An artistic composition perspective auxiliary design method and system

Abstract

The present invention discloses an artistic composition perspective auxiliary design method and system, which relates to the technical field of auxiliary design and is used to solve the problem that existing design software requires real-time calculation, and after mobilizing elements, there is still a waiting time, which slows down the work efficiency to a certain extent; obtaining a target image to be geometrically perspectived and obtaining relevant perspective parameters, matching the geometric features of the target image with the features of each preset splitting mode to determine the corresponding feature matching degrees under each preset splitting mode; determining the pre-calculation area during the geometric perspective of the target image according to the corresponding feature matching degrees under each preset splitting mode; by performing pre-operations, the buffer time during real-time operations is reduced, the creation efficiency is significantly improved, and the time for repeated modification is reduced. At the same time, by recording the operation history and feedback of the user, the system can continuously optimize the algorithm to meet the personalized needs of the user.

Description

Technical Field

[0001] The present invention relates to the technical field of assisted design, and more specifically, to an artistic composition perspective assisted design method and system. Background Art

[0002] With the rapid development of the digital art and design fields, creation tools and auxiliary software have been continuously evolving to meet the increasingly complex needs of artists, designers, and architects. Against this backdrop, the automatic generation of composition and perspective effects has become particularly important. Especially when dealing with various types of visual content, accurate perspective relationships and element layouts are crucial for enhancing the visual appeal and professionalism of works.

[0003] Currently, more and more design software has started to adopt an interactive feedback approach to help users adjust the elements in the composition in real time. The core of this technical background is to enable designers to conveniently perform various operations, such as moving, scaling, deleting, or adding elements, through a user-friendly interface, while the system can immediately calculate the new perspective effect and display it on the interface. This real-time feedback mechanism greatly accelerates the creation process, enabling designers to obtain instant visual effect feedback at every step of the creation.

[0004] The existing technologies have the following deficiencies:

[0005] Through real-time calculation, although existing design software can quickly update the perspective results according to each operation of the user. For example, when the user moves a certain element to a new position, the system will immediately recalculate the perspective relationship between this element and other elements. However, due to the need for real-time calculation, after moving the element, there is still a waiting time, which to a certain extent slows down the work efficiency.

[0006] In response to the above problems, the present invention proposes a solution. Summary of the Invention

[0007] To overcome the above-mentioned defects of the existing technologies, embodiments of the present invention provide an artistic composition perspective assisted design method and system to solve the problems raised in the above background art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] An artistic composition perspective assisted design method, which acquires a target image to be geometrically perspectived and relevant perspective parameters, matches the geometric features of the target image with the features of each preset splitting mode to determine the corresponding feature matching degrees under each preset splitting mode; the geometric features of the target image are obtained by combining multiple relevant perspective parameters, including the vanishing point of the target image and the viewpoint of the target image;

[0010] Determine the early calculation area when determining the geometric perspective of the target image according to the feature matching degree corresponding to each preset splitting mode.

[0011] In a preferred embodiment, the preset splitting modes include various fixed-direction splittings and disordered splittings.

[0012] In a preferred embodiment, the preset splitting mode feature is the core area of the preset splitting mode, including the starting area and the ending area corresponding to the preset splitting mode.

[0013] In a preferred embodiment, a method for matching the geometric features of the target image with the features of each preset splitting mode is as follows:

[0014] The geometric features of the target image include the vanishing point of the target image and the viewpoint of the target image;

[0015] Calculate the relative distance value between the viewpoint of the target image and the centroid of the starting area of the corresponding preset splitting mode;

[0016] And calculate the number value of the vanishing points where the vanishing point of the target image is located in the starting area and the ending area of the corresponding preset splitting mode;

[0017] After normalizing the relative distance value and the number value of the vanishing points, sum them up to determine the feature matching degree between the target image and the corresponding preset splitting mode.

[0018] In a preferred embodiment, determining the early calculation area when determining the geometric perspective of the target image according to the feature matching degree corresponding to each preset splitting mode specifically includes the following steps:

[0019] Sort the feature matching degrees corresponding to each preset splitting mode, and select the preset splitting mode with the largest feature matching degree value as the final splitting mode;

[0020] If the final splitting mode is disordered, no pre-operation is performed, otherwise, split perspective pre-operation is performed according to the final splitting mode.

[0021] In a preferred embodiment, if the feature matching degrees corresponding to multiple preset splitting modes are greater than the preset matching degree threshold, and the deviation of the feature matching degrees corresponding to multiple preset splitting modes is less than the preset deviation threshold, perform secondary screening on the feature matching degrees corresponding to multiple preset splitting modes to determine the final splitting mode.

[0022] In a preferred embodiment, the splitting habit data of the system user is obtained, including the usage ratio of each preset splitting mode of the user, and the similar images in the historical database are determined according to the geometric features of the target image. The usage ratio of each preset splitting mode corresponding to the similar images is obtained, and the corresponding weight coefficients of each preset splitting mode are comprehensively determined according to the usage ratio of each preset splitting mode of the user and the usage ratio of each preset splitting mode corresponding to the similar images. The weight coefficients of the preset splitting modes to be secondarily screened are extracted, and weighted calculations are performed according to the corresponding feature matching degrees. The preset splitting mode with the largest weighted calculation result is set as the final splitting mode;

[0023] If the final splitting mode is disordered, no pre-operation is performed. Otherwise, splitting perspective pre-operations are performed according to the final splitting mode.

[0024] An artistic composition perspective auxiliary design system includes a user interface module, an image processing module, a similarity analysis module, a splitting mode evaluation module, and a data storage module, and the modules are signal-connected to each other;

[0025] The user interface module is used to provide a front-end interface for the user to interact with the system, and is used for the user to input images and related parameters;

[0026] The image processing module is used to preprocess and extract features of the target image, and it also includes a Hough transform unit for implementing the Hough transform algorithm to detect straight lines and vanishing points in the image;

[0027] The similarity analysis module is used to compare the features of the target image with the images in the historical database to determine similar images;

[0028] The splitting mode evaluation module is used to evaluate the preset splitting modes, screen them according to the feature matching degree and user habits, and it also includes a weight calculation unit for calculating the weight coefficients of each preset splitting mode according to the splitting habits of the user and the historical usage ratio of similar images;

[0029] The data storage module is used to store the data in the data processing process of the artistic composition perspective auxiliary design system.

[0030] The technical effects and advantages of the artistic composition perspective auxiliary design method and system of the present invention:

[0031] While the user is adjusting the elements in the composition in real time, including adding, moving, and deleting objects, the system uses algorithms such as edge detection and Hough transform to quickly identify the vanishing point and center of gravity in the image, and then predicts the user's element adjustment method, preloads the perspective effect, and adopts an incremental update strategy. The system only performs perspective calculations on the affected areas to ensure fast feedback. Finally, after the user adjusts the elements, they can be displayed on the user interface in real time, enabling the designer to immediately see the result of the adjustment.

[0032] By performing pre-computations, the present invention reduces the buffer time during real-time operations, significantly improves the creation efficiency, and reduces the time for repeated modifications. At the same time, by recording the user's operation history and feedback, the system can continuously optimize the algorithm to meet the user's personalized needs. Brief Description of the Drawings

[0033] Figure 1 It is a flowchart of an artistic composition perspective-assisted design method of the present invention;

[0034] Figure 2 It is a structural diagram of an artistic composition perspective-assisted design system of the present invention. Detailed Embodiments

[0035] 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 of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0036] While the user is adjusting the elements in the composition in real time, including adding, moving, and deleting objects, the system uses algorithms such as edge detection and Hough transform to quickly identify the vanishing point and center of gravity in the image, and then predicts the user's element adjustment method, preloads the perspective effect, and adopts an incremental update strategy. The system only performs perspective calculations on the affected areas to ensure fast feedback. Finally, after the user adjusts the elements, they can be displayed on the user interface in real time, enabling the designer to immediately see the result of the adjustment, significantly improving the creation efficiency, and reducing the time for repeated modifications. At the same time, by recording the user's operation history and feedback, the system can continuously optimize the algorithm to meet the user's personalized needs.

[0037] Example 1, as Figure 1 shown, an artistic composition perspective-assisted design method of the present invention includes the following steps:

[0038] Obtain the target image to be geometrically perspective, which can be introduced into the scene or composition manually or through image input, such as photos or hand-drawn drafts, etc., and obtain relevant perspective parameters, such as viewpoints, lines of sight, vanishing points, and horizontal lines, etc. Similarly, the perspective parameters can also be manually input or obtained through algorithm calculation. Match the geometric features of the target image with the features of each preset splitting mode to determine the corresponding feature matching degrees under each preset splitting mode; the geometric features of the target image are obtained by combining multiple relevant perspective parameters, such as the vanishing point of the target image and the viewpoint of the target image, etc.

[0039] Determine the pre-calculation area during the geometric perspective of the target image according to the corresponding feature matching degrees under each preset splitting mode.

[0040] It should be noted that the preset splitting modes can be set according to the actual situation. For example, it can include but is not limited to the following 7 types:

[0041] From top to bottom, from bottom to top, from left to right, from right to left, from inside to outside, from outside to inside, and disordered.

[0042] From top to bottom means that the user's operation starts from the top of the picture and gradually splits or adjusts elements towards the bottom. It is common in compositions where the upper areas such as the sky, tree crowns, and building roofs are prioritized.

[0043] From bottom to top means that the user starts from the bottom of the picture and gradually adjusts or splits elements upwards. It is usually used for adjustments where the lower areas such as the ground and foreground objects are prioritized.

[0044] From left to right means that the user starts from the left side of the picture and gradually adjusts elements to the right.

[0045] From right to left means that the user starts from the right side of the picture and gradually adjusts to the left.

[0046] From inside to outside means that the user first adjusts the core elements in the center of the picture and then gradually expands outwards to adjust the peripheral elements. This method is usually used for compositions that emphasize the main object, such as portraits and the center of buildings.

[0047] From outside to inside means that the user starts adjusting from the edge or periphery and gradually moves towards the center. It is common in compositions with large depth of field. The user first processes the large scenery in the periphery and then gradually processes the details in the center.

[0048] Disordered means that the user's operation does not follow a fixed logic and randomly selects elements in the picture for adjustment or deletion. Such user behavior is relatively free and cannot be predicted linearly.

[0049] The preset splitting mode feature is the core area of the preset splitting mode, that is, the starting area and the ending area corresponding to the preset splitting mode. For example, in the top-down splitting mode, its feature is the starting top area and the ending bottom area, that is, its starting area is the top area and the ending area is the bottom area; in the outside-in splitting mode, its feature is the starting outer extension area and the ending inner area, that is, its starting area is the outer extension area and the ending area is the inner area, and so on.

[0050] A matching method between the geometric features of the target image and the features of each preset splitting mode is as follows:

[0051] The geometric features of the target image include the vanishing point of the target image and the viewpoint of the target image;

[0052] Calculate the relative distance value between the viewpoint of the target image and the centroid of the starting area of the corresponding preset splitting mode;

[0053] And calculate the number value of the vanishing points where the vanishing point of the target image is located in the starting area and the ending area of the corresponding preset splitting mode;

[0054] After normalizing the relative distance value and the number value of the vanishing points, add them up to determine the feature matching degree between the target image and the corresponding preset splitting mode.

[0055] It should be noted that the viewpoint of the target image is the position where the viewer's line of sight naturally stays, which is the visual center of the image. If the center of the image is obvious, the user is very likely to start splitting and adjusting elements from here. Therefore, in this embodiment, the viewpoint of the target image is compared with the starting area of the preset splitting mode, so as to reflect the possibility of starting splitting from the starting area. The smaller the relative distance value, the greater the possibility.

[0056] At the same time, the vanishing point of the target image will guide the viewer's line of sight. Usually, the user will adjust the composition along the direction of the perspective line, and may choose to start adjusting from the area where the vanishing point is located ("from inside to outside"), or start from one side according to the extension direction of the line (such as "from top to bottom" or "from left to right"). Its position can be determined by edge detection and Hough transform algorithm, or manually input when the image is acquired.

[0057] It should be noted that the vanishing point on an image depends on the number and direction of parallel lines in the scene, and is determined by the parallel line groups in different directions in the image. Each group of parallel lines will have a vanishing point, so there can be one or more vanishing points in the image.

[0058] Through the Hough transform, the straight lines in the image can be effectively detected and their intersection points can be calculated, so as to determine the position of the vanishing point. That is, the edge image is obtained through edge detection, then the Hough transform is applied to transform it into the parameter space, and finally the intersection points of the straight lines are calculated to obtain the vanishing point. This method is the prior art and will not be elaborated in detail here.

[0059] Therefore, in this embodiment, the vanishing points of the target image in the starting region and the ending region of the preset splitting mode are counted. If there are more vanishing points of the target image in the starting region and the ending region of the preset splitting mode, it indicates that the image is more likely to extend along this perspective direction, and at this time, it is more likely to be split according to this preset splitting mode.

[0060] Determine the pre-calculation region during the geometric perspective of the target image according to the feature matching degrees corresponding to each preset splitting mode, which specifically includes the following steps:

[0061] Sort the feature matching degrees corresponding to each preset splitting mode, and select the preset splitting mode with the largest feature matching degree value as the final splitting mode;

[0062] If the final splitting mode is disordered, no pre-operation is performed, otherwise, the splitting perspective pre-operation is performed according to the final splitting mode.

[0063] Embodiment 2. In Embodiment 1 of the present invention, by matching the geometric features of the target image with the features of each preset splitting mode, the feature matching degrees corresponding to each preset splitting mode are determined, so as to determine the final splitting mode. However, in the actual process, for a certain target image, it is very likely that the feature matching degree values corresponding to multiple preset splitting modes calculated finally are similar. At this time, only screening by the feature matching degree obviously has a certain error. Therefore, in this embodiment, for the above problems, further supplements are made.

[0064] If the feature matching degrees corresponding to multiple preset splitting modes are greater than the preset matching degree threshold, and the deviation of the feature matching degrees corresponding to multiple preset splitting modes is less than the preset deviation threshold, perform secondary screening on the feature matching degrees corresponding to multiple preset splitting modes to determine the final splitting mode.

[0065] Specifically, it includes the following steps:

[0066] Obtain the splitting habit data of system users, including the usage proportions of each preset splitting mode of the users, and determine similar images in the historical database according to the geometric features of the target image. Obtain the usage proportions of each preset splitting mode corresponding to the similar images, and comprehensively determine the corresponding weight coefficients of each preset splitting mode according to the usage proportions of each preset splitting mode of the users and the usage proportions of each preset splitting mode corresponding to the similar images. Extract the weight coefficients of the preset splitting modes to be secondarily screened, perform weighted calculations based on the corresponding feature matching degrees, and set the preset splitting mode with the largest weighted calculation result as the final splitting mode.

[0067] If the final splitting mode is disordered, no pre-operation is performed; otherwise, splitting perspective pre-operation is performed according to the final splitting mode.

[0068] Through secondary screening of the feature matching degrees of multiple preset splitting modes, especially in the case where the feature matching degree values are similar, by combining the user's splitting habits and the usage proportions of historical similar images, the present invention can significantly reduce the risk of misjudgment, thereby improving the accuracy of the final splitting mode. By combining feature matching, user habits, and historical data, the system forms a comprehensive judgment mechanism, which can more intelligently adapt to the splitting requirements in different situations and improve the flexibility and practicality of composition.

[0069] Furthermore, determining similar images in the historical database according to the geometric features of the target image specifically includes the following steps:

[0070] Calculate the similarity between the images in the historical database and the number of vanishing points and the centroid position of the target image in different directions, and compare it with the preset similarity threshold. Mark the images in the historical database that are greater than the preset similarity threshold as similar images.

[0071] It should be noted that the evaluation and calculation of similarity are prior arts. The present embodiment provides a similarity calculation method, including the following steps:

[0072] Perform vanishing point detection, use the Hough transform to detect the vanishing points, determine the intersection coordinates of the straight lines of the target image (i.e., the vanishing points), and retrieve the vanishing point coordinates of the images in the historical database.

[0073] Calculate the centroid coordinates of the target image through pixel weighting, and retrieve the centroid coordinates of the images in the historical database.

[0074] Construct the feature vector of each image, including information such as the number of vanishing points, vanishing point coordinates, and centroid position.

[0075] For the target image and the images in the historical database, calculate the similarity through the Euclidean distance or other distance metrics. The similarity value is between 0 and 1, and the closer it is to 1, the more similar it is.

[0076] Based on the calculated similarity values, the image with the highest similarity can be selected for further analysis. If the similarity values of multiple images exceed a preset threshold, they can be regarded as similar images, and a comprehensive evaluation can be carried out according to the usage ratios of their splitting patterns.

[0077] It should be noted that the detection of vanishing points using the Hough transform specifically includes:

[0078] Use the Canny edge detection algorithm to extract edges and obtain a binary image E;

[0079] Input the edge image E into the Hough transform, and calculate the parameters (r, θ) of each edge point (x, y); r = xcos(θ) + ysin(θ); in the parameter space, count the votes for each (r, θ);

[0080] Find the (r, θ) with the most votes in the parameter space, which corresponds to the straight line in the image;

[0081] For each two detected straight lines L1 and L2, calculate their intersection point (i.e., the vanishing point);

[0082] The straight line equation can be expressed as: y = -(cos(θ) / sin(θ))x + (r / sin(θ));

[0083] Solve the system of equations to obtain the vanishing point coordinates as (xd, yd).

[0084] The calculation expression for calculating the centroid by pixel weighting is:

[0085]

[0086] Among them, I(i, j) is the intensity value of the image at pixel (i, j), usually the brightness or color value, (Cx, Cy) is the centroid coordinate, H is the height of the image, representing the number of pixels in the vertical direction. That is, the number of rows of the image; W is the width of the image, representing the number of pixels in the horizontal direction. That is, the number of columns of the image; when calculating the centroid, these two parameters are used to traverse each pixel in the image to calculate the centroid coordinate of the image.

[0087] Substitute the calculated vanishing point coordinates, centroid coordinates, and the number of vanishing points into the feature vector for similarity calculation, so as to determine similar images.

[0088] Comprehensively determine the corresponding weight coefficients of each preset splitting pattern according to the usage ratios of each preset splitting pattern of the user and the usage ratios of each preset splitting pattern corresponding to the similar images. The specific method is as follows:

[0089] Mark the usage proportions of each preset splitting mode of the user and the usage proportions of each preset splitting mode corresponding to the similar images as a and b respectively. Then, the calculation formula for the importance coefficient of each preset splitting mode can be Imp(i) = a + b. In the formula, Imp(i) is the importance coefficient of each preset splitting mode, and i represents the serial number of each preset splitting mode;

[0090] After calculating the importance coefficients of each preset splitting mode, compare the magnitudes of the importance coefficients of each preset splitting mode;

[0091] Obviously, the larger the usage proportions of each preset splitting mode of the user and the usage proportions of each preset splitting mode corresponding to the similar images, the more frequently used the preset splitting mode is. At this time, when the matching degrees are not much different, the preset splitting mode is more important.

[0092] At the same time, it should be noted that the usage proportions of each preset splitting mode of the user and the usage proportions of each preset splitting mode corresponding to the similar images can also be weighted and calculated according to the actual situation, which will not be elaborated here.

[0093] Assign weights to the importance coefficients of each preset splitting mode respectively by the priority chart method to determine the weight values of each preset splitting mode.

[0094] For example, if the number of preset splitting modes to be secondarily screened is 4, then the weights are assigned to the importance coefficients of each preset splitting mode by the priority chart method as shown in Table 1 below:

[0095]

[0096]

[0097] Table 1

[0098] After sorting the magnitudes of the importance coefficients of each preset splitting mode, correspond them to splitting modes 1, 2, 3, and 4 in descending order respectively, so as to obtain the corresponding weight coefficients for each.

[0099] As Figure 2 shown, the present invention also discloses an artistic composition perspective auxiliary design system for implementing the above design method, including a user interface module, an image processing module, a similarity analysis module, a splitting mode evaluation module, and a data storage module, and the modules are signal-connected to each other;

[0100] The user interface module is used to provide a front-end interface for the user to interact with the system, including a toolbar, a canvas area, and real-time feedback display, and helps the user input images and related parameters.

[0101] The image processing module is used to preprocess and extract features from the target image for subsequent analysis and calculation. It also includes a Hough transform unit for implementing the Hough transform algorithm to detect straight lines and vanishing points in the image.

[0102] The similarity analysis module is used to compare the features of the target image with the images in the historical database to determine similar images.

[0103] The splitting mode evaluation module is used to evaluate the preset splitting modes and screen them according to the feature matching degree and user habits. It also includes a weight calculation unit for calculating the weight coefficients of each preset splitting mode according to the user's splitting habits and the historical usage proportion of similar images.

[0104] The data storage module is used to store the data in the data processing process of the artistic composition perspective auxiliary design system.

[0105] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0106] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed in this document can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application of the technical solution and the invention constraints. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0107] In addition, in each embodiment of this application, the various functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0108] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0109] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An artistic composition perspective auxiliary design method, characterized in that, Including the following steps; Obtain a target image to be geometrically perspective, and obtain relevant perspective parameters. Match the geometric features of the target image with the features of each preset splitting mode to determine the feature matching degree corresponding to each preset splitting mode; The geometric features of the target image are obtained by combining multiple relevant perspective parameters, including the vanishing point of the target image and the viewpoint of the target image; Determine the pre-calculation area during the geometric perspective of the target image according to the feature matching degree corresponding to each preset splitting mode; The feature of the preset splitting mode is the core area of the preset splitting mode, including the starting area and the ending area corresponding to the preset splitting mode; A method for matching the geometric features of the target image with the features of each preset splitting mode is as follows: The geometric features of the target image include the vanishing point of the target image and the viewpoint of the target image; Calculate the relative distance value between the viewpoint of the target image and the centroid of the starting area of the corresponding preset splitting mode; And calculate the number value of the vanishing points where the vanishing point of the target image is located in the starting area and the ending area of the corresponding preset splitting mode; After normalizing the relative distance value and the number value of the vanishing points, sum them to determine the feature matching degree between the target image and the corresponding preset splitting mode.

2. The perspective auxiliary design method for artistic composition according to claim 1, wherein: The preset splitting modes include unordered splitting and multiple fixed-direction splittings.

3. The method for auxiliary design of artistic composition perspective according to claim 2, wherein: Determine the pre-calculation area during the geometric perspective of the target image according to the feature matching degree corresponding to each preset splitting mode, specifically including the following steps: Sort the feature matching degrees corresponding to each preset splitting mode, and select the preset splitting mode with the largest feature matching degree value as the final splitting mode; If the final splitting mode is unordered, no pre-operation is performed, otherwise, split perspective pre-operation is performed according to the final splitting mode.

4. The method for auxiliary design of artistic composition perspective according to claim 1, wherein: If the feature matching degrees corresponding to multiple preset splitting modes are greater than a preset matching degree threshold, and the deviation of the feature matching degrees corresponding to multiple preset splitting modes is less than a preset deviation threshold, perform secondary screening on the feature matching degrees corresponding to multiple preset splitting modes to determine the final splitting mode.

5. The method for auxiliary design of artistic composition perspective according to claim 4, wherein: Obtain the splitting habit data of the system user, including the usage proportion of each preset splitting mode of the user, and determine the similar images in the historical database according to the geometric features of the target image. Obtain the usage proportion of each preset splitting mode corresponding to the similar images. Comprehensively determine the corresponding weight coefficients of each preset splitting mode according to the usage proportion of each preset splitting mode of the user and the usage proportion of each preset splitting mode corresponding to the similar images. Extract the weight coefficients of the preset splitting modes to be secondarily screened, perform weighted calculation according to the corresponding feature matching degrees, and set the preset splitting mode with the largest weighted calculation result as the final splitting mode; If the final splitting mode is unordered, no pre-operation is performed, otherwise, split perspective pre-operation is performed according to the final splitting mode.

6. An artistic composition perspective auxiliary design system for implementing the artistic composition perspective auxiliary design method according to any one of claims 1-5, characterized in that: It includes a user interface module, an image processing module, a similarity analysis module, a splitting mode evaluation module, and a data storage module, with signal connections between the modules; The user interface module is used to provide a front-end interface for the user to interact with the system, for the user to input images and related parameters; The image processing module is used to preprocess and extract features from the target image. It also includes a Hough transform unit for implementing the Hough transform algorithm to detect lines and vanishing points in the image; The similarity analysis module is used to compare the features of the target image with the images in the historical database to determine similar images; The splitting mode evaluation module is used to evaluate the preset splitting modes, screen them according to the feature matching degree and user habits. It also includes a weight calculation unit for calculating the weight coefficients of each preset splitting mode according to the user's splitting habits and the historical usage proportion of similar images; The data storage module is used to store the data in the data processing process of the artistic composition perspective auxiliary design system.

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