Agricultural plant growth three-dimensional visual synthesis method based on topology and geometric structure data
Through the three-dimensional visual synthesis method of agricultural plant growth based on topological and geometric structure data, the problem of low accuracy in the existing technology is solved, and high-precision three-dimensional visualization of plant growth is achieved.
Patent Information
- Application Number
- CN202510198574.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-23
- Publication Date
- 2025-06-10
AI Technical Summary
The existing plant growth simulation methods cannot take into account the dynamic changes of topological structure and the true presentation of geometric details, resulting in low accuracy.
A three-dimensional visual synthesis method for agricultural plant growth based on topology and geometric structure data is proposed. By obtaining the growth parameters and environmental conditions of the target plant, the first topology structure is constructed and refined into the first geometric structure, and the topology structure and geometric structure are then optimized, and the growth three-dimensional model data is finally integrated.
This method can effectively improve the accuracy of three-dimensional visualization of plant growth, so that the growth three-dimensional model data takes into account the dynamic changes of topological structure and the true presentation of geometric details.
Smart Images
Figure CN120125751A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of agricultural informatization technology, and in particular, to a three-dimensional visualization synthesis method for agricultural plant growth based on topological and geometric structure data. Background Art
[0002] In the process of agricultural scientific research and crop growth monitoring, simulating the growth process of plants is of great significance for understanding plant growth laws, predicting yields, and optimizing agricultural management measures. However, existing modeling methods usually cannot simultaneously take into account the dynamic changes of topological structures and the realistic presentation of geometric details, resulting in low accuracy of existing plant growth simulations.
[0003] In summary, the technical problems existing in the related art need to be improved. Summary of the Invention
[0004] The main purpose of the embodiments of this application is to propose a three-dimensional visualization synthesis method for agricultural plant growth based on topological and geometric structure data, which can effectively improve the accuracy of three-dimensional visualization of plant growth.
[0005] To achieve the above object, the embodiments of this application propose a three-dimensional visualization synthesis method for agricultural plant growth based on topological and geometric structure data, and the method includes the following steps:
[0006] Obtain the growth parameters of the target plant and the environmental conditions where the target plant is located;
[0007] Construct a first topological structure of the target plant according to the growth parameters and the environmental conditions;
[0008] Refine a first geometric structure in the first topological structure through a preset algorithm to obtain a second geometric structure;
[0009] Optimize the first topological structure and the second geometric structure to obtain a second topological structure and a third geometric structure;
[0010] Integrate the second topological structure and the third geometric structure to obtain the three-dimensional model data of the growth of the target plant.
[0011] In some embodiments, the obtaining the growth parameters of the target plant and the environmental conditions where the target plant is located includes:
[0012] Obtain the growth parameters of the target plant at different growth stages, where the growth parameters include growth rate, number of leaves, or number of branches;
[0013] And obtain the environmental conditions corresponding to the target plant at different growth stages, where the environmental conditions include light information or temperature and humidity information.
[0014] In some embodiments, constructing the first topological structure of the target plant according to the growth parameters and the environmental conditions includes:
[0015] Generating the target connection relationships of the various parts in the target plant based on a graph theory algorithm and a geometric constraint algorithm according to the growth parameters and the environmental conditions;
[0016] Constructing the first topological structure according to the connection relationships of the various parts in the target plant.
[0017] In some embodiments, generating the target connection relationships of the various parts in the target plant based on a graph theory algorithm and a geometric constraint algorithm according to the growth parameters and the environmental conditions includes:
[0018] Determining the to-be-processed connection relationships of the various parts in the target plant according to the growth parameters and the graph theory algorithm;
[0019] Determining the geometric constraint conditions in the geometric constraint algorithm according to the growth parameters and the environmental conditions;
[0020] Adjusting the to-be-processed connection relationships according to the geometric constraint conditions to obtain the target connection relationships of the various parts in the target plant.
[0021] In some embodiments, refining the first geometric structure in the first topological structure through a preset algorithm includes:
[0022] Refining the first geometric structure in the first topological structure through a parametric surface fitting algorithm, a spline interpolation algorithm, or a geometric evolution algorithm, where the geometric evolution algorithm includes a geometric evolution model based on plant growth rules.
[0023] In some embodiments, refining the first geometric structure in the first topological structure through a parametric surface fitting algorithm, a spline interpolation algorithm, or a geometric evolution algorithm includes:
[0024] Generating the geometric shapes of the main trunk and branches in the first geometric structure through a parametric surface fitting algorithm;
[0025] Simulating the unfolded shape of the leaves in the first geometric structure through the spline interpolation algorithm;
[0026] Refining the geometric shapes of the main trunk and branches in the first geometric structure and the unfolded shape of the leaves in the first geometric structure through the geometric evolution algorithm.
[0027] In some embodiments, optimizing the first topological structure and the second geometric structure includes:
[0028] Optimize the first topological structure and the second geometric structure through a joint optimization strategy, where the joint optimization strategy includes a geometric smoothness optimization strategy, a topological rationality maintenance strategy, a growth consistency optimization strategy, or an overall aesthetics optimization strategy.
[0029] In some embodiments, optimizing the first topological structure and the second geometric structure through the joint optimization strategy includes:
[0030] Optimize the branch surface shape data and the leaf surface shape data in the second geometric structure through the geometric smoothness optimization strategy;
[0031] Optimize the branch connection relationship in the first topological structure through the topological rationality maintenance strategy;
[0032] Optimize the growth data in the first topological structure and the second geometric structure through the growth consistency optimization strategy;
[0033] Optimize the leaf arrangement data and the branch distribution data in the second geometric structure through the overall aesthetics optimization strategy.
[0034] In some embodiments, the method further includes the following steps:
[0035] Convert the format of the growth three-dimensional model data to obtain data in a preset file format.
[0036] In some embodiments, the method further includes the following steps:
[0037] Obtain a visualization request instruction;
[0038] Retrieve target visualization data from several pieces of the preset file format data according to the visualization request instruction;
[0039] Control the visualization display state according to the target visualization data.
[0040] The embodiments of the present application at least include the following beneficial effects: The present application provides a three-dimensional visualization synthesis method for agricultural plant growth based on topological and geometric structure data. After obtaining the growth parameters and growth environment conditions of a target plant, construct the first topological structure of the target plant according to the growth parameters and environmental conditions, then refine the first geometric structure in the first topological structure through a preset algorithm to obtain a second geometric structure, and then optimize the first topological structure and the second geometric structure to obtain a second topological structure and a third geometric structure. After that, integrate the second topological structure and the third geometric structure to obtain the growth three-dimensional model data of the target plant, so that the dynamic changes of the topological structure and the real presentation of geometric details can be taken into account in the growth three-dimensional model data, and thus the accuracy of plant growth three-dimensional visualization can be effectively improved. Description of the Drawings
[0041] Figure 1 It is a flowchart of the three-dimensional visualization synthesis method for agricultural plant growth based on topological and geometric structure data provided by an embodiment of the present application. Detailed implementation manners
[0042] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application.
[0043] It can be understood that the terms "first", "second", etc. used in the present application can be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, as used herein, the words "if", "when" can be interpreted as "when...", "when...", or "in response to determining".
[0044] The terms "at least one", "a plurality", "each", "any one", etc. used in the present application, at least one includes one, two or more than two, a plurality includes two or more than two, each refers to each of the corresponding plurality, and any one refers to any one of the plurality.
[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.
[0046] In the related art, during agricultural scientific research and crop growth monitoring, simulating the growth process of plants is of great significance for understanding plant growth laws, predicting yields, and optimizing agricultural management measures. However, existing modeling methods usually cannot simultaneously take into account the dynamic changes in topological structures and the realistic presentation of geometric details, resulting in low accuracy of existing plant growth simulations.
[0047] In view of this, an agricultural plant growth three-dimensional visualization synthesis method based on topological and geometric structure data is provided in an embodiment of the present application. After obtaining the growth parameters and growth environment conditions of the target plant, a first topological structure of the target plant is constructed according to the growth parameters and environmental conditions. Then, the first geometric structure in the first topological structure is refined through a preset algorithm to obtain a second geometric structure. After optimizing the first topological structure and the second geometric structure to obtain a second topological structure and a third geometric structure, the second topological structure and the third geometric structure are integrated to obtain the three-dimensional model data of the growth of the target plant, so that the dynamic changes of the topological structure and the true presentation of geometric details can be taken into account in the three-dimensional model data of the growth, and thus the accuracy of the three-dimensional visualization of plant growth can be effectively improved.
[0048] The embodiments of the present application will be specifically described below with reference to the accompanying drawings:
[0049] Figure 1 is an optional flowchart of the agricultural plant growth three-dimensional visualization synthesis method based on topological and geometric structure data provided by an embodiment of the present application, Figure 1 The method in may include but is not limited to steps S101 to S105:
[0050] Step S101, obtain the growth parameters of the target plant and the environmental conditions where the target plant is located;
[0051] Step S102, construct a first topological structure of the target plant according to the growth parameters and environmental conditions;
[0052] Step S103, refine the first geometric structure in the first topological structure through a preset algorithm to obtain a second geometric structure;
[0053] Step S104, optimize the first topological structure and the second geometric structure to obtain a second topological structure and a third geometric structure;
[0054] Step S105, integrate the second topological structure and the third geometric structure to obtain the three-dimensional model data of the growth of the target plant.
[0055] It can be understood that obtaining the growth parameters of the target plant can be achieved by obtaining the growth parameters of the target plant at different growth stages. Among them, the growth parameters include growth rate, number of leaves or number of branches. Obtaining the environmental conditions where the target plant is located can be to obtain the environmental conditions corresponding to the target plant at different growth stages. Among them, the environmental conditions include light information or temperature and humidity information. Specifically, there is a temporal connection between the growth parameters and environmental conditions of the target plant at each growth stage. Exemplarily, when a batch of fruit trees are planted in spring, since spring is the time when they are just planted and there is more rain and suitable temperature in spring, this growth stage belongs to the budding period of the fruit trees. During the budding period, the corresponding growth parameters of the fruit trees are fast growth rate, many leaves and fewer branches, and the environmental conditions are suitable light, lower temperature but higher humidity. When the fruit trees enter the growth period, perhaps this period enters summer, so the corresponding growth parameters of the fruit trees are relatively fast growth rate, many leaves and many branches, and the environmental conditions are sufficient light, higher temperature but lower humidity. Thus, it can be seen that the growth parameters and environmental conditions of plants vary at different growth stages. In this embodiment, by obtaining the growth parameters and environmental conditions at different growth stages, the accuracy of subsequent modeling can be effectively improved.
[0056] In the embodiment of the present application, the process of constructing the first topological structure of the target plant based on the growth parameters and environmental conditions can be to generate the target connection relationships of each part of the target plant based on the growth parameters and environmental conditions, using graph theory algorithms and geometric constraint algorithms, and then construct the first topological structure according to the connection relationships of each part of the target plant. It can be understood that the specific processing process of the target connection relationships of each part of the target plant can be to determine the connection relationships to be processed of each part of the target plant according to the growth parameters and graph theory algorithms, and at the same time determine the geometric constraint conditions in the geometric constraint algorithms according to the growth parameters and environmental conditions, and then adjust the connection relationships to be processed according to the geometric constraint conditions, so as to obtain the target connection relationships of each part of the target plant.
[0057] Specifically, graph theory algorithms are a series of methods used to solve problems related to graphs. Among them, a graph is a data structure composed of nodes and edges, used to represent the relationships between different elements. The graph theory algorithm adopted in this embodiment can be a depth-first search algorithm or a breadth-first search algorithm. The depth-first search algorithm starts from a given starting node and goes as deep as possible along the path until there are no unvisited adjacent nodes, and then returns to the previous node to continue the visit. The breadth-first search algorithm starts from a given starting node, first visits all the nodes directly adjacent to this node, and then visits the nodes directly adjacent to these nodes, and so on. In the application process of this embodiment, a specific graph theory algorithm can be selected according to the actual situation. The geometric constraint algorithm refers to the restrictions and regulations imposed on the shape, size, position, orientation, etc. of geometric figures or models when performing geometric figure or model design to meet specific requirements and goals. These constraints can be achieved in different ways, such as using elements such as points, lines, circles, angles, etc. for precise positioning and control to ensure that geometric figures or models meet certain specific constraint conditions.
[0058] It can be understood that after obtaining the first topological structure in this embodiment, the first geometric structure in the first topological structure can be refined through a preset algorithm. The refinement process of this embodiment can be to refine the first geometric structure in the first topological structure through a parametric surface fitting algorithm, a spline interpolation algorithm, or a geometric evolution algorithm. Among them, the geometric evolution algorithm includes a geometric evolution model based on the growth law of plants. Specifically, when refining the first geometric structure in this embodiment, the geometric shapes of the trunk and branches in the first geometric structure are generated through a parametric surface fitting algorithm; the leaf unfolding shape in the first geometric structure is simulated through a spline interpolation algorithm, and thus the leaf unfolding process can be simulated; the geometric shapes of the trunk and branches in the first geometric structure and the leaf unfolding shape in the first geometric structure are refined through a geometric evolution algorithm to ensure that the geometric features in the model conform to the actual growth form of plants.
[0059] It can be understood that after obtaining the first topological structure and the second geometric structure in this embodiment, the first topological structure and the second geometric structure can be optimized through a joint optimization strategy. Among them, the joint optimization strategy includes a geometric smoothness optimization strategy, a topological rationality maintenance strategy, a growth consistency optimization strategy, or an overall aesthetics optimization strategy. Specifically, the process of optimizing the first topological structure and the second geometric structure through the joint optimization strategy can be to optimize the shape data of the branch surface and the leaf surface in the second geometric structure through the geometric smoothness optimization strategy; to optimize the branch connection relationship in the first topological structure through the topological rationality maintenance strategy; to optimize the growth data in the first topological structure and the second geometric structure through the growth consistency optimization strategy; to optimize the leaf arrangement data and the branch distribution data in the second geometric structure through the overall aesthetics optimization strategy.
[0060] In the embodiments of the present application, the geometric smoothness optimization strategy includes, but is not limited to, the curvature smoothing algorithm. The curvature smoothing algorithm is a technique used to reduce jagged lines in 3D models. It achieves a smoothing effect by moving vertices along the direction of the vertex normal vector, thereby better maintaining the original shape of the model. Different from Laplacian smoothing, in curvature-based smoothing, when moving vertices, their positions are opposite to the direction of the normal vector. In this embodiment, by optimizing the geometric smoothness optimization strategy for the surface shape data of branches and the surface shape data of leaves in the second geometric structure, the irregularities on the surfaces of branches and leaves can be reduced, ensuring the smooth continuity of the geometric model.
[0061] Specifically, in the processing process of the topological rationality maintenance strategy, the biological characteristics of plant growth can be combined to ensure the rationality of the topological structure through topological constraint conditions, such as avoiding branch intersections or leaf overlaps. The growth consistency optimization strategy can utilize the growth model of plants to ensure that the generated geometric shapes and topological structures are consistent with the growth process of plants under different environmental conditions. The overall aesthetics optimization strategy can ensure that the finally generated three-dimensional model has natural aesthetic features by simulating growth patterns in nature, such as the spiral arrangement of leaves and the distribution angles of branches.
[0062] In the embodiments of the present application, after integrating the second topological structure and the third geometric structure to obtain the growth three-dimensional model data of the target plant, the growth three-dimensional model data is format-converted to obtain preset file format data. Among them, the preset file format data can include, but is not limited to, data saved in common three-dimensional file formats such as STL, OBJ, and PLY, which is convenient for use in scenarios such as agricultural scientific research, plant growth monitoring, and smart agriculture management. Specifically, after the data format is converted in this embodiment, when a visualization request instruction is obtained, the target visualization data can be retrieved from several preset file format data according to the visualization request instruction, and then the visualization display state can be controlled according to the target visualization data, facilitating the observation and analysis of the dynamic process of plant growth by agricultural researchers.
[0063] In some embodiments, the embodiments of the present application can also provide a visualization synthesis system corresponding to the above method. Specifically, the visualization synthesis system has the following modules:
[0064] Topology generation module: used to generate the first topological structure of the plant at different growth stages according to the growth parameters and environmental conditions of the input plant. Among them, the topology generation module can generate the connection relationships between various parts of the plant (such as the main trunk, branches and leaves, roots) by combining graph theory algorithms and geometric constraint techniques, ensuring that the topological structure conforms to the natural growth law and biological significance of the plant.
[0065] Geometric refinement module: used to further refine the geometric structure based on the generation of the first topological structure.
[0066] Joint optimization strategy: used to adopt a joint optimization strategy for real-time synchronous optimization throughout the processes of topology generation and geometric refinement.
[0067] Data synthesis and output: used to integrate the optimized topology and geometric data and output the final 3D model data of plant growth.
[0068] It can be understood that the method of this embodiment can be applied to agricultural scientific research, and a 3D plant model conforming to real growth characteristics can be generated through the method of this application embodiment. Specifically, during the application of this embodiment, the connection structure of the plant at different growth stages is generated by the topology generation module in the corresponding system of the method of this application embodiment, and then the geometric refinement module is used to perform surface fitting and refinement processing on the topological structure. Finally, the generated model conforms to the growth law of the plant both in topological connection and geometric shape.
[0069] Specifically, this embodiment can also be applied to intelligent agricultural monitoring, and the growth process of crops can be simulated through the method of this application embodiment. Specifically, after inputting the plant growth environment and structural constraint conditions, this embodiment can utilize the topology generation module and geometric refinement module in the corresponding system of the method of this application embodiment to work together to generate a 3D plant model with a real topological structure and fine geometric details, so as to monitor the growth process of crops and predict the yield of crops through the 3D plant model.
[0070] In summary, the method of this application embodiment has the following beneficial effects:
[0071] First, through the joint optimization strategy of topology and geometry, this embodiment realizes efficient geometric model synthesis, significantly improving the efficiency of designing and generating complex models;
[0072] Second, through joint optimization, this embodiment ensures the consistency of the topological structure and geometric shape during the generation process, reducing the mismatch problems caused by independently processing topological and geometric data;
[0073] Third, the method of this embodiment can also be applicable to various application scenarios, including industrial design, virtual reality content generation, game development, etc., and has high versatility.
[0074] The preferred embodiments of this application embodiment have been illustrated above with reference to the accompanying drawings, and thus do not limit the scope of rights of this application embodiment. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of this application embodiment shall fall within the scope of rights of this application embodiment.
Claims
1. A three-dimensional visualization synthesis method for agricultural plant growth based on topological and geometric structure data, characterized in that: The method comprises the following steps: Acquiring growth parameters of a target plant and environmental conditions of the target plant; constructing a first topological structure of the target plant according to the growth parameters and the environmental conditions; Refining the first geometric structure in the first topological structure by using a preset algorithm to obtain a second geometric structure; Optimizing the first topological structure and the second geometric structure to obtain a second topological structure and a third geometric structure; The second topological structure and the third geometric structure are integrated to obtain the three-dimensional growth model data of the target plant.
2. The method according to claim 1, characterized in that The step of obtaining the growth parameters of the target plant and the environmental conditions of the target plant includes: Acquiring growth parameters of the target plant at different growth stages, wherein the growth parameters include growth rate, number of leaves or number of branches; And obtaining the environmental conditions corresponding to the target plant at different growth stages, wherein the environmental conditions include light information or temperature and humidity information.
3. The method according to claim 1, characterized in that The step of constructing the first topological structure of the target plant according to the growth parameters and the environmental conditions comprises: According to the growth parameters and the environmental conditions, generating target connection relationships of various parts of the target plant based on a graph theory algorithm and a geometric constraint algorithm; The first topological structure is constructed according to the connection relationship between various parts of the target plant.
4. The method according to claim 3, characterized in that The step of generating target connection relationships of various parts of the target plant based on the growth parameters and the environmental conditions and based on a graph theory algorithm and a geometric constraint algorithm includes: Determine the connection relationship to be processed of each part of the target plant according to the growth parameter and the graph theory algorithm; Determining geometric constraints in the geometric constraint algorithm according to the growth parameters and the environmental conditions; The connection relationship to be processed is adjusted according to the geometric constraint condition to obtain the target connection relationship of each part in the target plant.
5. The method according to claim 1, characterized in that The step of refining the first geometric structure in the first topological structure by using a preset algorithm includes: The first geometric structure in the first topological structure is refined by a parameterized surface fitting algorithm, a spline interpolation algorithm or a geometric evolution algorithm, and the geometric evolution algorithm includes a geometric evolution model based on plant growth laws.
6. The method according to claim 5, characterized in that The step of refining the first geometric structure in the first topological structure by using a parameterized surface fitting algorithm, a spline interpolation algorithm or a geometric evolution algorithm comprises: Generate the geometric shapes of the trunk and branches in the first geometric structure by using a parametric surface fitting algorithm; simulating the unfolded shape of the blade in the first geometric structure by the spline interpolation algorithm; The geometric shapes of the trunk and branches in the first geometric structure and the unfolded shape of the leaves in the first geometric structure are refined by the geometric evolution algorithm.
7. The method according to claim 1, characterized in that The optimizing the first topological structure and the second geometric structure comprises: The first topological structure and the second geometric structure are optimized by a joint optimization strategy, wherein the joint optimization strategy includes a geometric smoothness optimization strategy, a topological rationality maintenance strategy, a growth consistency optimization strategy or an overall aesthetics optimization strategy.
8. The method according to claim 7, characterized in that The optimizing the first topological structure and the second geometric structure by a joint optimization strategy comprises: Optimizing the branch surface shape data and the leaf surface shape data in the second geometric structure by using the geometric smoothness optimization strategy; Optimizing the branch connection relationship in the first topological structure by using the topological rationality maintenance strategy; optimizing the growth data in the first topological structure and the second geometric structure by the growth consistency optimization strategy; The leaf arrangement data and branch distribution data in the second geometric structure are optimized by the overall aesthetic optimization strategy.
9. The method according to claim 1, characterized in that: The method further comprises the following steps: The growth three-dimensional model data is format converted to obtain data in a preset file format.
10. The method according to claim 9, characterized in that The method further comprises the following steps: Get visualization request instructions; Retrieving target visualization data from a plurality of preset file format data according to the visualization request instruction; The visualization display state is controlled according to the target visualization data.