3D digital printing pattern verification method and system

Abstract

The application 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 and steps are executed as follows: sample size data is acquired; actual printing image size is acquired; a target printing picture is generated; actual printing single-pixel size is acquired; a point cloud is acquired by scanning the sample according to the single-pixel size, and the point cloud is arranged at intervals of single-pixel size; pixels in the target printing picture are matched with points in the point cloud; points in the point cloud are colored according to the color of the pixels in the target printing picture, and a color 3D verification model is generated. According to the application, the matching verification of the sample and the picture can be performed by observing the color 3D model, repeated verification by printing the sample and adjusting the image multiple times is not needed, the verification efficiency is improved, and 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 printed graphics verification method and system. Background Art

[0002] With the development of product diversity, the requirements for color printing on the outer surface of three-dimensional products are becoming increasingly higher. In the patent document entitled “3D Embossed Inkjet Printing Image Processing Method and System” with application number CN202411197734.3, the applicant disclosed a printing technology suitable for cylindrical products with three-dimensional concave-convex shapes on the surface. By color mapping and matching the flat image with the cylindrical outer surface and the concave-convex shape of the surface, surface printing of such products can be achieved. However, before printing, it is necessary to print samples to verify whether the shape of the product matches the flat image to be printed and whether the expected printing effect can be achieved. If the effect does not meet the expectations, it is necessary to repeatedly adjust the corresponding flat image and print samples. Since products such as pen holders, water cups, and vases have various sizes and specifications, the applicable surface printing patterns are also different. Therefore, verifying the printing effect through sample printing requires a large number of processes, which is inefficient and consumes a lot of materials. Summary of the Invention

[0003] In a first aspect, embodiments of the present application provide a 3D digitally printed graphics verification method that solves the problem of matching testing through samples and can perform digital matching verification on a planar image printed on a cylindrical 3D surface.

[0004] In order to solve the above problem, the method comprises the steps of:

[0005] Measure samples and obtain sample size data;

[0006] Obtaining actual printed image size according to the sample size data;

[0007] Processing the image to be printed according to the actual printing image size to generate a target printing image;

[0008] According to the printing resolution of the target printing device, the actual printing single pixel size is obtained;

[0009] Scanning the sample to obtain a point cloud according to a single pixel size, and arranging the point cloud with a single pixel size as a spacing;

[0010] Matching pixels in the target printed image with points in the point cloud;

[0011] Color 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.

[0012] 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 target printing image so that the size of the printing area of ​​the sample matches the target printing image. Then, by matching the pixel information of the target printing image with the corresponding point cloud, 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. There is no need to print the sample multiple times and adjust the image for repeated verification, which improves the verification efficiency and effectively saves material consumption.

[0013] In a possible implementation, measuring the sample and obtaining sample size data further includes:

[0014] Acquire a point cloud of the sample;

[0015] Sample size data is generated based on the primary point cloud.

[0016] In a possible implementation, processing the image to be printed according to the actual printing image size to generate a target printing image includes:

[0017] Get the size of the image to be printed;

[0018] comparing the size of the image to be printed with the actual printed image size;

[0019] 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.

[0020] In a possible implementation, obtaining the single-pixel size includes:

[0021] The single pixel size is the inverse of the printing resolution.

[0022] In a possible implementation, scanning the sample according to a single pixel size to obtain a point cloud includes:

[0023] 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.

[0024] 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:

[0025] The primary point cloud is filtered using the single pixel size as a spacing to obtain a secondary point cloud.

[0026] 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.

[0027] In a possible implementation, resizing the points in the secondary point cloud includes:

[0028] Adjust the radius of points in the secondary point cloud to half the size of a single pixel.

[0029] In a possible implementation, matching pixels in the target printed image with points in the point cloud includes:

[0030] Setting a starting pixel, traversing all pixels in the target printed image from the starting point in the order of first horizontally and then vertically, and obtaining the coordinates and color value of each pixel;

[0031] 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;

[0032] Matching the coordinates of the pixel with the XY coordinates of the point cloud to obtain corresponding pixels and points;

[0033] Assign the color value of the pixel to the corresponding point.

[0034] In a second aspect, an embodiment of the present application further provides a 3D digital printed graphic verification system, the system comprising:

[0035] The printing device module obtains the actual printed single pixel size according to the printing resolution of the target printing device;

[0036] The sample scanning module is used to scan the sample and obtain the point cloud of the sample;

[0037] An image processing module processes the image to be printed according to the actual printing image size to generate a target printing image;

[0038] a point cloud processing module, communicating with the printing device module and the sample scanning module, scanning the sample according to a single pixel size to obtain a point cloud, and arranging the point cloud with a single pixel size as a spacing;

[0039] 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

[0040] Figure 1 This is a flow chart of the first embodiment;

[0041] Figure 2 Further flowchart for step S1 of the first embodiment;

[0042] Figure 3 Further flowchart for step S6 of the first embodiment;

[0043] Figure 4 Schematic diagram of the module structure of the second embodiment. DETAILED DESCRIPTION

[0044] For the purposes of the present application, the technical solutions and advantages will be clearer, and the technical solutions will be described in detail below 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, rather than all the embodiments. In the absence of conflicts, 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 those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0045] The 3D digital printing pattern verification method in the present embodiment is mainly applicable to the digital verification of the surface color printing effect of a cylindrical product and a product with a relief type three-dimensional modeling on the surface. The existing printing of such products has been disclosed in the prior patent of the applicant. The embodiments of the present application mainly verify and preview the matching of the product modeling and the picture and the printing effect before printing for such products, to replace the existing way of achieving similar effects by printing actual samples.

[0046] The purpose of making such verification is generally two-fold. First, there are various types of products with different specifications, and the sizes of the pictures matched with the printing on the surface are also different. The size matching between the sample and the picture needs a lot of work. Second, whether the pattern and design of the picture applied to the actual product has the expected aesthetic degree needs to be evaluated through product verification to achieve the expected acceptance of appearance.

[0047] In order to save a lot of pre-printing procedures for verification, the first embodiment of the present application provides a 3D digital printing pattern verification method, as shown in Figure 1 The method comprises the steps of:

[0048] S1. measuring a sample to obtain sample size data;

[0049] S2. obtaining an actual printing image size according to the sample size data;

[0050] S3. processing a to-be-printed picture according to the actual printing image size to generate a target printing picture;

[0051] S4. Obtain the actual printed single pixel size according to the printing resolution of the target printing device;

[0052] S5. Scanning the sample to obtain a point cloud according to a single pixel size, so that the point cloud is arranged at a spacing of a single pixel size;

[0053] S6. Matching pixels in the target printed image with points in the point cloud;

[0054] 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.

[0055] 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. 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 using computer graphic 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 are irregular shapes, so special processing is required. In this embodiment, the acquisition and processing are performed by obtaining point clouds, as shown in the following example. Figure 2 As shown, the measuring of the sample and obtaining the sample size data further includes:

[0056] S11. Obtaining a point cloud of the sample;

[0057] S12. Compute sample size data based on the primary point cloud.

[0058] 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 dataset that describes the shape and surface characteristics of an object by collecting the coordinates (usually x, y, z three-dimensional coordinates) of a large number of discrete points on the surface of the object. Common ways to obtain point cloud data include laser scanning (LiDAR), structured light scanning (Structured Light Scanning), photogrammetry (Photogrammetry), coordinate measuring machines, handheld 3D scanners, ultrasonic scanning, depth cameras (Depth Cameras), etc. Based on the implementation scenario and product requirements of the present 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 an object. These depth cameras can capture three-dimensional data of an object or scene, generating real-time point clouds.

[0059] Selecting the appropriate point cloud collection method requires considering application requirements, object characteristics, budget, and precision requirements.

[0060] After collecting the point cloud, the distance of all points in the point cloud from the center axis can be calculated, and then the average distance can be calculated based on the length distribution of the distance of the points from the center axis. The circumference length can be calculated using the average distance as the radius. The circumference length can also be calculated based on the length distribution of the distance of the points from the center axis, combined with the number of distribution points in each distance interval and the corresponding weight. For example, if 60% of the points have a distance from the center axis greater than the average length, then the distance value is assigned a weight of 60% for calculation.

[0061] After calculating the sample size, the actual printing image size can be obtained directly from the sample size in step S2. The actual printing image size is the length and width of the picture that is actually printed on the side surface of the sample, so its length is equal to the circumference of the sample outer surface, and its width is equal to the height of the sample.

[0062] 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 uniform. Therefore, based on the actual printing image size obtained in step S2, the image to be printed can be processed. 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 within the sampling area. After confirming the sampling area, the target printing image is obtained, that is, an image of the same size as the actual printing image obtained after processing the design sample 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.

[0063] Since the present embodiment needs to simulate the actual printing sample, the actual printing rendering effect that the printing device can achieve must also be considered. Therefore, in step S4, the actual printing single pixel size is obtained according to the printing resolution of the target printing device.

[0064] The target printing device's print resolution can be obtained through the printing device's control port. If the target printing device has multiple print resolutions, one of these resolutions can be selected as the execution resolution of this embodiment based on actual needs. Once the execution resolution is obtained, the actual print pixel size achievable by the target printing device can be determined. The actual print pixel size is the inverse of the execution resolution.

[0065] After obtaining the single pixel size, 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 a single pixel size as a spacing;

[0066] 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.

[0067] 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 mentioned 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.

[0068] Generally speaking, the length and width are equal in a single pixel size.

[0069] There is another implementation method of step S5. Since in this embodiment, the sample is measured in step S1 by obtaining a point cloud, the acquisition of the secondary point cloud can be obtained based on the screening of the primary point cloud.

[0070] 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:

[0071] The primary point cloud is filtered using the single pixel size as a spacing to obtain a secondary point cloud.

[0072] The point cloud can be filtered again and arranged with a single pixel size as the spacing, which can be processed by the following steps.

[0073] First, determine the set distance and set the single pixel size as the interval distance.

[0074] 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.

[0075] Surface evaluation: If the surface is clearly too sparse, further high-density point cloud acquisition is performed.

[0076] Then, the point cloud is resampled based on the distance.

[0077] Through resampling technology, point clouds can be arranged according to the set spacing. The resampling method can be selected as needed:

[0078] Use pixel size to select or generate a point cloud. For example, starting from a certain point, points are searched for at intervals of pixel size on a cylindrical surface along a predetermined direction until the search is complete. If there are no points at a pixel-size interval, the nearest point is searched.

[0079] Finally, the point cloud is rearranged, the found points are retained, the points outside the query results in the point cloud are deleted, and the retained points are rearranged at their positions to form a secondary point cloud.

[0080] The following is a simple example code showing how to rearrange a point cloud based on a set distance.

[0081] Rearranging point clouds using Python and Open3D

[0082] First, you need to install the open3d library:

[0083] pip install open3d

[0084] You can then use the following code to load the point cloud, calculate the point spacing, and rearrange it:

[0085] python

[0086] import open3d as o3d

[0087] import numpy as np

[0088] # Load point cloud

[0089] pcd = o3d.io.read_point_cloud("your_point_cloud.ply")

[0090] # Get point cloud data

[0091] points = np.asarray(pcd.points)

[0092] # Assume the set interval is d

[0093] d = 0.0033 (corresponding to 300 dpi resolution)

[0094] # Calculate the distance between all points

[0095] for i in range(1, len(points)):

[0096] # Calculate the distance between the two adjacent points

[0097] distance = np.linalg.norm(points[i] - new_points[-1])

[0098] if distance = d:

[0099] points.append(points[i])

[0100] # Set the new point cloud data to the open3d object

[0101] new_pcd = o3d.geometry.PointCloud()

[0102] new_pcd.points = o3d.utility.Vector3dVector(np.array(new_points))

[0103] # Visualize the new point cloud

[0104] o3d.visualization.draw_geometries([new_pcd])

[0105] Following the above steps, you can use programming or point cloud processing software to arrange the point cloud of a cylindrical product at a set distance. The key steps include setting the sampling interval, calculating the distance between points, resampling the point cloud based on these distances, and finally visualizing and verifying it. You can choose a point cloud processing library and tool that suits your needs to achieve this.

[0106] 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. Therefore, the next step is to match the pixels in the target printed image with the points in the point cloud in step S6.

[0107] 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 to achieve this:

[0108] 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;

[0109] S62. Setting a starting point, and starting from the starting point, unfolding the point cloud so that the point cloud is arranged in a plane in the XY axis direction;

[0110] S63. Matching the coordinates of the pixel with the XY coordinates of the point cloud to obtain corresponding pixels and points;

[0111] 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 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.

[0112] 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.

[0113] Through the processing of the above steps, the point cloud in space can be arranged according to the 3D morphology of the actual sample surface, and the points in the point cloud are displayed according to the corresponding pixels in the target printed picture, so that the actual morphology of the target printed picture printed on the sample surface can be accurately restored, thereby realizing digital verification of the matching degree of the printed design and the sample morphology, and the final printing effect of the actual product can be previewed more flexibly.

[0114] The color 3D verification model can reproduce the printing effect of the target printed picture on the sample by the target printing equipment in actual printing.

[0115] Since the points in the point cloud are points without actual physical size, they are often particularly small on the interface display, and the color cannot be clearly reproduced by the original display size points. In order to achieve better reproduction effect, the points in the secondary point cloud are adjusted in size in the embodiment, so that the projection edges of adjacent points in the secondary point cloud are in an abutting state.

[0116] Specifically, the size adjustment of the points in the secondary point cloud comprises:

[0117] The radius of the points in the secondary point cloud is adjusted to one-half of the single-pixel size.

[0118] The adjusted points can be as close as possible to the actual single-pixel size, thereby more completely reproducing the digitalized graphics.

[0119] Through the above method, first, the actual required printing image size can be obtained according to the printing area of the sample, so that the target printed picture is processed to match the size of the printing area of the sample, then the pixel information of the target printed picture is matched with the corresponding point cloud, and the corresponding point cloud is colored, so that the color 3D model based on the point cloud can be obtained, and the matching verification of the sample and the picture can be performed by observing the color 3D model, without repeatedly printing the sample to adjust the image for repeated verification, thereby improving the verification efficiency and effectively saving material consumption.

[0120] The second embodiment of the present application also provides a 3D digitalized printed graphic verification system, which comprises:

[0121] A printing equipment module 1 acquires the actual printing single-pixel size according to the printing resolution of the target printing equipment;

[0122] A sample scanning module 2 is used for scanning the sample to acquire the point cloud of the sample;

[0123] A picture processing module 3 processes the to-be-printed picture according to the actual printing image size to generate a target printed picture;

[0124] The point cloud processing module 4 communicates 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;

[0125] 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.

[0126] 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: Including steps: Measuring a sample to obtain sample dimension data, wherein the sample includes a cylindrical product body and a three-dimensional configuration located on an outer surface of the product body, wherein the three-dimensional configuration is a relief-like three-dimensional configuration with a low height difference; Obtaining an actual printed image size according to the sample size data, wherein the actual printed image size is the length and width of the image actually covered on the side surface of the sample during printing; Processing the image to be printed according to the actual printing image size to generate a target printing image, wherein the target printing image is an image file actually printed on the outer surface of the product in subsequent printing processing; According to the printing resolution of the target printing device, the actual printing single pixel size is obtained; Scanning the sample to obtain a point cloud according to a single pixel size, and arranging the point cloud with a single pixel size as a spacing; Matching pixels in the target printed image with points in the point cloud; Color 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.

2. The 3D digital printed graphics verification method according to claim 1, wherein: The measuring of the sample and obtaining the sample size data further comprises: Acquire a 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, wherein: Processing the image to be printed according to the actual printing image size to generate a target printing 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, wherein: The obtaining of the actual printed single pixel size includes: The single pixel size is the inverse of the printing resolution.

5. The 3D digital printed graphics verification method according to claim 1, wherein: Scanning the sample according to the 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.

6. The 3D digital printed graphics verification method according to claim 2, wherein: 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: The primary point cloud is filtered using 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, wherein: 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.

9. The 3D digital printed graphics verification method according to claim 1, wherein: 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 starting from the starting pixel in the order of first horizontally and then vertically, 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 coordinates of the point cloud to obtain corresponding pixels and points; Assign the color value of the pixel to the corresponding point.

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