An adaptive printing imposition symmetric overlay method and system

Abstract

The present invention discloses a symmetric overlay method and system for adaptive printing imposition, which relates to the technical field of printing symmetric overlay. By extracting the pattern feature vector F, the complexity coefficient C, pattern area A, and symmetry score S of each pattern are accurately analyzed, providing detailed basic information for subsequent pattern optimization. Based on the pattern feature vector F, an adaptive adjustment parameter set P is generated, and combined with the simulated annealing algorithm, the spatial optimization vector O of the imposition area is realized, greatly improving the spatial utilization rate of the paper and ensuring the rationality of the pattern layout. Further, in the generation stage of the symmetry optimization vector Sopt, based on the pattern positions and spacings after spatial optimization, through fine adjustment of the micro-rotation angle, the symmetry and visual balance of the imposition are significantly improved. It effectively solves the problem of space waste in pattern layout, enabling the printing scheme to more efficiently and accurately meet the production requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of printing symmetric overlay, and specifically provides a symmetric overlay method and system for adaptive printing layout. Background Art

[0002] In the field of modern manufacturing and production, printing technology, as a fundamental and widely applied technical means, has long been spread across all industries. From traditional graphic printing to recent high-precision printing, the continuous progress of printing technology has promoted the upgrading of multiple industries. With the development of technology, digital printing and automated production have gradually replaced traditional printing processes, bringing higher efficiency and lower costs. In this process, how to maximize the use of limited paper space and maintain high-quality printing effects has become an urgent problem to be solved.

[0003] Especially in the fields of customized product printing and high-end art reproduction, printed patterns usually need to have high artistic value and precise visual effects, which requires the layout design not only to optimize the typesetting but also to maintain symmetry and balance in the design.

[0004] However, existing layout technologies often have insufficient symmetry and space optimization when dealing with complex patterns. In traditional printing layout, especially when the pattern content is complex or there are irregular designs, the layout process often relies on manual experience or fixed algorithms for layout. Although this method can operate effectively in some simple designs, when facing diverse and complex design requirements, the following problems often occur: First, due to the limitations of the automated system, the arrangement of patterns may not fully ensure symmetry, resulting in a final printing effect that is not as expected; second, the space utilization rate during the layout process may not be maximized, which may cause unnecessary material waste; finally, manual intervention requires a large amount of time and effort, resulting in low production efficiency and unable to meet the needs of high-efficiency batch production. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a symmetric overlay method and system for adaptive printing layout, which solves the problems mentioned in the background art.

[0006] To achieve the above object, the first aspect of the present invention provides a symmetric overlay method for adaptive printing layout, including the following steps:

[0007] S1. Obtain the pattern image of the printing layout, extract the pattern features of the pattern image to obtain the pattern features of the pattern image, where the pattern features include the complexity coefficient C of the pattern, the pattern area A, and the symmetry score S, and integrate the complexity coefficient C, the pattern area A, and the symmetry score S to obtain the feature vector F of the pattern;

[0008] S2. Perform pattern analysis on the feature vector F to obtain the adjustment position and rotation angle of the pattern respectively, and form an adaptive adjustment parameter set P for the pattern;

[0009] S3. Adjust the position of the pattern according to the adaptive adjustment parameter set P, and at the same time use the simulated annealing algorithm to optimize the maximum paper space utilization rate, and output the space optimization vector O of the imposition scheme;

[0010] S4. Based on the space optimization vector O, perform symmetry adjustment on the position and spacing of the adjusted pattern, and calculate the micro-rotation angle of each pattern to obtain the symmetry optimization vector Sopt;

[0011] S5. By evaluating the space optimization vector O and the symmetry optimization vector Sopt, calculate the comprehensive score R of the overall imposition scheme, and compare it with the preset iteration threshold Rold to determine whether the current overall imposition scheme is used as the printing scheme.

[0012] Preferably, in the S1, pattern feature extraction from the pattern image includes: using an edge detection algorithm to extract the edge information of the pattern, calculating the total edge length L of the pattern, and calculating the complexity coefficient C through the total edge length L and the pattern area A;

[0013] Among them, the pattern area A is obtained by calculating the number of pixels in the pattern part after binarizing the pattern image.

[0014] Preferably, in the S1, pattern feature extraction from the pattern image further includes: the extraction process of the symmetry score S is as follows: by dividing the pattern image into left and right parts and upper and lower parts, and using image processing techniques to calculate the symmetry of the left and right parts and the upper and lower parts respectively, specifically: by calculating the pixel difference and shape matching degree between the left and right parts and the upper and lower parts, and measuring the symmetry of the left and right parts and the upper and lower parts based on the pixel difference and the shape matching degree;

[0015] Extract the left symmetry score Sleft and the right symmetry score Sright of the left and right parts of the pattern image, and extract the upper symmetry score Stop and the lower symmetry score Sbottom of the upper and lower parts, calculate the average value of the left symmetry score Sleft, the right symmetry score Sright, the upper symmetry score Stop and the lower symmetry score Sbottom, and mark this average value as the symmetry score S of the pattern.

[0016] Preferably, in the S2, the pattern analysis of the feature vector F includes:

[0017] Adjust the position of the pattern in the layout area according to the complexity coefficient C, the pattern area A, and the symmetry score S, and obtain the position adjustment (x, y) of the pattern in the layout;

[0018] Use the position adjustment (x, y) to adaptively adjust the position of the pattern in the layout. When adjusting the position of the pattern in the layout area, adjust according to the linear relationship between the complexity coefficient C and the pattern position, and the linear relationship between the symmetry score S and the pattern space size;

[0019] Among them, the specific linear relationship between the complexity coefficient C and the pattern position is:

[0020] When the complexity coefficient C is large, the pattern position is close to the center position of the layout;

[0021] When the complexity coefficient C is small, the pattern position is far from the center position of the layout;

[0022] The specific linear relationship between the symmetry score S and the pattern space size is:

[0023] When the symmetry score S is large, the pattern position occupies a large layout space;

[0024] When the symmetry score S is small, the pattern position occupies a small layout space.

[0025] Preferably, in the S2, when performing pattern analysis on the feature vector F, it further includes: performing pattern rotation angle analysis on the pattern after adaptively adjusting the position of the pattern in the layout,

[0026] The pattern rotation angle analysis includes analyzing the complexity coefficient C and the symmetry score S in the feature vector F, adjusting the angle of the pattern in the layout area, and determining the angle adjustment θ of the pattern in the layout;

[0027] Based on the angle adjustment θ, adaptively adjust the angle of the pattern in the layout, and integrate the position adjustment (x, y) and the angle adjustment θ to form an adaptive adjustment parameter set P;

[0028] Among them, when adjusting the angle of the pattern in the layout area, adjust according to the linear relationship between the complexity coefficient C and the symmetry score S and the pattern rotation angle; when the symmetry score S is large, the adjustment of the pattern rotation angle is small; when the symmetry score S is small, the pattern rotation angle is large.

[0029] Preferably, in the S3, adjusting the position of the pattern according to the adaptive adjustment parameter set P includes:

[0030] Adjust the pattern in the layout to the position adjustment (x, y), and then rotate it using the angle adjustment θ to obtain the adjusted pattern;

[0031] Use the simulated annealing algorithm to optimize the maximum paper space utilization rate for the adjusted pattern. By simulating the annealing phenomenon in the physical process, gradually optimize the imposition solution space. In each iteration, calculate the space utilization rate U of the current imposition scheme, and explore in the solution space through temperature control. After multiple iterations, form an iteration list with the space utilization rate U obtained in each iteration;

[0032] Sort the space utilization rate U in the iteration list, select the space utilization rate U with the subscript 1 in the sorted iteration list as the layout scheme with the best space utilization rate. At the same time, adjust the position (x, y) and angle adjustment θ corresponding to the space utilization rate U with the subscript 1, and output it as the space optimization vector O of the imposition scheme.

[0033] Preferably, in the step S4, perform symmetry adjustment on the position and spacing of the adjusted pattern, including:

[0034] Perform symmetry adjustment on the position and spacing of the adjusted pattern based on the space optimization vector O, calculate the symmetry score S of the pattern, and determine the micro-rotation angle θ of each pattern final and, according to the micro-rotation angle θ final optimize the adjusted pattern to obtain the symmetry optimization vector Sopt of the optimized imposition area;

[0035] Among them, the optimization of the adjusted pattern includes: using the micro-rotation angle θ final adjust the angle adjustment θ of the adjusted pattern, extract the space utilization rate U and position adjustment (x, y) in the space optimization vector O, and integrate them with the micro-rotation angle θ final for integration.

[0036] Preferably, in the step S5, evaluate the space optimization vector O and the symmetry optimization vector Sopt, including:

[0037] Perform a proportional evaluation on the angle adjustment θ and the micro-rotation angle θ in the space optimization vector O and the symmetry optimization vector Sopt final to determine the difference ratio between the angle adjustment θ and the micro-rotation angle θ final and mark it as the comprehensive score R.

[0038] Compare the comprehensive score R with the preset iteration threshold Rold to determine the iteration optimization trigger status result of the current imposition scheme, and judge whether the current overall imposition scheme is used as the printing scheme according to the iteration optimization trigger status result;

[0039] Among them, the iteration optimization trigger status result is obtained through the following comparison method:

[0040] When the comprehensive score R ≥ the iteration threshold Rold, it is determined that the iteration optimization trigger status result of the current imposition scheme is the trigger result, triggering the execution of S3 and S4, indicating that the optimization of the current imposition scheme is insufficient and there are significant differences in the adjustment angles of the patterns in the imposition;

[0041] When the comprehensive score R < the iteration threshold Rold, it is determined that the iteration optimization trigger status result of the current imposition scheme is the non-trigger result, stopping the execution of S3 and S4, indicating that the optimization of the current imposition scheme meets the expectations, and the imposition pattern after adjusting the symmetry optimization vector Sopt is output as the printing scheme.

[0042] Preferably, the position adjustment (x, y) is obtained through the following calculation formula:

[0043] ;

[0044] In the formula, x(i) and y(i) respectively represent the horizontal and vertical position adjustment coordinates of the i-th pattern, α and β represent the weight coefficients used to adjust the influence of the complexity coefficient C and the symmetry score S on the position adjustment (x, y), and S(i), C(i), and A(i) respectively represent the symmetry score S, complexity coefficient C, and pattern area A of the i-th pattern.

[0045] The second aspect of the present invention provides a symmetric stacking system for adaptive printing imposition, which is applied to a symmetric stacking method for adaptive printing imposition as described above, and is characterized in that it includes a pattern extraction module, a pattern analysis module, a pattern layout optimization module, a pattern fine-tuning module, and an iteration evaluation and decision module;

[0046] The pattern extraction module extracts pattern features from the input image data to obtain each pattern feature, and the pattern features include the complexity coefficient C, pattern area A, and symmetry score S of the pattern, forming a feature vector F of the pattern;

[0047] The pattern analysis module performs pattern analysis based on the obtained feature vector F to obtain the adjustment position and rotation angle of the pattern, forming an adaptive adjustment parameter set P of the pattern;

[0048] The pattern layout optimization module adjusts the position of the pattern according to the obtained adaptive adjustment parameter set P, and at the same time uses the simulated annealing algorithm to optimize the maximum paper space utilization rate, and outputs the space optimization vector O of the imposition scheme;

[0049] The pattern fine-tuning module adjusts the position and spacing of the pattern after being adjusted based on the space optimization vector O, performs symmetry adjustment, calculates the micro-rotation angle of each pattern, and obtains the symmetry optimization vector Sopt;

[0050] The iterative evaluation and decision-making module evaluates the spatial optimization vector O and the symmetry optimization vector Sopt, calculates the comprehensive score R of the overall layout plan, and compares it with the preset iterative threshold Rold to determine whether the current overall layout plan is used as the printing plan.

[0051] The present invention provides a symmetric overlapping method and system for adaptive printing layout, having the following beneficial effects:

[0052] (1) Through the extraction of the pattern feature vector F, the complexity coefficient C, the pattern area A, and the symmetry score S of each pattern are accurately analyzed, providing detailed basic information for subsequent pattern optimization. Then, based on the set of adaptive adjustment parameters P generated by the pattern feature vector F and combined with the simulated annealing algorithm, the spatial optimization vector O of the layout area is realized, greatly improving the spatial utilization rate of the paper while ensuring the rationality of the pattern layout. In the stage of generating the symmetry optimization vector Sopt, based on the position and spacing of the patterns after spatial optimization, through the fine adjustment of the micro-rotation angle, the symmetry and visual balance of the layout are significantly improved. Finally, through the comprehensive evaluation of the spatial optimization vector O and the symmetry optimization vector Sopt, the calculated comprehensive score R helps to accurately judge the pros and cons of the layout plan, and combined with the preset iterative threshold Rold, it is determined whether to enter the printing stage finally. The special advantage of this method is that it not only effectively solves the problem of space waste in pattern layout, but also improves the aesthetics of the layout plan through symmetry optimization, enabling the printing plan to more efficiently and accurately meet the production requirements, thereby reducing resource waste, improving production efficiency, and solving the problem of imbalance between pattern symmetry and spatial utilization rate in the previous layout process.

[0053] (2) Due to the linear relationship between the complexity coefficient C and the position, the complex patterns are closer to the center of the layout, while the simple patterns are farther away from the center, improving the visual balance of the layout; the symmetry score S is proportional to the space occupied by the pattern, enabling the patterns with higher symmetry to occupy more space, ensuring the symmetry and reasonable layout of the layout. Further, combined with the linear relationship between the complexity coefficient and the symmetry score, the rotation angle θ of the pattern is optimized to ensure the matching of the angle adjustment of the pattern with its symmetry condition, improving the symmetry and visual effect of the entire layout plan. Combined with the application of the simulated annealing algorithm, through multiple iterations, the spatial utilization rate U is optimized, effectively improving the spatial utilization efficiency of the layout, ensuring the maximum utilization of the layout area, and avoiding space waste. Finally, the spatial optimization vector O and the angle adjustment of the layout plan are optimized more precisely, ensuring that the layout not only has the best spatial utilization, but also meets the symmetry requirements, and can improve the aesthetics and symmetry of the patterns while ensuring the reasonable layout of the layout, solving the common problems of insufficient spatial utilization and symmetry in traditional layout methods, and the optimization process is more intelligent and efficient.

[0054] (3) Through the fine combination of the spatial optimization vector O and the symmetry optimization vector Sopt, the double optimization of the layout plan is achieved: not only the space utilization rate U is optimized, but also the symmetry is improved, ensuring the efficiency and aesthetics of the layout. By adjusting the pattern position and spacing, combined with the micro-rotation angle θ final for precise symmetry optimization, the problem that it is difficult to balance space utilization and symmetry in traditional layout methods is solved. Especially in the adjustment of θ final , combined with the symmetry score S and the complexity coefficient C, the rotation amplitude is finely controlled to ensure that the symmetry of the pattern is effectively enhanced. At the same time, the simulated annealing algorithm is used to further optimize the space utilization rate, achieving the best spatial layout, thereby improving the overall efficiency of the layout plan. Finally, by calculating the comprehensive score R and comparing it with the preset iteration threshold Rold, it is accurately judged whether the layout plan has been optimized to reach the standard, avoiding multiple ineffective optimizations. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the steps of a symmetric overlapping method for adaptive printing layout of the present invention;

[0056] Figure 2 It is a schematic block diagram of a symmetric overlapping system for adaptive printing layout of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0057] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present invention.

[0058] Embodiment 1

[0059] The present invention provides a symmetric overlapping method for adaptive printing layout. Please refer to Figure 1 , including the following steps:

[0060] S1. Obtain the pattern image of the printing layout, extract the pattern features of the pattern image to obtain the pattern features of the pattern image. The pattern features include the complexity coefficient C, the pattern area A, and the symmetry score S of the pattern. Integrate the complexity coefficient C, the pattern area A, and the symmetry score S to obtain the feature vector F of the pattern;

[0061] S2. Perform pattern analysis on the feature vector F to respectively obtain the adjustment position and rotation angle of the pattern, and form the adaptive adjustment parameter set P of the pattern;

[0062] S3. Adjust the position of the pattern according to the adaptive adjustment parameter set P, and at the same time use the simulated annealing algorithm to optimize the maximum paper space utilization rate, and output the space optimization vector O of the imposition scheme;

[0063] S4. Based on the space optimization vector O, symmetrically adjust the position and spacing of the adjusted pattern, and calculate the micro-rotation angle of each pattern to obtain the symmetry optimization vector Sopt;

[0064] S5. By evaluating the space optimization vector O and the symmetry optimization vector Sopt, calculate the comprehensive score R of the overall imposition scheme, and compare it with the preset iteration threshold Rold to determine whether the current overall imposition scheme is used as the printing scheme.

[0065] In this embodiment, by precisely combining pattern feature extraction, space optimization, and symmetry adjustment, the efficiency and accuracy of the imposition process are significantly improved. First, through the extraction of the pattern feature vector F, the complexity coefficient C, pattern area A, and symmetry score S of each pattern are accurately analyzed, providing detailed basic information for subsequent pattern optimization. Then, based on the adaptive adjustment parameter set P generated from the pattern feature vector F, the space optimization vector O of the imposition area is realized by combining the simulated annealing algorithm, greatly improving the space utilization rate of the paper while ensuring the rationality of the pattern layout. Further, in the stage of generating the symmetry optimization vector Sopt, based on the position and spacing of the patterns optimized in space, through the fine adjustment of the micro-rotation angle, the symmetry and visual balance of the imposition are significantly improved. Finally, by comprehensively evaluating the space optimization vector O and the symmetry optimization vector Sopt, the calculated comprehensive score R helps to accurately judge the quality of the imposition scheme, and combined with the preset iteration threshold Rold, it is determined whether to enter the printing stage finally. The special advantage of this method is that it not only effectively solves the problem of space waste in pattern layout, but also improves the aesthetics of the imposition scheme through symmetry optimization, enabling the printing scheme to more efficiently and accurately meet the production requirements, thereby reducing resource waste, improving production efficiency, and solving the problem of imbalance between pattern symmetry and space utilization rate in the previous imposition process.

[0066] It should be noted that the Simulated Annealing (SA) algorithm is a probability-based optimization algorithm. This algorithm simulates the process of a solid gradually cooling at high temperature, randomly searches for the global optimal solution in the solution space, and thus avoids being trapped in the dilemma of local optimal solutions. The core idea of the simulated annealing algorithm is to analogize the optimization problem with the process of solid annealing. During the annealing process, the solid is heated to a high temperature and then slowly cooled, and the internal particles gradually change from a disordered state to an ordered state, and finally reach the stable state with the lowest energy at room temperature. The simulated annealing algorithm draws on this physical phenomenon, and through controlling the temperature parameter and acceptance probability, randomly searches in the solution space, has the opportunity to jump out of the local optimal solution, and search for the global optimal solution. In this example, the simulated annealing algorithm is used for tasks such as image restoration, that is, to restore a contaminated image back to a clear original image, filter out the distorted parts, so as to optimize the maximum paper space utilization rate (prior art).

[0067] Embodiment 2

[0068] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: S1 includes S11 and S12;

[0069] S11. Extract the pattern features from the input image data, extract the complexity coefficient C and pattern area A of each pattern. The complexity coefficient C is used to measure the geometric complexity of the pattern;

[0070] The complexity coefficient C is specifically obtained by using an edge detection algorithm to extract the edge information of the pattern, calculating the total edge length L of the pattern, and calculating through the ratio of the total edge length L to the pattern area A to obtain the complexity coefficient C;

[0071] The pattern area A is obtained by calculating the number of pixels in the pattern part after binarizing the pattern;

[0072] S12. Analyze the symmetry of the patterns in the image data, calculate the symmetry score of the pattern. Specifically, the pattern is divided into different regions, including dividing the pattern into left and right parts and upper and lower parts. The symmetry of the left and right parts and the upper and lower parts is calculated through image processing technology. Specifically, the symmetry of the left and right parts and the upper and lower parts is measured by calculating the pixel difference and shape matching degree between the left and right parts and the upper and lower parts, and obtain the left symmetry score Sleft, right symmetry score Sright, upper symmetry score Stop, and lower symmetry score Sbottom of the left and right parts and the upper and lower parts of the pattern. After calculating the average value of the left symmetry score Sleft, right symmetry score Sright, upper symmetry score Stop, and lower symmetry score Sbottom, it is marked as the symmetry score S of the pattern;

[0073] Then, through the integration of the complexity coefficient C, the pattern area A, and the symmetry score S, the feature vector F of the pattern is obtained.

[0074] In this embodiment, through the precise analysis of pattern feature extraction, the complexity coefficient C and the pattern area A of each pattern are effectively quantified, thus providing important geometric and visual features for subsequent layout optimization. The total edge length L of the pattern is extracted using an edge detection algorithm, and combined with the area A of the pattern, the complexity coefficient C is calculated. This coefficient reflects the geometric complexity of the pattern and helps to determine whether the pattern requires more spatial adjustment to adapt to the layout process. By calculating the left symmetry score Sleft, the right symmetry score Sright, the top symmetry score Stop, and the bottom symmetry score Sbottom of the pattern, the symmetry of the pattern is further analyzed. Combining the complexity coefficient C and the pattern area A, the feature vector F of the pattern is obtained by integrating these data, providing comprehensive numerical support for the adaptive adjustment of each pattern during the layout process. The special advantage of this method lies in the quantification of the pattern complexity coefficient C and the symmetry score S, which can accurately evaluate the geometric complexity and symmetry of each pattern, providing a reliable reference for the spatial utilization and layout optimization of the layout plan, thus effectively improving the overall layout efficiency and aesthetics of the layout. This process effectively solves the problem of insufficiently refined processing of pattern geometric complexity and symmetry in traditional layout methods, achieving a more intelligent and efficient layout design.

[0075] Among them, the edge detection algorithm in this example is actually a basic technique in image processing and computer vision, aiming to identify points with obvious brightness changes in digital images, reflecting important events and changes in attributes, such as discontinuities in depth, discontinuities in surface direction, changes in material properties, and changes in scene lighting; specifically, the edges are detected by calculating the gradients of pixel points in the image, calculating the gradients in the horizontal and vertical directions respectively, and then combining the gradients in these two directions to obtain the final edge image (prior art).

[0076] Embodiment 3

[0077] This embodiment is an explanatory description based on Embodiment 2. Please refer to Figure 1 , specifically: S2 includes S21 and S22;

[0078] S21. Perform pattern analysis based on the obtained feature vector F. The pattern analysis includes analyzing the complexity coefficient C and the symmetry score S in the feature vector F, adjusting the position of the pattern in the layout area, and then combining the pattern area A to obtain the position adjustment (x, y) of the pattern in the layout, and adaptively adjusting the position of the pattern in the layout through the position adjustment (x, y);

[0079] Among them, when adjusting the position of the pattern in the layout area, the adjustment is made according to the linear relationship between the complexity coefficient C and the pattern position and the linear relationship between the symmetry score S and the pattern space size;

[0080] The specific linear relationship between the complexity coefficient C and the pattern position is: when the complexity coefficient C is large, the pattern position is close to the center position of the layout; when the complexity coefficient C is small, the pattern position is far from the center position of the layout;

[0081] The specific linear relationship between the symmetry score S and the pattern space size is: when the symmetry score S is large, the pattern position occupies a large layout space; when the symmetry score S is small, the pattern position occupies a small layout space;

[0082] The position adjustment (x, y) is obtained through the following calculation formula:

[0083] ;

[0084] In the formula, x(i) and y(i) respectively represent the horizontal and vertical position adjustment coordinates of the i-th pattern, and α and β represent weight coefficients, which are specifically used to adjust the influence of the complexity coefficient C and the symmetry score S on the position adjustment (x, y). S(i), C(i), and A(i) respectively represent the symmetry score S, the complexity coefficient C, and the pattern area A of the i-th pattern.

[0085] S22. After the position of the pattern in the layout is adaptively adjusted, analyze the rotation angle of the pattern. The analysis of the pattern rotation angle includes analyzing the complexity coefficient C and the symmetry score S in the feature vector F, adjusting the angle of the pattern in the layout area, obtaining the angle adjustment θ of the pattern in the layout, and adaptively adjusting the angle of the pattern in the layout through the angle adjustment θ. By integrating the position adjustment (x, y) and the angle adjustment θ, an adaptive adjustment parameter set P is formed;

[0086] Among them, when adjusting the angle of the pattern in the layout area, the adjustment is made according to the linear relationship between the complexity coefficient C and the symmetry score S and the pattern rotation angle;

[0087] When the symmetry score S is large, the adjustment of the pattern rotation angle is small; when the symmetry score S is small, the adjustment of the pattern rotation angle is large;

[0088] The angle adjustment θ is obtained through the following calculation formula:

[0089] ;

[0090] In the formula, θ(i) represents the angle adjustment of the i-th pattern, and γ(i) represents the adjustment amplitude coefficient of the symmetry score S(i) of the i-th pattern.

[0091] S3 includes S31 and S32;

[0092] S31. Adjust the position of the pattern according to the obtained set of adaptive adjustment parameters P. By adjusting the pattern in the layout to the position adjustment (x, y), and then rotating it using the angle adjustment θ, the adjusted pattern is obtained;

[0093] S32. Optimize the maximum paper space utilization rate for the adjusted pattern using the simulated annealing algorithm. The simulated annealing algorithm optimizes the layout solution space by simulating the annealing phenomenon in the physical process. In each iteration, the simulated annealing algorithm calculates the space utilization rate U of the current layout plan and explores in the solution space through temperature control. After multiple iterations, the space utilization rates U obtained in each iteration are formed into an iteration list. The simulated annealing algorithm sorts the space utilization rates U in the iteration list and selects the space utilization rate U with the subscript 1 in the sorted iteration list as the layout plan with the best space utilization rate. At the same time, the position adjustment (x, y) and the angle adjustment θ corresponding to the space utilization rate U with the subscript 1 are obtained, and the output is the space optimization vector O of the layout plan;

[0094] The space utilization rate U is obtained by the ratio of the total area Atotal of the layout area to the sum of all As of the patterns in the layout area.

[0095] In this embodiment, through the adjustment of the adaptive pattern position and rotation angle, significant improvements have been achieved in optimizing the imposition scheme. Based on the pattern feature vector F, by comprehensively analyzing the complexity coefficient C and symmetry score S of the pattern, the position of each pattern in the imposition area is intelligently adjusted, enabling the pattern to be automatically optimized according to its complexity and symmetry. There is a linear relationship between the complexity coefficient C and the position, making complex patterns closer to the center of the imposition, while simple patterns are farther away from the center, enhancing the visual balance of the imposition. The symmetry score S is proportional to the space size occupied by the pattern, allowing patterns with higher symmetry to occupy more space, ensuring the symmetry and reasonable layout of the imposition. Further, combining the linear relationship between the complexity coefficient and symmetry score, the rotation angle θ of the pattern is optimized to ensure that the angle adjustment of the pattern matches its symmetry condition, improving the symmetry and visual effect of the entire imposition scheme. Combining the application of the simulated annealing algorithm, the space utilization rate U is optimized through multiple iterations, effectively enhancing the space utilization efficiency of the imposition, ensuring the maximum utilization of the imposition area, and avoiding space waste. Finally, the space optimization vector O and angle adjustment of the imposition scheme are optimized more precisely, ensuring that the imposition not only has the optimal space utilization but also meets the symmetry requirements, achieving the dual optimization effects of aesthetics and balance. The special advantage of this method is that through the complexity coefficient C, symmetry score S, and the adaptively adjusted position and rotation angle, it can improve the aesthetics and symmetry of the pattern while ensuring the reasonable layout of the imposition, solving the common problems of insufficient space utilization and symmetry in traditional imposition methods, and making the optimization process more intelligent and efficient.

[0096] Embodiment 4

[0097] This embodiment is an explanatory note for Embodiment 3. Please refer to Figure 1 , specifically: S4 includes S41;

[0098] S41. Based on the position and spacing of the patterns adjusted by the space optimization vector O, symmetry adjustment is performed. The symmetry adjustment calculates the symmetry score S of the pattern to obtain the micro-rotation angle θ of each pattern final , and based on the micro-rotation angle θ final optimizes the patterns adjusted by the space optimization vector O. The optimization specifically involves applying the obtained micro-rotation angle θ final to adjust the angle adjustment θ of the patterns adjusted by the space optimization vector O. By extracting the space utilization rate U and position adjustment (x, y) in the space optimization vector O, and then integrating with the micro-rotation angle θ final to obtain the symmetry optimization vector Sopt for optimizing the imposition area;

[0099] The micro-rotation angle θ final is obtained through the following calculation formula:

[0100] ;

[0101] In the formula, θ(final, i) represents the micro-rotation angle of the i-th pattern, θ(i) represents the angle adjustment of the i-th pattern, β represents the fine-tuning coefficient, which is specifically used to control the adjustment amplitude of the micro-rotation angle, S(i) represents the symmetry score of the i-th pattern, and C(i) represents the complexity coefficient of the i-th pattern.

[0102] S5 includes S51 and S52;

[0103] S51, by evaluating the spatial optimization vector O and the symmetry optimization vector Sopt, the evaluation is carried out by extracting the angle adjustment θ and the micro-rotation angle θ in the spatial optimization vector O and the symmetry optimization vector Sopt final perform proportional evaluation to obtain the angle adjustment θ and the micro-rotation angle θ final The difference ratio is marked as the comprehensive score R, which reflects the optimization effect of the imposition area;

[0104] S52, compare the obtained comprehensive score R with the preset iteration threshold Rold, obtain the iteration optimization trigger status result of the current imposition scheme, and judge whether the current overall imposition scheme is used as the printing scheme according to the iteration optimization trigger status result;

[0105] The iteration optimization trigger status result is obtained through the following comparison method:

[0106] When the comprehensive score R ≥ the iteration threshold Rold, the iteration optimization trigger status result of the current imposition scheme is obtained as the trigger result, and S3 and S4 are triggered to execute, indicating that the optimization of the current imposition scheme is insufficient and there are large differences in the adjustment angles of the patterns in the imposition;

[0107] When the comprehensive score R < the iteration threshold Rold, the iteration optimization trigger status result of the current imposition scheme is obtained as the non-trigger result, and S3 and S4 are stopped from being executed, indicating that the optimization of the current imposition scheme meets the expectation, and the imposition pattern after adjusting the symmetry optimization vector Sopt is output as the printing scheme.

[0108] In this embodiment, through the fine combination of the spatial optimization vector O and the symmetry optimization vector Sopt, the double optimization of the imposition scheme is realized: not only the space utilization rate U is optimized, but also the symmetry is improved, ensuring the efficiency and beauty of the imposition layout. By adjusting the pattern position and spacing, combined with the micro-rotation angle θ final perform precise symmetry optimization, which solves the problem that it is difficult to balance space utilization and symmetry in traditional imposition methods. Especially when θ finalIn the adjustment, by combining the symmetry score S and the complexity coefficient C, the rotation amplitude was finely controlled to ensure that the symmetry of the pattern was effectively enhanced. At the same time, the simulated annealing algorithm was used to further optimize the space utilization rate to achieve the best spatial layout, thereby improving the overall efficiency of the imposition scheme. Finally, by calculating the comprehensive score R and comparing it with the preset iteration threshold Rold, it was accurately judged whether the imposition scheme had been optimized to meet the standard, avoiding multiple ineffective optimizations. During the optimization process, if the comprehensive score R is greater than or equal to the preset threshold Rold, more optimization iterations are triggered until the expected effect is achieved. Through this precise iterative optimization mechanism, the scheme not only ensures the maximization of space, but also ensures the visual symmetry and balance of the pattern, solving the problems of inconsistent optimization effects and difficult symmetry unification in traditional imposition methods, and finally achieving the output of an efficient and beautiful imposition scheme.

[0109] Example 5

[0110] An adaptive printing imposition symmetric overlay system, please refer to Figure 2 , specifically: including a pattern extraction module, a pattern analysis module, a pattern layout optimization module, a pattern fine-tuning module, and an iterative evaluation and decision-making module;

[0111] The pattern extraction module extracts pattern features from the input image data to obtain each pattern feature. The pattern features include the complexity coefficient C, the pattern area A, and the symmetry score S of the pattern, forming the feature vector F of the pattern;

[0112] The pattern analysis module performs pattern analysis based on the obtained feature vector F to obtain the adjustment position and rotation angle of the pattern, forming the adaptive adjustment parameter set P of the pattern;

[0113] The pattern layout optimization module adjusts the position of the pattern according to the obtained adaptive adjustment parameter set P, and at the same time uses the simulated annealing algorithm to optimize the maximum paper space utilization rate, and outputs the space optimization vector O of the imposition scheme;

[0114] The pattern fine-tuning module adjusts the position and spacing of the pattern after being adjusted based on the space optimization vector O, performs symmetry adjustment, calculates the micro-rotation angle of each pattern, and obtains the symmetry optimization vector Sopt;

[0115] The iterative evaluation and decision-making module evaluates the space optimization vector O and the symmetry optimization vector Sopt, calculates the comprehensive score R of the overall imposition scheme, and compares it with the preset iteration threshold Rold to judge whether the current overall imposition scheme is used as the printing scheme.

[0116] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A symmetric superimposed layout method for adaptive printing imposition, characterized in that: It includes the following steps: S1. Obtain the pattern image of the printing layout, extract the pattern features of the pattern image to obtain the pattern features of the pattern image. The pattern features include the complexity coefficient C of the pattern, the pattern area A, and the symmetry score S. Integrate the complexity coefficient C, the pattern area A, and the symmetry score S to obtain the feature vector F of the pattern; S2. Perform pattern analysis on the feature vector F to respectively obtain the adjustment position and rotation angle of the pattern, and form the adaptive adjustment parameter set P of the pattern, including: According to the complexity coefficient C, the pattern area A, and the symmetry score S, adjust the position of the pattern in the layout area to obtain the position adjustment (x, y) of the pattern in the layout; Use the position adjustment (x, y) to adaptively adjust the position of the pattern in the layout. When adjusting the position of the pattern in the layout area, adjust according to the linear relationship between the complexity coefficient C and the pattern position, and according to the linear relationship between the symmetry score S and the pattern space size; Perform pattern rotation angle analysis on the pattern after adaptively adjusting the position of the pattern in the layout. The pattern rotation angle analysis includes analyzing the complexity coefficient C and symmetry score S in the feature vector F, adjusting the angle of the pattern in the layout area, and determining the angle adjustment θ of the pattern in the layout; Based on the angle adjustment θ, adaptively adjust the angle of the pattern in the layout, and integrate the position adjustment (x, y) and the angle adjustment θ to form the adaptive adjustment parameter set P; Among them, the specific linear relationship between the complexity coefficient C and the pattern position is: When the complexity coefficient C is large, the pattern position is close to the center position of the layout; When the complexity coefficient C is small, the pattern position is far from the center position of the layout; The specific linear relationship between the symmetry score S and the pattern space size is: When the symmetry score S is large, the layout space occupied by the pattern position is large; When the symmetry score S is small, the layout space occupied by the pattern position is small; When adjusting the angle of the pattern in the layout area, adjust according to the linear relationship between the complexity coefficient C and the symmetry score S and the pattern rotation angle: when the symmetry score S is large, the adjustment of the pattern rotation angle is small; when the symmetry score S is small, the pattern rotation angle is large; S3. Adjust the position of the pattern according to the adaptive adjustment parameter set P, and at the same time use the simulated annealing algorithm to optimize the maximum paper space utilization rate, and output the space optimization vector O of the layout plan; S4. Based on the space optimization vector O, perform symmetry adjustment on the position and spacing of the adjusted pattern, and calculate the micro-rotation angle of each pattern to obtain the symmetry optimization vector Sopt; S5. Evaluate the space optimization vector O and the symmetry optimization vector Sopt, calculate the comprehensive score R of the overall layout plan, and compare it with the preset iteration threshold Rold to determine whether the current overall layout plan is used as the printing plan.

2. The symmetric overlay method for adaptive printing imposition according to claim 1, wherein In the S1, extracting the pattern features of the pattern image includes: Extract the edge information of the pattern using an edge detection algorithm, calculate the total edge length L of the pattern, and calculate the complexity coefficient C through the total edge length L and the pattern area A; wherein, the pattern area A is obtained by calculating the number of pixels in the pattern part after binarizing the pattern image.

3. The symmetric overlapping and tiling method for adaptive printing imposition according to claim 2, wherein In the S1, for the pattern feature extraction of the pattern image, it further includes: Divide the pattern image into left and right parts and upper and lower parts, and calculate the symmetry of the left and right parts and the upper and lower parts respectively through image processing techniques. Specifically, calculate the pixel difference and shape matching degree of the left and right parts and the upper and lower parts, and measure the symmetry of the left and right parts and the upper and lower parts based on the pixel difference and the shape matching degree. Extract the left symmetry score Sleft and the right symmetry score Sright of the left and right parts of the pattern image, and extract the upper symmetry score Stop and the lower symmetry score Sbottom of the upper and lower parts. Calculate the average value of the left symmetry score Sleft, the right symmetry score Sright, the upper symmetry score Stop and the lower symmetry score Sbottom, and mark this average value as the symmetry score S of the pattern.

4. A symmetric superimposed layout method for adaptive printing imposition according to claim 1, characterized in that: In the S3, adjust the position of the pattern according to the adaptive adjustment parameter set P, including: Adjust the pattern in the imposition to the position adjustment (x, y), and then rotate it using the angle adjustment θ to obtain the adjusted pattern. Use the simulated annealing algorithm to optimize the maximum paper space utilization rate for the adjusted pattern. By simulating the annealing phenomenon in the physical process, gradually optimize the imposition solution space. In each iteration, calculate the space utilization rate U of the current imposition scheme, and explore in the solution space through temperature control. After multiple iterations, form an iteration list with the space utilization rate U obtained in each iteration. Sort the space utilization rate U in the iteration list, select the space utilization rate U with the subscript 1 in the sorted iteration list as the layout scheme with the best space utilization rate, and at the same time output the position adjustment (x, y) and the angle adjustment θ corresponding to the space utilization rate U with the subscript 1 as the space optimization vector O of the imposition scheme.

5. The symmetric overlay method for adaptive printing imposition according to claim 4, wherein In the S4, perform symmetry adjustment on the position and spacing of the adjusted pattern, including: Based on the spatial optimization vector O, perform symmetry adjustment on the position and spacing of the adjusted pattern, calculate the symmetry score S of the pattern, and determine the micro-rotation angle θ of each pattern final , and according to the micro-rotation angle θ final optimize the adjusted pattern to obtain the symmetry optimization vector Sopt for optimizing the layout area; Among them, the optimization of the adjusted pattern includes: using the micro-rotation angle θ final Adjust the angle adjustment θ of the adjusted pattern, extract the space utilization rate U and position adjustment (x, y) in the space optimization vector O, and combine them with the micro-rotation angle θ final for integration.

6. The symmetric overlay method for adaptive printing imposition according to claim 5, wherein In the S5, evaluate through the space optimization vector O and the symmetry optimization vector Sopt, including: Adjust the angles θ and the micro-rotation angle θ in the space optimization vector O and the symmetry optimization vector Sopt final Perform a proportional evaluation to determine the angles θ and the micro-rotation angle θ final Calculate the difference ratio and label it as the comprehensive score R; Compare the comprehensive score R with the preset iteration threshold Rold to determine the iteration optimization trigger status result of the current imposition scheme, and judge whether the current overall imposition scheme is used as the printing scheme according to the iteration optimization trigger status result. Among them, the iteration optimization trigger status result is obtained through the following comparison method: When the comprehensive score R ≥ the iteration threshold Rold, it is determined that the iteration optimization trigger status result of the current imposition scheme is the trigger result, triggering the execution of S3 and S4, indicating that the optimization of the current imposition scheme is insufficient and there are large differences in the adjustment angles of the patterns in the imposition. When the comprehensive score R < the iterative threshold Rold, it is determined that the iterative optimization trigger status result of the current imposition scheme is a non-trigger result, and S3 and S4 are stopped from being executed, indicating that the optimization of the current imposition scheme has reached the expectation, and the imposition pattern after adjusting the symmetry optimization vector Sopt is output as the printing scheme.

7. A symmetric overlay method for adaptive printing imposition according to claim 1, characterized in that, The position adjustment (x, y) is obtained through the following calculation formula: ； In the formula, x(i) and y(i) respectively represent the horizontal and vertical position adjustment coordinates of the i-th pattern, and α and β represent weight coefficients used to adjust the influence of the complexity coefficient C and the symmetry score S on the position adjustment (x, y). S(i), C(i), and A(i) respectively represent the symmetry score S, the complexity coefficient C, and the pattern area A of the i-th pattern.

8. An adaptive printing imposition symmetric overlay system for performing an adaptive printing imposition symmetric overlay method according to any one of claims 1 to 7, characterized in that, Including: A pattern extraction module, a pattern analysis module, a pattern layout optimization module, a pattern fine-tuning module, and an iterative evaluation and decision module; The pattern extraction module extracts pattern features from the input image data to obtain each pattern feature. The pattern features include the complexity coefficient C, the pattern area A, and the symmetry score S of the pattern, forming a feature vector F of the pattern; The pattern analysis module performs pattern analysis based on the obtained feature vector F to obtain the adjustment position and rotation angle of the pattern, forming an adaptive adjustment parameter set P of the pattern, including: According to the complexity coefficient C, the pattern area A, and the symmetry score S, the position of the pattern in the imposition area is adjusted to obtain the position adjustment (x, y) of the pattern in the imposition; The position of the pattern in the imposition is adaptively adjusted using the position adjustment (x, y). When adjusting the position of the pattern in the imposition area, the adjustment is performed according to the linear relationship between the complexity coefficient C and the pattern position, and the linear relationship between the symmetry score S and the pattern space size; After the pattern whose position in the imposition has been adaptively adjusted, the pattern rotation angle analysis is performed. The pattern rotation angle analysis includes analyzing the complexity coefficient C and the symmetry score S in the feature vector F, adjusting the angle of the pattern in the imposition area, and determining the angle adjustment θ of the pattern in the imposition; Based on the angle adjustment θ, the angle of the pattern in the imposition is adaptively adjusted, and the position adjustment (x, y) and the angle adjustment θ are integrated to form the adaptive adjustment parameter set P; Among them, the specific linear relationship between the complexity coefficient C and the pattern position is: When the complexity coefficient C is large, the pattern position is close to the center position of the imposition; When the complexity coefficient C is small, the pattern position is far from the center position of the imposition; The specific linear relationship between the symmetry score S and the pattern space size is: When the symmetry score S is large, the pattern position occupies a large imposition space; When the symmetry score S is small, the pattern position occupies a small imposition space; When adjusting the angle of the pattern in the imposition area, the adjustment is performed according to the linear relationship between the complexity coefficient C and the symmetry score S and the pattern rotation angle: when the symmetry score S is large, the adjustment of the pattern rotation angle is small, and when the symmetry score S is small, the pattern rotation angle is large; The pattern layout optimization module adjusts the positions of the patterns according to the obtained set of adaptive adjustment parameters P, and at the same time uses the simulated annealing algorithm to optimize the maximum paper space utilization rate, and outputs the space optimization vector O of the imposition scheme; The pattern fine-tuning module adjusts the positions and spacings of the patterns based on the space optimization vector O, performs symmetry adjustment, calculates the micro-rotation angle of each pattern, and obtains the symmetry optimization vector Sopt; The iterative evaluation and decision-making module evaluates the space optimization vector O and the symmetry optimization vector Sopt, calculates the comprehensive score R of the overall imposition scheme, and compares it with the preset iterative threshold Rold to determine whether the current overall imposition scheme is used as the printing scheme.

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