A printing method and a printing apparatus

Abstract

The application provides a printing method and a printing device. The printing method comprises the following steps: splitting an obtained portrait to be printed to obtain a grayscale portrait image and a color portrait image; determining a target laser energy value of each pixel point in the grayscale portrait image, and performing laser etching on the grayscale portrait image on a printing medium based on the target laser energy value; and obtaining target printing data of the color portrait image according to the color portrait image and laser etching parameters. After obtaining the printing position of the grayscale portrait image on the printing medium, the color portrait image can be printed on the position where the grayscale portrait image is printed according to the target printing data, so as to complete the printing of the portrait to be printed. The embodiment of the application can effectively improve the fineness and color expression capability of image printing, so as to realize high-precision and high-quality portrait printing effect.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to, but are not limited to, the technical field of printing, and particularly to a printing method and a printing device. BACKGROUND

[0002] In the current printing technical field, portrait printing as an important application form is widely used in photo printing, ID card printing and other fields. Traditional portrait printing methods mostly adopt inkjet printing technology. Although these technologies can meet the basic printing needs to some extent, there are still many limitations in printing quality, printing speed and adaptability of printing materials. In recent years, laser etching technology has gradually shown great potential in the field of portrait printing. Laser etching technology can achieve high-precision and high-efficiency printing effect by directly etching or coloring on the printing medium through a laser beam. However, the existing laser etching methods mostly target monochrome or simple color images for printing, and there are still certain technical challenges for printing portrait images containing complex color information and portrait outlines. SUMMARY

[0003] The following is a summary of the subject matter of the detailed description herein. This summary is not intended to limit the scope of the claims.

[0004] Embodiments of the present application provide a printing method, which can effectively improve the fineness and color expression ability of image printing, thereby improving the quality of printed images.

[0005] In a first aspect, a printing method is provided, including: obtaining a to-be-printed portrait, splitting the to-be-printed portrait to obtain a grayscale portrait image and a color portrait image; determining a target laser energy value of each pixel point in the grayscale portrait image, and laser etching the grayscale portrait image on a to-be-printed medium based on the target laser energy value; obtaining target printing data of the color portrait image according to the color portrait image and parameters of laser etching; obtaining a printing position of the grayscale portrait image on the to-be-printed medium; and printing the color portrait image at the printing position according to the target printing data.

[0006] In combination with the first aspect, in an embodiment of the present application, the target printing data of the color portrait image is obtained according to the color portrait image and the parameters of laser etching, including: obtaining RGB data of the color portrait image; determining CMYK data of the color portrait image according to the RGB data, a preset color characteristic curve and a color management curve; and optimizing the CMYK data to obtain the target printing data of the color portrait image; wherein the color characteristic curve and the color management curve are set according to material information of the to-be-printed medium and the parameters of laser etching.

[0007] With reference to the first aspect, in an embodiment of the present application, the method further comprises: performing contour recognition on the color portrait image to obtain portrait contour data; generating portrait contour filling data according to the portrait contour data; and performing gloss oil filling printing on a portrait contour range of the color portrait image according to the portrait contour filling data, while the color portrait image is being printed on the printing position.

[0008] With reference to the first aspect, in an embodiment of the present application, the performing gloss oil filling printing on a portrait contour range of the color portrait image according to the portrait contour filling data, while the color portrait image is being printed on the printing position, comprises: identifying an offset of the grayscale portrait image on the printing position; adjusting the target printing data and the portrait contour filling data based on the offset; and printing the color portrait image on the printing position based on the adjusted target printing data, and performing gloss oil filling printing on the portrait contour range of the color portrait image according to the adjusted portrait contour filling data.

[0009] With reference to the first aspect, in an embodiment of the present application, the determining the target laser energy value of each pixel point in the grayscale portrait image comprises: determining a grayscale low-frequency region and a grayscale high-frequency region in the grayscale portrait image according to a grayscale value of each pixel point in the grayscale portrait image; performing smoothing processing on a grayscale transition region between the grayscale low-frequency region and the grayscale high-frequency region to obtain a target grayscale portrait image; and determining the target laser energy value of each pixel point in the grayscale portrait image according to the target grayscale portrait image.

[0010] With reference to the first aspect, in an embodiment of the present application, the determining the grayscale low-frequency region and the grayscale high-frequency region in the grayscale portrait image according to the grayscale value of each pixel point in the grayscale portrait image comprises: calculating a gradient value of the grayscale portrait image according to the grayscale values of all the pixel points; and performing region division on the grayscale portrait image according to a preset gradient threshold and the gradient value to obtain the grayscale low-frequency region and the grayscale high-frequency region.

[0011] With reference to the first aspect, in an embodiment of the present application, the smoothing processing on the gray transition region between the gray low-frequency region and the gray high-frequency region to obtain the target gray portrait image comprises: determining a gray transition region according to a gradient value change between the gray low-frequency region and the gray high-frequency region; performing average calculation on the gray values of all pixel points in the gray transition region to obtain average gray values of the pixel points; updating the gray values of the pixel points to the average gray values to obtain processed pixel points; and combining the processed pixel points, pixel points in the gray low-frequency region and pixel points in the gray high-frequency region to obtain the target gray portrait image.

[0012] With reference to the first aspect, in an embodiment of the present application, the determining of the target laser energy value of each pixel point in the gray portrait image according to the target gray portrait image comprises: determining an initial laser energy value of each pixel point in the target gray portrait image; determining, for each pixel point in the target gray portrait image, a laser energy compensation value of each pixel point in the target gray portrait image according to the initial laser energy values of each pixel point in adjacent regions; determining a target laser energy value of each pixel point in the target gray portrait image according to the laser energy compensation value and the initial laser energy value of each pixel point in the target gray portrait image; and determining a target laser energy value of each pixel point in the gray portrait image according to the target laser energy value of each pixel point in the target gray portrait image.

[0013] With reference to the first aspect, in an embodiment of the present application, the determining of the initial laser energy value of each pixel point in the target gray portrait image comprises: obtaining target gray dot array data according to the gray values of each pixel point in the target gray portrait image; performing energy mapping on the target gray dot array data according to a preset gray energy mapping table to obtain a laser energy dot array; and determining the initial laser energy value of each pixel point in the target gray portrait image according to the laser energy dot array.

[0014] The second aspect, the embodiments of the present application also provide a printing device, using the printing method as described above to print.

[0015] In the embodiment of the present application, first, an image to be printed is acquired, and the image to be printed is split to obtain a grayscale image and a color image; then, a target laser energy value of each pixel point in the grayscale image is determined, and the grayscale image is laser etched on a printing medium based on the target laser energy value; next, target printing data of the color image is obtained according to the color image and laser etching parameters. After the printing position of the grayscale image on the printing medium is acquired, the color image can be printed on the position where the grayscale image is printed according to the target printing data, so as to complete the printing of the image to be printed. The embodiment of the present application can effectively improve the fineness and color expression capability of image printing by splitting the image to be printed into a grayscale image and a color image and using laser etching and color filling technology, so as to realize high-precision and high-quality image printing effect. Moreover, when the present application is applied to card printing, it can better meet the requirements of the card field on the preservation effect and preservation time of the printed card at a lower cost. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a flowchart of the printing method provided by the embodiment of the present application;

[0017] Figure 2 is a two-state printing schematic diagram provided by the embodiment of the present application;

[0018] Figure 3 is a grayscale level printing schematic diagram provided by the embodiment of the present application;

[0019] Figure 4 is a color printing schematic diagram provided by the embodiment of the present application Figure 1 is a specific flowchart of step 120 in the embodiment of the present application;

[0020] Figure 5 is a specific flowchart of step 220 in the embodiment of the present application; Figure 4 is a specific flowchart of step 420 in the embodiment of the present application;

[0021] Figure 6 is a specific flowchart of step 430 in the embodiment of the present application; Figure 4

[0022] Figure 7 is a specific flowchart of step 610 in the embodiment of the present application; Figure 6

[0023] Figure 8 is a printing process schematic diagram provided by one specific example of the present application;

[0024] Figure 9 is a printing process schematic diagram provided by another specific example of the present application;

[0025] Figure 10 ​​is a print process schematic diagram provided by another specific example of the present application;

[0026] Figure 11 is a flowchart of the print method provided by an embodiment of the present application Figure 1 is a specific flowchart of step 130 in the method

[0027] Figure 12 is a flowchart of the print method provided by another embodiment of the present application

[0028] Figure 13 is a flowchart of the print method provided by an embodiment of the present application Figure 12 is a specific flowchart of step 1230 in the method

[0029] Figure 14 is a print result schematic diagram provided by a specific example of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0031] It should be noted that although a logical order is shown in the flowchart, in some cases, the steps shown or described in the flowchart can be performed in an order different from that in the flowchart. The terms "first", "second", etc. in the specification and claims and the above drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the structure, proportion, size, etc. shown in the drawings of the present specification are only used to cooperate with the content disclosed in the specification, so that those skilled in the art can understand and read, and do not limit the defined conditions under which the present application can be implemented, so they do not have technical significance. Any modification of the structure, change of the proportion relationship or adjustment of the size, without affecting the effect and purpose that the present application can produce, should still fall within the scope of the technical content disclosed by the present application. At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" used in the specification are only for the convenience of clear description, and are not intended to limit the scope of the present application, and the change or adjustment of the relative relationship, without substantially changing the technical content, is also considered as the scope of the present application.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0033] In the current printing technology field, portrait printing as an important application form is widely used in photo printing, ID card printing and other fields. Traditional portrait printing methods mostly use inkjet printing or thermal transfer printing technology. Although these technologies can meet the basic printing needs to some extent, they still have many limitations in printing quality, printing speed and adaptability of printing materials. Specifically, although inkjet printing technology can achieve high printing resolution, it is easily affected by ink diffusion, drying speed and nozzle clogging during printing, resulting in unstable printing quality and poor adaptability to some special printing media. Thermal transfer printing technology has the defects of high printing cost, slow printing speed and difficulty in realizing high-precision color restoration, which limits its application in high-end portrait printing field.

[0034] In recent years, with the rapid development of laser technology, laser etching technology has gradually shown great potential in the field of portrait printing. Laser etching technology can achieve high-precision and high-efficiency printing effect by directly etching or coloring on the printing medium with laser beam, and shows good adaptability to various materials of printing medium. However, the existing laser etching methods mostly target monochrome or simple color images for printing, and there are still certain technical challenges for printing portrait images containing complex color information and portrait outlines.

[0035] Therefore, the embodiment of the present application provides a printing method and a printing device. Firstly, the obtained portrait to be printed is split to obtain a grayscale portrait image and a color portrait image, which can lay a foundation for subsequent differential processing. Then, for the grayscale portrait image, the target laser energy value of each pixel point is determined, and the grayscale portrait image is laser etched on the printing medium based on the target laser energy value, which can ensure high-fidelity restoration of portrait outlines and details. Next, the target printing data of the color portrait image is obtained according to the color portrait image and the laser etching parameters. After obtaining the printing position of the grayscale portrait image on the printing medium, the color portrait image can be further printed on the position where the grayscale portrait image is printed according to the target printing data, that is, the color information is superimposed on the basis of the grayscale portrait image to complete the printing of the portrait to be printed. The embodiment of the present application can effectively improve the fineness and color expression ability of image printing by splitting the portrait to be printed into a grayscale portrait image and a color portrait image, and using laser etching and color filling technology respectively, so as to realize high-precision and high-quality portrait printing effect. Moreover, when the present application is applied to ID card printing, it can better meet the requirements of ID card field for the preservation effect and preservation time after ID card printing at a lower cost.

[0036] The embodiments of the present application will be further described below with reference to the accompanying drawings.

[0037] Referring toFigure 1 , Figure 1 is a flowchart of a printing method provided by an embodiment of the present application. The specific process can include but is not limited to steps 110 to 150.

[0038] Step 110: Obtain a to-be-printed portrait, split the to-be-printed portrait to obtain a grayscale portrait image and a color portrait image;

[0039] Step 120: Determine a target laser energy value of each pixel point in the grayscale portrait image, and laser etch the grayscale portrait image on a to-be-printed medium based on the target laser energy value;

[0040] Step 130: Obtain target printing data of the color portrait image according to the color portrait image and laser etching parameters;

[0041] Step 140: Obtain a printing position of the grayscale portrait image on the to-be-printed medium;

[0042] Step 150: Correspondingly print the color portrait image on the printing position according to the target printing data.

[0043] In a feasible embodiment, the to-be-printed portrait refers to an original portrait image ready for digital printing processing. It is usually a digital image file stored in digital form, which can be derived from a digital camera, a scanner, a mobile phone camera or other digital image capture devices. The to-be-printed portrait can cover various types, including but not limited to personal daily photos, portraits in artistic works, and portrait images presented on ID cards, etc., which can be transferred to various physical media such as paper, cloth, plastic, etc. via printing equipment or other printing technologies.

[0044] In an implementable embodiment, in the process of preprocessing the portrait to be printed to obtain the grayscale portrait image and the color portrait image, the color channel parameters of the portrait to be printed can be acquired first, and then the color portrait image of the portrait to be printed is extracted according to the color channel parameters, and then the original color parameters of the color portrait image are converted in color space to obtain the grayscale portrait image. It can be understood that, since most of the portraits to be printed are usually stored in the red, green, blue (RGB) color space, when the color channel parameters are acquired, the color channel parameters of the portrait to be printed can be obtained by reading the values of the three channels of red, green and blue of each pixel in the image. It should be noted that, if the image itself is color and needs to retain its original color information, the color portrait image can be directly acquired. At the same time, according to actual needs, the color portrait image can be color corrected or enhanced by adjusting the color channel parameters, so as to further improve its visual effect. When the original color parameters of the color portrait image are converted in color space to obtain the grayscale portrait image, each pixel value in the RGB color space can be converted into its corresponding grayscale value. Generally, the weighted average method can be used to calculate the grayscale value of the grayscale portrait image. It is worth noting that the formula for calculating the grayscale value by using the weighted average method is designed based on the difference in sensitivity of the human eye to different colors. In the RGB color space, the values of the three channels of red, green and blue correspond to different weights, which reflect the relative sensitivity of the human eye to each color. The formula for calculating the grayscale value by using the weighted average method is as follows: Gray = W x R + H x G + K x B. In this formula, the values of red, green and blue are usually integers from 0 to 255, representing the intensity of each color channel. By multiplying the three values by their corresponding weights and adding the results, a grayscale value between 0 and 255 can be obtained. This grayscale value represents the brightness information of the corresponding pixel point in the color portrait image, without any color information. Among them, W is the weight of the red channel, H is the weight of the green channel, and K is the weight of the blue channel. It is worth noting that, generally, the sensitivity of green to the human eye is the highest, followed by red, and then blue. For example, the value of W can be 0.299, the value of H can be 0.587, and the value of K can be 0.114. It should be noted that, although this formula is a commonly used method for calculating grayscale values, in some specific cases, other weights or formulas can be used to calculate grayscale values to adapt to different application scenarios and needs.

[0045] It can be understood that the gray value of each pixel point in the gray portrait image can be accurately mapped to the corresponding laser energy value to ensure that the required image is accurately presented on the printing medium during laser etching. The target laser energy value of each pixel point in the gray portrait image refers to the specific laser energy value assigned to each pixel point in the laser etching imaging process to accurately reproduce the image on the medium. Each pixel point in the gray portrait image has a gray value, which can intuitively reflect the brightness or lightness of the pixel point. It is worth noting that in the laser etching process, there is a clear mapping relationship between the gray value and the laser energy value: specifically, a pixel point with a higher gray value requires higher laser energy for printing; correspondingly, a pixel point with a lower gray value only needs lower laser energy to complete printing.

[0046] It is worth noting that in the current printing technology field, especially in high-precision image output applications such as certificate printing, traditional binary printing methods have significant limitations. As shown in Figure 2 In this method, in binary printing, the pixel points presented on the certificate medium are only white (illustrated as Grey_level_0, the gray value of the pixel point is 128 to 255) and black (illustrated as Grey_level_1, the gray value of the pixel point is 0 to 127). This simple binary processing method greatly limits the fineness and color expression ability of the image. Since the nozzle can only generate fixed-size ink droplets, it cannot adjust the size of the ink droplets according to the changes in image content, which leads to the loss of detailed information in color imaging during printing, and the overall quality of the image is greatly compromised. In order to overcome this defect to some extent, related technologies increase the number of bits of pixel value encoding to improve the gray level. As shown in Figure 3 2-bit or 3-bit data encoding can be used to represent the ink droplet size information of the current pixel point. This method does improve the gray level compared to the binary method and can present more intermediate tones, such as Figure 3The four states of Grey_level_0 (pixel gray value is 221-255), Grey_level_1 (pixel gray value is 128-220), Grey_level_2 (pixel gray value is 51-127) and Grey_level_3 (pixel gray value is 0-50) are displayed. However, this improvement is still limited because even if the number of encoding bits is increased, the number of gray levels that can be presented is still limited by the physical performance of the nozzle, which cannot fully meet the needs of high-precision image printing, and some color information will inevitably be lost. In addition, the traditional printing method often ignores the smooth transition of gray values between different regions when processing gray portrait images, which further exacerbates the loss of image details and the visual discontinuity. Especially between the low-frequency region and the high-frequency region in the gray portrait image, the lack of effective smoothing processing strategy makes the printed image appear harsh and unnatural in visual effect. In view of this, in the process of determining the target laser energy value of each pixel point in the gray portrait image, smoothing processing can be performed between the low-frequency region and the high-frequency region in the gray portrait image to obtain a high-quality gray portrait image, thereby improving the accuracy of the target laser energy value of each pixel point in the gray portrait image.

[0047] In a feasible embodiment, as shown in FIG. 4, the specific process of determining the target laser energy value of each pixel point in the gray portrait image in step 120 can include but is not limited to steps 410-430. Figure 4

[0048] Step 410: According to the gray value of each pixel point in the gray portrait image, determine the gray low-frequency region and the gray high-frequency region in the gray portrait image.

[0049] Step 420: Smooth the gray transition region between the gray low-frequency region and the gray high-frequency region to obtain a target gray portrait image.

[0050] Step 430: According to the target gray portrait image, determine the target laser energy value of each pixel point in the gray portrait image.

[0051] ​In an embodiment, after obtaining the grayscale portrait image of the portrait to be printed, the grayscale low-frequency region and the grayscale high-frequency region in the grayscale portrait image can be accurately distinguished according to the distribution characteristics of the grayscale values. Specifically, the gradient value of the grayscale portrait image can be calculated according to the grayscale values of all the pixel points. It can be understood that the gradient can reflect the speed of change of the pixel value in the image. In the grayscale portrait image, the gradient value is calculated by comparing the grayscale difference between adjacent pixel points. It can help to identify the edge, texture and other detailed features in the image. Common gradient calculation methods include Sobel operator, Prewitt operator and Roberts operator, which can accurately detect the change of grayscale value based on different directions and weights. Then, the preset gradient threshold is compared with the calculated gradient value, so as to divide the grayscale portrait image into regions. It should be noted that the gradient threshold, as a key parameter, can determine which pixel points should be classified as low-frequency regions and which pixel points belong to high-frequency regions. Specifically, the pixel points with a gradient value lower than the threshold are usually divided into low-frequency regions, which often correspond to the smooth part or background information in the image; and the pixel points with a gradient value higher than the threshold are considered as high-frequency regions, which usually reflect the edge, texture and other detailed features in the image.

[0052] In an embodiment, as shown in FIG. 4, the specific process of performing smoothing processing on the grayscale transition region between the grayscale low-frequency region and the grayscale high-frequency region in step 420 to obtain the target grayscale portrait image can include, but is not limited to, steps 510 to 540. Figure 5

[0053] Step 510: determining the grayscale transition region according to the change of the gradient value between the grayscale low-frequency region and the grayscale high-frequency region;

[0054] Step 520: performing average calculation on the grayscale values of all the pixel points in the grayscale transition region to obtain the average grayscale value of the pixel points;

[0055] Step 530: updating the grayscale value of the pixel points to the average grayscale value to obtain the processed pixel points;

[0056] Step 540: combining the processed pixel points, the pixel points in the grayscale low-frequency region and the pixel points in the grayscale high-frequency region to obtain the target grayscale portrait image.

[0057] It can be understood that the smoothing processing on the transition region between the low-frequency region and the high-frequency region in the grayscale portrait image aims to generate a more uniform and better visual effect target grayscale portrait image. This processing procedure not only improves the visual quality of the image, but also helps the subsequent image analysis or printing and other applications.

[0058] ​In one feasible embodiment, step 510 aims to accurately delineate the grayscale transition region based on the changes in gradient values ​​between low-frequency and high-frequency regions in the grayscale portrait image. Changes in gradient values ​​reflect the degree of abrupt changes in pixel grayscale values ​​and are a key basis for distinguishing different frequency regions. By calculating the grayscale differences between adjacent pixels, regions with significant gradient value changes can be identified, thereby determining the range of the grayscale transition region.

[0059] In one feasible embodiment, after determining the grayscale transition region, the average grayscale value of all pixels within that region can be further calculated. This step aims to obtain a value that represents the overall grayscale level of the region by calculating the average grayscale value of the pixels within it. It is worth noting that calculating the average grayscale value helps reduce grayscale fluctuations, laying the foundation for subsequent smoothing processing.

[0060] In one feasible embodiment, after obtaining the average grayscale value, the grayscale value of each pixel within the grayscale transition region can be updated to this average value. The purpose of this step is to make the pixel grayscale values ​​within the transition region more uniform by replacing the original grayscale values, thereby achieving a smooth transition of grayscale values. This processing method helps to eliminate abrupt grayscale changes, making the image visually smoother.

[0061] In one feasible embodiment, pixels within the processed grayscale transition region, pixels from the original low-frequency grayscale region, and pixels from the high-frequency grayscale region are combined to generate the final target grayscale portrait image. This step ensures that the overall structure and features of the image are preserved, while achieving a smooth transition of grayscale values. Through this processing flow, a visually more uniform and smooth grayscale portrait image (i.e., the target grayscale portrait image) can be obtained.

[0062] In one feasible embodiment, such as Figure 6 As shown, the specific process of determining the target laser energy value of each pixel in the target grayscale portrait image based on the target grayscale portrait image in step 430 may include, but is not limited to, steps 610 to 640.

[0063] Step 610: Determine the initial laser energy value for each pixel in the target grayscale portrait image;

[0064] Step 620: For each pixel in the target grayscale portrait image, determine the laser energy compensation value for each pixel in the target grayscale portrait image based on the initial laser energy value of each pixel in the adjacent region;

[0065] Step 630: Determine the target laser energy value of each pixel in the target grayscale portrait image based on the laser energy compensation value and the initial laser energy value of each pixel in the target grayscale portrait image;

[0066] Step 640: determining the target laser energy value of each pixel point in the target grayscale portrait image according to the target laser energy value of each pixel point in the target grayscale portrait image.

[0067] In a feasible embodiment, in step 610, the laser energy value corresponding to each pixel point can be initially determined according to the grayscale value of each pixel point in the target grayscale portrait image by using a predefined mapping relationship or algorithm. This initially determined laser energy value is the initial laser energy value of each pixel point.

[0068] In a feasible embodiment, as shown in FIG. 7, the specific process of determining the initial laser energy value of each pixel point in the target grayscale portrait image in step 610 can include but is not limited to steps 710 to 730. Figure 7

[0069] Step 710: obtaining target grayscale dot array data according to the grayscale value of each pixel point in the target grayscale portrait image;

[0070] Step 720: performing energy mapping on the target grayscale dot array data according to a preset grayscale energy mapping table to obtain a laser energy dot array;

[0071] Step 730: determining the initial laser energy value of each pixel point in the target grayscale portrait image according to the laser energy dot array.

[0072] In a feasible embodiment, the grayscale value of each pixel point in the image can constitute a two-dimensional array, i.e., target grayscale dot array data. The position of each element (or “dot”) in the array corresponds to the position of the pixel point in the image, and the value of the element represents the grayscale value of the pixel point. Specifically, the grayscale of each element (representing a pixel point) in the target grayscale dot array data refers to the transition color level from black to white, which is usually represented by a grayscale value of 0-255, where 0 represents black, 255 represents white, and the intermediate values represent different degrees of gray, which are used to simulate the brightness information in the color portrait image. The more the grayscale levels, the more natural the transition of black and white colors, and the stronger the level of the picture, and the better the printing effect.

[0073] In a feasible embodiment, a preset grayscale energy mapping table can be used to map each grayscale value in the target grayscale dot array data to the corresponding laser energy value. This mapping table is usually determined in advance according to the characteristics of the laser etching equipment and the properties of the printing medium to ensure that the printed image can achieve the expected visual effect. Through the mapping process, a laser energy dot array corresponding to the target grayscale dot array data can be obtained, in which the value of each element represents the required laser energy value of the corresponding pixel point.

[0074] ​In a feasible embodiment, as shown in the gray scale energy mapping table in Table I, for each element in the target gray scale dot array data, there is a clear correspondence between its gray scale value and the laser energy value. Specifically, the element with a gray scale value of 0 corresponds to a laser energy value of P_0; the element with a gray scale value of 1 corresponds to a laser energy value of P_1; the element with a gray scale value of 2 corresponds to a laser energy value of P_2; the element with a gray scale value of 3 corresponds to a laser energy value of P_3. This rule continues to the upper limit of the gray scale value, i.e., the element with a gray scale value of 255 corresponds to a laser energy value of P_255. According to this mapping relationship, the corresponding laser energy dot array can be effectively derived from the gray scale dot array data.

[0075] Table I Gray scale energy mapping table

[0076] 0 1 2 3 … 255 P_0 P_1 P_2 P_3 … P_255

[0077] In a feasible embodiment, according to the data in the laser energy dot array, the initial laser energy value of each pixel point in the target gray scale portrait image can be directly determined. These initial laser energy values can serve as the basis for calculating the laser energy compensation value and the final target laser energy value in subsequent steps.

[0078] In a feasible embodiment, after determining the initial laser energy value of each pixel point, the mutual influence between pixel points can be further considered. Specifically, according to the initial laser energy values of the pixel points in the adjacent region of each pixel point in the target gray scale portrait image, a laser energy compensation value can be calculated. This compensation value can be used to adjust the laser energy value of the current pixel point to better reflect the details and edge features in the image and avoid the appearance of overly harsh or blurred transition areas in the printed result. Further, by adding the initial laser energy value of each pixel point to the laser energy compensation value, the target laser energy value of each pixel point can be obtained. This value can serve as the basis for the laser etching equipment to irradiate each pixel point with laser during the printing process, to ensure that the printed image accurately reflects the gray scale information and detail features in the target gray scale portrait image.

[0079] In a feasible embodiment, in order to accurately print the target gray-scale portrait image onto the printing medium according to the required laser energy value, two key factors, i.e., local energy compensation value and global energy compensation value, can be considered comprehensively when determining the laser energy compensation value of each pixel point in the target gray-scale portrait image. The determination of these two compensation values aims to ensure that each pixel point can obtain accurate and appropriate energy adjustment, thereby realizing accurate printing of the gray-scale portrait image. Specifically, the calculation of the local energy compensation value can be based on the initial laser energy value and the compensation coefficient of the pixel point, as well as the initial laser energy value and the compensation coefficient of each pixel point in the adjacent region of the pixel point. Further, after calculating the local energy compensation value of all pixel points, the energy value of the current pixel point needs to be further compensated according to the regional energy compensation calculation to obtain the global energy compensation value.

[0080] As shown in Table 2 and Table 3, the initial laser energy values and compensation coefficients of the pixel points in the local region are listed respectively. For the initial laser energy value X of the pixel point, the calculation of the local laser energy compensation value Y1 is as follows: Y1 = (X-XL1)×Kxl1+(X-XL2)×Kxl2+(X-XR1)×Kxr1+(X-XR2)×Kxr2+(X-XB1)×Kxb1+(X-XB1L1)×Kxb1l1+(X-XB1L2)×Kxb1l2+(X-XB1R1)×Kxb1r1+(X-XB1R2)×Kxb1r2+(X-XB2)×Kxb2+(X-XB2L1)×Kxb2l1+(X-XB2R1)×Kxb2r1. Wherein, the meanings of the symbols are as follows: Y1 is the local laser energy compensation value of the processed pixel point; X is the initial laser energy value of the pixel point; XL1 and XL2 are the energy values of the first two pixel points from left to right in the laser etching direction, and the compensation coefficients are Kxl1 and Kxl2 respectively; XR1 and XR2 are the energy values of the first two pixel points from right to left in the laser etching direction, and the compensation coefficients are Kxr1 and Kxr2 respectively; XB1 is the processed heat energy of the corresponding point in the previous row, and the compensation coefficient is Kxb1; XB1L1 and XB1L2 are the processed energy data of the first and second points on the left of the previous row, and the compensation coefficients are Kxb1l1 and Kxb1l2 respectively; XB1R1 and XB1R2 are the processed energy data of the first and second points on the right of the previous row, and the compensation coefficients are Kxb1r1 and Kxb1r2 respectively; XB2 is the processed heat energy of the corresponding point in the previous two rows, and the compensation coefficient is Kxb2; XB2L1 is the processed energy data of the first point on the left of the previous two rows, and the compensation coefficient is Kxb2l1; XB2R1 is the processed energy data of the first point on the right of the previous two rows, and the compensation coefficient is Kxb2r1.

[0081] Table 2 Initial laser energy values of pixel points in local region

[0082]

[0083] Table III Compensation coefficient table of local region pixel points

[0084]

[0085] In a feasible embodiment, after the local energy compensation value Y1 of a pixel point is calculated, the global energy compensation value Y2 can be further calculated according to the regional energy compensation calculation. For example, for the first row of the current gray portrait image, the local energy compensation values of every 100 pixel points (corresponding to one laser etching region) are added to obtain the energy statistical values of multiple regions (such as LX1, LX2, LX3, etc.) in the first row. For example, if the global energy compensation value of the 150th pixel point is to be calculated, since the pixel point is located in the LX2 region, the calculation formula of the global energy compensation value Y2 of the pixel point can be expressed as follows: Y2 = LX2 × Kl1 + (2 × LX2 - LX1 - LX3) × Kl2. Wherein, Kl1 is the compensation coefficient of the energy of the previous region (LX1), and Kl2 is the compensation coefficient of the energy difference between the previous region and the adjacent region. Finally, the calculation formula of the target laser energy value of the current pixel point is: Y = X + Y1 + Y2.

[0086] In addition, in order to continuously update and iteratively calculate the energy value of each row, the laser energy of every 100 pixel points can be added, and the energy influence decay coefficient Kl3 can be used for iterative updating. The specific formula is as follows:

[0087] LXn(L2) = Kl3 × LXn(L1).

[0088] Wherein, LXn(L2) is the regional energy of every 100 points in the current row, and LXn(L1) is the iterative regional energy of every 100 points in the previous row of the current row. By continuously calculating the energy value of the next row and iteratively updating the energy values of the regions LX1, LX2, LX3, etc., the target laser energy value of each pixel point in the target gray portrait image can be finally determined.

[0089] In a feasible embodiment, after the target laser energy value of each pixel point in the target gray portrait image is determined, the target laser energy value of each pixel point in the original gray portrait image can be determined according to the target laser energy value of each pixel point in the target gray portrait image, and the gray portrait image can be laser etched on the printing medium based on the target laser energy value. It can be understood that in the process of etching the gray portrait image on the printing medium by using the laser etching device, the laser etching device can present each pixel point in the gray portrait image on the printing medium at a corresponding gray level by controlling the intensity and position of the laser beam, thereby realizing high-quality gray portrait image printing.

[0090] In one feasible embodiment, during the process of printing a grayscale portrait image onto a printing medium based on the target laser energy value, the area and specific dimensions for laser etching can be determined first based on the printing coordinates, width, height, and target laser energy values ​​of each pixel of the grayscale portrait image. Then, using contour curve information, the start-stop matching timing between the optical lens and the laser beam energy output during laser etching can be calculated. It is worth noting that laser etching is a complex process involving the coordinated action of the control module, the laser, and the optical reflector motor. For example... Figure 8 As shown, the bulging phenomenon at both ends of the etched line (points A and B) is caused by the optical reflector motor stopping operation while the laser beam continues to output energy, resulting in excessively long etching time in that area, thus causing localized aggravation and the formation of bulges. In contrast, Figure 9 This demonstrates the ideal state of synchronized start and stop between the laser beam and the optical reflector, where no drumming phenomenon occurs at points A and B. To achieve this, the laser control module can precisely calculate the timing sequence of the laser beam and optical reflector movement based on the contour of the etched image. Furthermore, the frequency settings of the energy output of the optical reflector and laser beam during laser etching can be adjusted according to the contour curve. Figure 10 As shown, during the etching of line AC, the laser beam and the motor of the optical reflector are moving at high speed at a frequency of F1. However, when the etched image line reaches the turning region BC, if the motor maintains its original high-speed change of direction, the inertia of the lens may cause under-rotation, resulting in asynchronous movement of the laser beam and the lens, leading to over-etching in the turning region. To solve this problem, the motor's drive frequency can be reduced to F2 before the etched line enters the BC turning region, ensuring that the optical lens motor and the laser beam can change direction synchronously and stably. Finally, the laser focus with a certain power density, under the deflection of the optical reflector, scans along the specified X and Y directions, and can undergo a color-developing chemical reaction with the engraving layer material inside the printing medium (such as PC material), thereby completing the image etching.

[0091] It's important to note that CMYK data is a commonly used color model in color printing, representing the mixing proportions of four colors: cyan, magenta, yellow, and key / black. This color model is based on the principle of mixing the three primary colors of pigments; by adjusting the mixing proportions of these four colors, a rich range of colors can be produced. In color portrait images, CMYK data describes the color information of each pixel in the image and is the basis for controlling the amount of ink ejected during printing. Specifically, each value in CMYK data represents the intensity of a color, typically ranging from 0% to 100%. For example, a combination of C=50%, M=30%, Y=20%, and K=0% can produce a specific color. During the printing process, the printing equipment can control the amount of cyan, magenta, yellow, and black ink ejected based on this CMYK data, thus presenting the corresponding colors on the paper. Portrait outline fill data refers to the filling method of specific areas in an image (such as the outline of a portrait). In image processing software, the appearance of these areas can be controlled by specifying parameters such as fill color and fill mode. In portrait printing, portrait outline fill data is often used to define how the edges of a portrait are filled to make them smoother, more natural, or to create specific visual effects. For example, in portrait printing, it may be necessary to blur the edges of a portrait or add specific color gradient effects. These effects can be achieved by adjusting the portrait outline fill data. Specifically, the fill color can be specified as a gradient color, and the fill mode can be specified as a specific texture or pattern. It is worth noting that although portrait outline fill data and CMYK data describe different aspects of an image (color information and fill mode), in the actual printing process, their synergy ensures the production of high-quality portrait images.

[0092] In one feasible embodiment, such as Figure 11 As shown, the specific process of obtaining the target printing data of the color portrait image based on the parameters of the color portrait image and the laser etching in step 130 may include, but is not limited to, steps 1110 to 1140.

[0093] Step 1110: Obtain the RGB data of the color portrait image;

[0094] Step 1120: Obtain the CMYK data of the color portrait image based on the RGB data, the preset color characteristic curve and the color management curve. The color characteristic curve and the color management curve are set according to the material information of the printing medium and the laser etching parameters.

[0095] Step 1130: Optimize the CMYK data to obtain the target printing data of the color portrait image.

[0096] In an embodiment, step 1110 aims to acquire the basic color information of the color portrait image. It can be understood that RGB data represents the intensity of red (R), green (G) and blue (B) colors, which is a common color mode of electronic display devices such as computer displays, mobile phone screens, etc. In image processing software, the RGB data of an image can be directly read, and the data is usually stored in the form of one RGB value corresponding to each pixel.

[0097] In an embodiment, it should be noted that the color profile is an ICC (International Color Consortium) profile, which is key data for describing the color performance of a device. For a printing process, in particular, the color profile can establish a mapping relationship between the RGB color space and the CMYK color space specific to the device, and by applying the color profile, it can be ensured that the RGB data accurately reflects the color performance of the printing device when converted to CMYK data. In addition, the color management profile has the color management function of a raster image processor (RIP), which can convert image data into a format that the printing device can understand and apply color management strategies during the conversion process. For example, the color management profile can use the color profile to adjust the image data to ensure that the printed image is accurate and consistent in color.

[0098] In an embodiment, the color profile and the color management profile can be pre-set according to the material characteristics and the base color parameters of the printing medium. The material characteristics of the printing medium here include the color of the printing medium material itself, and the base color of the printing medium here refers to the color generated by subsequent processing of the printing medium, such as the base color formed by laser etching technology. When the base color is generated by laser etching technology, the relevant key parameters (i.e., base color parameters) can be the concentration and gray value of laser etching. For example, when generating the color profile and the color management profile according to the material characteristics and the base color parameters, all the material characteristics and the base color parameters on the current printing medium can be collected first, and then the color profile corresponding to each material and base color parameter is generated based on the material characteristics. Subsequently, using these color profiles, the color management profile is further generated.

[0099] In a feasible embodiment, in the process of obtaining the CMYK data of the color portrait image according to the RGB data, the preset color characteristic curve and the color management curve, the RGB data can be input into the image processing software or the RIP software, and the color characteristic curve prepared in advance can be applied. The color characteristic curve can convert the RGB data into the CMYK data matched with the printing device. The RIP software can read the color data converted by the color characteristic curve, and further perform color adjustment and optimization according to the color management strategy built-in. This can include steps such as color correction, brightness adjustment, contrast enhancement, etc., to ensure that the image can present the best effect on the printing device. After the processing of the RIP software, the CMYK data suitable for the printing device is finally generated. These data will guide the printing device to spray corresponding amounts of cyan, magenta, yellow and black ink to reproduce the color of the original image on the printing medium.

[0100] In a feasible embodiment, after obtaining the CMYK data of the color portrait image, the data can be further optimized to generate the required printing data. In this process, considering that cyan (Cyan), magenta (Magenta) and yellow (Yellow) in the CMYK color mode are the three primary colors, rich color effects can be created through different combinations and superpositions. Although black (K) plays an important role in the CMYK mode, given that the embodiments of the present application involve a process of first laser etching on the printing medium (such as the card substrate) and then color inkjet printing, in order to present better color effects, only the CMY three colors can be used to print the color portrait image in the inkjet printing stage after laser etching. Therefore, when preparing the printing data, it should be ensured that only the color information of the CMY part is included in the data. Specifically, the value of black (K) can be set to 0, so as to obtain the target printing data containing only the CMY color components.

[0101] In a feasible embodiment, in order to enhance the visual effect of the printed image, further light oil filling printing can be performed on the portrait contour range of the color portrait image at the position of printing the color portrait image. Referring to Figure 12 , Figure 12 is a flowchart of the printing method provided by another embodiment of the present application, which can include but is not limited to steps 1210 to 1230.

[0102] Step 1210: contour recognition is performed on the color portrait image to obtain portrait contour data;

[0103] Step 1220: portrait contour filling data is generated according to the portrait contour data;

[0104] Step 1230: At the same time as printing the color portrait image on the printing position, perform gloss filling printing on the portrait contour range of the color portrait image according to the portrait contour filling data.

[0105] In an implementable embodiment, step 1210 aims to identify the portrait contour in the color portrait image. This usually involves steps such as image preprocessing, edge detection, and contour extraction. Specifically, the color portrait image can be preprocessed first, such as adjusting the brightness, contrast, color balance, etc. of the image, to improve the image quality and make the subsequent contour identification more accurate; then an edge detection algorithm (such as Canny edge detection, Sobel operator, etc.) is used to identify the edges in the image. These edges usually correspond to the contour of the portrait, hair, facial features, etc. On the basis of edge detection, a contour extraction algorithm (such as Hough transform, contour tracking, etc.) can be further used to extract the complete portrait contour. These contour data can usually be represented in the form of coordinate points, describing the boundary of the portrait.

[0106] In an implementable embodiment, the portrait contour filling data refers to the gloss filling printing data used to fill the portrait contour. Gloss filling printing can usually be used to enhance the visual effect of the printed image, such as improving the glossiness, increasing the stereoscopic effect, or protecting the image surface.

[0107] In an implementable embodiment, in step 1220, when generating the portrait contour filling data according to the portrait contour data, the area that needs to be filled with gloss can be defined first according to the portrait contour data; then the parameters of gloss filling printing are set, such as the filling color (in this case, it is usually a transparent gloss layer), the filling mode (such as uniform filling, gradient filling, or texture filling, etc.) and the filling thickness or number of layers; then the data used to guide the printing equipment to fill the gloss is generated according to the filling area and the filling parameters. These data can usually be stored in a specific file format (such as PDF, PostScript, or printer-specific format), and contain information about the location, shape, size of the filling area and the filling parameters.

[0108] In an implementable embodiment, in step 1230, at the same time as printing the color portrait image on the printing position where the grayscale portrait image is printed, the range of the portrait contour can also be subjected to detailed gloss processing according to the portrait contour filling data. The addition of gloss not only significantly improves the visual effect of the portrait, such as increasing the glossiness and stereoscopic effect, but also provides an additional protective layer for the image, making it more durable and easier to preserve.

[0109] Referring to Figure 13 , Figure 13 is a specific flowchart of step 1230 provided by the embodiments of the present application. The flowchart can include but is not limited to steps 1310 to 1330.

[0110] Step 1310: identifying the offset of the grayscale portrait image on the printing position;

[0111] Step 1320: adjusting the target printing data and the portrait contour filling data based on the offset;

[0112] Step 1330: printing the color portrait image on the printing position based on the adjusted target printing data, and performing the varnish filling printing on the portrait contour range of the color portrait image according to the adjusted portrait contour filling data.

[0113] In a feasible embodiment, after the grayscale portrait image is printed on the printing medium, a specific identification technology or device (such as image matching technology, laser projection lens offset detection device, etc.) can be used to detect the offset of the printing medium on which the grayscale portrait image has been printed, which usually includes horizontal, vertical and rotational direction offsets. It can be understood that the offset may be caused by various factors during the printing process (such as slight movement of the paper, positioning error of the print head, etc.), which may cause misalignment between the color portrait image and the grayscale portrait image. Through offset identification, these slight position deviations can be obtained to provide accurate data support for subsequent adjustment.

[0114] In a feasible embodiment, after obtaining the offset identification result, the target printing data (only containing color information of CMY part) and the portrait contour filling data can be adjusted according to the result. Specifically, the target printing data is adjusted according to the obtained offset data. The adjustment process needs to ensure that the color portrait image can be accurately superimposed on the grayscale portrait image during printing without any deviation. This may involve recalculation of the printing data to ensure the alignment accuracy of the color portrait image and the grayscale portrait image. At the same time, the portrait contour filling data is adjusted according to the offset data, which can ensure that the varnish filling printing of the portrait contour perfectly fits the contour of the grayscale portrait image without misalignment or omission. This may require adjusting the path, speed, pressure and other parameters of the varnish filling printing to ensure that the varnish can be uniformly and accurately filled in the portrait contour.

[0115] In a feasible embodiment, after completing the offset identification and the adjustment of the related inkjet printing parameters (including the target printing data and the portrait contour filling data), the color portrait image can be printed on the printing medium on which the grayscale portrait image has been printed using the adjusted data to ensure the accurate alignment between the color portrait image and the grayscale portrait image. For example, Figure 14The shown printing result diagram shows that after laser engraving the gray portrait image A on the to-be-printed medium, the color portrait image B can be printed on the corresponding position of the gray portrait image A according to the target printing data, and meanwhile, the light oil filling printing is performed within the range of the portrait contour according to the portrait contour filling data, so as to complete the overall printing task of the to-be-printed portrait.

[0116] In addition, one embodiment of the present application further discloses a printing device which can use the printing method in any of the foregoing embodiments to perform printing, so as to significantly improve the fineness and color expression capability of the printed image, and further greatly improve the overall quality of the printed image.

[0117] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A printing method characterized by, The method comprises: acquiring a portrait to be printed, and splitting the portrait to be printed to obtain a grayscale portrait image and a color portrait image; determining a target laser energy value of each pixel point in the grayscale portrait image, and performing laser etching on the grayscale portrait image on a printing medium based on the target laser energy value; obtaining target printing data of the color portrait image according to the color portrait image and parameters of laser etching; performing contour recognition on the color portrait image to obtain portrait contour data; generating portrait contour filling data according to the portrait contour data; acquiring a printing position of the grayscale portrait image on the printing medium; corresponding printing of the color portrait image on the printing position while performing light oil filling printing on a portrait contour range of the color portrait image according to the portrait contour filling data, according to the target printing data; wherein the corresponding printing of the color portrait image on the printing position while performing light oil filling printing on a portrait contour range of the color portrait image according to the portrait contour filling data comprises: identifying an offset of the grayscale portrait image on the printing position; adjusting the target printing data and the portrait contour filling data based on the offset; corresponding printing of the color portrait image on the printing position according to the adjusted target printing data, and performing light oil filling printing on a portrait contour range of the color portrait image according to the adjusted portrait contour filling data.

2. The printing method according to claim 1, characterized by, The method of obtaining target printing data of the color portrait image according to the color portrait image and parameters of laser etching comprises: acquiring RGB data of the color portrait image; determining CMYK data of the color portrait image according to the RGB data, a preset color characteristic curve and a color management curve; optimizing the CMYK data to obtain target printing data of the color portrait image; wherein the color characteristic curve and the color management curve are set according to material information of the printing medium and the parameters of laser etching.

3. The printing method according to claim 1, characterized by, The method of determining a target laser energy value of each pixel point in the grayscale portrait image comprises: determining a grayscale low-frequency region and a grayscale high-frequency region in the grayscale portrait image according to a grayscale value of each pixel point in the grayscale portrait image; performing smoothing processing on a grayscale transition region between the grayscale low-frequency region and the grayscale high-frequency region to obtain a target grayscale portrait image; determining a target laser energy value of each pixel point in the grayscale portrait image according to the target grayscale portrait image.

4. The printing method according to claim 3, characterized by, The method of determining a grayscale low-frequency region and a grayscale high-frequency region in the grayscale portrait image according to a grayscale value of each pixel point in the grayscale portrait image comprises: calculating a gradient value of the grayscale portrait image according to the grayscale values of all the pixel points; performing region division on the grayscale portrait image according to a preset gradient threshold and the gradient value to obtain a grayscale low-frequency region and a grayscale high-frequency region.

5. The printing method according to claim 3, wherein, The method of performing smoothing processing on a grayscale transition region between the grayscale low-frequency region and the grayscale high-frequency region to obtain a target grayscale portrait image comprises: determining a gray scale transition region according to a gradient value change between the gray scale low frequency region and the gray scale high frequency region; averaging the gray scale values of all pixel points in the gray scale transition region to obtain an average gray scale value of the pixel points; updating the gray scale value of the pixel points to the average gray scale value to obtain processed pixel points; combining the processed pixel points, pixel points in the gray scale low frequency region and pixel points in the gray scale high frequency region to obtain a target gray scale portrait image.

6. The printing method according to claim 3, wherein determining a target laser energy value of each pixel point in the gray scale portrait image according to the target gray scale portrait image, includes: determining an initial laser energy value of each pixel point in the target gray scale portrait image; for each pixel point in the target gray scale portrait image, determining a laser energy compensation value of each pixel point in the target gray scale portrait image according to the initial laser energy value of each pixel point in the adjacent region; determining a target laser energy value of each pixel point in the target gray scale portrait image according to the initial laser energy value and the laser energy compensation value of each pixel point in the target gray scale portrait image; determining a target laser energy value of each pixel point in the gray scale portrait image according to the target laser energy value of each pixel point in the target gray scale portrait image.

7. The printing method according to claim 6, characterized in that, determining an initial laser energy value of each pixel point in the target gray scale portrait image, includes: obtaining target gray scale dot array data according to the gray scale value of each pixel point in the target gray scale portrait image; performing energy mapping on the target gray scale dot array data according to a preset gray scale energy mapping table to obtain a laser energy dot array; determining an initial laser energy value of each pixel point in the target gray scale portrait image according to the laser energy dot array.

8. A printing device, characterized by, printing using the printing method according to any one of claims 1 to 7.

Images