Environment-friendly printing platemaking method and device

Abstract

The invention discloses a green and environment-friendly printing plate-making method and device, and the method comprises the steps: collecting an exposed offset plate image, dividing the offset plate image into detection blocks, and calculating the image definition through an edge detection algorithm and a block gray value; if the image definition does not meet the requirement, constructing an image definition and exposure time sequence, and determining an association condition of the image definition and the exposure time sequence through association degree analysis; and if the correlation exists, marking the offset plate with the image definition lower than the minimum value as an exposure optimization plate, performing fitting analysis on the image definition and the exposure time to obtain compensation time, and performing compensation exposure on the exposure optimization plate based on the exposure compensation time. The device comprises an image acquisition module, an image analysis module, an association calculation module and a compensation optimization module. According to the method, the exposure time can be optimized, the definition of the offset plate is improved, material waste is reduced, and green and environment-friendly plate making is facilitated.

Description

Technical Field

[0001] The invention relates to the technical field of printing plate making, and in particular to a green and environmentally friendly printing plate making method and device. Background Art

[0002] In the field of printing plate making, the quality of offset printing plates directly affects the final effect of printed products. With the increasing awareness of environmental protection and the continuous increase in market demand for high-quality printed products, traditional printing plate making technology has gradually exposed some problems.

[0003] In the prior art, due to inaccurate exposure parameter adjustment, the printing plate is discarded because the clarity does not meet the standard, resulting in waste of photosensitive materials, chemicals, etc. At the same time, repeated production of offset printing plates also increases energy consumption, which is not in line with the concept of green environmental protection.

[0004] In the existing technology, it is rare to monitor the exposure effect of the offset printing plate in real time and provide timely feedback and adjustment. This means that if there is a problem during the exposure process, it cannot be discovered and corrected in time, and the problem is not discovered until the offset printing plate is completed. At this time, it can only be discarded or remade, which increases cost and time consumption.

[0005] To this end, the present invention provides a green and environmentally friendly printing plate making method and device. Summary of the invention

[0006] The object of the present invention is to provide a green and environmentally friendly printing plate making method and device to solve at least one of the above-mentioned prior art problems.

[0007] In a first aspect, the present invention provides a green and environmentally friendly printing plate making method, comprising:

[0008] Step 1: Use an image sensor to collect an image of an offset printing plate after exposure, divide the image into multiple detection blocks, and obtain the grayscale value of each pixel in the detection block;

[0009] Step 2: Analyze the exposure results of each detection block, use the edge detection algorithm to obtain the edge strength of each monitoring block, perform numerical analysis based on the block gray value, and obtain the image clarity Tx. Based on the image clarity Tx, determine whether the image clarity meets the requirements;

[0010] Step 3: If the image clarity does not meet the requirements, obtain the historical image clarity and exposure time, construct an image clarity sequence and an exposure time sequence, and perform a correlation analysis on the image clarity sequence and the exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity;

[0011] Step 4: If the exposure time of the offset printing plate is correlated with the image clarity Tx, mark the offset printing plate whose image clarity Tx is lower than the minimum value of the image clarity range as an exposure optimized plate, perform fitting analysis on the image clarity and exposure time, obtain the exposure compensation time, and compensate the exposure time of the exposure optimized plate based on the exposure compensation time.

[0012] In a second aspect, the present invention provides a green and environmentally friendly printing platemaking device, comprising: an image acquisition module: using an image sensor to acquire an image of an offset printing plate after exposure, dividing the image into a plurality of detection blocks, and obtaining a grayscale value of each pixel in the detection block;

[0013] Image analysis module: analyzes the exposure results of each detection block, uses the edge detection algorithm to obtain the edge strength of each monitoring block, performs numerical analysis based on the block gray value, obtains the image clarity Tx, and based on the image clarity Tx, determines whether the image clarity meets the requirements;

[0014] Correlation calculation module: If the image clarity does not meet the requirements, obtain the historical image clarity and exposure time, construct the image clarity sequence and exposure time sequence, and perform correlation analysis on the image clarity sequence and exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity;

[0015] Compensation optimization module: If the exposure time of the offset printing plate is correlated with the image clarity Tx, the offset printing plate whose image clarity Tx is lower than the minimum value of the image clarity range is marked as an exposure optimized plate, and a fitting analysis is performed on the image clarity and exposure time to obtain the exposure compensation time. Based on the exposure compensation time, the exposure time of the exposure optimized plate is compensated.

[0016] Beneficial effects of the present invention:

[0017] 1. By collecting the offset printing plate image and dividing it into detection blocks, the edge detection algorithm is used in combination with the block grayscale value to accurately calculate the image clarity Tx, so as to judge the exposure effect. For offset printing plates that do not meet the clarity requirements, the historical image clarity and exposure time data are further obtained, and the correlation analysis is performed to determine the relationship between exposure time and image clarity.

[0018] 2. For the exposure optimization board with image clarity Tx lower than the minimum value of the range, the exposure compensation time is obtained through fitting analysis and compensation is performed. This data-driven precision optimization method can make the exposure time more accurately adapt to the characteristics of each offset printing plate, effectively improve image clarity, reduce edge blur and abnormal contrast caused by underexposure or overexposure, and reduce the number of repeated production due to offset printing plate quality problems, thereby achieving green and environmentally friendly printing platemaking. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flowchart of image acquisition and analysis provided by Embodiment 1 of the present invention;

[0021] Figure 2 is a flow chart of association analysis and exposure optimization provided by Embodiment 2 of the present invention;

[0022] Figure 3 It is a module diagram of a green and environmentally friendly printing plate-making device provided by the present invention;

[0023] Figure 4 It is a structural diagram of a computer analysis device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] Embodiment 1

[0026] Figure 1 The flowchart of the image acquisition and analysis method provided in the first embodiment of the present invention is applicable to the case of offset plate image acquisition and image analysis. The image acquisition and analysis method can be executed by a green and environmentally friendly printing platemaking system. The green and environmentally friendly printing platemaking system can be implemented by software and / or hardware. The green and environmentally friendly printing platemaking system can be configured in a green and environmentally friendly printing platemaking device. Optionally, a green and environmentally friendly printing platemaking device can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc., and the embodiment of the present invention does not limit this.

[0027] like Figure 1 As shown, the method for image acquisition and analysis provided by the embodiment of the present invention specifically includes the following steps:

[0028] Step 1: Use an image sensor to collect and expose the image of the offset printing plate in real time, divide the image into multiple detection blocks, and obtain the grayscale value of each pixel in the detection block;

[0029] In some embodiments, an image sensor is installed on the top of the exposure device, and the image sensor is used to obtain an image of the offset printing plate, and the image is divided into a plurality of detection blocks;

[0030] It should be noted that in the process of offset printing, the photosensitive material will undergo a photochemical reaction under the action of ultraviolet rays. After the exposed image and text part of the offset printing plate is developed, the unexposed part will be removed during the development process, and the exposed image and text part will be retained;

[0031] In some embodiments, an image of the offset printing plate after exposure of each monitoring block is acquired, and the color image is converted into a grayscale image;

[0032] Specifically, the gray value Gray of each pixel in each monitoring block of the image is obtained by the gray value calculation formula: Gray = 0.299*R+0.587*G+0.114*B, and the gray value of each pixel is adjusted according to the gray value, where R, G, and B are the pixel values ​​of the red, green, and blue channels of the offset plate image, respectively, and the pixel values ​​of the red, green, and blue channels are obtained by the image sensor;

[0033] For example, if the pixel values ​​of the R, G, and B channels of a pixel are 100, 120, and 80 respectively, the gray value Gray is 109.46 according to the gray value calculation formula;

[0034] Based on the grayscale calculation formula, the grayscale value of each pixel is extracted;

[0035] Step 2: Based on the gray value of each pixel, analyze the exposure result of each detection block, use the edge detection algorithm to obtain the edge strength G(i,j) of each monitoring block, and perform numerical analysis in combination with the block gray value to obtain the image clarity Tx. Based on the image clarity Tx, determine whether the image clarity meets the requirements;

[0036] In some embodiments, an edge detection algorithm is used to obtain the edge strength G(i, j) of each detection block;

[0037] Specifically, the Sobel operator of the edge detection algorithm is used to construct two 3x3 convolution kernels, and the coordinate system is established with the upper left vertex of the image as the origin. The coordinates of each pixel are (i, j);

[0038] Based on the grayscale value of the pixel in each monitoring block, the grayscale change gradient of the image of each detection block in the horizontal and vertical directions is calculated respectively, and the gradient in the horizontal direction is marked as Gx (i, j), the gradient value in the vertical direction is G y (i,j);

[0039] Exemplarily, the convolution kernel in the vertical direction of the pixel point (1, 1) coordinate is: The horizontal convolution kernel is:

[0040] Get the coordinates (i, j) of the pixel point in the monitoring block and the convolution kernel corresponding to the pixel coordinates, and calculate the horizontal gradient value G of each pixel point in the monitoring block x (i,j);

[0041] By formula: Get the gradient value in the horizontal direction;

[0042] Where I(i+m, j+n) is the grayscale value of the pixel with coordinates (i+m, j+n) in the detection block, and K x (m,n) is the corresponding element in the horizontal convolution kernel, and m and n are index variables used to traverse the position of the convolution kernel elements;

[0043] It should be noted that for the Sobel convolution kernel in the horizontal direction, it is a 3x3 matrix with 9 elements. The value range of m and n is [0,2]. When m=0 and n=0, it represents the element in the upper left corner of the convolution kernel. When m=0 and n=1, it represents the element in the first row and second column of the convolution kernel. Based on the increasing element number, it is ensured that each element can be multiplied with the corresponding pixel in the image pixel area.

[0044] Based on the horizontal gradient value calculation method of the pixel point in the monitoring block, the vertical gradient value G of the pixel point is obtained. y (i,j);

[0045] Based on the horizontal gradient value G x (i, j), the gradient value G in the vertical direction y (i, j), obtain the edge strength G(i, j) of each detection block;

[0046] By formula Get the edge strength G(i,j) of each pixel in the detection block;

[0047] For example, taking the pixel (1, 1) as an example, when m = 0 and n = 0, 1, 2, G x (1,1)=-20, -40, -20, when m=1 and n=0, 1, 2, G x (1,1)=20,0,0, when m=2 and n=0,1,2, G x(1,1) = -20, -40, -20, and the horizontal gradient value G is obtained by summing x (1,1) = -140, based on the vertical gradient calculation method in the horizontal direction, the vertical gradient value G is obtained y (1,1)=0, edge strength G(1,1)=140;

[0048] Obtain the edge strength G(i,j) of all pixels in the monitoring block, sum and average the edge strength G(i,j) of all pixels to obtain the block edge strength;

[0049] Obtain the block edge strength of all monitoring blocks, sum and average the edge strength of all monitoring blocks to obtain the image edge strength, and mark the image edge strength as By;

[0050] Obtain the grayscale value of each pixel in the monitoring block, put the grayscale value of each pixel into a grayscale value data group, and obtain the maximum and minimum grayscale values ​​in the grayscale value data group;

[0051] Perform difference processing on the maximum and minimum gray values ​​in the gray value data group to obtain the block contrast;

[0052] Obtain the block contrast of all monitoring blocks, sum and average the block contrast of all monitoring blocks to obtain the image contrast, and mark the image contrast as Db;

[0053] Based on the image edge intensity By and image contrast Db, dimensionless processing is performed to calculate the image clarity Tx;

[0054] By formula: Get the image clarity Tx, where a=0.561, b=0.439;

[0055] Compare the image clarity Tx with the image clarity range to determine whether the clarity of the offset printing plate image after exposure meets the requirements;

[0056] If the image clarity Tx is within the image clarity range, it indicates that the clarity of the offset printing plate image after exposure meets the requirements;

[0057] If the image clarity Tx is not within the image clarity range, it means that the image clarity Tx does not meet the requirements within the offset printing plate image after exposure;

[0058] For example, if the block edge strength is 140 and the block contrast is 70, the image clarity calculation formula is used to obtain the image clarity Tx=0.713 and the image clarity range is [1,2.5], indicating that the image clarity of the offset printing plate is not within the image clarity range and the image clarity does not meet the requirements;

[0059] It should be noted that edge strength reflects the degree of edge prominence in an image. If the edge strength of each detected block of an image is higher, the image will be clearer and sharper. If the edge strength is lower, the clarity of the image text will be lower.

[0060] Block contrast reflects the degree of difference between the bright and dark parts of the image. High-contrast blocks tend to have higher clarity and greater grayscale differences, that is, high block contrast, which can make the outline and details of the object clearer;

[0061] The technical solution of this embodiment is: using an image sensor to collect in real time, the image of the offset printing plate after exposure is divided into multiple detection blocks, and the grayscale value of each pixel in the detection block is obtained. Based on the grayscale value of each pixel, the exposure result of each detection block is analyzed, and the edge detection algorithm is used to obtain the edge strength of each monitoring block. The block grayscale value is combined for numerical analysis to obtain the image clarity Tx. Based on the image clarity Tx, it is judged whether the image clarity meets the requirements, thereby realizing the analysis and judgment of the offset printing plate clarity, and laying a data foundation for subsequent optimization analysis.

[0062] Embodiment 2

[0063] like Figure 2 As shown, the method for association analysis and exposure optimization provided by the embodiment of the present invention specifically includes the following steps:

[0064] Step 3: If the image clarity does not meet the requirements, obtain the historical image clarity and exposure time, construct an image clarity sequence and an exposure time sequence, and perform a correlation analysis on the image clarity sequence and the exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity;

[0065] If the image clarity does not meet the requirements, obtain the historical image clarity data and construct the image clarity sequence X;

[0066] Where X=[Tx1 Tx2 ... Tx z ], z is the total number of historical images, Tx1 represents the clarity of the first image;

[0067] In some embodiments, a timer is installed in the exposure device to obtain the exposure time of each exposure offset printing plate, and the exposure time is marked as Pg;

[0068] Get the exposure time of each historical image and construct the exposure time series Y;

[0069] Where Y=[Pg1 Pg2 ... Pg z ], z is the total number of images, Pg1 is the exposure time of the first image;

[0070] Normalize the image clarity sequence X and the exposure time sequence Y;

[0071] Specifically, through the formula: Get the average value of the image clarity sequence X The clarity of each image in the image clarity sequence is equal to the average value of the image clarity sequence X. Perform ratio processing to obtain the image clarity sequence X′;

[0072] Based on the acquisition method of the image definition sequence X′, the exposure time sequence Y′ is obtained;

[0073] Calculate the correlation coefficient ξ based on the image clarity sequence X′ and exposure time sequence Y′ i (k);

[0074] By formula: Get the correlation coefficient ξ i (k), where k represents the kth data point in the image clarity sequence X′ or the exposure time sequence Y′, k = 1, 2, ..., z, ρ is the resolution coefficient, ρ = 0.5, min i min k |X i ′(k)-Y i ′(k)| represents the absolute value of the minimum difference between the two levels, max i max k |X i ′(k)-Y i ′(k)| represents the absolute value of the maximum difference between the two levels;

[0075] It should be noted that the minimum difference between the two levels and the maximum difference between the two levels reflect the degree of difference in the sequence;

[0076] Based on the correlation coefficient ξ i (k) Calculate the correlation coefficient ξ of the image clarity sequence X′ and the exposure time sequence Y′ i (k);

[0077] By formula: Get the grey relational degree r, where r ranges from (0,1);

[0078] It should be noted that the closer r is to 1, the higher the correlation between exposure time and image clarity Tx, and the closer r is to 0, the lower the correlation;

[0079] The grey relational degree r is processed with the maximum endpoint value of the r value range (0,1) to obtain the relational difference;

[0080] The correlation difference is processed by ratioing the length of the r value range to obtain the correlation closeness ratio;

[0081] Compare the correlation proximity ratio with the proximity ratio threshold to determine whether the exposure time of the offset printing plate is correlated with the image definition Tx;

[0082] If the correlation proximity ratio is higher than the proximity ratio threshold, it indicates that the exposure time of the offset printing plate is correlated with the image definition Tx;

[0083] If the correlation proximity ratio is lower than the proximity ratio threshold, it indicates that the exposure time of the offset printing plate is not correlated with the image definition Tx;

[0084] Step 4: If the exposure time of the offset printing plate is correlated with the image definition Tx, the offset printing plate whose image definition Tx is lower than the minimum value of the image definition range is marked as an exposure optimized plate, and the image definition and exposure time are fitted and analyzed to obtain the exposure compensation time. Based on the exposure compensation time, the exposure time of the exposure optimized plate is compensated;

[0085] If the image clarity Tx is lower than the minimum value of the image clarity range, the offset printing plate corresponding to the image is marked as an exposure optimized plate;

[0086] If the image clarity Tx is higher than the maximum value of the image clarity range, no processing is performed;

[0087] It should be noted that when the image clarity Tx is higher than the maximum value of the image clarity range, the situation of excessive edge intensity or excessive contrast caused by overexposure cannot be repaired by adjusting the exposure time, that is, the image clarity cannot be compensated and repaired by adjusting the exposure time;

[0088] Obtain the image clarity Tx under the historical exposure time, and draw a scatter plot of exposure time-image clarity Tx in a two-dimensional rectangular coordinate system;

[0089] Taking the minimum and maximum values ​​of the image clarity range as reference values, reference lines corresponding to the reference values ​​are drawn in a two-dimensional rectangular coordinate system;

[0090] Use the polofit function in the numpy library in Python to perform a quadratic polynomial fit on the image clarity and exposure time to obtain a fitting curve;

[0091] Obtaining the intersection point of the fitting curve and the minimum value of the image definition range, and taking the intersection point of the fitting curve and the minimum value of the image definition range as the compensation time point;

[0092] Obtain the exposure time corresponding to the exposure optimization board, and mark the exposure time corresponding to the exposure optimization board as the time point to be compensated;

[0093] Perform difference processing on the time corresponding to the calculation point to be compensated and the compensation time point to obtain the exposure compensation time;

[0094] The exposure time of the exposure optimization board is compensated based on the exposure compensation time, that is, the exposure optimization board is exposed according to the exposure compensation time through the exposure device;

[0095] It should be noted that by performing exposure compensation on the exposure optimization plate, the offset printing plate with a definition lower than the range can be improved, thereby improving the quality of the offset printing plate, reducing the material waste of the offset printing plate, reducing the number of repeated offset printing plates, and realizing green and environmentally friendly printing plate making;

[0096] The technical solution of this embodiment is: if the clarity of the image does not meet the requirements, obtain the historical image clarity and historical exposure time, construct an image clarity sequence and an exposure time sequence, and perform correlation analysis on the image clarity sequence and the exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity. If the exposure time of the offset printing plate is correlated with the image clarity Tx, mark the offset printing plate whose image clarity Tx is lower than the minimum value of the image clarity range as an exposure optimized plate, perform fitting analysis on the image clarity and exposure time, and obtain the exposure compensation time. Based on the exposure compensation time, compensate the exposure time of the exposure optimized plate to reduce problems such as blurred edges and abnormal contrast caused by under- or over-exposure, reduce the number of repeated production due to quality problems of the offset printing plate, and thereby achieve green and environmentally friendly printing platemaking.

[0097] Embodiment 3

[0098] like Figure 3 As shown, an embodiment of the present invention provides a green and environmentally friendly printing plate making device, including:

[0099] Image acquisition module: Use the image sensor to collect the exposed offset printing plate image, divide the image into multiple detection blocks, and obtain the grayscale value of each pixel in the detection block;

[0100] Image analysis module: analyzes the exposure results of each detection block, uses the edge detection algorithm to obtain the edge strength of each monitoring block, performs numerical analysis based on the block gray value, obtains the image clarity Tx, and based on the image clarity Tx, determines whether the image clarity meets the requirements;

[0101] Correlation calculation module: If the image clarity does not meet the requirements, obtain the historical image clarity and exposure time, construct the image clarity sequence and exposure time sequence, and perform correlation analysis on the image clarity sequence and exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity;

[0102] Compensation optimization module: If the exposure time of the offset printing plate is correlated with the image clarity Tx, the offset printing plate whose image clarity Tx is lower than the minimum value of the image clarity range is marked as an exposure optimized plate, and the image clarity and exposure time are fitted and analyzed to obtain the exposure compensation time. Based on the exposure compensation time, the exposure time of the exposure optimized plate is compensated;

[0103] Embodiment 4

[0104] Reference Figure 3 The embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a green and environmentally friendly printing platemaking method as described in any one of the above methods is implemented.

[0105] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that

[0106] Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0107] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0108] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0109] Embodiment 5

[0110] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, a green and environmentally friendly printing platemaking method as described in any one of the above methods is implemented.

[0111] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0112] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0113] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0114] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0115] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0116] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0117] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A green and environmentally friendly printing plate making method, characterized in that: The following steps are involved: Step 1: Use an image sensor to collect an image of an offset printing plate after exposure, divide the image into multiple detection blocks, and obtain the grayscale value of each pixel in the detection block; Step 2: Analyze the exposure results of each detection block, use the edge detection algorithm to obtain the edge strength of each monitoring block, perform numerical analysis based on the block gray value, and obtain the image clarity Tx. Based on the image clarity Tx, determine whether the image clarity meets the requirements; Step 3: If the image clarity does not meet the requirements, obtain the historical image clarity and exposure time, construct an image clarity sequence and an exposure time sequence, and perform a correlation analysis on the image clarity sequence and the exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity; Step 4: If the exposure time of the offset printing plate is correlated with the image clarity Tx, mark the offset printing plate whose image clarity Tx is lower than the minimum value of the image clarity range as an exposure optimized plate, perform fitting analysis on the image clarity and exposure time, obtain the exposure compensation time, and compensate the exposure time of the exposure optimized plate based on the exposure compensation time.

2. A green and environmentally friendly printing plate making method according to claim 1, characterized in that: The method for judging whether the image clarity meets the requirements is: Calculate the image clarity Tx based on the image edge intensity By and image contrast Db; By formula: Get the image definition Tx, where a and b are preset proportional coefficients; If the image clarity Tx is within the image clarity range, it indicates that the clarity of the offset printing plate image after exposure meets the requirements.

3. A green and environmentally friendly printing plate making method according to claim 2, characterized in that: The image edge strength By is obtained as follows: Use the Sobel operator of the edge detection algorithm to construct two 3x3 convolution kernels, take the upper left vertex of the image as the coordinate origin, establish a coordinate system, and the coordinates of each pixel are (i, j); Based on the grayscale value of the pixel in each monitoring block, the grayscale change gradient of the image of each detection block in the horizontal and vertical directions is calculated respectively, and the gradient in the horizontal direction is marked as G x (i, j), the gradient value G in the vertical direction y (i,j); Get the coordinates (i, j) of the pixel point in the monitoring block and the convolution kernel corresponding to the pixel coordinates, and calculate the horizontal gradient value G of each pixel point in the monitoring block x (i,j); By formula: Get the horizontal gradient value, where I(i+m, j+n) is the grayscale value of the pixel with coordinates (i+m, j+n) in the detection block, and K x (m,n) is the corresponding element in the horizontal convolution kernel, and m and n are index variables used to traverse the position of the convolution kernel elements; Based on the horizontal gradient value calculation method of the pixel point in the monitoring block, the vertical gradient value G of the pixel point is obtained. y (i,j); Based on the horizontal gradient value G x (i, j), the gradient value G in the vertical direction y (i, j), get the edge strength G(i, j) of each detection block: By formula Get the edge strength G(i,j) of each pixel in the detection block; Obtain the edge strength G(i,j) of all pixels in the monitoring block, sum and average the edge strength G(i,j) of all pixels to obtain the block edge strength, and mark the block edge strength as By; Obtain the block edge strengths of all monitoring blocks, sum and average the edge strengths of all monitoring blocks to obtain the image edge strength, and mark the image edge strength as By.

4. A green and environmentally friendly printing plate making method according to claim 2, characterized in that: The image contrast Db is obtained as follows: Obtain the grayscale value of each pixel in the monitoring block, put the grayscale value of each pixel into a grayscale value data group, and obtain the maximum and minimum grayscale values ​​in the grayscale value data group; Perform difference processing on the maximum and minimum gray values ​​in the gray value data group to obtain the block contrast; Obtain the block contrast of all monitoring blocks, sum and average the block contrast of all monitoring blocks to obtain the image contrast, and mark the image contrast as Db.

5. A green and environmentally friendly printing plate making method according to claim 1, characterized in that: The method for determining whether the exposure time of the offset printing plate is correlated with the image clarity is as follows: The grey relational degree r is processed with the maximum endpoint value of the r value range (0,1) to obtain the relational difference; The correlation difference is processed by ratioing the length of the r value range to obtain the correlation closeness ratio; Compare the correlation proximity ratio with the proximity ratio threshold to determine whether the exposure time of the offset printing plate is correlated with the image definition Tx; If the correlation proximity ratio is higher than the proximity ratio threshold, it indicates that the exposure time of the offset printing plate is correlated with the image definition Tx.

6. A green and environmentally friendly printing plate making method according to claim 5, characterized in that: The grey relational degree r is obtained as follows: Based on the correlation coefficient ξ i (k) Calculate the grey relational degree r of the image definition sequence X′ and the exposure time sequence Y′; By formula: Get the grey relational degree r.

7. A green and environmentally friendly printing plate making method according to claim 6, characterized in that: The correlation coefficient ξ i (k) can be obtained by: If the image clarity does not meet the requirements, obtain the historical image clarity data and construct the image clarity sequence X; Where X=[Tx1 Tx2 ... Tx z ], z is the total number of historical images, Tx1 represents the clarity of the first image; A timer is installed in the exposure device to obtain the exposure time of each exposure offset printing plate, and the exposure time is marked as Pg; Get the exposure time of each historical image and construct the exposure time series Y; Where Y=[Pg1 Pg2 ... Pg z ], z is the total number of images, Pg1 is the exposure time of the first image; Normalize the image clarity sequence X and the exposure time sequence Y; By formula: Get the average value of the image clarity sequence X The clarity of each image in the image clarity sequence is equal to the average value of the image clarity sequence X. Perform ratio processing to obtain the image clarity sequence X′; Based on the acquisition method of the image definition sequence X′, the exposure time sequence Y′ is obtained; Calculate the correlation coefficient ξ based on the image clarity sequence X′ and exposure time sequence Y′ i (k); By formula: Get the correlation coefficient ξ i (k), where k represents the kth data point in the image clarity sequence X′ or the exposure time sequence Y′, k = 1, 2, ..., z, ρ is the resolution coefficient, min i min k |X i ′(k)-Y i ′(k)| represents the absolute value of the minimum difference between the two levels, max i max k |X i ′(k)-Y i ′(k)| represents the absolute value of the maximum difference between the two levels.

8. The green and environmentally friendly printing plate making method according to claim 1, characterized in that: The exposure compensation time is obtained as follows: Obtaining the intersection point of the fitting curve and the minimum value of the image definition range, and taking the intersection point of the fitting curve and the minimum value of the image definition range as the compensation time point; Obtain the exposure time corresponding to the exposure optimization board, and mark the exposure time corresponding to the exposure optimization board as the time point to be compensated; Perform difference processing on the time corresponding to the calculation point to be compensated and the compensation time point to obtain the exposure compensation time; The exposure time of the exposure optimization board is compensated based on the exposure compensation time, that is, the exposure optimization board is exposed according to the exposure compensation time through the exposure device.

9. A green and environmentally friendly printing plate making method according to claim 8, characterized in that: The fitting curve is obtained as follows: If the image clarity Tx is lower than the minimum value of the image clarity range, the offset printing plate corresponding to the image is marked as an exposure optimized plate; Obtain the image clarity Tx under the historical exposure time, and draw a scatter plot of exposure time-image clarity Tx in a two-dimensional rectangular coordinate system; Taking the minimum and maximum values ​​of the image clarity range as reference values, reference lines corresponding to the reference values ​​are drawn in a two-dimensional rectangular coordinate system; Use the polynomial function in the numpy library in Python to perform quadratic polynomial fitting on the image clarity and exposure time to obtain the fitting curve.

10. A green and environmentally friendly printing plate making device, characterized in that: include: Image acquisition module: Use the image sensor to collect the exposed offset printing plate image, divide the image into multiple detection blocks, and obtain the grayscale value of each pixel in the detection block; Image analysis module: analyzes the exposure results of each detection block, uses the edge detection algorithm to obtain the edge strength of each monitoring block, performs numerical analysis based on the block gray value, obtains the image clarity Tx, and based on the image clarity Tx, determines whether the image clarity meets the requirements; Correlation calculation module: If the image clarity does not meet the requirements, obtain the historical image clarity and exposure time, construct the image clarity sequence and exposure time sequence, and perform correlation analysis on the image clarity sequence and exposure time sequence to determine whether the exposure time of the offset printing plate is correlated with the image clarity; Compensation optimization module: If the exposure time of the offset printing plate is correlated with the image clarity Tx, the offset printing plate whose image clarity Tx is lower than the minimum value of the image clarity range is marked as an exposure optimized plate, and a fitting analysis is performed on the image clarity and exposure time to obtain the exposure compensation time. Based on the exposure compensation time, the exposure time of the exposure optimized plate is compensated.

Images