Halftone dot generation method and apparatus based on amplitude-modulated screening, and device

Abstract

The present invention relates to the field of image reproduction. Provided are a halftone dot generation method and apparatus based on amplitude-modulated screening, and a device. The method comprises: acquiring dot threshold matrices of all single dot shapes required in a target halftone dot image; respectively performing binarization processing on the dot threshold matrices of all the dot shapes by means of preset thresholds, so as to generate corresponding dot table sets, wherein each dot table set comprises multi-level binarized matrices; on the basis of the number of dot threshold matrices of the dot shapes, performing level-based interval division processing on the binarized matrices of each dot table set, and performing matrix extraction processing after the level-based interval division processing, so as to obtain a plurality of target sub-interval matrices; and performing recombination processing on the plurality of target sub-interval matrices in an order of continuous levels, so as to obtain a target halftone dot table. The solution of the present invention implements screening processing for a plurality of dots of different dot shapes, thereby improving the image quality during amplitude-modulated screening processing.

Description

A method, apparatus and equipment for generating halftone dots based on amplitude modulation halftone. Technical Field

[0001] This invention relates to the field of image reproduction, and specifically to a method, apparatus, and device for generating halftone dots based on amplitude modulation halftone. Background Technology

[0002] In the printing industry, halftone dots are the basic unit of image reproduction. The shape of the halftone dot directly affects whether the printed material can accurately reproduce the tonal and color variations of the original. Traditional halftone dot shapes include round, square, oval, diamond, and linear. Different shapes of halftone dots exhibit different patterns of change during image reproduction, resulting in different reproduction effects. Halftone dots are generally classified into two types according to the halftone method: amplitude modulation (AM) halftone dots and screen modulation (SMT) halftone dots. Among them, AM halftone dots are currently the most widely used type. In AM halftone dots, the center is fixed, and small dots diffuse outward from the center in a regular pattern, concentrating and distributing to form halftone dots. The diffusion pattern determines the shape of the halftone dot and the halftone angle. AM halftone dots are generally generated using traditional halftone dot generation methods. Traditional halftone dot generation methods have the following problems: they cannot represent the subtle levels of an image in both highlights and shadows; small dots in highlights are easily lost; and in shadows, as the dot area increases, dots tend to overlap, creating jumps in tonal gradations. Furthermore, they cannot handle complex dot shapes or mixtures of different dot shapes. A single dot shape may excel in one aspect, but it cannot surpass other dot shapes in other aspects. Therefore, while a single dot shape may be useful in traditional printing, it is clearly insufficient for other applications, such as anti-counterfeiting or more complex printing applications involving partial halftone dotting. Summary of the Invention

[0003] This invention provides a method, apparatus, and device for generating halftone dots based on amplitude modulation screening, which solves the problems of existing amplitude modulation screening that cannot represent the subtle details of the image in the highlights and shadows, and cannot screen mixed dots of different shapes.

[0004] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0005] Embodiments of the present invention provide a method for generating halftone dots based on amplitude modulation halftone, comprising:

[0006] Obtain the dot threshold matrix for all individual halftone dot shapes required within the target halftone dot image;

[0007] By setting a preset threshold, the dot threshold matrix of all mesh shapes is binarized to generate a corresponding dot table set. Each dot table set includes binarized matrices of multiple levels.

[0008] Based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is subjected to hierarchical interval partitioning, and matrix extraction is performed after hierarchical interval partitioning to obtain multiple target sub-interval matrices.

[0009] The target sub-interval matrices are recombined in a sequential order to obtain the target halftone dot table.

[0010] Optionally, by using a preset threshold, the dot threshold matrix of all mesh shapes is binarized to generate a corresponding dot table set, including:

[0011] Determine the maximum number of levels corresponding to the threshold matrix of each point;

[0012] Based on the maximum number of layers and the preset threshold, the dot threshold matrix of each mesh shape is binarized to obtain the corresponding binarized matrix.

[0013] Based on the corresponding binarized matrix, generate the corresponding set of dot tables.

[0014] Optionally, based on each maximum number of layers and a preset threshold, the dot threshold matrix of each mesh shape is binarized to obtain the corresponding binarized matrix, including:

[0015] Based on each maximum number of layers and a preset threshold, a corresponding binarized matrix is ​​obtained by comparing the preset threshold with the value m of each element in the dot threshold matrix. During the comparison, if the preset threshold is greater than the value of the current element, the value of the current element in the corresponding binarized matrix is ​​0; otherwise, the value of the current element is 255. Here, 0 ≤ m ≤ N-1, and N is the maximum number of layers.

[0016] Optionally, based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is subjected to hierarchical interval partitioning, and matrix extraction is performed after hierarchical interval partitioning to obtain multiple target sub-interval matrices, including:

[0017] Based on the number of dot threshold matrices in the mesh, the binarized matrix of each dot table set is divided into hierarchical intervals to obtain the target hierarchical interval corresponding to the binarized matrix of each dot table set.

[0018] The target hierarchical interval is subjected to matrix extraction processing by preset rules to obtain multiple target sub-interval matrices.

[0019] Optionally, based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is divided into hierarchical intervals to obtain the target hierarchical intervals corresponding to the binarized matrix of each dot table set, including:

[0020] The width of each target level interval is determined by a preset function f(i) = c × i + d, where c and d are preset constants and i is the interval number;

[0021] Determine the total hierarchical interval [0, L-1] of the binarized matrix of the current dot matrix set, where L is the total number of levels of the binarized matrix of the previous dot matrix set;

[0022] Based on the number of dot threshold matrices and the width of the target level interval, the total level interval [0, L-1] of the binarized matrix of the current dot table set is divided into n target level intervals to obtain the target level interval corresponding to the binarized matrix of the current dot table set, where n is the number of dot threshold matrices.

[0023] Optionally, the target hierarchical interval is subjected to matrix extraction processing according to preset rules to obtain multiple target sub-interval matrices, including:

[0024] Extract all binary matrices corresponding to the i-th target level interval from the i-th dot matrix set, and use them as the target sub-interval matrix.

[0025] Optionally, the multiple target sub-interval matrices are recombinated in a sequential order to obtain a target halftone dot table, including:

[0026] Arrange the target sub-interval matrix in ascending or descending order of hierarchy to obtain the target halftone dot table.

[0027] Embodiments of the present invention also provide a halftone dot generation device based on amplitude modulation halftone, comprising:

[0028] The acquisition module is used to obtain the dot threshold matrix of all single mesh shapes required within the target halftone dot image;

[0029] The processing module is used to binarize the dot threshold matrices of all mesh types according to a preset threshold, generating corresponding dot table sets. Each dot table set includes multiple levels of binarized matrices. Based on the number of dot threshold matrices of each mesh type, the binarized matrices of each dot table set are divided into hierarchical intervals. After the hierarchical interval division, matrix extraction is performed to obtain multiple target sub-interval matrices. The multiple target sub-interval matrices are recombined in a continuous hierarchical order to obtain the target halftone dot table.

[0030] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program is executed by the processor to perform the above-described method.

[0031] Embodiments of the present invention also provide a computer-readable storage medium, comprising: storage instructions that, when executed on a computer, cause the computer to perform the method described above.

[0032] The above-described solution of the present invention has at least the following beneficial effects:

[0033] The halftone dot generation method based on amplitude modulation screening described in this invention obtains the dot threshold matrix of all single mesh types required within the target halftone dot image; using a preset threshold, the dot threshold matrix of each mesh type is binarized to generate corresponding dot table sets, each dot table set including multiple levels of binarized matrices; based on the number of dot threshold matrices for each mesh type, the binarized matrix of each dot table set is divided into hierarchical intervals, and matrix extraction is performed after the hierarchical interval division to obtain multiple target sub-interval matrices; the multiple target sub-interval matrices are recombinated in a continuous hierarchical order to obtain the target halftone dot table. This method enables screening of multiple different mesh types while improving image quality during amplitude modulation screening. Attached Figure Description

[0034] Figure 1 is a flowchart illustrating the halftone dot generation method based on amplitude modulation halftone of the present invention.

[0035] Figure 2 is a schematic diagram of the preset dot matrix of the halftone dot generation method based on amplitude modulation halftone according to the present invention;

[0036] Figure 3 is a schematic diagram of linear dots in the halftone dot generation method based on amplitude modulation halftone of the present invention;

[0037] Figure 4 is a schematic diagram of the circular dots after binarization in the halftone dot generation method based on amplitude modulation halftone in this invention.

[0038] Figure 5 is a schematic diagram of the linear dots after binarization in the halftone dot generation method based on amplitude modulation halftone in this invention.

[0039] Figure 6 is a schematic diagram of the set of circular halftone dots at different levels in the halftone dot generation method based on amplitude modulation halftone in this invention;

[0040] Figure 7 is a schematic diagram of the set of linear dot tables at different levels in the halftone dot generation method based on amplitude modulation halftone of the present invention;

[0041] Figure 8 is a schematic diagram of the target halftone dot table in the halftone dot generation method based on amplitude modulation halftone of the present invention;

[0042] Figure 9 is a schematic diagram of the specific process of the halftone dot generation method based on amplitude modulation screening of the present invention;

[0043] Figure 10 is a block diagram of the halftone dot generation device based on amplitude modulation halftone according to the present invention. Detailed Implementation

[0044] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0045] As shown in Figure 1, an embodiment of the present invention proposes a method for generating halftone dots based on amplitude modulation halftone, including:

[0046] Step 11: Obtain the dot threshold matrix of all single mesh shapes required within the target halftone dot image;

[0047] Step 12: Binarize the dot threshold matrix of all mesh shapes using a preset threshold to generate a corresponding dot table set. Each dot table set includes multiple levels of binarized matrices.

[0048] Step 13: Based on the number of dot threshold matrices in the mesh pattern, perform hierarchical interval partitioning on the binarized matrix of each dot table set, and perform matrix extraction after hierarchical interval partitioning to obtain multiple target sub-interval matrices.

[0049] Step 14: Recombine the multiple target sub-interval matrices in a sequential order to obtain the target halftone dot table.

[0050] In this embodiment, the halftone dot generation method based on amplitude modulation halftone is mainly used to generate a target halftone dot image by performing halftone halftone processing on the target halftone dot table; in this embodiment, the target halftone dot image includes a dot threshold matrix of at least two single mesh shapes, and the shape of the mesh shape includes a circle, a square, an ellipse, a rhombus, or a line.

[0051] The dot threshold matrix of the mesh shape described in step 11 can be expressed as:

[0052] Here, T1 can be designated as the main threshold matrix, and the threshold matrices of other mesh types as auxiliary matrices, where n represents the number of mesh types; u represents the width of the threshold matrix, and v represents the height of the threshold matrix. In this embodiment, the halftone dot generation method based on amplitude modulation screening obtains the threshold matrix of one or more dots with the same parameters, and then converts them into binarized matrices of different levels corresponding to multiple dot table sets. These binarized matrices are then subjected to cross-recombination and other operations such as copying and substitution among multiple dot table sets to finally generate a new mixed dot lookup table, thereby obtaining a new target halftone dot table with different levels of mesh type changes. This achieves screening processing of multiple dots with different mesh types, while improving the image quality during amplitude modulation screening. By using existing simple shape dots (circles)... The method of generating new complex dot shapes (such as square, elliptical, rhomboid, and linear) by extracting and combining different dot matrices of different halftone types at different levels during the dot table assembly stage not only retains the advantages of the original halftone dots, but also effectively avoids or reduces the problems of existing amplitude modulation halftones, such as the inability to represent the subtle details of the image in the highlights and shadows, and the inability to process mixed halftone dots of different shapes. At the same time, by organically combining and calculating dots of various basic shapes, complex dot shapes can be constructed to meet different printing suitability needs. This can better realize the transfer of graphic information from the original to the substrate, and also has unique advantages and new ideas for anti-counterfeiting in printing when combining complex editing and customization of different halftone types.

[0053] In an optional embodiment of the present invention, in step 12, the dot threshold matrices of all mesh types are binarized using a preset threshold to generate corresponding dot table sets, including:

[0054] Step 121: Determine the maximum number of levels corresponding to each point threshold matrix;

[0055] Step 122: Based on the maximum number of layers and the preset threshold, the dot threshold matrix of each mesh shape is binarized to obtain the corresponding binarized matrix;

[0056] Step 123: Generate the corresponding set of dot matrix tables based on the corresponding binarized matrix.

[0057] In an optional embodiment of the present invention, step 122 may include:

[0058] Based on each maximum number of layers and a preset threshold, a corresponding binarized matrix is ​​obtained by comparing the preset threshold with the value m of each element in the dot threshold matrix. During the comparison, if the preset threshold is greater than the value of the current element, the value of the current element in the corresponding binarized matrix is ​​0; otherwise, the value of the current element is 255. Here, 0 ≤ m ≤ N-1, and N is the maximum number of layers.

[0059] In this embodiment, the number of different thresholds in the dot threshold matrix is ​​the maximum number of layers that the dot represented by the dot threshold matrix can be replicated. For a dot threshold matrix of size u×v, the maximum number of layers it represents is N=u*v-1. The preset threshold k∈{0,1,2…N-1} is used to binarize the dot threshold matrix to obtain a dot table set containing N binarized matrices.

[0060] Specifically, step 122 involves comparing the preset threshold k with the value m (0 ≤ m ≤ N-1) of each element in the dot threshold matrix. If k > m, the value of that element in the binarized threshold matrix is ​​0; otherwise, the value of that element is 255. The threshold matrices of n meshes can be represented as follows after K-level binarization:

[0061] Where k∈{0,1,2…N-1};

[0062] Step 123 may include: binarizing the thresholds of each level into matrices, and finally, the set of dot tables after binarizing the threshold matrices of all mesh types is as follows: H1={Tk1|0≤k≤N-1}, H2={Tk2|0≤k≤N-1}…H n ={Tk n |0≤k≤N-1}.

[0063] In an optional embodiment of the present invention, step 13 may include:

[0064] Step 131: Based on the number of dot threshold matrices in the mesh pattern, perform hierarchical interval division processing on the binarized matrix of each dot table set to obtain the target hierarchical interval corresponding to the binarized matrix of each dot table set.

[0065] Step 132: Perform matrix extraction processing on the target hierarchical intervals according to preset rules to obtain multiple target sub-interval matrices.

[0066] In an optional embodiment of the present invention, step 131 may include:

[0067] Step 1311: Determine the width of each target level interval using the preset function f(i) = c × i + d, where c and d are preset constants and i is the interval number;

[0068] Step 1312: Determine the total hierarchical interval [0, L-1] of the binarized matrix of the current dot matrix set, where L is the total number of levels of the binarized matrix of the previous dot matrix set;

[0069] Step 1313: Based on the number of dot threshold matrices of the mesh and the width of the target level interval, divide the total level interval [0, L-1] of the binarized matrix of the current dot table set into n target level intervals to obtain the target level interval corresponding to the binarized matrix of the current dot table set, where n is the number of dot threshold matrices.

[0070] In this embodiment, step 131 may include:

[0071] From H1, H2…H n These network point sets are divided into continuous target hierarchical intervals R1, R2...Rn, corresponding to the set number. The method for dividing these hierarchical intervals is typically as follows:

[0072] The total number of levels can be defined as [0, L-1], where L is the total number of levels. The number of amplitude modulation meshes with different dot shapes is set to n as above. The method for dividing the level interval is as follows: First, the general level interval can be set as [a, b]. The level division algorithm is based on the quantile algorithm under specific conditions. A function f(i) is introduced to represent the width of the i-th interval, thus ensuring that the width of the interval is editable. The specific calculation method is as follows: Let the lower bound of the i-th interval be L. i The upper bound is U i Where i = 1, 2, ..., n, the lower and upper bounds of each partitioned interval can be calculated by accumulating the widths of all previous intervals: Where a is the starting interval value of the level and b is the ending interval value of the level. In this embodiment, f(i) can be a linear function, an exponential function or any other function based on i. In this invention, f(i) is a function that increases linearly with i, set as f(i) = c*i + d, where c and d are constants. This setting allows the width of the interval to increase or decrease proportionally as the level increases.

[0073] Step 132, specifically, involves, after the above-mentioned hierarchical division, assigning H1, H2…H to the corresponding levels. n Taking the matrices from the corresponding hierarchical intervals, we can represent them as follows: The present invention does not require the order of the extracted sub-matrices to be in the same order as the original matrix; the sub-matrix data can be extracted in any order.

[0074] In an optional embodiment of the present invention, step 132 may include:

[0075] Extract all binary matrices corresponding to the i-th target level interval from the i-th dot matrix set, and use them as the target sub-interval matrix.

[0076] In an optional embodiment of the present invention, step 14 may include:

[0077] Arrange the target sub-interval matrix in ascending or descending order of hierarchy to obtain the target halftone dot table.

[0078] In this embodiment, the target sub-interval matrix is ​​combined and arranged to obtain the result that is the same as the original H1, H2…H n A new set of binary halftone matrix H, composed of multiple halftone table sets of the same size, is represented as follows: H = {Hk|0≤k≤N-1}. Given a level k (0≤k≤N-1), the corresponding binary halftone matrix after combination can be retrieved from H by indexing. This matrix comes from the original sets H1, H2…H n A set of matrices in the dataset.

[0079] As shown in Figure 9, the specific implementation process of the halftone dot generation method based on amplitude modulation halftone according to the present invention will be illustrated below with a specific example:

[0080] Assume that the thresholding matrix for all single halftone dots required in the target halftone halftone image is of two types: the thresholding matrix for circular dots (the thresholding matrix for the first halftone dot) and the thresholding matrix for linear dots (the thresholding matrix for the second halftone dot);

[0081] First, the threshold matrices for circular and linear dots are obtained. Here, circular and linear dots with a 75° mesh angle are used, as shown in Figures 2 and 3. Partial data from the corresponding threshold matrices T1 and T2 are as follows:

[0082] Then, using a preset threshold, the dot threshold matrices of all mesh types are binarized to generate corresponding dot tables. Each dot table set includes binarized matrices at multiple levels. Specifically, the value of each element in the dot threshold matrices T1 and T2 is read, normalized to 256 levels, and then binarized using k as the threshold to obtain Tk1 and Tk2 (0≤k≤255). Finally, the binarized data of 256 levels are written into sets H1 and H2 respectively. The form of the binarized matrix of a certain item in H1 or H2 can be represented as the following set, taking p = 237 for binarized matrix T1 and q = 248 for binarized matrix T2. The partial data of its binarized matrix is ​​as follows:

[0083] The corresponding dot patterns are shown in Figures 4 and 5. Similarly, each threshold is traversed from the full [0, 255] interval, and the threshold matrices T1 and T2 are binarized sequentially to obtain the dot matrices of sets H1 and H2 within the [0, 255] interval, as shown in Figures 6 and 7. Then, based on the number of dot threshold matrices in the mesh shape, the binarized matrix of each dot table set is divided into hierarchical intervals, and matrix extraction is performed after the hierarchical interval division to obtain multiple target sub-interval matrices. Specifically, the hierarchical division and matrix extraction of the binarized matrices H1 and H2 are as follows: In this embodiment, because two mesh shapes are used, the interval division calculation is as follows: The full number of levels L is 256, n = 2, so the length of the hierarchical interval c is: c = 256 / 2 = 128. Therefore, two hierarchical intervals are divided, 0-127 and 128-255, and the 0-127 hierarchical interval of set H1 is extracted respectively. All matrices within H2 and all matrices within the 128-255 interval are used as elements for combining new matrix spaces later. Here, the division of intervals and the data taken from which existing dot matrix set within the interval are not limited to the division and extraction methods in this embodiment. The multiple target sub-interval matrices are recombined in a continuous hierarchical order to obtain the target halftone dot matrix table. Specifically, the extracted matrix sets of the two levels are merged to reconstruct a matrix set H with full levels of 0-255. The matrix distribution characteristics are that the 0-127 level interval adopts circular dot matrix integration, and the 128-255 level adopts linear dot matrix. The effect is shown in Figure 8. Thus, a dot matrix table set consisting of a mixture of circular and linear dots is generated, namely the target halftone dot matrix table. This target halftone dot matrix table can be used for subsequent halftone screening operations. By performing halftone screening processing on the target halftone dot matrix table, a target halftone dot image is generated.

[0084] The halftone dot generation method based on amplitude modulation screening described in this invention can construct complex-shaped dots from simple-shaped dots. Compared with traditional dot generation methods, it is simpler and easier to implement. It can generate a combination effect of amplitude modulation dots of arbitrary shapes. By performing cross-recombination operations such as copying and substitution between multiple dot lookup tables through a binarization matrix, a new mixed dot lookup table is finally generated, thereby obtaining new halftone dots with different levels of dot pattern changes. At the same time, the new combined dots generated by this patent can not only maintain the advantages of the original amplitude modulation dots, but also effectively avoid or reduce the shortcomings of the above-mentioned amplitude modulation screening. It also has unique advantages and new anti-counterfeiting encryption technology methods in printing anti-counterfeiting when combining complex editing and customization of different dot patterns.

[0085] As shown in Figure 10, an embodiment of the present invention also provides a halftone image generation apparatus 90, comprising:

[0086] The acquisition module 91 is used to acquire the dot threshold matrix of all single mesh shapes required within the target halftone dot image;

[0087] The processing module 92 is used to perform binarization processing on the dot threshold matrix of all mesh types according to a preset threshold, generating a corresponding dot table set. Each dot table set includes multiple levels of binarized matrices. Based on the number of dot threshold matrices of the mesh type, the binarized matrix of each dot table set is divided into hierarchical intervals. After the hierarchical interval division, matrix extraction processing is performed to obtain multiple target sub-interval matrices. The multiple target sub-interval matrices are recombined in a continuous hierarchical order to obtain a target halftone dot table.

[0088] Optionally, by using a preset threshold, the dot threshold matrix of all mesh shapes is binarized to generate a corresponding dot table set, including:

[0089] Determine the maximum number of levels corresponding to the threshold matrix of each point;

[0090] Based on the maximum number of layers and the preset threshold, the dot threshold matrix of each mesh shape is binarized using a preset method to obtain the corresponding binarized matrix.

[0091] Based on the corresponding binarized matrix, generate the corresponding set of dot tables.

[0092] Optionally, based on each maximum number of layers and a preset threshold, the dot threshold matrix of each mesh shape is binarized to obtain the corresponding binarized matrix, including:

[0093] Based on each maximum number of layers and a preset threshold, a corresponding binarized matrix is ​​obtained by comparing the preset threshold with the value m of each element in the dot threshold matrix. During the comparison, if the preset threshold is greater than the value of the current element, the value of the current element in the corresponding binarized matrix is ​​0; otherwise, the value of the current element is 255. Here, 0 ≤ m ≤ N-1, and N is the maximum number of layers.

[0094] Optionally, based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is subjected to hierarchical interval partitioning, and matrix extraction is performed after hierarchical interval partitioning to obtain multiple target sub-interval matrices, including:

[0095] Based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is divided into hierarchical intervals using a preset partitioning method to obtain the target hierarchical intervals corresponding to the binarized matrix of each dot table set.

[0096] The target hierarchical interval is subjected to matrix extraction processing by preset rules to obtain multiple target sub-interval matrices.

[0097] Optionally, based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is divided into hierarchical intervals to obtain the target hierarchical intervals corresponding to the binarized matrix of each dot table set, including:

[0098] The width of each target level interval is determined by a preset function f(i) = c × i + d, where c and d are preset constants and i is the interval number;

[0099] Determine the total hierarchical interval [0, L-1] of the binarized matrix of the current dot matrix set, where L is the total number of levels of the binarized matrix of the previous dot matrix set;

[0100] Based on the number of dot threshold matrices and the width of the target level interval, the total level interval [0, L-1] of the binarized matrix of the current dot table set is divided into n target level intervals to obtain the target level interval corresponding to the binarized matrix of the current dot table set, where n is the number of dot threshold matrices.

[0101] Optionally, the target hierarchical interval is subjected to matrix extraction processing according to preset rules to obtain multiple target sub-interval matrices, including:

[0102] Extract all binary matrices corresponding to the i-th target level interval from the i-th dot matrix set, and use them as the target sub-interval matrix.

[0103] Optionally, the multiple target sub-interval matrices are recombinated in a sequential order to obtain a target halftone dot table, including:

[0104] Arrange the target sub-interval matrix in ascending or descending order of hierarchy to obtain the target halftone dot table.

[0105] It should be noted that this device is the same as the method described above. All implementations of the method described above are applicable to the embodiments of this device and can achieve the same technical effect.

[0106] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the above-described method. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0107] Embodiments of the present invention also provide a computer-readable storage medium, comprising: stored instructions, which, when executed on a computer, cause the computer to perform the above-described method. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0108] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0109] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0110] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0111] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0113] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0114] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above-described series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0115] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code for implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps for performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0116] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An AM-based halftone dot generation method, characterized by, include: Obtain the dot threshold matrix for all individual halftone dot shapes required within the target halftone dot image; By setting a preset threshold, the dot threshold matrix of all mesh shapes is binarized to generate a corresponding dot table set. Each dot table set includes binarized matrices of multiple levels. Based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is subjected to hierarchical interval partitioning, and matrix extraction is performed after hierarchical interval partitioning to obtain multiple target sub-interval matrices. The target sub-interval matrices are recombined in a sequential order to obtain the target halftone dot table.

2. The AM-based halftone dot generation method of claim 1, wherein, By using a preset threshold, the dot threshold matrix of all mesh types is binarized to generate a corresponding dot table set, including: Determine the maximum number of levels corresponding to the threshold matrix of each point; Based on the maximum number of layers and the preset threshold, the dot threshold matrix of each mesh shape is binarized to obtain the corresponding binarized matrix. Based on the corresponding binarized matrix, generate the corresponding set of dot tables.

3. The AM-based halftone dot generation method of claim 2, wherein, Based on the maximum number of layers and the preset threshold, the dot threshold matrix of each mesh shape is binarized to obtain the corresponding binarized matrix, including: Based on each maximum number of layers and a preset threshold, a corresponding binarized matrix is ​​obtained by comparing the preset threshold with the value m of each element in the dot threshold matrix. During the comparison, if the preset threshold is greater than the value of the current element, the value of the current element in the corresponding binarized matrix is ​​0; otherwise, the value of the current element is 255. Here, 0 ≤ m ≤ N-1, and N is the maximum number of layers.

4. The AM-based halftone dot generation method of claim 1, wherein, Based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is subjected to hierarchical interval partitioning. After hierarchical interval partitioning, matrix extraction is performed to obtain multiple target sub-interval matrices, including: Based on the number of dot threshold matrices in the mesh, the binarized matrix of each dot table set is divided into hierarchical intervals to obtain the target hierarchical interval corresponding to the binarized matrix of each dot table set. The target hierarchical interval is subjected to matrix extraction processing by preset rules to obtain multiple target sub-interval matrices.

5. The AM-based halftone dot generation method of claim 4, wherein, Based on the number of dot threshold matrices in the mesh pattern, the binarized matrix of each dot table set is divided into hierarchical intervals to obtain the target hierarchical intervals corresponding to the binarized matrix of each dot table set, including: The width of each target level interval is determined by a preset function f(i) = c × i + d, where c and d are preset constants and i is the interval number; Determine the total hierarchical interval [0, L-1] of the binarized matrix of the current dot matrix set, where L is the total number of levels of the binarized matrix of the previous dot matrix set; Based on the number of dot threshold matrices and the width of the target level interval, the total level interval [0, L-1] of the binarized matrix of the current dot table set is divided into n target level intervals to obtain the target level interval corresponding to the binarized matrix of the current dot table set, where n is the number of dot threshold matrices.

6. The AM-based halftone dot generation method of claim 4, wherein, The target hierarchical intervals are subjected to matrix extraction processing using preset rules to obtain multiple target sub-interval matrices, including: Extract all binary matrices corresponding to the i-th target level interval from the i-th dot matrix set, and use them as the target sub-interval matrix.

7. The method of generating a halftone image according to Claim 1, wherein The multiple target sub-interval matrices are recombinated in a sequential hierarchical order to obtain a target halftone dot table, including: Arrange the target sub-interval matrix in ascending or descending order of hierarchy to obtain the target halftone dot table.

8. An amplitude-modulation based halftone dot generation apparatus, characterized by comprising: include: The acquisition module is used to obtain the dot threshold matrix of all single mesh shapes required within the target halftone dot image; The processing module is used to binarize the dot threshold matrices of all mesh types according to a preset threshold, generating corresponding dot table sets. Each dot table set includes multiple levels of binarized matrices. Based on the number of dot threshold matrices of each mesh type, the binarized matrices of each dot table set are divided into hierarchical intervals. After the hierarchical interval division, matrix extraction is performed to obtain multiple target sub-interval matrices. The multiple target sub-interval matrices are recombined in a continuous hierarchical order to obtain the target halftone dot table.

9. A computing device, comprising: include: A processor, a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A storage instruction that, when executed on a computer, causes the computer to perform the method as described in any one of claims 1 to 7.

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