute S2211, the value represented by the step size has been initially set. For example, the initial value represented by the step size is set to 2. Before obtaining the candidate specific value corresponding to the test image with the highest problem level, the initial specific value is reduced by one step each time, that is, reduced by 2. This will be further explained below. After obtaining the candidate specific value corresponding to the test image with the highest problem level, how to dynamically adjust the value represented by the step size that reduces the initial specific value will be discussed later.

[0074] Furthermore, reducing the initial specific value by one step includes the following steps:

[0075] S22141. Determine the experimental image for which a specific value was obtained in the previous test, compare the standard information surface image with the determined experimental image, obtain several differences corresponding to each image block in the determined experimental image, and establish a first distribution histogram of several differences.

[0076] S22142. Compare the standard information surface image with the selected test image to obtain several differences corresponding to each image block in the selected test image, and establish a second distribution histogram of several differences.

[0077] S22143. Find the difference between the candidate specific value and the determined test image in the first distribution histogram, and determine the difference corresponding to the first trough in the second distribution histogram. If the difference between the two is greater than the preset first threshold, increase the value represented by the step size to reduce the initial specific value by one step size. If the difference between the two is less than the preset second threshold, decrease the value represented by the step size to reduce the initial specific value by one step size.

[0078] Specifically, the process of reducing the initial specific value by one step size after obtaining the candidate specific value corresponding to the test image of the highest problem level is described. In S22141, the test image for which the candidate specific value was obtained last time is determined. A comparison processing is performed between the standard information surface image and the determined test image. The comparison processing process here is the same as the comparison processing process between the standard information surface image and the information surface image, so it will not be repeated. Through the comparison processing, several differences corresponding to each image block in the determined test image are obtained, and a first distribution histogram of several differences is established. The horizontal axis of the first distribution histogram represents the difference, and the vertical axis represents the frequency of occurrence of the difference. In S22142, a comparison processing is performed between the standard information surface image and the test image selected this time. The comparison processing process here is the same as the comparison processing process between the standard information surface image and the information surface image, so it will not be repeated. Through the comparison processing, several differences corresponding to each image block in the selected test image are obtained, and a second distribution histogram of several differences is established. The horizontal axis of the second distribution histogram also represents the difference, and the vertical axis also represents the frequency of occurrence of the difference. In S22143, the difference between the selected specific value and the determined test image corresponding to the first distribution histogram is searched. This difference may be the same as or similar to the selected specific value corresponding to the determined test image. The difference corresponding to the first trough is determined in the second distribution histogram. Since there are no problem images in most of the selected test images, there are many small differences. Therefore, it is possible to determine all the problem images in the selected test images based on the difference corresponding to the first trough. The difference between the two is calculated. If it is greater than the preset first threshold, the preset first threshold is determined according to the actual application. In order to shorten the time to obtain the selected specific value corresponding to the selected test image, the value represented by the step size should be increased, for example, from 2 to 4. Then the initial specific value is reduced by one step size, that is, reduced by 4. If the difference between the two is less than the preset second threshold, the preset second threshold is determined according to the actual application. The preset second threshold is less than the preset first threshold. In order to ensure that the accurate selected specific value corresponding to the selected test image can be obtained, the value represented by the step size should be reduced, for example, from 2 to 1. The initial specific value is reduced by one step size, that is, reduced by 1.

[0079] The present invention also provides a composite label paper, including an information surface and a back surface. The composite label paper is produced using any of the methods described above, wherein the information surface is a face paper and the back surface is a hot melt adhesive film, and the face paper and the hot melt adhesive film are firmly laminated together.

[0080] Specifically, the face paper can be either ordinary paper or coated paper. The hot melt adhesive film is a thin film made of hot melt adhesive material, typically between 0.02 and 0.05 mm thick. Once heated to its melting point, the film melts into a liquid adhesive, providing excellent adhesion during bonding. Depending on the thickness and melting point of the hot melt adhesive film, the heating temperature and time need to be adjusted. Generally, labels are heated to 80-150°C for 15-30 seconds until the hot melt adhesive film on the back of the label is melted, at which point it can be applied. If the object to be labeled is itself a high-temperature object (80-150°C), the label can be applied directly without heating. After application, the label becomes even more secure and difficult to remove as the temperature decreases. During the production process, the face paper roll is preheated and then laminated with the hot melt adhesive roll. It passes between the heating roller and the pressure roller. Under the dual action of heating and pressure, the face paper and the hot melt adhesive film are firmly laminated together. After being cooled by cold air, it is cut according to the size of the target label to obtain the label paper product.

[0081] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating composite label paper based on graphic and textual information, characterized in that, The method includes: S1. Obtain in advance the standard information surface image corresponding to the information surface of the composite label paper and the standard back surface image corresponding to the back surface of the composite label paper. During the generation process, obtain the information surface image corresponding to the information surface of the composite label paper and the back surface image corresponding to the back surface of the composite label paper. S2. Compare the standard information surface image with the information surface image to identify several problematic parts in the information surface image; S3. Compare the standard rear surface image with the rear surface image to identify several problematic parts in the rear surface image; S4. Based on the comparison results of the information surface image and the comparison results of the back surface image, determine the cause of the problem corresponding to each problem part in the information surface image, and control the generation process according to the cause of the problem. The standard information surface image and the information surface image are compared to identify several problematic parts in the information surface image, including the following steps: S21. Establish an image coordinate system on the standard information surface image with the image element in the upper left corner as the origin, the horizontal direction to the right as the positive x-axis, and the vertical direction downward as the positive y-axis. Establish an image coordinate system on the information surface image using the same method. Divide the standard information surface image and the information surface image into several image blocks, each containing the same number of image elements. S22. For image blocks in the information plane image, identify image blocks in the standard information plane image with the same address, calculate the sum of the image element values ​​of all image elements contained in the image block in the information plane image, calculate the sum of the image element values ​​of all image elements contained in the image block in the standard information plane image, calculate the difference between the two, and if the difference is greater than a certain value, determine that the image block in the information plane image is a problem image block. S23. In the information surface image, use several adjacent problem image blocks to form a problem section, and record the address of the problem section; Set a specific value by following these steps: S221. Generate test images of different problem levels, and compare the standard information surface image with the test images of each problem level to obtain the specific values ​​to be selected for each test image of each problem level. S222. Set the problem level range, determine several candidate specific values ​​corresponding to the problem level range, and take the smallest candidate specific value among the several candidate specific values ​​as the specific value. S223. Determine whether a specific value needs to be reset. If yes, proceed to S221. If no, end all steps. The standard information surface image is compared with the test images for each problem level to obtain the specific candidate values ​​corresponding to the test images for each problem level. This includes the following steps: S2211. Set initial specific values ​​and select the test image of the highest problem level; S2212. Compare the standard information surface image with the selected test image to identify several problem parts in the selected test image. Determine whether the several problem parts include all the problem images in the selected test image. If yes, use the preliminary specific value as the candidate specific value and continue to the next step. If no, continue to S2214. S2213. Determine whether the specific values ​​corresponding to the test images of each problem level have been obtained. If yes, end all steps; otherwise, continue to the next step. S2214. Select the test image with the highest problem level from all test images that have not yet obtained the candidate specific value, reduce the preliminary specific value by one step, and jump to S2212. Decrease the initial specific value by one step, including the following steps: S22141. Determine the experimental image for which a specific value was obtained in the previous test, compare the standard information surface image with the determined experimental image, obtain several differences corresponding to each image block in the determined experimental image, and establish a first distribution histogram of several differences. S22142. Compare the standard information surface image with the selected test image to obtain several differences corresponding to each image block in the selected test image, and establish a second distribution histogram of several differences. S22143. Find the difference between the candidate specific value and the determined test image in the first distribution histogram, and determine the difference corresponding to the first trough in the second distribution histogram. If the difference between the two is greater than the preset first threshold, increase the value represented by the step size to reduce the initial specific value by one step size. If the difference between the two is less than the preset second threshold, decrease the value represented by the step size to reduce the initial specific value by one step size.

2. The method for generating composite label paper based on graphic and textual information according to claim 1, characterized in that, The standard rear surface image and the rear surface image are compared to identify several problematic parts in the rear surface image, including the following steps: S31. Establish an image coordinate system on the standard back surface image with the image element in the upper right corner as the origin, the horizontal leftward direction as the positive x-axis, and the vertical downward direction as the positive y-axis. Establish an image coordinate system on the back surface image using the same method. Divide the standard back surface image and the back surface image into several image blocks by dividing the information surface image. S32. For image blocks in the rear surface image, determine the image blocks in the standard rear surface image with the same address, calculate the sum of the image element values ​​of all image elements contained in the image block in the rear surface image, calculate the sum of the image element values ​​of all image elements contained in the image block in the standard rear surface image, and if the difference between the two is greater than a preset value, determine that the image block in the rear surface image is a problem image block. S33. In the back surface image, use several adjacent problem image blocks to form a problem section, and record the address of the problem section.

3. The method for generating composite label paper based on graphic and textual information according to claim 2, characterized in that, Generating test images with different problem levels includes: setting several problem types, generating problem images of different problem levels for each problem type, with the problem images based on image blocks as the basic unit, and adding several problem images of the same problem level to the standard information surface image to obtain test images of the corresponding problem levels.

4. The method for generating composite label paper based on graphic and textual information according to claim 3, characterized in that, Based on the comparison results of the information surface image and the corresponding rear surface image, the causes of problems for each problematic part in the information surface image are determined, including the following steps: S41. For the problematic part in the information surface image, determine whether there is a problematic part with the same address in the rear surface image. If not, determine that the problematic part in the information surface image is caused by printing issues. If yes, continue to the next step. S42. Determine whether the size of the problematic part in the information surface image is greater than a preset threshold. If not, remove the problematic part from the information surface image. If yes, determine that the problematic part in the information surface image is caused by the composite label paper itself.

5. A composite label paper, comprising an information surface and a back surface, characterized in that, The composite label paper is produced using the method described in any one of claims 1-4.

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