Method and system for verifying 3D (three-dimensional) digital printing graph

Abstract

The invention relates to the technical field of graphic processing in the printing industry, in particular to a 3D digital printing graphic verification method and system. The method comprises the following steps: acquiring sample size data; acquiring an actual printing image size; generating a target printing picture; obtaining an actual printing single pixel size; scanning the sample according to the size of a single pixel to obtain point clouds, and arranging the point clouds by taking the size of the single pixel as an interval; matching the pixels in the target printing picture with the points in the point cloud; and coloring points in the corresponding matched point cloud according to pixel colors in the target printing picture to generate a color 3D verification model. According to the embodiment of the invention, matching verification of the sample and the picture can be carried out by observing the color 3D model, repeated verification by printing the sample for multiple times and adjusting the image is not needed, the verification efficiency is improved, and meanwhile, the material consumption is effectively saved.

Description

Technical Field

[0001] The present application relates to the field of graphics processing technology in the printing industry, and in particular to a 3D digital printing graphics verification method and system. Background Art

[0002] With the development of product diversity, higher and higher requirements are put forward for color printing on the outer surface of three-dimensional products. The applicant disclosed a printing technology suitable for cylindrical products with three-dimensional concave-convex shapes on the surface in the patent document with application number CN202411197734.3, entitled "3D relief inkjet printing image processing method and system". The plane image is matched with the cylindrical outer surface and the concave-convex shape of the surface by color mapping, so that the surface printing of such products can be realized. However, before the printing process is carried out, whether the shape of the product matches the plane image to be printed and whether the expected printing effect can be obtained needs to be verified by printing samples. If the effect is not as expected, it is necessary to repeatedly adjust the corresponding plane image and print samples. Since the size specifications of products such as pen holders, water cups, vases, etc. are diverse, the applicable surface printing patterns are also different. Therefore, it takes a lot of processes to verify the printing effect through sample printing, which is inefficient and consumes a lot of materials. Summary of the invention

[0003] In a first aspect, the embodiments of the present application provide a 3D digital printed graphics verification method that can perform digital matching verification on a planar image printed on a cylindrical 3D surface by performing matching test through a sample.

[0004] In order to solve the above problem, the method comprises the steps of: Measure samples and obtain sample size data; According to the sample size data, obtaining the actual printed image size; Process the image to be printed according to the actual printing image size to generate a target printing image; According to the printing resolution of the target printing device, the actual printing single pixel size is obtained; Scanning the sample according to a single pixel size to obtain a point cloud, so that the point cloud is arranged with a single pixel size as a spacing; Matching pixels in the target printed image with points in the point cloud; The points in the corresponding matching point cloud are colored according to the pixel colors in the target printed image to generate a color 3D verification model.

[0005] Through the above method, the actual required printing image size can be obtained according to the printing area of ​​the sample, so as to process the image to be printed so that the target printing image matches the size of the printing area of ​​the sample, and then the pixel information of the target printing image is matched with the corresponding point cloud, and then the corresponding point cloud is colored, so as to obtain a color 3D model based on the point cloud. The matching of the sample and the image can be verified by observing the color 3D model, and there is no need to print the sample multiple times to adjust the image for repeated verification, which improves the verification efficiency and effectively saves material consumption.

[0006] In a possible implementation, measuring the sample and obtaining sample size data further includes: Acquire a primary point cloud of the sample; Sample size data is generated based on the primary point cloud.

[0007] In a possible implementation, processing the to-be-printed image according to the actual printed image size to generate a target printed image includes: Get the size of the image to be printed; Comparing the size of the image to be printed with the actual printed image size; The image to be printed is scaled and cropped so that the size of the image to be printed is equal to the actual printing image size.

[0008] In a possible implementation manner, obtaining the single pixel size includes: The single pixel size is the inverse of the printing resolution.

[0009] In a possible implementation manner, scanning the sample according to a single pixel size to obtain a point cloud includes: The sample is scanned with the central axis of the sample as the rotation axis and the single pixel size as the scanning interval to obtain a secondary point cloud of the sample.

[0010] In a possible implementation, the primary point cloud is a dense point cloud, and scanning the sample according to a single pixel size to obtain a point cloud includes: From the primary point cloud, the primary point cloud is screened with the single pixel size as a spacing to obtain a secondary point cloud.

[0011] In a possible implementation, the points in the secondary point cloud are resized so that the projection edges of adjacent points in the secondary point cloud are adjacent to each other.

[0012] In a possible implementation, resizing points in the secondary point cloud includes: Adjust the radius of points in the secondary point cloud to half the size of a single pixel.

[0013] In a possible implementation, matching pixels in the target printed image with points in the point cloud includes: Setting a starting pixel, traversing all pixels in the target printed image from the starting point in the order of first horizontal and then vertical, and obtaining the coordinates and color value of each pixel; Setting a starting point, and starting from the starting point to unfold the point cloud, so that the point cloud is arranged in a plane in the XY axis direction; Matching the coordinates of the pixel with the XY axis coordinates of the point cloud to obtain corresponding pixels and points; Assign the color value of the pixel to the corresponding point.

[0014] In a second aspect, an embodiment of the present application further provides a 3D digital printed graphics verification system, the system comprising: The printing device module obtains the actual printing single pixel size according to the printing resolution of the target printing device; A sample scanning module is used to scan the sample and obtain a point cloud of the sample; An image processing module processes the image to be printed according to the actual printing image size to generate a target printing image; A point cloud processing module performs data communication with the printing device module and the sample scanning module, scans the sample according to a single pixel size to obtain a point cloud, and arranges the point cloud at a spacing of a single pixel size; The point cloud coloring module communicates data with the image processing module and the point cloud processing module, matches the pixels in the target printed image with the points in the point cloud, colors the corresponding matching points in the point cloud according to the pixel colors in the target printed image, and generates a color 3D verification model. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of the first embodiment; Figure 2 is a further flow chart of step S1 of the first embodiment; Figure 3 is a further flow chart of step S6 of the first embodiment; Figure 4 FIG. 4 is a schematic diagram of the module structure of the second embodiment. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described in detail by way of implementation methods with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, but not all of the embodiments. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0017] The 3D digital printing graphic verification method in this embodiment is mainly suitable for digital verification of surface color printing effects of cylindrical products with embossed three-dimensional shapes on the surface. The existing printing of such products has been disclosed in the applicant's prior patents. The embodiments of this application mainly verify and preview the matching of product shapes with pictures and printing effects before printing such products, to replace the existing method of achieving similar effects by printing actual samples.

[0018] There are generally two purposes for this type of verification. First, there are many types of products with different specifications, and the sizes of the images printed on the surface are also different. Matching the sizes between samples and images requires a lot of work. Secondly, whether the patterns and designs in the images have the expected aesthetics when applied to actual products needs to be evaluated through product verification to achieve the expected appearance acceptance.

[0019] In order to save a lot of early printing processes for verification, the first embodiment of the present application provides a 3D digital printing graphic verification method, such as Figure 1 As shown, the method comprises the steps of: S1. Measure the sample and obtain the sample size data; S2. According to the sample size data, obtain the actual printed image size; S3. Process the image to be printed according to the actual printed image size to generate a target printed image; S4. Obtaining the actual printed single pixel size according to the printing resolution of the target printing device; S5. Scanning the sample according to a single pixel size to obtain a point cloud, so that the point cloud is arranged at a spacing of a single pixel size; S6. Matching pixels in the target printed image with points in the point cloud; S7. Coloring the points in the corresponding matching point cloud according to the pixel colors in the target printed image to generate a color 3D verification model.

[0020] Among them, the sample in step S1 includes a cylindrical product body and a three-dimensional configuration located on the outer surface of the product body, and the three-dimensional configuration is mainly a relief-type three-dimensional configuration with a low height difference. The sample can be measured manually or by computer graphics data. The purpose of product measurement is to calculate the size of the actual printed image covering the side surface of the product. The height of the product is the width of the actual printed size, and the circumference of the cylindrical circle of the product is the length of the actual printed size. Among them, the cylindrical product has two parallel bottom surfaces, and the distance between the two parallel bottom surfaces is the height of the product, so the height is easy to measure. Since the product surface has a three-dimensional configuration, the circumference of most cross sections on the product is irregular, so special processing is required. In this embodiment, the acquisition and processing is performed by acquiring point clouds, as shown in the following example. Figure 2 As shown, the measuring sample and obtaining the sample size data further includes: S11. Obtaining a point cloud of the sample; S12. Compute sample size data based on the primary point cloud.

[0021] Among them, in step S11, obtaining the point cloud data of the sample product is an important step in the fields of three-dimensional modeling, reverse engineering, quality control, etc. Point cloud is a data set that describes the shape and surface features of an object by collecting the coordinates of a large number of discrete points on the surface of the object (usually x, y, z three-dimensional coordinates). Common ways to obtain point cloud data include laser scanning (LiDAR), structured light scanning (Structured Light Scanning), photogrammetry (Photogrammetry), coordinate measuring machine, handheld 3D scanner, ultrasonic scanning, depth camera (Depth Cameras), etc. Based on the implementation scenario and product requirements of this embodiment, it is preferred to use a depth camera to collect data and generate a point cloud. Depth cameras (such as Kinect, Intel RealSense) use infrared or structured light principles to obtain depth information of objects. These depth cameras can capture three-dimensional data of objects or scenes and generate real-time point clouds.

[0022] Choosing the appropriate point cloud acquisition method should be determined based on application requirements, object characteristics, budget, and accuracy requirements.

[0023] After collecting the point cloud, the distance from all points in the point cloud to the central axis can be calculated, and then the average distance can be calculated based on the length distribution of the distance from the point to the central axis, and then the circumference can be calculated using the average distance as the radius. The circumference can also be calculated based on the length distribution of the distance from the point to the central axis, combined with the number of distribution points in each distance interval and the corresponding weight. For example, if the distance from 60% of the points to the central axis is greater than the average length, the distance value is assigned a weight of 60% for calculation.

[0024] After obtaining the sample size by calculation, the size of the actual printed image can be directly obtained according to the size of the sample in step S2. The size of the actual printed image is the length and width of the image actually covered on the side surface of the sample during printing, so its length is equal to the circumference of the outer surface of the sample, and its width is equal to the height of the sample.

[0025] Step S3. Process the image to be printed according to the actual printing image size to generate a target printing image. Step S3 is mainly used to match the design draft size with the sample size. Since a design draft image is often used on products of various specifications, and a product can often print multiple images to form different product designs, when performing graphic verification, it is first necessary to make the size reach a unified state. Therefore, based on the actual printing image size obtained in step S2, the image to be printed can be processed. The specific processing methods include scaling and cropping. A sampling area can be formed by the size of the actual printing image. Then the operator moves and scales the image to be printed in the sampling area, and after confirming the sampling area, the target printing image is obtained, that is, the image obtained after processing the design sample image is the same size as the actual printing image. The target printing image is the image file of the actual printing and the outer surface of the product in the subsequent printing process.

[0026] Since the actual printing sample needs to be simulated in this embodiment, the printing presentation effect that can actually be achieved by the printing device must also be considered. Therefore, step S4. obtains the actual printing single pixel size according to the printing resolution of the target printing device.

[0027] The printing resolution of the target printing device can be obtained through the printing device control port. When the target printing device has multiple printing resolutions, one of the multiple printing resolutions can be selected as the execution resolution of this embodiment according to actual needs. After the execution resolution is obtained, the actual printing single pixel size that can be achieved by the target printing device can be obtained, and the actual printing single pixel size is the reciprocal of the execution resolution.

[0028] After the single pixel size is obtained, step S5 is performed. The sample is scanned according to the single pixel size to obtain a point cloud, and the point cloud is arranged with the single pixel size as a spacing; There are two implementation methods in step S5. The first is to scan the sample again to obtain a point cloud. At this time, the central axis of the sample is used as the rotation axis, and the single pixel size is used as the scanning interval to scan the sample to obtain a secondary point cloud of the sample.

[0029] It should be noted that when scanning the secondary point cloud, when the horizontal scanning is performed with the central axis of the sample as the rotation axis, the actual point cloud is located on the circumference, so the single pixel size at this time is represented by the scanning interval. The length of the single pixel size is equal to the arc length between two horizontally adjacent points on the circumference, and the width of the single pixel size is equal to the straight-line distance between two vertically adjacent points.

[0030] Generally speaking, the length and width are equal in a single pixel size.

[0031] There is another implementation method of step S5. Since in this embodiment, the sample is measured in step S1 by acquiring a point cloud, the acquisition of the secondary point cloud can be obtained based on the screening of the primary point cloud.

[0032] In this processing method, the primary point cloud is required to be a dense point cloud, and scanning the sample according to a single pixel size to obtain a point cloud includes: From the primary point cloud, the primary point cloud is screened with the single pixel size as a spacing to obtain a secondary point cloud.

[0033] The point cloud can be filtered again and arranged at a spacing of single pixel size, which can be processed by the following steps.

[0034] First, determine the set distance and set the single pixel size as the interval distance.

[0035] Secondly, the point cloud is processed. Before processing the point cloud, make sure to remove redundant points (such as noise) and irrelevant parts to ensure that the data is clean.

[0036] Surface evaluation: If the surface is clearly too sparse, further high-density point clouds are acquired.

[0037] Then, the point cloud is resampled based on the distance.

[0038] Through resampling technology, point clouds can be arranged according to the set spacing. The resampling method can be selected as needed: Use a single pixel size to select or generate a point cloud. For example, starting from a certain point, search for points with a single pixel size interval on the cylindrical surface along a predetermined direction until the search is completed. If there is no point at the position with a single pixel size interval, search for the nearest point nearby.

[0039] Finally, the point cloud is rearranged, the found points are retained, the points other than the search results in the point cloud are deleted, and the retained points are rearranged at their locations to form a secondary point cloud.

[0040] The following is a simple example code showing how to rearrange a point cloud according to a set distance.

[0041] Rearranging point clouds using Python and Open3D First, you need to install the open3d library: pip install open3d Then you can use the following code to load the point cloud, calculate the point spacing, and rearrange it: Python import open3d as o3d import numpy as np # Load point cloud pcd = o3d.io.read_point_cloud("your_point_cloud.ply") # Get point cloud data points = np.asarray(pcd.points) # Assume that the set spacing is d d = 0.0033 (corresponding to 300 dpi resolution) # Calculate the distance between all points for i in range(1, len(points)): # Calculate the distance between two adjacent points distance = np.linalg.norm(points[i] - new_points[-1]) if distance = d: points.append(points[i]) # Set the new point cloud data to the open3d object new_pcd = o3d.geometry.PointCloud() new_pcd.points = o3d.utility.Vector3dVector(np.array(new_points)) # Visualize the new point cloud o3d.visualization.draw_geometries([new_pcd]) Through the above steps, you can use programming or point cloud processing software to arrange the point cloud of cylindrical products at set distances. The key steps include setting the sampling interval, calculating the distance between points, resampling the point cloud according to these distances, and finally visualizing and verifying. You can choose the point cloud processing library and tools that suit your needs to achieve this.

[0042] After processing in step S5, the distance between each point in the point cloud and its adjacent points in the horizontal and vertical directions is a single pixel size. Therefore, the next step is to match the pixels in the target printed image with the points in the point cloud in step S6; Since the distance between each point in the point cloud and its adjacent points in the horizontal and vertical directions is a single pixel, the point cloud can be expanded to form a plane point cloud in the XY axis display coordinate system, such as Figure 3 As shown, the following steps are required: S61. Set a starting pixel, and traverse all pixels in the target printed image from the starting point in the order of first horizontal and then vertical, to obtain the coordinates and color value of each pixel; S62. Setting a starting point, and starting from the starting point to unfold the point cloud, so that the point cloud is arranged in a plane in the XY axis direction; S63. Matching the coordinates of the pixel with the XY axis coordinates of the point cloud to obtain corresponding pixels and points; Since the pixels in the target printed image are arranged in a matrix, the coordinates and color values ​​of all pixels in the target printed image can be obtained through step S61; after the secondary point cloud is expanded in step S62, the point cloud is also arranged in a matrix in the XY axis coordinate system. Therefore, after setting the starting pixel and the starting point, the pixels in the target printed image and the point cloud can form a physical correspondence, and each pixel has a matching point.

[0043] Then, through S7., the points in the corresponding matching point cloud are colored according to the pixel colors in the target printed image to generate a color 3D verification model.

[0044] Through the processing of the above steps, the point cloud in space can be arranged according to the 3D shape of the actual sample surface, and the points in the point cloud are displayed according to the pixels in the corresponding target printed image, so as to accurately restore the actual shape of the target printed image after being printed on the sample surface, thereby realizing the digital verification of the matching degree between the printing design and the sample shape, and the final printing effect of the actual product can be previewed more flexibly.

[0045] The color 3D verification model can be used to reproduce the printing effect of the target printing image on the sample through the target printing equipment in actual printing.

[0046] Since the points in the point cloud have no actual physical size, they are often very small in the interface display, and the colors of the points at the original display size often cannot be clearly reproduced. In order to achieve a better reproduction effect, this embodiment also includes resizing the points in the secondary point cloud so that the projection edges of adjacent points in the secondary point cloud are adjacent.

[0047] Specifically, the resizing of points in the secondary point cloud includes: Adjust the radius of points in the secondary point cloud to half the size of a single pixel.

[0048] The adjusted dots are as close as possible to the actual single pixel size, thus more completely reproducing the digitized graphics.

[0049] Through the above method, the actual required printing image size can be obtained according to the printing area of ​​the sample, so as to process the image to be printed so that the target printing image matches the size of the printing area of ​​the sample, and then the pixel information of the target printing image is matched with the corresponding point cloud, and then the corresponding point cloud is colored, so as to obtain a color 3D model based on the point cloud. The matching of the sample and the image can be verified by observing the color 3D model, and there is no need to print the sample multiple times to adjust the image for repeated verification, which improves the verification efficiency and effectively saves material consumption.

[0050] The second embodiment of the present application further provides a 3D digital printed graphics verification system, the system comprising: Printing device module 1, obtaining the actual printing single pixel size according to the printing resolution of the target printing device; The sample scanning module 2 is used to scan the sample and obtain the point cloud of the sample; The image processing module 3 processes the image to be printed according to the actual printing image size to generate a target printing image; The point cloud processing module 4 performs data communication with the printing device module and the sample scanning module, scans the sample according to the single pixel size to obtain the point cloud, and arranges the point cloud with the single pixel size as the spacing; The point cloud coloring module 5 communicates data with the image processing module and the point cloud processing module, matches the pixels in the target printed image with the points in the point cloud, colors the corresponding matching points in the point cloud according to the pixel colors in the target printed image, and generates a color 3D verification model.

[0051] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A 3D digital printed graphics verification method, characterized in that: Includes steps: Measure samples and obtain sample size data; According to the sample size data, obtaining the actual printed image size; Process the image to be printed according to the actual printing image size to generate a target printing image; According to the printing resolution of the target printing device, the actual printing single pixel size is obtained; Scanning the sample according to a single pixel size to obtain a point cloud, so that the point cloud is arranged with a single pixel size as a spacing; Matching pixels in the target printed image with points in the point cloud; The points in the corresponding matching point cloud are colored according to the pixel colors in the target printed image to generate a color 3D verification model.

2. The 3D digital printed graphics verification method according to claim 1, characterized in that: The measuring of the sample and obtaining the sample size data further comprises: Acquire a primary point cloud of the sample; Sample size data is generated based on the primary point cloud.

3. The 3D digital printed graphics verification method according to claim 1, characterized in that: Processing the image to be printed according to the actual printed image size to generate a target printed image includes: Get the size of the image to be printed; Comparing the size of the image to be printed with the actual printed image size; The image to be printed is scaled and cropped so that the size of the image to be printed is equal to the actual printing image size.

4. The 3D digital printed graphics verification method according to claim 1, characterized in that: The obtaining of the single pixel size comprises: The single pixel size is the inverse of the printing resolution.

5. The 3D digital printed graphics verification method according to claim 1, characterized in that: Scanning the sample according to the single pixel size to obtain a point cloud comprises: The sample is scanned with the central axis of the sample as the rotation axis and the single pixel size as the scanning interval to obtain a secondary point cloud of the sample.

6. The 3D digital printed graphics verification method according to claim 2, characterized in that: The primary point cloud is a dense point cloud, and scanning the sample according to a single pixel size to obtain a point cloud includes: From the primary point cloud, the primary point cloud is screened with the single pixel size as a spacing to obtain a secondary point cloud.

7. The 3D digital printed graphics verification method according to claim 5 or 6, characterized in that: The points in the secondary point cloud are resized so that the projection edges of adjacent points in the secondary point cloud are adjacent.

8. The 3D digital printed graphics verification method according to claim 7, characterized in that: The resizing of points in the secondary point cloud comprises: Adjust the radius of points in the secondary point cloud to half the size of a single pixel.

9. The 3D digital printed graphics verification method according to claim 1, characterized in that: The matching of pixels in the target printed image with points in the point cloud comprises: Setting a starting pixel, traversing all pixels in the target printed image from the starting point in the order of first horizontal and then vertical, and obtaining the coordinates and color value of each pixel; Setting a starting point, and starting from the starting point to unfold the point cloud, so that the point cloud is arranged in a plane in the XY axis direction; Matching the coordinates of the pixel with the XY axis coordinates of the point cloud to obtain corresponding pixels and points; Assign the color value of the pixel to the corresponding point. 10.3D digital printing graphics verification system, characterized in that: include: The printing device module obtains the actual printing single pixel size according to the printing resolution of the target printing device; A sample scanning module is used to scan the sample and obtain a point cloud of the sample; An image processing module processes the image to be printed according to the actual printing image size to generate a target printing image; A point cloud processing module performs data communication with the printing device module and the sample scanning module, scans the sample according to a single pixel size to obtain a point cloud, and arranges the point cloud at a spacing of a single pixel size; The point cloud coloring module communicates data with the image processing module and the point cloud processing module, matches the pixels in the target printed image with the points in the point cloud, colors the corresponding matching points in the point cloud according to the pixel colors in the target printed image, and generates a color 3D verification model.

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