Methods and corresponding systems for printing images on substrates

Abstract

This invention relates to a method for printing an image on a substrate, comprising: providing image template data of an image to be printed by an image providing computing device; analyzing the image template data by identifying image components of the image; providing a substrate for printing the image by a substrate supply device; providing ink for printing the image by an ink supply device; printing the image on the substrate using the image template data based on printing parameters of a printer operated using printer configuration parameters; capturing the printed image on the substrate by an image capturing device and providing captured image data of the captured image; analyzing the captured image data using an analysis computing device using an analysis program; associating the identified image components in the image template data with the identified image components of an ROI related to an image metric; selecting printer configuration parameters and / or printing parameters for correction; and using an image metric to calculate image component-specific actual correction parameters for the selected printer configuration parameters and / or printing parameters.

Description

Technical Field

[0001] This invention relates to a method for printing images on a substrate, preferably glass, ceramic or glass-ceramic.

[0002] The present invention also relates to a system for printing images on a substrate, preferably glass, ceramic, or glass-ceramic.

[0003] The present invention also relates to a non-tangible computer-readable medium storing a program comprising computer-readable instructions for causing a computer or computer network to perform a method of printing an image on a substrate, preferably glass, ceramic or glass-ceramic.

[0004] Although generally applicable to any printing method, the invention will be described in the context of inkjet printing.

[0005] Although generally applicable to any kind of substrate, the invention will be described in the context of ceramics. Background Technology

[0006] Traditional inkjet printing technology and corresponding machines are illustrated, for example, in EP 3421250 A1. EP 3421250A1 demonstrates single-pass digital printing on glass using digital printheads on a movable print bridge. These digital printheads can be used for multi-pass printing to correct printing defects detected after printing or for more complex printing. When a defect occurs during single-pass printing, the defect is detected by an optical graphics aid connected to the printer's central processing and control unit, which can instruct the print bridge to perform additional high-precision print passes on the glass to correct the detected defect. These graphics aids are, for example, located in the print bridge that analyzes the printed image and detects defects.

[0007] However, one problem is that while printing defects can be detected, the method is extremely time-consuming and inefficient: the glass must be reprocessed multiple times to detect and correct defects. Furthermore, the total printed area of ​​the glass must be examined to detect defects. Another problem arises because the definition of a defect can vary depending on the printer and its configuration, as well as the type of optical graphics aids. A further problem is that the same defects may appear when the same image is printed again on the same type of substrate. Summary of the Invention

[0008] Therefore, one object of the present invention is to provide a method and system for printing images on a substrate that is more efficient, requires less time to obtain printed products, and provides printed products of a defined quality for different printers and different images to be printed. In particular, another object of the present invention is to provide a method and system that can achieve a defined print quality with a reduced number of defects for a large number of substrates of the same type and a large number of identical images to be printed. Another object of the present invention is to provide alternative methods and systems for printing images on a substrate.

[0009] In one embodiment, the present invention provides a method for printing an image on a substrate, preferably glass, ceramic, or glass-ceramic, the method comprising the following steps:

[0010] - Image template data of the image to be printed is provided by the image-providing computing device.

[0011] - Analyze the image template data by identifying the image components of the image.

[0012] - A substrate for printing the image thereon is provided by a substrate supply device.

[0013] Ink for printing the image is supplied by an ink supply device.

[0014] - Based on the printer's printing parameters operated using printer configuration parameters, a printing program, preferably an inkjet printing program, is used to print the image on the substrate using the image template data and the ink. - The printed image on the substrate is captured by one or more image capture devices, and captured image data of the captured image is provided.

[0015] - The captured image data is analyzed using an analysis program via an analysis computing device, the analysis program comprising:

[0016] Provide definition parameters for defining at least one Region of Interest (ROI).

[0017] Based on the provided defined parameters, at least one ROI within the captured image data is determined.

[0018] ο Identify at least one image component in the at least one ROI,

[0019] For the at least one ROI, determine at least one image metric, and

[0020] The at least one image metric is associated with the at least one image component.

[0021] - Associate at least one identified image component in the image template data with at least one identified image component of the at least one ROI associated with the at least one image metric.

[0022] - Select one or more printer configuration parameters and / or printing parameters for calibration, preferably based on at least one image metric and / or at least one image component.

[0023] - Based on an optimized calculation procedure, at least one image metric is used to calculate at least one actual correction parameter of the selected printer configuration parameter and / or the selected printing parameter, wherein the at least one actual correction parameter is specific to the image component.

[0024] In a further embodiment, the present invention provides a system for printing images on a substrate, preferably glass, ceramic, or glass-ceramic, the system comprising:

[0025] - An image-providing computing device for providing image template data for the image to be printed.

[0026] - An image analysis device for analyzing the image template data by identifying the image components of the image; - A substrate supply device for providing a substrate for printing the image thereon.

[0027] - An ink supply device for providing ink for printing the image.

[0028] - A printer, adapted to operate based on printing parameters of the printer using printer configuration parameters, using a printing program, preferably an inkjet printing program, to print the image on a substrate using the image template data and the ink.

[0029] - One or more image capture devices for capturing printed images on the substrate and providing captured image data.

[0030] - An analysis and computing device, configured to analyze the captured image data using an analysis program, adapted to perform the following steps:

[0031] Provide definition parameters for defining at least one Region of Interest (ROI).

[0032] Based on the provided defined parameters, at least one ROI is determined within the captured image data.

[0033] ο Identify at least one image component in the at least one ROI,

[0034] For the at least one ROI, determine at least one image metric, and

[0035] The at least one image metric is associated with the at least one image component.

[0036] - A relation calculation device for associating at least one identified image component in the image template data with at least one identified image component of the at least one ROI associated with the at least one image metric.

[0037] - A selection device for selecting one or more printer configuration parameters and / or printing parameters for calibration, preferably based on at least one image metric and / or at least one image component.

[0038] - A calibration calculation device for calculating, based on an optimization calculation program, at least one actual calibration parameter of the selected printer configuration parameters and / or the selected printing parameters using the at least one image metric, wherein the at least one actual calibration parameter is specific to the image component.

[0039] In a further embodiment, the present invention provides a non-tangible computer-readable medium storing a program including computer-readable instructions that cause a computer or computer network to perform a method of printing an image on a substrate, preferably glass, ceramic, or glass-ceramic, the method comprising the following steps:

[0040] - Image template data of the image to be printed is provided by the image-providing computing device.

[0041] - Analyze the image template data by identifying the image components of the image.

[0042] - A substrate for printing the image thereon is provided by a substrate supply device.

[0043] Ink for printing the image is supplied by an ink supply device.

[0044] -Based on the printer's printing parameters, which are operated using printer configuration parameters, a printing program, preferably an inkjet printing program, is used to print the image on the substrate using the image template data and the ink.

[0045] - Capture a printed image on the substrate using one or more image capture devices, and provide captured image data of the captured image.

[0046] - The captured image data is analyzed using an analysis program via an analysis computing device, the analysis program comprising:

[0047] Provide definition parameters for defining at least one Region of Interest (ROI).

[0048] Based on the provided defined parameters, at least one ROI within the captured image data is determined.

[0049] ο Identify at least one image component in the at least one ROI,

[0050] For the at least one ROI, determine at least one image metric, and

[0051] The at least one image metric is associated with the at least one image component.

[0052] - Associate at least one identified image component in the image template data with at least one identified image component of the at least one ROI associated with the at least one image metric.

[0053] - Select one or more printer configuration parameters and / or printing parameters for calibration, preferably based on at least one image metric and / or at least one image component.

[0054] - Based on an optimized calculation procedure, at least one image metric is used to calculate at least one actual correction parameter of the selected printer configuration parameter and / or the selected printing parameter, wherein the at least one actual correction parameter is specific to the image component.

[0055] One of the advantages that can be provided by at least one of the embodiments is optimized printed products. Another advantage may be that, particularly due to the defined ROI, printing and defect detection can be performed in a shorter time, thereby improving efficiency. Another advantage is the ability to quickly and easily compare different print qualities based on defined parameters. A further advantage may be the ability to provide a large number of identical printed products with improved quality.

[0056] The terms "device" and "storage device," particularly in the claims and preferably in the specification, each refer to a device suitable for performing computation, such as a personal computer, tablet computer, mobile phone, server, etc., and include one or more processors having one or more cores, and can be connected to memory for storing one or more applications adapted to perform corresponding steps of one or more embodiments of the invention. Any application can be software-based and / or hardware-based, installed in memory on which the processor can operate. Devices, apparatuses, etc., can be adapted to perform the corresponding steps to be computed in an optimized manner. For example, different steps can be executed in parallel on different cores of a single processor. Furthermore, different storage devices can be identical, forming a single storage computing device. One or more devices can also be instantiated as virtual devices running on physical computing resources. Thus, different devices can be executed on said physical computing resources.

[0057] The terms "computing device" or "computing apparatus," "computing instrument," etc., particularly in the claims and preferably in the specification, each refer to a device suitable for performing computations, such as a personal computer, tablet computer, mobile phone, server, etc., including one or more processors having one or more cores, and which can be connected to memory for storing an application adapted to perform corresponding steps of one or more embodiments of the invention. Any application can be software-based and / or hardware-based, installed in memory on which the processor can operate. The computing device or apparatus can be adapted to perform the corresponding steps to be computed in an optimized manner. For example, different steps can be executed in parallel on different cores of a single processor. Furthermore, computing devices or apparatuses can be identical, forming a single computing device. Devices or instruments can also be instantiated as virtual devices running on physical computing resources. Thus, different devices can be executed on said physical computing resources. Each device or apparatus may have one or more interfaces for communicating with the environment, such as other devices, people, etc.

[0058] The terms "computer-readable medium" or "storage medium" can refer to any kind of medium that can be used with a computing device or computer and on which information can be stored. The information can be any kind of data that can be read into the computer's memory. For example, the information may include program code for execution with the computer. Examples of computer-readable media are magnetic tape, CD-ROM, DVD-ROM, DVD-RAM, DVD-RW, Blu-ray, DAT, MiniDisk, SSD, floppy disk, SD card, CF card, Memory Stick, USB stick, EPROM, EEPROM, etc.

[0059] The term "printed product" in the specification, and preferably in the claims, specifically refers to one or more physical objects that can be manufactured like glass, ceramics, etc., and on which one or more images are printed. Generally speaking, any physical object that can be manufactured or physically provided can be considered a "product".

[0060] The optimization program may include, but is not limited to, one of the following optimization algorithms or a combination of at least two of the following optimization algorithms:

[0061] • Ad-hoc On-demand Distance Vector

[0062] Ant colony optimization algorithm

[0063] Approximation Algorithm

[0064] • Back propagation

[0065] Hill climbing algorithm

[0066] • Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm

[0067] ·dichotomy

[0068] Paulufka algorithm

[0069] Branch-and-Bound

[0070] Branch-and-Cut

[0071] Christofides Algorithm

[0072] • Conjugate gradient method

[0073] • Covariance Matrix Adaptation Evolution Strategy

[0074] • Constraint shortest path first

[0075] • D-Star algorithm

[0076] Dijkstra's Shortest Path First Algorithm

[0077] Dinic Algorithm

[0078] The Nelder-Mead method

[0079] Edmonds-Karp algorithm

[0080] ·Ellipsoid method

[0081] Ford–Fulkerson Algorithm (FFA)

[0082] Gauss-Newton algorithm

[0083] • Push-relabel algorithm

[0084] Gotoh algorithm

[0085] Gradient descent algorithm

[0086] Greedy algorithm

[0087] Hopcroft–Karp algorithm

[0088] Interior point method

[0089] Johnson Algorithm

[0090] Kruskal algorithm

[0091] Lee's Algorithm

[0092] Levenberg–Marquardt algorithm

[0093] Linear optimization

[0094] Line search algorithm

[0095] • Moving asymptote method

[0096] The Metropolis-Hastings algorithm

[0097] • Modified distribution method / UV method

[0098] Minimum Spanning Tree

[0099] Natural analogy optimization

[0100] Needleman-Wunsch Algorithm

[0101] • Network Simplex Algorithm

[0102] Nussinov algorithm

[0103] Multi-objective optimization

[0104] Particle Swarm Optimization

[0105] • Pivot algorithm

[0106] Prim Algorithm

[0107] • Quasi-Newtonian method

[0108] • Adjusted Winner procedure

[0109] Threshold accepting procedure

[0110] Simplex algorithm

[0111] Simulated Annealing algorithm

[0112] Macro heuristic (Great Deluge algorithm)

[0113] Smith-Waterman Algorithm

[0114] Spanning Tree Protocol

[0115] Folding Spectrum Method

[0116] • Stochastic tunneling

[0117] Tabu search algorithm

[0118] • Trust Region Approach

[0119] • Viterbi algorithm

[0120] Stepping-Stone Method

[0121] Further features, advantages, and preferred embodiments are disclosed or become apparent below.

[0122] According to one embodiment, the method further includes the steps of: thermally fixing a printed image using a thermal fixing device; determining at least one of optical, chemical, and mechanical properties of the thermally fixed image using a thermal fixing measurement device; and receiving data from the thermal fixing measurement device for the properties used in the analysis procedure. This further improves the quality of the printed product and future similar printed products. In particular, data regarding the mechanical, physical, or optical properties of the product can be obtained, which can be used to optimize the entire printing process.

[0123] According to a further embodiment, the defined parameters and the image measurements are at least based on ISO / IEC 24790:2017(E) or a later version. This allows for a simple and explicit comparison of printed products. Any further, newer, more recent, or different versions of ISO / IEC 24790 can also be used to provide the defined parameters and image measurements. The following... Figure 1 and Figure 2Examples of defining parameters and image metrics are given in the context of the example.

[0124] According to another embodiment, at least one of the image metrics, the captured image data, the image template data, the correction parameters, and the selection parameters is stored in a storage device and / or on a portable storage medium. One advantage is that a centralized device in the form of a database can provide corresponding data for analysis to multiple users. Portable storage media have the advantage of greater flexibility, for example, data read from the storage medium can be made available through software applications. The software application and the database can store data and metrics in any suitable format, such as as TXT files, and convert the corresponding data into the appropriate format necessary for processing by the other device when the data for analysis is delivered to it.

[0125] According to a further embodiment, the optimization calculation program is based on a machine learning program, preferably executed using a neural network. This enables the efficient learning of the correlation between parameters of the printing process on one hand and defects in the printed product on the other, thereby improving the quality of future printed products.

[0126] According to another embodiment, all steps are repeated, preferably for multiple substrates on which the same image and / or at least one identical image component is printed. This allows for the improvement of correction parameters, thereby enabling future printed products to achieve further improvements in image or print quality.

[0127] According to another embodiment for determining image metrics, a wavelet transform procedure and / or a Fourier transform procedure are performed on the data of the ROI. Wavelet transform provides better results than short-time Fourier transform and is able to obtain accurate image metrics. Wavelet transform, particularly discrete wavelet transform (DWT), is a recursive application of iterative low-pass and high-pass filtering, reducing resolution until the signal length corresponds to the filter length. Fourier transform makes implementation easier and requires fewer computational resources.

[0128] According to another embodiment, a single overall metric is determined for the at least one image metric to determine image quality, and the single overall metric is a weighted sum of at least two metrics. One advantage is that the quality of different images can be compared quickly and easily.

[0129] According to a further embodiment, the selection step includes the following steps:

[0130] – Calculate the impact value associated with the enhancement or degradation of at least one image metric for each of the multiple printer configuration parameters and / or printing parameters.

[0131] - Select one or more printer configuration parameters and / or printing parameters based on one or more influence values.

[0132] This allows for the simple and effective selection or selection of multiple parameters for optimizing subsequent print results during optimization.

[0133] According to another embodiment, one or more maximum influence values ​​are used to select one or more printer configuration parameters and / or printing parameters. This enables the automatic selection or selection of a limited number of parameters that have the greatest impact on the print results when being optimized, for subsequent optimization of print results, in a more efficient manner.

[0134] According to another embodiment, a model is generated at least based on selected printer configuration parameters and / or printing parameters. This model describes the relationship between the printer configuration parameters and / or printing parameters and at least one image metric for at least one image component. Preferably, the model is generated using artificial intelligence, preferably a machine learning program, preferably a deep learning program, preferably a neural network. The model allows different image components to be mapped to different image metrics independently of image template data and independently of captured image data. In other words, for each image component, an image metric can be provided, which can be obtained from multiple comparisons between image template data and extracted data of the image components of the captured image. Therefore, when printing a future image containing the image components, a printed image with enhanced image quality in some or all image components can be obtained.

[0135] The generated model can be based on one or more of the following model types: statistical model or dynamic model. Dynamic models include time discrete model, time continuous model, spatial discrete model, and spatial continuous model.

[0136] According to a further embodiment, the plurality of printer configuration parameters and / or printing parameters are obtained by repeating all the steps multiple times, preferably including the following steps:

[0137] - The at least one image metric is compared with a previously determined corresponding metric and / or one or more predetermined corresponding thresholds by a comparison computing device, and

[0138] - Based on the comparison performed by the calibration calculation device, calibration parameters are provided for the printer configuration parameters and / or the printing parameters, such that the differences between the previous and the calibration parameters are minimized.

[0139] This also allows for continuous refinement of the correction parameters as printing conditions change slowly over time.

[0140] According to another embodiment of the system, the system further includes a storage device, preferably a database and / or a portable storage medium, for storing at least one of the image measurements, the captured image data, image template data, correction parameters, and selection parameters. One advantage is that a centralized device in the form of a database can provide corresponding data for analysis to multiple users, while a portable storage medium provides simple and flexible processing.

[0141] According to another embodiment of the system, the thermal fixing measurement device is adapted to perform thermal stress analysis. This enables the determination of the mechanical, chemical, and / or physical properties of the printed product in a simple manner, and this data can be further used to optimize the printing process.

[0142] According to a further embodiment, the system also includes a machine learning computing device connected to the storage device and / or the storage medium, acting as a relational computing device and / or a correction computing device and adapted to perform machine learning, preferably using a neural network. This enables an effective understanding of the correlation between parameters of the printing process on one hand and defects in the printed product on the other hand, thereby improving the quality of future printed products.

[0143] According to a further embodiment, the substrate supply device provides a substrate in the form of a glass object, a ceramic object, or a glass-ceramic object. This particularly provides for image printing on glass or glass-ceramic. Attached Figure Description

[0144] Several ways exist to advantageously design and further develop the teachings of the invention. Therefore, reference is made, on the one hand, to the claims dependent on claims 1 and 12, and on the other hand, to the following description of preferred examples of embodiments of the invention shown in the accompanying drawings. Further development of the generally preferred embodiments and teachings will be explained in conjunction with the explanation of the preferred embodiments of the invention by means of the accompanying drawings.

[0145] In the diagram:

[0146] Figure 1 The steps of a method according to an embodiment of the present invention are shown;

[0147] Figure 2 The steps of a method according to an embodiment of the present invention are shown;

[0148] Figure 3 The steps of a method according to an embodiment of the present invention are shown;

[0149] Figure 4 A system according to an embodiment of the present invention is illustrated schematically, and

[0150] Figure 5 The steps of a method according to an embodiment of the present invention are shown. Detailed Implementation

[0151] Figure 1 The steps of a method according to an embodiment of the present invention are shown.

[0152] In detail, Figure 1 P1a is displayed: Provides the digital image data to be printed and specifies the parameters of the digital image, such as the resolution and size of the image to be printed. The digital image data is considered "constant" and is provided by the customer.

[0153] also, Figure 1 P1b is displayed: This provides the substrate on which the image will be printed, along with parameters specifying the substrate, such as substrate material, substrate pretreatment, substrate cleaning, etc. The substrate is considered "constant" and is provided by the customer.

[0154] Further Figure 1 P1c is displayed: Provides printing ink, including parameters for specifying the printing ink, such as pigment data, glass frit data, solvent, binder, etc.

[0155] All the data, parameters, ink, and substrate provided in steps P1a-P1c are provided to the printer in step P2 for printer configuration and for the printing process performed by the printer. In a further step P3, the printing process is performed by printing an image onto the substrate, where the printing process is defined by printing process parameters. The result of the printing process, P4, is the substrate on which the image has been printed. The printing substrate has certain optical, mechanical, and chemical properties. In alternative additional steps that the customer or client may require, thermal fixing in step P5 can be performed to fix the mechanical, chemical, and / or optical properties of the printing substrate. Thermal stress analysis (TSA) can provide information about the physical, chemical, and optical properties of the printed product. For example, a thermal imaging camera can be used, and the obtained data can be used in conjunction with the optical data described below.

[0156] An optical device detects the characteristics of the printing substrate and its image, and a corresponding processing device calculates a parameter or set of parameters in a further step P6. This parameter or set of parameters represents the combined or overall characteristics of the printed image on the substrate with respect to defects, or certain defined characteristics. Further processing can provide correction parameters for printer P2 and correction parameters for the printing process P3 to minimize identified defects on future printing substrates of the same type.

[0157] Optical devices, such as multiple cameras, capture printed images at different angles, wavelengths, focal lengths, etc., and may also include different light sources to emit light of different wavelengths onto the printed images on the substrate. For example, thermal imaging cameras can be used.

[0158] In step P6, the captured image data can be processed as described above to obtain an overall value for the quality of the specified printed image. Using ISO standard 24790, here ISO / IEC 24790:2017(E), first edition 2017-02, which is incorporated herein by reference, at least 14 evaluation parameters are provided.

[0159] The following provides an overview of the variables used to evaluate image quality and measure image quality attributes. These are detailed in the aforementioned ISO standard, ISO / IEC 24790:2017(E).

[0160] The following definitions apply:

[0161] -Reflection coefficient R:

[0162] Defined as the ratio of the measured reflection flux to the reflection flux for an ideal 100% diffuse surface under the same geometric and spectral conditions.

[0163] -Reflection threshold:

[0164] R min +n(R max -R min )

[0165] - Edge threshold: From the minimum reflectance (R) min ) to maximum reflectance (R max ) 40% of the transition

[0166] R 40 =R min +0.4(R max -R min )

[0167] -Outer boundary: from the minimum reflection coefficient (R) min ) to maximum reflectance (R max ) 70% of the transition

[0168] R 70 =R min +0.7(R max -R min )

[0169] -Inner boundary: 10% of the transition from minimum to maximum reflectance.

[0170] R 10 =R min +0.1(R max -R min )

[0171] - Optical density:

[0172]

[0173] -Background area:

[0174] The area outside the edges of any image element, where the image element is a separate, clearly intentional object that is not connected to other objects.

[0175] -Image area:

[0176] - The area inside the inner boundary.

[0177] -Region of Interest (ROI):

[0178] The region within the defined boundary to be analyzed.

[0179] The following describes the quality properties of large-area graphic images, which can be used to evaluate the quality of printed images:

[0180] a) The quality attributes of large-area graphic images can be defined as follows:

[0181] area > 161mm 2 (=12.7 2 mm 2 )

[0182] οROI minimum dimensions: 12.7mm x 12.7mm (approximately 1 / 2 inch) 2 )

[0183] οROI: Region of Interest.

[0184] b) Large area R min and R max It can be defined as follows:

[0185] οR min [%]: Average reflectance of the background area

[0186]

[0187] n: Number of cells in the x-direction

[0188] m: Number of cells in the y-direction

[0189] Y backgr (x,y): Reflectance coefficient at position (x,y) in the background area.

[0190] οR max [%]: Average reflectance of the image area

[0191]

[0192] n: Number of cells in the x-direction

[0193] m: Number of cells in the y-direction

[0194] Y image (x,y): Reflectance coefficient at position (x,y) in the image region.

[0195] c) Large-area darkness measurement can be defined as follows:

[0196] ο Large area measurement [1 / 1%]:

[0197] • The region of interest (ROI) is completely contained within the inner boundary (R). 10 )Inside

[0198] Minimum ROI size: 12.7mm x 12.7mm

[0199]

[0200] d) The darkness measurement of a large area background can be defined as follows:

[0201] Background darkness measurement [1 / %):

[0202] • The region of interest (ROI) is completely contained within the background area.

[0203] • The ROI should be at least 500 μm away from the outer boundary (R 10 )

[0204] Minimum size: 12.7mm x 12.7mm

[0205]

[0206] e) Granularity [%] can be defined as follows:

[0207] Unexpected, microscopic, but visible, non-periodic brightness fluctuations occurred.

[0208] ο ROI in the image region

[0209] Minimum size: 12.7mm x 12.7mm

[0210] Prepare the test matrix:

[0211] Selecting a regional wavelet filter (Welvet filter) to remove boundaries, dividing the area into 9x9 blocks (h_min = w_min = 1.27mm) with a 0.635mm margin, and measuring the 60x60 reflectance particle size within each block, the program may include the following steps:

[0212] Select the region of interest in the image.

[0213] ο Measure the reflectance R(x,y), G(x,y), B(x,y) of 360,000 pixels.

[0214] Convert R, G, and B values ​​to CIE values.

[0215] o Wavelet transform (16th-order Daubechies wavelet and n=6 level) zero detail components,

[0216] ο Zero approximate component,

[0217] Apply inverse wavelet transform,

[0218] Remove 0.635mm from each side.

[0219] Divide the image into 9x9 tiles.

[0220] ο Calculate the reflection variance,

[0221]

[0222] Assuming each tile is 60x60 = 3600 pixels

[0223] ο Calculate granularity measurement

[0224] Assuming there are 9x9 = 81 tiles

[0225]

[0226] f) The pattern [%] can usually be determined according to the grain size measurement procedure shown above, which doubles the grain size (120x120 pixels) compared to the grain size, but is not a 16th-order and n=6-level Daubechies wavelet transform, but performs a 9th-order and 16th-order Daubechies wavelet transform.

[0227] h) Background-independent markers [%] can be defined and determined as follows:

[0228] Select a ROI (minimum size 12.7 x 12.7 mm) in the background, at least 500 μm from the outer boundary.

[0229] Use edge threshold

[0230] ·Find R <R 40 The marker m for connecting pixels

[0231] • Mark the area A m and total area A EM Calculated as σ(A) m )

[0232] ·min(A m = 7.850μm 2

[0233] ·min(A m = 7.850μm 2

[0234]

[0235] i) Large-area void metric can be defined as follows:

[0236] Select the ROI (minimum size 12.7mm x 12.7mm) in the image area.

[0237] Using edge thresholds to

[0238] Find R>R 40 The marker m for connecting pixels

[0239] · Calculate the total area A of the marked area v

[0240] ·min(A m = 7.850μm 2

[0241]

[0242] j) Striping – defined as “the appearance of one-dimensional stripes in a region that should be uniform” – can be determined as follows:

[0243] Select a ROI of 150mm x 100mm within the image area.

[0244] ο Measure the reflectance of R(x), G(x), and B(x).

[0245] For each R, G, B, take the average value in the y-direction.

[0246] Convert R, G, B to CIE.

[0247] οCalculate L * ,

[0248] ο will L * Modulated as L'(x),

[0249] ο divide L'(x) into three frequency channels.

[0250] ο Discard 5mm on each side of each channel,

[0251] Find local extrema based on absolute values, and collect local extrema using tent pole summation.

[0252] ο Calculate the striping metric:

[0253]

[0254] The following describes the character and line image quality attributes, which can be used to evaluate the quality of printed images:

[0255] k) Character and line images R min and R max It can be determined as follows:

[0256] ο Measure three or more locations in the horizontal and vertical directions within the image and background areas.

[0257] ο Determine R min [%] and R max [%] as average

[0258] l) The line width L [μm] can be defined and determined as follows:

[0259] Choosing ROI makes

[0260] • ROI includes lines and background

[0261] • Height ≥ 5mm

[0262] Width ≥ (line width) + 2mm

[0263] • Remove particles with a diameter ≥100μm for measurement

[0264] ο Calculate the edge threshold R 40

[0265] The line width [μm] is calculated as the average distance between the right and left edges.

[0266]

[0267] m) The darkness of a character can be defined and determined as follows:

[0268] ο Line width selection ROI

[0269] οCalculate R 25

[0270] οCalculate R 25 Average line image density in

[0271]

[0272] ο Calculate character darkness measure

[0273]

[0274] The ambiguity can be defined and determined as follows:

[0275] ο Line width selection ROI

[0276] οCalculate R 10 and R 70 average distance between

[0277] οR 25 Computer average line image density

[0278]

[0279] ο Calculate the average ambiguity B1

[0280]

[0281] ο) Roughness (reggedness) [μm] can be defined as the geometrical deformation appearance of an edge from its ideal position, and is determined as follows:

[0282] ο Line width selection ROI

[0283] Fit the straight line to R 40 threshold

[0284] ο Calculate the standard deviation of the fitted residuals (perpendicular to the straight line).

[0285] Roughness is the average of the left and right standard deviations.

[0286]

[0287] p) Character spacing can be defined and determined as follows:

[0288] Definition: "The appearance of uniformity of darkness within the boundaries of a line segment, character image, or other glyph image."

[0289] Use XOR or OR.

[0290] Compare two images and only show the areas that have changed.

[0291] Character spacing [%] can be determined through the following steps:

[0292] Select the ROI (text and background).

[0293] οCalculate R 25 And convert it to binary.

[0294] To remove fine scattering,

[0295] Fill all the holes.

[0296] ο Calculate exclusive OR.

[0297] Fill the holes in the character design.

[0298] ο Calculate the area A4 of the image.

[0299] ο Calculate the OR image and image area A5,

[0300] The character spacing is calculated as A4 / A5.

[0301] q) Character wrapping region-independent tags can be defined and determined as follows:

[0302] Select a ROI that is 10mm long (at least 0.5mm wide) containing the characters and background.

[0303] οCalculate R 40 And set as a threshold

[0304] ο Calculate the 500μm scattering area A at the edge of the character. EM and total area A CF

[0305] οCalculate CSEAM

[0306]

[0307] r) The haze of the character wrapping area can be defined and determined as follows:

[0308] Select a ROI that is 10mm long (at least 0.5mm wide) containing the characters and background.

[0309] ο Calculate the average reflectance R of the area surrounding the character HC

[0310] ο Calculate the background reflectance coefficient R BKG

[0311] ο Calculate CSAH as

[0312]

[0313] In summary, the large-area image quality attributes (left side) represent the following characteristics (right side):

[0314]

[0315] The character and line quality attributes (left) represent the following characteristics (right):

[0316]

[0317] When determining the overall metric or parameter(s) used to represent the image quality, each of the different metrics described above can be taken into account. Different metrics could be weight, etc., to account for different quality requirements of customers for the printed product.

[0318] Figure 2 The steps of a method according to an embodiment of the present invention are shown.

[0319] In detail, Figure 2 In step T1, parameters defined, provided, or obtained before or after image printing (P1a, P1b, P1c, P2-P6) are sent to database 2 for storage. Database 2 can conceal the obtained data in a format suitable for storage in the database. A corresponding analysis device 3, which may be database 2 itself or [other components], is also present. Figure 2 Another external computing device can request all or specific data for one or more printed products. This external computing device 3 can act as an analysis device for determining the correlation between different data points of the same or different printed images, substrates, etc. This external computing device 3 can use any software, such as... JMP, Python, and R, or any other suitable programming language.

[0320] The generation result representing the determined correlation is sent to the correction calculation device 4 in step T3, which can also be instantiated within the external calculation device 3. The correction calculation device 4 provides actual correction parameters for the printer configuration parameters and / or the printing parameters based on the comparison, minimizing the difference between the previous and the actual correction parameters.

[0321] In a further step T4, the calibration parameters and / or updated printer configuration parameters and / or updated printing parameters are sent to the printer P2 and / or to the ink supply device corresponding to step P1c via the corresponding interface 5 in a further step T5.

[0322] Figure 1 and Figure 2 Specifically, it illustrates image capture, a stable stream of optical property data that "converts" the captured image into a printed image, analysis and determination of correlations within the data, and determination of correction parameters based on these correlations to optimize the printing process to meet customer requirements. This enhances the actual product and allows for the development of future products.

[0323] Figure 3 The steps of a method according to an embodiment of the present invention are shown.

[0324] In detail, Figure 3 The steps of a method for printing an image on a substrate, preferably glass, ceramic, or glass-ceramic, are shown.

[0325] The method includes the following steps:

[0326] The first step S1 includes providing image template data of the image to be printed by an image providing computing device.

[0327] A further step S1' involves analyzing the image template data by identifying image components of the image. The analysis includes dividing the image into image characters such as lines, large areas, etc. The identified image characters form the basis for providing printing parameters for each image character. As previously described, such image characters are, in particular, areas of the image template that are substantially different in their visual appearance, such as characters, lines, and / or large areas. In addition to image quality attributes corresponding to or associated with each image component, the thus identified characters then form the basis for providing, adapting, and / or adjusting printing parameters for each identified image character.

[0328] A further step S2 includes providing a substrate for printing the image thereon via a substrate supply device.

[0329] The further step S3 includes supplying ink for printing the image by an ink supply device.

[0330] Further step S4 includes printing the image on the substrate using the image template data, based on the printing parameters of the printer operated using printer configuration parameters, and using a printing program, preferably an inkjet printing program, with the ink.

[0331] A further step S5 includes capturing the printed image on the substrate using one or more image capture devices and providing capture image data of the captured image.

[0332] A further step S6 includes analyzing the captured image data by an analysis computing device using an analysis program, the analysis program including:

[0333] The first sub-step S6a provides definition parameters for defining at least one region of interest (ROI).

[0334] A further sub-step S6b includes determining the at least one ROI within the captured image data of the captured image based on the provided defined parameters.

[0335] A further sub-step S6c includes identifying at least one image component within the at least one ROI.

[0336] The further sub-step S6d includes determining at least one image metric for the at least one ROI, and

[0337] A further sub-step S6e includes associating the at least one image metric with the at least one image component.

[0338] A further step S7 includes associating the identified at least one image component in the image template data with the at least one identified image component of the at least one ROI associated with the at least one image metric.

[0339] Further step S8 includes selecting one or more printer configuration parameters and / or printing parameters for calibration, preferably based on at least one image metric and / or at least one image component.

[0340] Step S8 may include the following steps:

[0341] –S8a: Calculates the impact value associated with the enhancement or degradation of at least one image metric for each of the multiple printer configuration parameters and / or printing parameters.

[0342] –S8b: Select one or more printer configuration parameters and / or printing parameters based on one or more influence values.

[0343] Preferably, one or more of the highest impact values ​​are used to select one or more printer configuration parameters and / or printing parameters.

[0344] A further step S9 includes, based on an optimization calculation procedure, using the at least one image metric to calculate at least one actual correction parameter for the selected printer configuration parameters and / or the selected printing parameters, wherein the at least one actual correction parameter is specific to the image components.

[0345] Figure 4 A system according to an embodiment of the present invention is illustrated schematically.

[0346] In detail, Figure 4 A system 1 for printing images on a substrate, preferably glass, ceramic, or glass-ceramic, is shown.

[0347] System 1 includes:

[0348] - An image providing computing device 10, such as a computer, for providing image data for an image to be printed.

[0349] - Image analysis device 10', used to analyze the image template data by identifying the image components of the image.

[0350] - A substrate supply device 11, such as a conveyor belt, for providing a substrate for printing images thereon, and

[0351] - Ink supply device 12, for providing ink for printing the image.

[0352] Image providing computing device 10 and image analysis device 10', substrate supply device 11 and ink supply device are all connected to printer 13, which is adapted to operate using printer configuration parameters, and based on the printing parameters, print the image on the substrate using a printing program, preferably an inkjet printing program, and using the ink on the image template data.

[0353] During printing and / or after the image has been printed onto the substrate, one or more image capturing devices 14 capture the partially or fully printed image on the substrate and provide electronic data of the optically captured image, the captured image data. The provided electronic data is sent to database 2 for storage, so that the analysis and computing device 15a can request corresponding data from database 2. Therefore, the image capturing device 14 is connected to the database 2.

[0354] The thermal fixing apparatus 17a can provide thermal fixing of the printing substrate. The corresponding thermal fixing measuring apparatus 17b can measure fixing characteristics, such as the optical, mechanical and / or optical properties of the printing substrate.

[0355] The analysis computing device 15a is also connected to the database 2 for analyzing the captured image data using an analysis program adapted to perform the following steps:

[0356] Provide definition parameters for defining at least one Region of Interest (ROI).

[0357] Based on the provided defined parameters, determine at least one ROI within the captured image data.

[0358] ο Identify at least one image component in the at least one ROI,

[0359] For the at least one ROI, determine at least one image metric, and

[0360] The at least one image metric is associated with the at least one image component.

[0361] and relation calculation device 15b, for associating the identified at least one image component in the image template data with the at least one identified image component of the at least one ROI associated with the at least one image metric. Devices 15a and 15b form according to Figure 2 External computing device 3.

[0362] The results are sent to the correction calculation device 16 via the selection device 18. The selection device 18 is adapted to select one or more printer configuration parameters and / or printing parameters for correction, preferably based on at least one image metric and / or at least one image component. The correction calculation device 16 is adapted to calculate, based on an optimization calculation program, at least one actual correction parameter for the selected printer configuration parameter and / or the selected printing parameter using the at least one image metric, wherein the at least one actual correction parameter is specific to the image component. The selection device 18 may, for example, select those one or more printer configuration parameters and / or printing parameters having one or more highest influence values ​​for correction.

[0363] The calibration calculation device 16 can also be connected to the database 2, which stores the calculated calibration parameters. The selection device 18 can also be connected to the database to obtain parameter selection data, such as indicating some effect on image measurement, previously selected parameters, etc. The calibration calculation device 16 can send the corresponding calibration parameters to the printer 13 for use when printing images on other substrates. If stored in the database 2, the printer 13 itself can request calibration parameters from the database 2. For example, different calibration parameters for different images and different substrates can be stored in the database 2. Then the printer 13 itself can request calibration parameters when printing is required. Alternatively, the image providing calculation device 10, the image analysis device 10', the substrate supply device 11, and the ink supply device 12 can each request their own calibration parameters from the database 2 and feed them to the printer 13.

[0364] Figure 5 The steps of a method according to an embodiment of the present invention are shown.

[0365] In detail, Figure 5 A method 100 for printing an image on a substrate is shown, preferably glass, ceramic, or glass-ceramic.

[0366] Reference numeral 101 indicates that an image template is provided. This image template includes image components, such as a photograph including points, lines, and areas, and has a certain resolution, etc. The image components of the image template are determined in step 105. Furthermore, in step 102, an application or printing technology and corresponding system, such as a screen printing system, an inkjet printer, etc., are provided and applied to a substrate.

[0367] To perform the printing, more parameters and materials can be specified. In step 103a, colors and expandable materials are provided, including, for example, screen printing paste, ink, pigment data, glass frit data, solvents, adhesives, etc. Furthermore, in step 103b, parameters of the application system are provided, such as frequency, travel speed, etc. Even in step 103c, a substrate on which the image will be printed is provided, and parameters specifying the substrate are provided, such as substrate material, substrate pretreatment, substrate cleaning, substrate form, such as panes, tubes, etc. The provided parameters and materials are used for printing in step 102.

[0368] The result 104 of the printing process is a product, such as a glass cooktop. This product is inspected in step 106, and based on this inspection, a quality metric for the printed image used on the substrate, particularly for the image components of the printed image, is determined. In step 107, a setpoint / actual value comparison based on the quality metric is performed, and corresponding deviations are also determined using image template data. In step 103b, these deviations are used to adapt the parameters of the application system. The quality metric for an image component describes the quality of a specific area of ​​the image or image component. All image component-specific quality metrics together form the overall quality of the image.

[0369] In parallel with the setpoint / actual value comparison in step 107, data is collected in step 108, for example, by systematically changing the operating parameters of the application system provided in step 103b based on the identified image components and image component-specific image quality metrics determined using the Design of Experiments (DoE). Data collection can also be performed by an automated measurement system at the printer. Then, changing the operating parameters is typically not possible. However, a large amount of data can be obtained.

[0370] In a further step 109, the collected data is specifically filtered for the quality metric to determine the parameter that has the greatest impact on the quality metric.

[0371] Optionally, in step 110, the collected data may be filtered, for example, to provide data suitable for generating a model, such as through mathematical modeling, and to generate, for example, a linear model, a polynomial-based model, or a model using a neural network, etc. In other words, step 110 derives a model that models the relationship between image quality metrics for different image components and the application and process parameters of steps 103a-103b and 101.

[0372] Now, in step 111, one or more optimization procedures are used to optimize the results of step 109 and / or the model generated in step 110. The results of the optimization process are performed based on the determined image components (step 112). Then, for example, the results of step 112, particularly the parameters for optimization to achieve better image quality, are included in the provided image template (step 101) or in the applied parameters (step 103b).

[0373] In other words, information about image quality and image components can be used to select one or more optimization algorithms and to determine the optimal operating point for the application system. Once the optimal operating point is determined, the printing process is adapted accordingly by adjusting the image template data or parameters related to the printing process. Furthermore, the printing ink and / or substrate can be adapted.

[0374] For example, an image template is provided along with an initial set of printing parameters. When using the method described above, the image template and printing parameters are optimized with respect to different image components that result in enhanced print quality of the image printed on the substrate. Once the corresponding optimal image component-specific printing parameters have been determined, further printing procedures can be performed as follows: First, the image to be printed is analyzed for each image component. For each image component, a print job is generated: for example, first, the image component "line" is printed using the corresponding set of printing parameters for that image component, then the image component "dot" is printed using the corresponding set of printing parameters for that image component, and so on. Of course, other methods are also possible.

[0375] Steps 101-112 above can be repeated. This allows, for example, the following operations: the embodiment enables the generation of models that produce different image components with different image metrics, and these components are correlated with one or more application parameters along with their behavioral or functional relationships when one or more of these application parameters or image template parameters are changed. One advantage here might be that future prints will have higher image metrics. Additionally, slow degradation of the printer's printhead, etc., can be compensated for, and so on.

[0376] All collected or generated data may be stored (step 113) and provided, if needed, on request, or automatically, to any of the devices performing steps 101-112.

[0377] In summary, at least one embodiment of the present invention may have at least one of the following advantages and / or provide:

[0378] - Associate customer / customer specifications with printing program parameters.

[0379] - Easily and accurately identify correlations in the captured data by analyzing the data.

[0380] - Provides an enhanced printing process, resulting in higher quality printed products.

[0381] - Centralized data storage and data delivery

[0382] - Improve the flexibility of products to be printed and meet customer requirements.

[0383] - Higher quality printing products

[0384] - Scalability; suitable for mass production of printed products.

[0385] - Fast and efficient printing, with a low number of products failing to meet predetermined quality requirements.

[0386] - Easily comparable quality results for printed products.

[0387] Benefiting from the teachings presented in the foregoing description and the accompanying drawings, those skilled in the art will conceive of many modifications and other embodiments of the invention set forth herein. Therefore, it should be understood that the invention is not limited to the specific embodiments disclosed, and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terminology is used herein, it is used in a general and descriptive sense only and not for limiting purposes.

[0388] List of reference numerals

[0389] 1 System

[0390] 2. Database

[0391] 3 External computing device

[0392] 4. Calibration Calculation Device

[0393] 5 Interfaces

[0394] 10. Image provided by computing device

[0395] 10' Image Analysis Device

[0396] 11. Substrate supply device

[0397] 12 Ink supply device

[0398] 13 Printers

[0399] 14 Image capture device

[0400] 15a Analytical Computing Device

[0401] 15b Comparison Calculation Device

[0402] 16. Calibration Calculation Device

[0403] 17a Thermal fixing device

[0404] 17b Thermal fixing measuring device

[0405] 18 Selection device

[0406] Steps P1a–P1c

[0407] Steps P2-P6

[0408] Steps T1–T5

[0409] Steps S1–S9

Claims

1. A method for printing an image on a substrate, wherein the substrate is a glass, ceramic, or glass-ceramic substrate. The method includes the following steps: - Image template data of the image to be printed is provided by the image providing computing device (10); - Provides an initial set of printing parameters; - Analyze the image template data by identifying the image components of the image; - A substrate for printing the image thereon is provided by a substrate supply device (11); - Ink for printing the image is supplied by the ink supply device (12); - Provides an initial set of printing parameters for the identified image components; - Based on the printing parameters of the printer (13) operated using printer configuration parameters, the printing program uses the ink to print the image on the substrate using the image template data and initial printing parameters; - Capture an image printed on the substrate by one or more image capture devices (14) and provide capture image data of the captured image; - The captured image data is analyzed using an analysis program by an analysis computing device (15a), the analysis program including: ○ Provide definition parameters for defining at least one Region of Interest (ROI). ○ Determine the at least one ROI within the captured image data based on the provided defined parameters. ○ Identify at least one image component in the at least one ROI. For each ROI, at least one image metric is determined. ○ Associate the at least one image metric with the at least one image component, providing a specific image metric for each image component; - Associate at least one identified image component in the image template data with at least one identified image component of the at least one ROI associated with the at least one image metric; - Select one or more printer configuration parameters and / or printing parameters for correction based on at least one image metric and / or at least one image component; - Based on the optimization calculation procedure, at least one actual correction parameter of the selected printing parameters is calculated using the at least one image metric, wherein the at least one actual correction parameter is specific to the image component; - Calculate optimized printing parameters specific to the image components based on the at least one actual correction parameter specific to the image component; - Use the aforementioned optimized printing parameters to print images on other glass, ceramic, or glass-ceramic substrates.

2. The method according to claim 1, wherein, The printing program is an inkjet printing program.

3. The method according to claim 1 or 2 further comprises the steps of: thermally fixing the printed image by means of a thermal fixing device (17a), determining at least one of optical, chemical and mechanical properties of the thermally fixed image by means of a thermal fixing measuring device (17b), and providing data of the properties to the analysis procedure by means of the thermal fixing measuring device (17b).

4. The method according to claim 1 or 2, wherein, The defined parameters and the image metrics are based at least on ISO / IEC 24790:2017(E) or a later version.

5. The method according to claim 1 or 2, wherein, At least one of the image metrics, the captured image data, the image template data, the correction parameters, and the selection parameters is stored in a storage device and / or in a portable storage medium.

6. The method according to claim 1 or 2, wherein, The optimization calculation program is executed based on a machine learning program.

7. The method according to claim 6, wherein, The optimization calculation program is executed using a neural network.

8. The method according to claim 1 or 2, wherein, All steps are repeated for multiple substrates on which the same image and / or at least one of the same image components are printed.

9. The method according to claim 1 or 2, wherein, To determine the image metric, wavelet transform and / or Fourier transform procedures are performed on the data of the ROI.

10. The method according to claim 1 or 2, wherein, A single overall metric is determined for the at least one image metric to determine image quality, and the single overall metric is a weighted sum of at least two metrics.

11. The method according to claim 1 or 2, wherein, The steps for selecting one or more printer configuration parameters and / or printing parameters for calibration include the following: - Calculate the impact value associated with the enhancement or degradation of at least one image metric for each of the multiple printer configuration parameters and / or printing parameters. - Select one or more printer configuration parameters and / or printing parameters based on one or more impact values.

12. The method according to claim 11, wherein, One or more of the highest impact values ​​are used to select one or more printer configuration parameters and / or printing parameters.

13. The method according to claim 11, wherein, The multiple printer configuration parameters and / or printing parameters are obtained by repeating all the steps multiple times, including the following steps: - By comparing the at least one image metric with a previously determined corresponding metric and / or one or more predetermined corresponding thresholds using a comparison computing device, and - Based on the comparison performed by the calibration calculation device, calibration parameters are provided for the printer configuration parameters and / or the printing parameters, such that the differences between the previous and the calibration parameters are minimized.

14. The method according to claim 1 or 2, wherein, A model is generated based at least on selected printer configuration parameters and / or printing parameters, the model describing the relationship between the printer configuration parameters and / or printing parameters and at least one image metric of at least one image component.

15. The method according to claim 14, wherein, The model was generated using artificial intelligence.

16. The method of claim 14, wherein, The model was generated using a machine learning program.

17. The method of claim 14, wherein, The model was generated using a deep learning program.

18. The method according to claim 14, wherein, The model was generated using a neural network.

19. A system for printing an image on a substrate, said substrate being glass, ceramic, or glass-ceramic substrate, said system comprising: - Image providing computing device (10) for providing image template data for an image to be printed; - A device for providing an initial set of printing parameters; - Image analysis device (10') for analyzing the image template data by identifying the image components of the image; - Substrate supply device (11), for providing a substrate for printing the image thereon, - Ink supply device (12) for supplying ink for printing the image; - A device for providing an initial set of printing parameters for the identified image components; - A printer (13) adapted to use a printing program to print the image on the substrate using the ink based on the printing parameters of the printer, which is operated using printer configuration parameters; - One or more image capturing devices (14) for capturing printed images on the substrate and providing captured image data of the captured images; - Analysis computing device (15a), used to analyze the captured image data using an analysis program, adapted to perform the following steps: ○ Provide definition parameters for defining at least one Region of Interest (ROI). ○ Determine at least one ROI within the captured image data based on the provided defined parameters. ○ Identify at least one image component in the at least one ROI. For the at least one ROI, determine at least one image metric, and ○ Associate the at least one image metric with the at least one image component, providing a specific image metric for each image component; - Relationship calculation device (15b) for associating at least one identified image component in the image template data with at least one identified image component of the at least one ROI associated with the at least one image metric; - Selection device (18) for selecting one or more printer configuration parameters and / or printing parameters for correction based on at least one image metric and / or at least one image component; A correction calculation device (16) is used to calculate at least one actual correction parameter of a selected printing parameter based on an optimization calculation program using the at least one image metric, wherein the at least one actual correction parameter is specific to the image component; It also includes a storage device for storing at least one of the image measurement, the captured image data, the image template data, the correction parameters, and the selection parameters; An optimization device is used to calculate optimized printing parameters specific to the image components based on the at least one actual correction parameter specific to the image component.

20. The system of claim 19, wherein the printing program is an inkjet printing program.

21. The system of claim 19, wherein the storage device is a database and / or a portable storage medium.

22. The system according to any one of claims 19 to 21, further comprising a thermal fixing device (17a) for thermal fixing a printed image and a thermal fixing measurement device (17b) for determining at least one of optical, chemical and mechanical properties of the thermally fixed image and providing data of said properties to the analysis program, and / or further comprising a machine learning computing device connected to said storage device and / or storage medium, acting as a relational computing device (15b) and / or a correction computing device (16) and adapted to perform machine learning.

23. The system of claim 22, wherein the machine learning computing device is adapted to use a neural network.

24. The system of claim 22, wherein the thermal fixing measuring device (17b) is adapted to perform thermal stress analysis.

25. The system according to any one of claims 19 to 21, wherein, The substrate supply device (11) provides a substrate in the form of a glass object, a ceramic object, or a glass-ceramic object.

26. A non-tangible computer-readable medium storing a program, the program comprising computer-readable instructions that cause a computer or computer network to perform a method of printing an image on a substrate, said substrate being glass, ceramic, or a glass-ceramic substrate. The method includes the following steps: - Image template data of the image to be printed is provided by the image-providing computing device; - Provides an initial set of printing parameters; - Analyze the image template data by identifying the image components of the image; - A substrate for printing the image thereon is provided by a substrate supply device; - Ink for printing the image is supplied by an ink supply device; - Provides an initial set of printing parameters for the identified image components; - Based on the printer's printing parameters operated using printer configuration parameters, the printing program uses the ink to print the image on the substrate using the image template data and initial printing parameters; - Capture a printed image on the substrate using one or more image capture devices, and provide captured image data of the captured image; - The captured image data is analyzed using an analysis program via an analysis computing device, the analysis program comprising: ○ Provide definition parameters for defining at least one Region of Interest (ROI). ○ Determine at least one ROI within the captured image data based on the provided defined parameters. ○ Identify at least one image component in the at least one ROI. For the at least one ROI, determine at least one image metric, and ○ Associate the at least one image metric with the at least one image component, providing a specific image metric for each image component; - Associate at least one identified image component in the image template data with at least one identified image component of the at least one ROI associated with the at least one image metric; - Select one or more printer configuration parameters and / or printing parameters for correction based on at least one image metric and / or at least one image component; - Based on an optimized calculation procedure, at least one actual correction parameter of the selected printing parameters is calculated using the at least one image metric, wherein the at least one actual correction parameter is specific to the image component; - Calculate optimized printing parameters specific to the image components based on the at least one actual correction parameter specific to the image component; - Use the aforementioned optimized printing parameters to print images on other glass, ceramic, or glass-ceramic substrates.

27. The computer-readable medium of claim 26, wherein, The printing program is an inkjet printing program.

Images