Method, device and storage medium for generating a real vegetation brush for drawing software

Abstract

This invention discloses a method, apparatus, and medium for generating realistic vegetation brushes for drawing software, belonging to the field of digital painting. The method includes: Step 1, obtaining vegetation sample parameters: acquiring vegetation sample parameters according to a pre-determined type of vegetation sample parameters to be collected; Step 2, parsing and preprocessing the acquired vegetation sample parameters to obtain vegetation population characteristic parameters; Step 3, using the obtained vegetation population characteristic parameters, generating vegetation brushes for the drawing software based on a radial distribution function; Step 4, using the generated vegetation brushes to draw vegetation in the drawing software, determining whether the drawn vegetation meets the requirements; if yes, proceed to Step 5; otherwise, proceed to Step 1; Step 5, completing the generation of the vegetation brush. This method can generate vegetation brushes for drawing software that accurately reflect the natural characteristics of vegetation, and can be easily optimized based on user feedback to improve the realism of the drawn vegetation.

Description

Technical Field

[0001] This invention relates to the field of digital painting software technology, and more particularly to a method for generating realistic vegetation brushes for painting software. Background Technology

[0002] In digital painting, mainstream drawing software such as Photoshop and Procreate are widely used, and vegetation brushes are a common tool for creators to depict natural scenes. However, the construction method of these vegetation brushes is relatively basic, mainly relying on manually preset textures. In practice, although users can manually adjust some common attributes of vegetation brushes, such as size, transparency, and hardness, the drawn vegetation has obvious limitations in simulating the spatial distribution patterns of natural vegetation growth. Taking the drawing of forest scenes as an example, when using traditional vegetation brushes, the distribution of trees presents a relatively fixed uniformity, making it difficult to accurately reflect the "dense in the near and sparse in the far" cluster characteristics of real forest vegetation. In real forest ecosystems, due to the influence of various factors such as light, soil nutrients, and species competition, the distribution of vegetation is not uniform, but presents complex clusters and gradient changes. However, traditional vegetation brushes cannot simulate and reflect these natural factors, resulting in forest scenes that lack realism and ecological rationality.

[0003] To address the shortcomings of traditional vegetation brushes, some plugins are attempting to introduce vegetation generation algorithms into drawing software to create vegetation brushes, thereby enhancing the naturalness of the brush drawing effect. For example, some plugins use random functions to control the distribution of vegetation elements. However, these plugins rely solely on a single algorithm, lacking a close correlation with actual vegetation parameters, and may result in vegetation scenes that lack realism and ecological consistency.

[0004] Existing digital brush technologies, whether traditional brush tools or plugins based on single algorithms, fail to fully incorporate the biological characteristics of vegetation when generating vegetation brush effects, resulting in insufficient naturalness in the rendered vegetation scenes. Realistic vegetation growth is governed by multiple biological laws, including plant morphogenesis, photosynthesis, and competitive and symbiotic relationships. These factors collectively determine the appearance and spatial distribution of vegetation. However, current vegetation brush technologies often focus only on surface visual effects, neglecting these underlying biological mechanisms.

[0005] Furthermore, current vegetation brush generation technologies for drawing software, especially those plugins that generate vegetation brushes based on a single algorithm, exhibit significant limitations in adaptability when faced with diverse vegetation types (such as herbs, shrubs, and trees). They fail to reflect the vast differences in morphology, growth habits, and spatial distribution among different types of vegetation, and thus cannot create more realistic and ecologically sound vegetation scenes.

[0006] In view of this, the present invention is hereby proposed. Summary of the Invention

[0007] The purpose of this invention is to provide a method, device, and storage medium for generating realistic vegetation brushes for drawing software. This method can learn vegetation sample parameters and apply them to brush drawing in drawing software, so that the effect of brush drawing vegetation is consistent with the growth law of real vegetation, thereby solving the above-mentioned technical problems existing in the prior art.

[0008] The objective of this invention is achieved through the following technical solution: A method for generating realistic vegetation brushes for drawing software includes: Step 1, Obtain vegetation sample parameters: Obtain vegetation sample parameters according to the pre-determined type of vegetation sample parameters to be collected; Step 2: Analyze and preprocess the vegetation sample parameters obtained in Step 1 to obtain the result of XX; Step 3: Using the vegetation community characteristic parameters obtained in Step 2, generate vegetation brushes for the drawing software based on the radial distribution function; Step 4: Use the vegetation brush generated in Step 3 to draw vegetation in the drawing software. Determine whether the drawn vegetation meets the requirements. If yes, proceed to Step 5; otherwise, proceed to Step 1. Step 5: Complete the generation of this realistic vegetation brush.

[0009] A processing apparatus, comprising: At least one memory for storing one or more programs; At least one processor is capable of executing one or more programs stored in the memory, such that when the processor executes one or more programs, the processor can implement the method of the present invention.

[0010] A readable storage medium storing a computer program that, when executed by a processor, enables the implementation of the methods described in this invention.

[0011] Compared with the prior art, the method, apparatus and storage medium for generating realistic vegetation brushes for drawing software provided by the present invention have the following beneficial effects: By collecting vegetation sample parameters and generating vegetation brushes for drawing software based on these parameters using a radial distribution function, the brushes can learn from the vegetation sample parameters and draw vegetation scenes that conform to natural characteristics. By setting judgment and feedback steps, the brushes can be optimized based on the drawing results, thus improving the realism of the final vegetation drawing effect. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating a method for generating realistic vegetation brushes for drawing software, as provided in an embodiment of the present invention.

[0014] Figure 2 A flowchart illustrating the steps for obtaining vegetation sample parameters in the method provided in this embodiment of the invention.

[0015] Figure 3 This is a flowchart illustrating the practical application of the method for generating realistic vegetation brushes for drawing software, as provided in this embodiment of the invention. Detailed Implementation

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the specific content of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments, which do not constitute a limitation of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0017] First, the following explanations are provided for the terms that may be used in this article: The term "and / or" means that either or both can be achieved simultaneously. For example, X and / or Y means that it includes both "X" or "Y" as well as the three cases of "X and Y".

[0018] The terms "comprising," "including," "containing," "having," or other similar semantic descriptions should be interpreted as non-exclusive inclusion. For example, including a technical feature element (such as raw material, component, ingredient, carrier, dosage form, material, size, part, component, mechanism, device, step, process, method, reaction conditions, processing conditions, parameter, algorithm, signal, data, product or article of manufacture, etc.) should be interpreted as including not only the expressly listed technical feature element, but also other technical feature elements that are not expressly listed and are well-known in the art.

[0019] The term "composed of" excludes any technical features not expressly listed. When used in a claim, it closes the claim to exclude all technical features other than those expressly listed, except for associated conventional impurities. If the term appears only in a clause of a claim, it limits the claim to the elements expressly listed in that clause; elements recited in other clauses are not excluded from the overall claim.

[0020] Unless otherwise explicitly specified or limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this document according to the specific circumstances.

[0021] The terms “center,” “longitudinal,” “lateral,” “length,” “width,” “thickness,” “upper,” “lower,” “front,” “back,” “left,” “right,” “vertical,” “horizontal,” “top,” “bottom,” “inner,” “outer,” “clockwise,” and “counterclockwise” indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience and simplification of description and do not imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this document.

[0022] The solution provided by this invention will be described in detail below. Contents not described in detail in the embodiments of this invention are prior art known to those skilled in the art. Where specific conditions are not specified in the embodiments of this invention, they shall be performed according to conventional conditions in the art or conditions recommended by the manufacturer. Reagents or instruments used in the embodiments of this invention whose manufacturers are not specified are all conventional products that can be purchased commercially.

[0023] like Figure 1 As shown, this invention provides a method for generating realistic vegetation brushes for drawing software, comprising: Step 1, Obtain vegetation sample parameters: Obtain vegetation sample parameters according to the pre-determined type of vegetation sample parameters to be collected; Step 2: Analyze and preprocess the vegetation sample parameters obtained in Step 1 to obtain vegetation community characteristic parameters; Step 3: Using the vegetation community characteristic parameters obtained in Step 2, generate vegetation brushes for the drawing software based on the radial distribution function; Step 4: Use the vegetation brush generated in Step 3 to draw vegetation in the drawing software. Determine whether the drawn vegetation meets the requirements. If yes, proceed to Step 5; otherwise, proceed to Step 1. Step 5: Complete the generation of this realistic vegetation brush.

[0024] Preferably, in step 1 of the above method, the pre-determined types of vegetation sample parameters to be collected include: Individual size, population characteristics, and morphological parameters of vegetation.

[0025] Preferably, in the above method, the individual dimensions of the vegetation include: plant height and crown width; The community characteristics of the vegetation include: density gradient and distribution pattern; The morphological parameters of the vegetation include: leaf shape and branching angle.

[0026] See Figure 2 In step 1 of the above method, obtaining vegetation sample parameters includes: At least one of the following: on-site measurement and acquisition, image recognition and acquisition, and 3D software-generated sampling and acquisition.

[0027] Preferably, in the above method, the on-site measurement and acquisition is performed by using professional measuring tools to measure the parameters of the actual vegetation to obtain vegetation sample parameters; or, vegetation sample parameters are obtained from the vegetation sample data measured on-site. Image recognition acquisition involves processing vegetation images using image recognition software to automatically identify and extract relevant vegetation sample parameters; The sampling and acquisition of 3D software-generated vegetation involves sampling and acquiring vegetation sample parameters from the vegetation generated and rendered by 3D software.

[0028] Preferably, in step 3 of the above method, vegetation community characteristic parameters obtained in step 2 are used to generate vegetation brushes for the drawing software based on the radial distribution function, including: The obtained vegetation community characteristic parameters are converted into the characteristic values ​​of the radial distribution function curve. Based on the characteristic values ​​of the obtained radial distribution function curve, three-dimensional spatial distribution weights are assigned to the vegetation brush elements. The element density attenuation coefficient of the vegetation brush is adjusted with the three-dimensional spatial distribution weights. According to the predetermined parameter mapping rules, the correspondence between the feature parameters of vegetation samples and the attributes of vegetation brushes is established to obtain plant brushes generated for drawing software.

[0029] Preferably, step 3 of the above method further includes: dividing vegetation growth areas using an integrated Voronoi diagram algorithm, and optimizing the spatial layout of vegetation brush elements according to the divided vegetation growth areas. The integrated Voronoi algorithm is a constraint and modulation of the RDF algorithm, which runs automatically in the program without human intervention.

[0030] Preferably, in the above method, step 4 determines whether the drawn vegetation meets the requirements in the following ways:

[0031] Step 41: Combine the element density attenuation coefficient of the vegetation brush and calculate the statistical consistency of the L1 distance of the drawn vegetation. Step 41 above includes: Step 411: Determine the fitting error of the radial distribution function; Step 412: Based on the fitting error and combined with the element density attenuation coefficient of the vegetation brush set in step 3, the L1 distance of the drawn vegetation is calculated through the nearest neighbor distance distribution. The element density attenuation coefficient of the vegetation brush is used to weight the density contribution of different spatial regions. Step 42: Then, determine whether the drawn vegetation meets the requirements by using the area distribution of Voronoi cells.

[0032] This invention also provides a processing apparatus, comprising: At least one memory for storing one or more programs; At least one processor is capable of executing one or more programs stored in the memory, such that when the one or more programs are executed by the processor, the processor can implement the methods described above.

[0033] The present invention further provides a readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0034] In summary, the method of the present invention can generate vegetation brushes that accurately reflect the natural characteristics of vegetation for drawing software, and can be easily optimized based on user feedback to improve the realism of the drawn vegetation.

[0035] To more clearly demonstrate the technical solution and its effects provided by the present invention, the following detailed description of the solution provided by the embodiments of the present invention is provided with reference to specific examples.

[0036] Example 1 like Figure 1 As shown, this embodiment provides a method for generating realistic vegetation brushes for drawing software, the method comprising: The four stages—vegetation sample parameter collection and input, parameter analysis and preprocessing, brush generation based on algorithms such as the radial distribution function, and brush effect output and feedback optimization—are closely linked, forming a complete closed-loop method. This ensures that the generated vegetation brushes accurately reflect the natural characteristics of the vegetation and can be continuously optimized based on user feedback. The specific steps are as follows: Step 1, vegetation sample parameter collection: Determining the types of vegetation sample parameters: Identify the types of vegetation sample parameters to be collected, which mainly include: individual plant size parameters (such as plant height, crown width, leaf length, leaf width, etc.), population characteristic parameters (such as density gradient, distribution pattern, average spacing, etc.), and morphological parameters (such as leaf shape, branching angle, leaf color, etc.).

[0037] Use any of the following data collection methods: (11) Field Measurement and Collection: For existing vegetation, use professional measuring tools (such as measuring tapes, height gauges, etc.) to measure parameters. For example, when measuring the height of a tree, use a height gauge to measure vertically from the bottom of the trunk to the top of the crown; when measuring the length and width of leaves, select representative leaves and use a measuring tape to measure their longest and widest points. Record the measurement data in a data table, which includes information such as parameter name, measured value, measurement unit, measurement time, and measurement location.

[0038] (12) Image recognition acquisition: For vegetation that cannot be measured in the field, parameters are acquired through high-resolution images. Image recognition software (such as deep learning-based image recognition tools) is used to process the vegetation images to automatically identify and extract relevant parameters. For example, the shape and color parameters of the leaves are identified through leaf images. The software analyzes the outline features of the leaves to determine the shape and determines the RGB values ​​of the colors through color analysis.

[0039] Preferably, in the above image recognition acquisition, the image recognition software used can adopt an open-source vegetation feature adaptive recognition model: it can automatically recognize morphological parameters such as leaf shape (recognition accuracy rate of 92.3%) and branching angle (error ≤ 3°) through deep learning algorithms (such as ResNet-50 network), without the need for manual annotation.

[0040] (13) 3D software generation: For vegetation generated by 3D software, render a suitable distribution and perform relevant sampling.

[0041] Step 2, Vegetation Sample Parameter Input: Users input the collected vegetation sample parameters through the input interface provided by the plugin. The input interface is designed to be simple and intuitive, providing corresponding input controls for different types of parameters, such as numerical input boxes (for inputting numerical parameters such as plant height and crown width), drop-down selection boxes (for selecting optional parameters such as leaf shape), and image upload buttons (for uploading the original image collected through image recognition). After inputting the parameters, the user clicks the "Confirm Input" button, and the parameters are transmitted to the parameter parsing and preprocessing module for processing.

[0042] Parameter standardization pipeline: Automatically performs unit conversion (e.g., inches to centimeters), outlier filtering (based on the 3σ principle), and data completion (using the KNN algorithm with a completion rate of 89%) on the input vegetation sample parameters, and outputs a structured parameter set.

[0043] Step 3, simulation of vegetation spatial distribution based on radial distribution function (RDF): RDF parametric modeling: converting vegetation community characteristic parameters (such as average spacing and density gradient) into characteristic values ​​(peak position and curve slope) of the RDF curve. For example, "when the average spacing is 5 meters, the RDF curve has a peak at r=5 meters and a slope of 0.3". Spatial distribution weight allocation: Based on the RDF calculation results, three-dimensional spatial weights (x-axis density, y-axis direction, z-axis hierarchy) are assigned to brush elements to make the generated vegetation distribution present natural characteristics such as "dense near and sparse far" and "dominant species clusters".

[0044] This invention deeply integrates RDF with vegetation sample parameters, combining abstract mathematical functions with specific vegetation growth patterns, thus overcoming the limitations of a single random algorithm.

[0045] Step 4: Use the vegetation brush generated in Step 3 to draw vegetation in the drawing software. Determine whether the drawn vegetation meets the requirements. If yes, proceed to Step 5; otherwise, proceed to Step 1. Step 5: Complete the generation of this vegetation brush.

[0046] In summary, the method of this invention can generate vegetation brushes that accurately reflect the natural characteristics of vegetation for drawing software, and can be easily optimized based on user feedback to improve the realism of the drawn vegetation. It can demonstrate that herbaceous plants are typically short in stature, have short growth cycles, and are more densely and irregularly distributed, often forming large areas of ground cover; shrubs are characterized by multiple branches and relatively compact crowns, and their distribution often exhibits a certain degree of clustering, but the spacing between individuals is relatively larger than that of herbaceous plants; trees are tall, have diverse crown shapes, require more light and space, and their distribution is usually sparse and has a certain degree of layering.

[0047] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0048] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for generating realistic vegetation brushes for drawing software, characterized in that, include: Step 1, Obtain vegetation sample parameters: Obtain vegetation sample parameters according to the pre-determined type of vegetation sample parameters to be collected; Step 2: Analyze and preprocess the vegetation sample parameters obtained in Step 1 to obtain vegetation community characteristic parameters; Step 3: Using the vegetation community characteristic parameters obtained in Step 2, generate vegetation brushes for the drawing software based on the radial distribution function; Step 4: Use the vegetation brush generated in Step 3 to draw vegetation in the drawing software. Determine whether the drawn vegetation meets the requirements. If yes, proceed to Step 5; otherwise, proceed to Step 1. Step 5: Complete the generation of this vegetation brush.

2. The method for generating realistic vegetation brushes for drawing software according to claim 1, characterized in that, In step 1, the pre-determined types of vegetation sample parameters to be collected include: Individual size, population characteristics, and morphological parameters of vegetation.

3. The method for generating realistic vegetation brushes for drawing software according to claim 2, characterized in that, The individual dimensions of the vegetation include: plant height and crown width; The community characteristics of the vegetation include: density gradient and distribution pattern; The morphological parameters of the vegetation include: leaf shape and branching angle.

4. The method for generating realistic vegetation brushes for drawing software according to any one of claims 1-3, characterized in that, In step 1, obtaining vegetation sample parameters includes: At least one of the following: on-site measurement and acquisition, image recognition and acquisition, and 3D software-generated sampling and acquisition.

5. The method for generating realistic vegetation brushes for drawing software according to claim 4, characterized in that, The aforementioned field measurement and acquisition involves using professional measuring tools to measure the parameters of actual vegetation to obtain vegetation sample parameters; or, obtaining vegetation sample parameters from vegetation sample data measured in the field. Image recognition acquisition involves using image recognition software to process vegetation images, automatically identify and extract relevant vegetation sample parameters; The sampling and acquisition of 3D software-generated vegetation involves sampling and acquiring vegetation sample parameters from the vegetation generated and rendered by 3D software.

6. The method for generating realistic vegetation brushes for drawing software according to any one of claims 1-3, characterized in that, In step 3, vegetation community characteristic parameters obtained in step 2 are used to generate vegetation brushes for the drawing software based on the radial distribution function, including: The obtained vegetation community characteristic parameters are converted into the characteristic values ​​of the radial distribution function curve. Based on the characteristic values ​​of the obtained radial distribution function curve, three-dimensional spatial distribution weights are assigned to the vegetation brush elements. The element density attenuation coefficient of the vegetation brush is adjusted with the three-dimensional spatial distribution weights. According to the predetermined parameter mapping rules, the correspondence between the feature parameters of vegetation samples and the attributes of vegetation brushes is established to obtain plant brushes generated for drawing software.

7. The method for generating realistic vegetation brushes for drawing software according to claim 6, characterized in that, Step 3 further includes: dividing vegetation growth areas using the Voronoi diagram algorithm integrated into the drawing software, and optimizing the spatial layout of vegetation brush elements according to the divided vegetation growth areas.

8. The method for generating realistic vegetation brushes for drawing software according to any one of claims 1-3, characterized in that, In step 4, the following methods are used to determine whether the drawn vegetation meets the requirements: Step 41: Combine the element density attenuation coefficient of the vegetation brush and calculate the statistical consistency of the L1 distance of the drawn vegetation. Step 42: Then, determine whether the drawn vegetation meets the requirements by using the area distribution of Voronoi cells.

9. A processing device, characterized in that, include: At least one memory for storing one or more programs; At least one processor is capable of executing one or more programs stored in the memory, such that when the one or more programs are executed by the processor, the processor can perform the method according to any one of claims 1-8.

10. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it can implement the method described in any one of claims 1-8.

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