Rural cultural heritage protection method

Abstract

The invention relates to the technical field of data processing, and provides a rural cultural heritage protection method, which comprises the following steps: acquiring historical rural cultural heritage data, constructing a standard digital image, acquiring and processing the cultural heritage data in real time, performing feature extraction and coordinate data matching, comparing error information and determining an error region. And finally, performing field inspection by using inspection equipment. And when it is detected that the cultural heritage changes significantly, early warning information is generated in time. According to the method, the problem that the rural cultural heritage protection data cannot be dynamically detected in the prior art is solved, the protection efficiency and accuracy are improved, and powerful support is provided for sustainable development and inheritance of the rural cultural heritage.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a rural cultural heritage protection method. Background Art

[0002] Rural cultural heritage refers to the sum of various material and intangible cultural heritages that have been handed down from generation to generation in rural areas and have historical, artistic, scientific and social and cultural values. Rural cultural heritage includes ancient farming methods, traditional handicrafts, vernacular architecture, folk activities, oral legends, folk music and dance, and festival ceremonies. Rural cultural heritage not only reflects the historical changes and cultural diversity of rural society, but is also the crystallization of farmers' wisdom and creativity. It is of great significance to maintaining cultural diversity, promoting sustainable development of rural areas, and enhancing community cohesion.

[0003] In the process of protecting rural cultural heritage, the details of the shape, texture and color of rural cultural heritage are digitally collected with millimeter-level accuracy through advanced photogrammetry, 3D scanning and other technologies. The data are then classified and stored in a special database. The database not only provides researchers with convenient query and research tools, but also provides a guarantee for the long-term preservation of cultural heritage. At the same time, the collected data is modeled in 3D using computer software, so that rural cultural heritage can be "alive" in a virtual form. The virtual model can not only be used for display and dissemination, but also for simulated restoration and analysis. For example, the restoration plan is previewed on the digital model to evaluate the effects of different plans, so as to select the best restoration strategy.

[0004] Rural cultural heritage protection has the following technical pain points in data processing: the scale of rural cultural heritage protection data is huge, and is in dynamic change, and the formats are diverse, making it difficult to process. The existing rural cultural heritage protection cannot dynamically detect the rural cultural heritage protection data. When errors occur in the existing rural cultural heritage protection data, errors will occur in the prediction of rural cultural heritage protection. For this reason, the present invention provides a rural cultural heritage protection method. Summary of the invention

[0005] In view of the shortcomings of the existing technology, the present invention provides a rural cultural heritage protection method to solve the problem that the existing rural cultural heritage protection cannot dynamically detect the rural cultural heritage protection data. When errors occur in the existing rural cultural heritage protection data, it will lead to errors in the rural cultural heritage protection prediction.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: The present invention provides a method for protecting rural cultural heritage, comprising: Step S101, acquiring historical rural cultural heritage data, the historical rural cultural heritage data including historical rural cultural heritage basic information data, historical rural cultural heritage digital collection data, historical rural cultural heritage status monitoring data and historical and rural cultural heritage dynamic change data, the historical rural cultural heritage digital collection data including historical rural cultural heritage digital images, historical rural cultural heritage three-dimensional model data, historical rural cultural heritage texture information, historical rural cultural heritage color information, historical rural cultural heritage dimensions, historical rural cultural heritage surveying and mapping data, historical rural cultural heritage environmental data and historical rural cultural heritage image data, substituting the historical rural cultural heritage data into the digital twin model to generate rural cultural heritage digital images, and using the rural cultural heritage digital images as standard rural cultural heritage digital images; Step S102, collecting real-time rural cultural heritage data, substituting the real-time rural cultural heritage data into the digital twin model to generate a real-time rural cultural heritage digital image, obtaining the historical rural cultural heritage surveying and mapping data in the standard rural cultural heritage digital image, determining the standard rural cultural heritage digital image coordinate system according to the historical rural cultural heritage surveying and mapping data, converting the real-time rural cultural heritage digital image into a coordinate system consistent with the standard rural cultural heritage digital image, obtaining the real-time rural cultural heritage digital image coordinate system, and summarizing the coordinate data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system to establish a rural cultural heritage digital image coordinate database; Step S103, extracting data features from the standard rural cultural heritage digital image to obtain data features of the standard rural cultural heritage digital image, extracting data features from the real-time rural cultural heritage data to obtain data features of the real-time rural cultural heritage, matching the data features of the standard rural cultural heritage digital image and the data features of the real-time rural cultural heritage in a rural cultural heritage digital image coordinate database to obtain coordinate data corresponding to the data features of the standard rural cultural heritage digital image and coordinate data corresponding to the data features of the real-time rural cultural heritage data, using the coordinate data corresponding to the data features of the standard rural cultural heritage digital image as standard image coordinate data, and using the coordinate data corresponding to the data features of the real-time rural cultural heritage data as image coordinate data to be compared; Step S104, comparing the coordinate data of the image to be compared with the coordinate data of the standard image to obtain coordinate data comparison error information, substituting the coordinate data comparison error information into the real-time rural cultural heritage digital image to obtain a coordinate data comparison error region in the real-time rural cultural heritage digital image, obtaining image features within the coordinate data comparison error region in the real-time rural cultural heritage digital image, obtaining features of the error region to be compared, substituting the coordinate data comparison error information into the standard rural cultural heritage digital image to obtain a coordinate data comparison error region in the standard rural cultural heritage digital image, obtaining image features within the coordinate data comparison error region in the standard rural cultural heritage digital image, and obtaining standard features of the error region; Step S105, obtain the standard feature coordinate information of the error area, obtain the first inspection coordinate information, also obtain the feature coordinate information to be compared in the error area, obtain the second inspection coordinate information, send the first inspection coordinate information and the second inspection coordinate information to the inspection equipment, the inspection equipment includes an inspection robot and an inspection drone, receive data collected by the inspection robot and the inspection drone, obtain real-time inspection image data, compare the real-time inspection image data with the features to be compared in the error area and the standard features of the error area, obtain a real-time inspection error comparison result, if the image feature deformation in the real-time inspection error comparison result is greater than the preset maximum deformation value, then generate rural cultural heritage protection early warning information.

[0007] Furthermore, the rural cultural heritage protection method of the present invention, said S102, comprises: The historical rural cultural heritage data is matched in the preset digital twin model knowledge base to obtain the digital twin modeling corresponding to the historical rural cultural heritage data. The collected historical rural cultural heritage data is combined with digital twin technology to construct a digital twin model of the rural cultural heritage. On the basis of the digital twin model, the digital image of the rural cultural heritage is generated through rendering and other technologies. The digital image of the rural cultural heritage includes color, texture and size.

[0008] Furthermore, the rural cultural heritage protection method of the present invention, said S103, comprises: Extract coordinate point data from the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system; Merge the coordinate point data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system into the dataset; Import the coordinate data merged into the dataset into the database table, set the database access permissions, back up the database at a preset time period, and monitor the database operation information, including CPU usage, memory usage, and query response time.

[0009] Furthermore, the rural cultural heritage protection method of the present invention, said S104, comprises: For the coordinate points where the comparison image coordinate data matches the standard image coordinate data, the spatial distance between the comparison image coordinate data and the standard image coordinate data is calculated as the coordinate data comparison error; An error threshold is set. When the coordinate data comparison error exceeds the error threshold, the coordinate points whose errors exceed the difference threshold in the coordinate data of the image to be compared are marked, and the coordinate point marks whose errors exceed the difference threshold are located in the real-time rural cultural heritage digital image to form an error area of ​​the real-time rural cultural heritage digital image; The area corresponding to the coordinate point marks exceeding the difference threshold is located in the standard rural cultural heritage digital image to form the error area of ​​the standard rural cultural heritage digital image.

[0010] Furthermore, the rural cultural heritage protection method of the present invention, said S104, comprises: In the error area of ​​the real-time rural cultural heritage digital image, the feature extraction method is applied to obtain the image features to constitute the features to be compared in the error area; Using the same feature extraction method as that of real-time images, image features are extracted within the error region of the standard rural cultural heritage digital image to obtain standard features of the error region; The extracted features to be compared in the error area and the standard features in the error area are sorted, and the sorted feature information is output for visual display of the error area and the extracted features on the image.

[0011] Furthermore, the rural cultural heritage protection method of the present invention, said S105, comprises: Extracting coordinate information from the standard features of the error area to form first inspection coordinate information, and extracting coordinate information from the features to be compared in the error area to form second inspection coordinate information; Integrate the first inspection coordinate information and the second inspection coordinate information, and send the integrated coordinate information to the inspection robot and the inspection drone via wireless communication; Inspection robots and inspection drones move to the locations corresponding to the coordinate information for inspection based on the received coordinate information. After completing the task, the inspection equipment will transmit the collected real-time inspection image data back via wireless communication; Perform necessary preprocessing on the received real-time inspection image data, and compare the preprocessed real-time inspection image data with the extracted error area features to be compared and the error area standard features one by one; The deformation degree of the image features in the real-time inspection image is evaluated by a machine learning algorithm, and the calculated deformation degree is compared with the preset maximum deformation value; If the real-time inspection error comparison results show that the deformation of the image features exceeds the preset maximum deformation value, there is a potential risk of damage to the rural cultural heritage.

[0012] Furthermore, the rural cultural heritage protection method of the present invention, said S105, comprises: If the image feature deformation in the real-time inspection error comparison result is less than the preset maximum deformation value, there is no potential risk of damage to the rural cultural heritage. The real-time inspection error comparison result and the historical rural cultural heritage data are used to optimize the rural cultural heritage digital image using a genetic algorithm to obtain an optimized rural cultural heritage digital image, which is then used to replace the original rural cultural heritage digital image.

[0013] The beneficial effects of the present invention are mainly reflected in the following aspects: The present invention realizes dynamic monitoring of the status of cultural heritage by collecting rural cultural heritage data in real time and comparing it with standard digital images. When data anomalies are detected or cultural heritage undergoes significant changes, early warning information can be generated in a timely manner, making it possible to take protective measures in a timely manner. By using digital twin technology and three-dimensional modeling, the present invention can display the status of cultural heritage with a high-precision virtual model, allowing researchers and managers to understand the current status of cultural heritage more intuitively and improve the accuracy of protection work.

[0014] Through feature extraction and coordinate data matching, the present invention can accurately locate the error area in the cultural heritage, and generate inspection coordinate information to guide inspection equipment (such as inspection robots and inspection drones) to conduct on-site inspections, which not only reduces the blindness of the inspection work, but also improves the pertinence and efficiency of the inspection.

[0015] When the real-time inspection results show that there is no potential risk of damage to the cultural heritage, the present invention uses a genetic algorithm to optimize the digital image to obtain an image with higher quality and more obvious features, which not only improves the availability of the digital image, but also improves the timeliness of the digital record of cultural heritage.

[0016] The present invention protects rural cultural heritage through scientific methods and technical means, which helps to maintain cultural diversity, promote rural sustainable development, and enhance community cohesion. This is of great significance for inheriting and promoting rural culture and promoting rural revitalization.

[0017] The present invention combines digital twin technology, 3D modeling, machine learning algorithms and other advanced technologies to provide a new solution for the protection of rural cultural heritage. With the continuous development of technology and the expansion of application scenarios, this method has broad application prospects and huge social value.

[0018] In summary, the present invention provides a rural cultural heritage protection method, which realizes the functions of dynamic monitoring, precise positioning and inspection, data optimization and updating of the cultural heritage status, effectively improves the accuracy of cultural heritage protection, and provides strong support for the sustainable development and inheritance of rural cultural heritage. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 A schematic flow chart of a rural cultural heritage protection method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0022] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0023] The present invention provides a method for protecting rural cultural heritage, comprising: Step S101, acquiring historical rural cultural heritage data, the historical rural cultural heritage data including historical rural cultural heritage basic information data, historical rural cultural heritage digital collection data, historical rural cultural heritage status monitoring data and historical and rural cultural heritage dynamic change data, the historical rural cultural heritage digital collection data including historical rural cultural heritage digital images, historical rural cultural heritage three-dimensional model data, historical rural cultural heritage texture information, historical rural cultural heritage color information, historical rural cultural heritage dimensions, historical rural cultural heritage surveying and mapping data, historical rural cultural heritage environmental data and historical rural cultural heritage image data, substituting the historical rural cultural heritage data into the digital twin model to generate rural cultural heritage digital images, and using the rural cultural heritage digital images as standard rural cultural heritage digital images; In step S101, the present invention constructs a standard rural cultural heritage digital image as a basis for subsequent dynamic detection and comparative analysis. The following is a detailed analysis of this step: Basic information data of historical rural cultural heritage: including basic information such as the name, geographical location, historical background, and cultural value of the heritage.

[0024] Digital collection data of historical rural cultural heritage: Digital images: high-definition images of heritage obtained through photography technology.

[0025] 3D model data: A 3D model of the heritage site generated using 3D scanning technology, containing detailed geometric information.

[0026] Texture information: Material and texture data of heritage surfaces.

[0027] Color information: Heritage color data, ensuring color reproduction of digital images.

[0028] Dimensions: Exact dimensions of the property.

[0029] Surveying and mapping data: data on the spatial location, shape, size, etc. of heritage sites obtained through surveying and mapping methods.

[0030] Environmental data: data about the environment surrounding the heritage, such as light, temperature and humidity.

[0031] Image data: including multimedia data such as videos and dynamic images.

[0032] Historical rural cultural heritage status monitoring data: data obtained from regular or irregular monitoring of the heritage status, reflecting the health status of the heritage.

[0033] Data on dynamic changes in historical and rural cultural heritage: records changes in heritage over time, such as repair records, natural erosion, etc.

[0034] Substituting data into digital twin models: Substituting the collected data of historical rural cultural heritage into the preset digital twin model. A digital twin model is a virtual model that can highly restore real-world entities or systems, including their physical structure, functional characteristics, operating status, etc. Through digital twin technology, the data of historical rural cultural heritage is converted into virtual digital images, which can achieve a high level of accuracy, detail and realism.

[0035] Generate standard rural cultural heritage digital images: After being processed by the digital twin model, digital images of rural cultural heritage are generated. These digital images not only contain the appearance and internal structure information of the heritage, but also incorporate the historical, cultural and environmental background of the heritage. They are preserved as standard rural cultural heritage digital images for subsequent comparative analysis with real-time data.

[0036] The core of step S101 is to comprehensively collect relevant data on historical rural cultural heritage and use digital twin technology to generate high-precision digital images to provide a reliable benchmark for subsequent dynamic detection and early warning systems. This step lays a solid foundation for the collection, comparison and analysis of real-time data in subsequent steps.

[0037] Step S102, collecting real-time rural cultural heritage data, substituting the real-time rural cultural heritage data into the digital twin model to generate a real-time rural cultural heritage digital image, obtaining the historical rural cultural heritage surveying and mapping data in the standard rural cultural heritage digital image, determining the standard rural cultural heritage digital image coordinate system according to the historical rural cultural heritage surveying and mapping data, converting the real-time rural cultural heritage digital image into a coordinate system consistent with the standard rural cultural heritage digital image, obtaining the real-time rural cultural heritage digital image coordinate system, and summarizing the coordinate data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system to establish a rural cultural heritage digital image coordinate database; According to the historical rural cultural heritage surveying and mapping data, the standard rural cultural heritage digital image coordinate system is determined. The specific implementation steps are as follows: The surveying and mapping data of historical rural cultural heritage includes topographic maps, building plans, elevation data, GPS coordinate points, etc. The surveying and mapping data are preprocessed to remove duplicate, erroneous or incomplete data points. The coordinate system of the surveying and mapping data is converted so that all data are unified in the same geographic coordinate system (such as WGS84, UTM, etc.).

[0038] Select an appropriate coordinate system based on the characteristics and protection needs of historical rural cultural heritage. For example, for large cultural heritage areas, you can choose a geographic coordinate system based on the earth's ellipsoid; for small-scale or finely modeled heritage points, you can choose a plane rectangular coordinate system based on the local area. Define the origin, axis, and unit of the coordinate system. The origin can be the center point of the cultural heritage area or a significant landmark point; the axis is usually selected in the east-west or north-south direction; the unit can be meters, centimeters, or millimeters, etc., depending on the accuracy of the surveying and mapping data and the needs of subsequent applications.

[0039] Using the key control points in the surveying and mapping data (such as landmark points and intersections with known coordinates), a coordinate system is established in the digital twin model. The control points will serve as the reference points of the coordinate system for the positioning and registration of subsequent data. The accuracy of the coordinate system is verified by calculating the relative position and distance between the key control points. If large errors or inconsistencies are found, the data needs to be re-preprocessed and the coordinate system needs to be reselected. Other surveying and mapping data points are located and registered according to the established coordinate system so that the positions of all data points in the digital twin model are consistent with the actual ones.

[0040] In the digital twin model, the established coordinate system is used to perform three-dimensional modeling, texture mapping and other operations on the rural cultural heritage to generate high-precision digital images. In the subsequent data processing and analysis process, the stability and accuracy of the coordinate system are continuously monitored. If the coordinate system deviation is found due to data update or model change, it is necessary to correct and optimize it in time, and embed the coordinate system information into the metadata of the digital image to facilitate subsequent data management and application.

[0041] Through the above steps, the standard rural cultural heritage digital image coordinate system established based on the historical rural cultural heritage surveying and mapping data can have a high degree of accuracy and stability, providing a reliable basis for subsequent data processing, analysis and protection decisions. The implementation steps are clear and operational for technical personnel in this field, which helps them understand and implement the technical solution of the present invention.

[0042] In step S102, the present invention collects real-time rural cultural heritage data and unifies the coordinate system with the standard rural cultural heritage digital image for subsequent data comparison and analysis. The following is a detailed analysis of this step: Collect real-time rural cultural heritage data: Use the same or similar technical means as those used to collect historical data to obtain the latest data on rural cultural heritage in real time. This includes but is not limited to digital images, 3D model data, texture information, color information, dimensions, surveying and mapping data, environmental data, and image data.

[0043] Generate real-time digital images of rural cultural heritage: Substitute the collected real-time data into the digital twin model to generate digital images that reflect the current status of rural cultural heritage. These digital images should be consistent with standard rural cultural heritage digital images in format, accuracy and detail to facilitate subsequent comparative analysis.

[0044] Obtain historical surveying and mapping data and determine the coordinate system: Extract the surveying and mapping data of historical rural cultural heritage from the standard rural cultural heritage digital images. These data contain key information such as the spatial location, shape, size, etc. of the heritage.

[0045] Based on historical surveying and mapping data, the coordinate system of the standard rural cultural heritage digital image is determined. This coordinate system will serve as a unified benchmark for the subsequent coordinate conversion of real-time digital images.

[0046] Coordinate system unification: The real-time rural cultural heritage digital image is converted into a coordinate system consistent with the standard rural cultural heritage digital image. This step ensures the consistency of the spatial position and size of the two, which facilitates subsequent data comparison.

[0047] Coordinate data aggregation and database establishment: The coordinate data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system are aggregated and integrated into a unified database.

[0048] Establish a rural cultural heritage digital image coordinate database to store and manage these coordinate data. The database should have efficient data query, retrieval and analysis functions to facilitate data processing and analysis in subsequent steps.

[0049] The core of step S102 is to unify the coordinate systems of real-time rural cultural heritage data and standard data, and to establish a database containing the coordinate data of both. This step provides the necessary data basis for subsequent data feature extraction, comparative analysis and the establishment of an early warning system. By ensuring the temporal and spatial consistency of data, the present invention can more accurately detect changes in rural cultural heritage and issue early warning information in a timely manner.

[0050] Step S103, extracting data features from the standard rural cultural heritage digital image to obtain data features of the standard rural cultural heritage digital image, extracting data features from the real-time rural cultural heritage data to obtain data features of the real-time rural cultural heritage, matching the data features of the standard rural cultural heritage digital image and the data features of the real-time rural cultural heritage in a rural cultural heritage digital image coordinate database to obtain coordinate data corresponding to the data features of the standard rural cultural heritage digital image and coordinate data corresponding to the data features of the real-time rural cultural heritage data, using the coordinate data corresponding to the data features of the standard rural cultural heritage digital image as standard image coordinate data, and using the coordinate data corresponding to the data features of the real-time rural cultural heritage data as image coordinate data to be compared; In step S103, the present invention establishes a connection between the standard rural cultural heritage digital image and the real-time rural cultural heritage data through data feature extraction and matching. The specific process is as follows: Feature extraction is performed on the standard rural cultural heritage digital images. These features represent the key attributes of rural cultural heritage in different aspects, such as shape, texture, color, etc. The extracted features should be able to fully and accurately reflect the status and characteristics of the heritage. Similarly, feature extraction is performed on real-time rural cultural heritage data to obtain the data features of the heritage in its current state. These features should be consistent with the features in the standard images in type, format and accuracy to facilitate subsequent comparative analysis.

[0051] The extracted standard rural cultural heritage digital image data features and real-time rural cultural heritage data features are placed in the previously established rural cultural heritage digital image coordinate database for matching. The matching process is based on the similarity or correlation between the features, aiming to find the correspondence between the two. Through matching, the coordinate data corresponding to the standard rural cultural heritage digital image data features (called standard image coordinate data) and the coordinate data corresponding to the real-time rural cultural heritage data features (called image coordinate data to be compared) can be obtained. These coordinate data reflect the location information of the features in space.

[0052] The standard image coordinate data and the image coordinate data to be compared are classified and sorted to prepare for subsequent data comparison and analysis. The standard image coordinate data is used as a reference benchmark to measure the changes in real-time data; the image coordinate data to be compared represents the characteristic location information of the current heritage status.

[0053] The purpose of step S103 is to spatially associate the standard rural cultural heritage digital image with the real-time data through feature extraction and matching, providing a basis for subsequent data comparison and error analysis. Through this step, the present invention can more accurately locate and analyze the changes in rural cultural heritage, providing a scientific basis for heritage protection.

[0054] Step S104, comparing the coordinate data of the image to be compared with the coordinate data of the standard image to obtain coordinate data comparison error information, substituting the coordinate data comparison error information into the real-time rural cultural heritage digital image to obtain a coordinate data comparison error region in the real-time rural cultural heritage digital image, obtaining image features within the coordinate data comparison error region in the real-time rural cultural heritage digital image, obtaining features of the error region to be compared, substituting the coordinate data comparison error information into the standard rural cultural heritage digital image to obtain a coordinate data comparison error region in the standard rural cultural heritage digital image, obtaining image features within the coordinate data comparison error region in the standard rural cultural heritage digital image, and obtaining standard features of the error region; In step S104, the present invention identifies the error areas in the digital image of the rural cultural heritage by comparing the image coordinate data to be compared with the standard image coordinate data, and extracts the image features of these areas for subsequent analysis and evaluation. The following is a detailed analysis of this step: The coordinate data of the image to be compared is compared point by point with the coordinate data of the standard image. The comparison process focuses on the consistency of the coordinate data in the spatial position to identify any possible deviation or error. Through the comparison, the coordinate data comparison error information is obtained. This error information reflects the degree of difference in coordinate data between the real-time rural cultural heritage digital image and the standard rural cultural heritage digital image.

[0055] Substitute the coordinate data comparison error information into the real-time rural cultural heritage digital image, and locate the error area in the image based on the size and distribution of the error. These areas represent the parts of the real-time image that may have problems compared to the standard image. Similarly, substitute the coordinate data comparison error information into the standard rural cultural heritage digital image to locate the corresponding error area. This step helps to find the reference area in the standard image that corresponds to the real-time image error.

[0056] In the error region of the real-time rural cultural heritage digital image, the feature extraction method is used to obtain the image features. These features constitute the features to be compared in the error region, which reflect the specific performance of the error region in the real-time image, such as shape, texture, color, etc. The same feature extraction method as the real-time image is used to extract image features in the error region of the standard rural cultural heritage digital image. These features constitute the standard features of the error region, which serve as a reference benchmark for evaluating the changes in the error region of the real-time image.

[0057] The extracted error area features to be compared and error area standard features are sorted to ensure their format, accuracy and comparability. The sorted feature information is output for subsequent data analysis, visualization and decision-making for rural cultural heritage protection.

[0058] Step S104 provides important data support for the protection of rural cultural heritage by comparing coordinate data and extracting image features of error regions, helping to identify the differences between real-time images and standard images, and further assessing changes and potential risks in rural cultural heritage.

[0059] Step S105, obtain the standard feature coordinate information of the error area, obtain the first inspection coordinate information, also obtain the feature coordinate information to be compared in the error area, obtain the second inspection coordinate information, send the first inspection coordinate information and the second inspection coordinate information to the inspection equipment, the inspection equipment includes an inspection robot and an inspection drone, receive data collected by the inspection robot and the inspection drone, obtain real-time inspection image data, compare the real-time inspection image data with the features to be compared in the error area and the standard features of the error area, obtain a real-time inspection error comparison result, if the image feature deformation in the real-time inspection error comparison result is greater than the preset maximum deformation value, then generate rural cultural heritage protection early warning information.

[0060] In step S105, the present invention uses the error area feature coordinate information obtained in the previous step to guide the inspection equipment to conduct on-site inspections of rural cultural heritage, and evaluates the status of the cultural heritage by comparing the real-time inspection image data with the error area features. The specific process is as follows: Obtain inspection coordinate information, extract coordinate information from the standard features of the error area as the first inspection coordinate information. These coordinate information guide the inspection equipment to go to the location of the standard features for on-site inspection. Similarly, extract coordinate information from the features to be compared in the error area as the second inspection coordinate information. These coordinate information are used to guide the inspection equipment to focus on the areas that may have problems or changes shown in the real-time image.

[0061] Send inspection coordinate information: Send the first inspection coordinate information and the second inspection coordinate information to the inspection equipment, including the inspection robot and the inspection drone. These devices plan the inspection route according to the received coordinate information and go to the designated location for on-site inspection.

[0062] Collect real-time inspection image data: Inspection robots and inspection drones conduct on-site inspections at designated locations and collect real-time image data. These data reflect the current actual situation of rural cultural heritage, including information on shape, texture, color, etc.

[0063] Compare real-time inspection image data with error area features: Compare real-time inspection image data with previously extracted error area features to be compared and error area standard features. The comparison process focuses on the consistency of image features to assess whether cultural heritage has changed or there are potential risks.

[0064] Generate early warning information for rural cultural heritage protection: Based on the comparison results, calculate the deformation degree of the image features in the real-time inspection image data. If the deformation degree is greater than the preset maximum deformation value, it means that the rural cultural heritage may have changed significantly or there is a serious risk.

[0065] In this case, early warning information on the protection of rural cultural heritage is generated. The early warning information should include detailed descriptions, possible risk types, recommended protection measures, etc., so that relevant managers can take timely measures to protect cultural heritage.

[0066] Step S105 realizes accurate monitoring and early warning of rural cultural heritage by combining digital twin technology and on-site inspections. It can not only timely discover changes or potential risks of cultural heritage, but also provide a scientific basis for the formulation of protection decisions.

[0067] Specifically, the rural cultural heritage protection method of the present invention, said S102 includes: The historical rural cultural heritage data is matched in the preset digital twin model knowledge base to obtain the digital twin modeling corresponding to the historical rural cultural heritage data. The collected historical rural cultural heritage data is combined with digital twin technology to construct a digital twin model of the rural cultural heritage. On the basis of the digital twin model, the digital image of the rural cultural heritage is generated through rendering and other technologies. The digital image of the rural cultural heritage includes color, texture and size.

[0068] The collected historical rural cultural heritage data (such as surveying and mapping data, image data, and literature data) are matched in the preset digital twin model knowledge base. This knowledge base contains digital twin modeling rules and templates for various types of rural cultural heritage. Through matching, the digital twin modeling rules or templates corresponding to the historical data are found, providing a basis for building a digital twin model.

[0069] Using the matched digital twin modeling rules or templates, combined with the collected historical rural cultural heritage data, we begin to build a digital twin model of rural cultural heritage. This process may involve 3D modeling, data fusion, texture mapping and other technologies.

[0070] The digital twin model should accurately reflect key information such as the geometric shape, structural characteristics, and spatial position of rural cultural heritage, and provide a basis for subsequent digital image generation.

[0071] Based on the digital twin model, rendering technology (such as ray tracing, texture rendering, etc.) is used to generate digital images of rural cultural heritage. These digital images should have a high sense of reality and detail expression, and can accurately reflect the color, texture, size and other characteristics of rural cultural heritage. The digital image generation process also needs to consider factors such as lighting conditions, viewing angle selection, and image resolution to ensure that the generated digital images can meet the needs of subsequent analysis and application.

[0072] Through the detailed description of step S102, we can more clearly understand the construction process of the digital twin model of rural cultural heritage and the generation method of digital images. Digital images not only provide basic data for subsequent data feature extraction, comparative analysis and the establishment of early warning systems, but also provide strong support for the protection, display and dissemination of rural cultural heritage.

[0073] Specifically, the rural cultural heritage protection method of the present invention, said S103 includes: Extract coordinate point data from the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system; Merge the coordinate point data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system into the dataset; Import the coordinate data merged into the dataset into the database table, set the database access permissions, back up the database at a preset time period, and monitor the database operation information, including CPU usage, memory usage, and query response time.

[0074] The coordinate data of all key feature points are extracted from the standard rural cultural heritage digital image coordinate system. These coordinate data should accurately reflect the location information of each part of the rural cultural heritage in the standard image. Similarly, the coordinate data of the corresponding feature points are extracted from the real-time rural cultural heritage digital image coordinate system. These coordinate data represent the current status of the rural cultural heritage in the real-time image.

[0075] The coordinate point data extracted from the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system will be merged into a unified dataset, which will be used for subsequent coordinate data matching and comparative analysis.

[0076] Import the merged coordinate data set into a pre-established database table. The database table should be designed to efficiently store and query coordinate data while supporting subsequent data analysis and processing needs.

[0077] Set database access permissions so that only authorized users or systems can access and modify data in the database. This helps protect the security and integrity of the data.

[0078] Back up the database at a preset time period to prevent data loss or damage. The backup data should be stored in a safe and reliable location, and recovery tests should be performed regularly to ensure the effectiveness of the backup. Monitor the operation information of the database, including key indicators such as CPU usage, memory occupancy, and query response time. These indicators can reflect the performance status of the database and promptly discover and resolve potential performance problems. Coordinate data matching and feature extraction, in the database table, match the coordinate data of the standard rural cultural heritage digital image with the coordinate data of the real-time rural cultural heritage digital image. The matching process should be based on factors such as the similarity of feature points and positional relationships.

[0079] After the matching is completed, the coordinate data corresponding to the successfully matched feature points and the specific manifestations of these feature points in the image (such as color, texture, etc.) are extracted to provide a basis for subsequent data comparison and analysis.

[0080] In step S103 , coordinate data is extracted from the standard rural cultural heritage digital image and the real-time rural cultural heritage digital image, and the data is imported into a database for management and analysis.

[0081] Specifically, the rural cultural heritage protection method of the present invention, said S104, comprises: For the coordinate points where the comparison image coordinate data matches the standard image coordinate data, the spatial distance between the comparison image coordinate data and the standard image coordinate data is calculated as the coordinate data comparison error; An error threshold is set. When the coordinate data comparison error exceeds the error threshold, the coordinate points whose errors exceed the difference threshold in the coordinate data of the image to be compared are marked, and the coordinate point marks whose errors exceed the difference threshold are located in the real-time rural cultural heritage digital image to form an error area of ​​the real-time rural cultural heritage digital image; The area corresponding to the coordinate point marks exceeding the difference threshold is located in the standard rural cultural heritage digital image to form the error area of ​​the standard rural cultural heritage digital image.

[0082] For the coordinate points of the matched comparison image coordinate data and the standard image coordinate data, calculate the spatial distance between them. This spatial distance can be obtained by Euclidean distance, Manhattan distance or other suitable spatial distance calculation methods. The calculated spatial distance is used as the coordinate data comparison error, which reflects the degree of deviation in spatial position between the comparison image coordinate data and the standard image coordinate data.

[0083] According to actual needs and application scenarios, a reasonable error threshold is set. This threshold is used to determine whether the coordinate data comparison error exceeds the acceptable range. When the coordinate data comparison error exceeds the error threshold, the corresponding coordinate point in the coordinate data of the image to be compared is marked as an error point. These error points represent the locations in the real-time rural cultural heritage digital image that have significant deviations from the standard image.

[0084] In the real-time rural cultural heritage digital image, the error area is located and marked according to the marked error points. These error areas are the parts of the real-time image that are inconsistent with the standard image or may have problems, and need to be focused on and analyzed. At the same time, in the standard rural cultural heritage digital image, the coordinate points corresponding to the error points marked in the real-time image are found. According to the coordinate points, the area corresponding to the error area of ​​the real-time image is located and marked in the standard image, which is helpful for subsequent comparative analysis and understanding of the source and impact of the error. Step S104 calculates the coordinate data comparison error, sets the error threshold, marks the error point, and locates the error area.

[0085] Specifically, the rural cultural heritage protection method of the present invention, said S104, comprises: In the error area of ​​the real-time rural cultural heritage digital image, the feature extraction method is applied to obtain the image features to constitute the features to be compared in the error area; Using the same feature extraction method as that of real-time images, image features are extracted within the error region of the standard rural cultural heritage digital image to obtain standard features of the error region; The extracted features to be compared in the error area and the standard features in the error area are sorted, and the sorted feature information is output for visual display of the error area and the extracted features on the image.

[0086] Within the determined error region of the real-time rural cultural heritage digital image, appropriate feature extraction methods (such as SIFT, SURF, ORB and other image feature extraction algorithms) are applied to extract image features. Image features include edges, corners, textures, color histograms, etc., which can describe the unique visual attributes within the error region.

[0087] The extracted features are organized into features to be compared in the error region for subsequent comparison with the features of the standard image. The same feature extraction method as the real-time image is used to extract image features in the corresponding error region of the standard rural cultural heritage digital image. The consistency and comparability of feature extraction are ensured to accurately evaluate the difference between the real-time image and the standard image.

[0088] The extracted features are organized into standard features of the error region as a benchmark for comparative analysis. The extracted features to be compared in the error region and the standard features of the error region are organized, including feature descriptions, location information, feature types, etc.

[0089] Output the collated feature information to an appropriate visualization tool or platform, such as image annotation software, geographic information system (GIS), or a specialized cultural heritage management system. Overlay feature markers on the image to visually display error areas and extracted features. This can include drawing feature points, bounding boxes, or heat maps on the image.

[0090] Through visual representation, users can more easily understand the differences between real-time and standard images, and the changes or potential risks to cultural heritage these differences may represent.

[0091] In step S104, features are extracted within the error region between the real-time rural cultural heritage digital image and the standard rural cultural heritage digital image, and the features are sorted and visualized.

[0092] Specifically, the rural cultural heritage protection method of the present invention, said S105, comprises: Extracting coordinate information from the standard features of the error area to form first inspection coordinate information, and extracting coordinate information from the features to be compared in the error area to form second inspection coordinate information; Integrate the first inspection coordinate information and the second inspection coordinate information, and send the integrated coordinate information to the inspection robot and the inspection drone via wireless communication; Inspection robots and inspection drones move to the locations corresponding to the coordinate information for inspection based on the received coordinate information. After completing the task, the inspection equipment will transmit the collected real-time inspection image data back via wireless communication; Perform necessary preprocessing on the received real-time inspection image data, and compare the preprocessed real-time inspection image data with the extracted error area features to be compared and the error area standard features one by one; The deformation degree of the image features in the real-time inspection image is evaluated by a machine learning algorithm, and the calculated deformation degree is compared with the preset maximum deformation value; If the real-time inspection error comparison results show that the deformation of the image features exceeds the preset maximum deformation value, there is a potential risk of damage to the rural cultural heritage.

[0093] Extract key coordinate information from the standard features of the error area to form the first inspection coordinate information. These coordinate information represent the areas that need special attention in the standard image. At the same time, extract corresponding coordinate information from the features to be compared in the error area to form the second inspection coordinate information. These coordinate information represent the areas in the real-time image that are different from the standard image.

[0094] The first inspection coordinate information and the second inspection coordinate information are integrated to ensure that the inspection robot and the inspection drone can receive complete coordinate information that needs to be inspected. The integrated coordinate information is sent to the inspection robot and the inspection drone through wireless communication (such as Wi-Fi, 4G / 5G network, etc.) so that they can accurately move to the designated location for inspection.

[0095] Inspection robots and inspection drones autonomously plan paths based on the received coordinate information and move to the location corresponding to the coordinate information for inspection. During the inspection process, the inspection equipment should be able to capture high-quality real-time inspection image data for subsequent analysis and comparison.

[0096] After the inspection task is completed, the inspection robot and inspection drone will transmit the collected real-time inspection image data back to the central control system or data processing center through wireless communication. The received real-time inspection image data will be subjected to necessary pre-processing operations, such as denoising, correction, cropping, etc., to improve the quality and accuracy of the image data.

[0097] The pre-processed real-time inspection image data is compared with the previously extracted error area features to be compared and error area standard features one by one. Through the comparison, the changes in the image features in the real-time inspection image are analyzed, including changes in shape, position, texture, etc.

[0098] Use machine learning algorithms (such as convolutional neural networks, support vector machines, etc.) to evaluate the degree of deformation of image features in real-time inspection images. The algorithm should be able to accurately calculate the degree of deformation of image features and compare it with the preset maximum deformation value.

[0099] If the real-time inspection error comparison results show that the deformation of the image feature exceeds the preset maximum deformation value, it indicates that there is a potential risk of damage to the rural cultural heritage. At this time, appropriate protection measures should be taken immediately, such as strengthening monitoring and repairing, to ensure the safety and integrity of the rural cultural heritage.

[0100] Specifically, the rural cultural heritage protection method of the present invention, said S105, comprises: If the image feature deformation in the real-time inspection error comparison result is less than the preset maximum deformation value, there is no potential risk of damage to the rural cultural heritage. The real-time inspection error comparison result and the historical rural cultural heritage data are used to optimize the rural cultural heritage digital image using a genetic algorithm to obtain an optimized rural cultural heritage digital image, which is then used to replace the original rural cultural heritage digital image.

[0101] After the real-time inspection image data is compared with the error area features, the deformation degree of the image features is first evaluated. If the real-time inspection error comparison result shows that the deformation of the image features is less than the preset maximum deformation value, it is judged that there is no potential damage risk to the rural cultural heritage.

[0102] Collect and organize real-time inspection error comparison results, including the degree of deformation of image features, location information, etc. Obtain historical rural cultural heritage data, which may include past inspection records, image data, restoration records, etc., to provide a rich information basis for digital image optimization.

[0103] Genetic algorithm is applied for optimization. Genetic algorithm is selected as the optimization tool because it has strong search ability and global optimization ability, and is suitable for dealing with complex optimization problems. The real-time inspection error comparison results and historical rural cultural heritage data are used as the input of the genetic algorithm, and appropriate optimization goals are set (such as improving image clarity, reducing noise, enhancing feature expression, etc.). Through the iterative process of the genetic algorithm, the digital image of rural cultural heritage is continuously optimized until the preset optimization standard or the upper limit of the number of iterations is reached.

[0104] After optimization by genetic algorithm, digital images of rural cultural heritage with higher quality and more obvious features are obtained. Necessary post-processing is performed on the optimized digital images, such as color correction and contrast adjustment, to further improve the image quality.

[0105] Replace the original digital images with the optimized digital images of rural cultural heritage to ensure that the digital records of cultural heritage remain up-to-date and accurate. Update the relevant database or storage system to ensure that the new digital images can be correctly stored, retrieved and used.

[0106] Record the entire optimization and replacement process, including the algorithms used, optimization parameters, optimization results, etc., for subsequent analysis and reference. Archive the digital images and related data before and after optimization to provide strong data support for the long-term protection and management of cultural heritage.

[0107] Through step S105, when there is no potential risk of damage to the rural cultural heritage, the digital image is optimized using the real-time inspection error comparison results and historical data, and the optimized digital image can accurately reflect the current status of the cultural heritage. This step not only improves the quality of the digital image, but also provides a more reliable data basis for the protection and management of cultural heritage.

[0108] The technical solution of the present invention solves the problem that the existing rural cultural heritage protection cannot dynamically detect the rural cultural heritage protection data, and the protection prediction errors caused by the data errors through the following steps: Obtain historical rural cultural heritage data, including basic information, digital collection data, status monitoring data, and dynamic change data. Substitute these data into the digital twin model to generate rural cultural heritage digital images, which will be used as standard rural cultural heritage digital images.

[0109] Real-time rural cultural heritage data is collected and substituted into the digital twin model to generate real-time digital images of rural cultural heritage.

[0110] The coordinate system of the digital image of the standard rural cultural heritage is determined by using the surveying and mapping data, and the real-time digital image is converted into a coordinate system consistent with it. The data of the two coordinate systems are aggregated to establish a rural cultural heritage digital image coordinate database.

[0111] Data features are extracted from standard rural cultural heritage digital images and real-time rural cultural heritage data. Feature matching is performed in the rural cultural heritage digital image coordinate database to obtain standard image coordinate data and image coordinate data to be compared.

[0112] The coordinate data of the image to be compared is compared with the coordinate data of the standard image to obtain coordinate data comparison error information. According to the error information, the error area is located in the real-time rural cultural heritage digital image and the standard rural cultural heritage digital image, and the image features in the error area are extracted.

[0113] According to the coordinate information extracted from the error area features, the inspection coordinate information is generated and sent to the inspection equipment (inspection robot and inspection drone). The real-time inspection image data collected by the inspection equipment is received and compared with the error area features. If the real-time inspection error comparison result shows that the image feature deformation is greater than the preset maximum deformation value, the rural cultural heritage protection warning information is generated.

[0114] The present invention not only realizes the dynamic detection of rural cultural heritage protection data, but also can timely discover and warn when data errors occur, thereby avoiding the problem of errors in rural cultural heritage protection prediction. In addition, through the application of digital twin technology and machine learning algorithms, the present invention improves the accuracy of rural cultural heritage protection.

[0115] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-described embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A method for protecting rural cultural heritage, characterized in that: include: Step S101, acquiring historical rural cultural heritage data, the historical rural cultural heritage data including historical rural cultural heritage basic information data, historical rural cultural heritage digital collection data, historical rural cultural heritage status monitoring data and historical and rural cultural heritage dynamic change data, the historical rural cultural heritage digital collection data including historical rural cultural heritage digital images, historical rural cultural heritage three-dimensional model data, historical rural cultural heritage texture information, historical rural cultural heritage color information, historical rural cultural heritage dimensions, historical rural cultural heritage surveying and mapping data, historical rural cultural heritage environmental data and historical rural cultural heritage image data, substituting the historical rural cultural heritage data into the digital twin model to generate rural cultural heritage digital images, and using the rural cultural heritage digital images as standard rural cultural heritage digital images; Step S102, collecting real-time rural cultural heritage data, substituting the real-time rural cultural heritage data into the digital twin model to generate a real-time rural cultural heritage digital image, obtaining the historical rural cultural heritage surveying and mapping data in the standard rural cultural heritage digital image, determining the standard rural cultural heritage digital image coordinate system according to the historical rural cultural heritage surveying and mapping data, converting the real-time rural cultural heritage digital image into a coordinate system consistent with the standard rural cultural heritage digital image, obtaining the real-time rural cultural heritage digital image coordinate system, and summarizing the coordinate data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system to establish a rural cultural heritage digital image coordinate database; Step S103, extracting data features from the standard rural cultural heritage digital image to obtain data features of the standard rural cultural heritage digital image, extracting data features from the real-time rural cultural heritage data to obtain data features of the real-time rural cultural heritage, matching the data features of the standard rural cultural heritage digital image and the data features of the real-time rural cultural heritage in a rural cultural heritage digital image coordinate database to obtain coordinate data corresponding to the data features of the standard rural cultural heritage digital image and coordinate data corresponding to the data features of the real-time rural cultural heritage data, using the coordinate data corresponding to the data features of the standard rural cultural heritage digital image as standard image coordinate data, and using the coordinate data corresponding to the data features of the real-time rural cultural heritage data as image coordinate data to be compared; Step S104, comparing the coordinate data of the image to be compared with the coordinate data of the standard image to obtain coordinate data comparison error information, substituting the coordinate data comparison error information into the real-time rural cultural heritage digital image to obtain a coordinate data comparison error region in the real-time rural cultural heritage digital image, obtaining image features within the coordinate data comparison error region in the real-time rural cultural heritage digital image, obtaining features of the error region to be compared, substituting the coordinate data comparison error information into the standard rural cultural heritage digital image to obtain a coordinate data comparison error region in the standard rural cultural heritage digital image, obtaining image features within the coordinate data comparison error region in the standard rural cultural heritage digital image, and obtaining standard features of the error region; Step S105, obtain the standard feature coordinate information of the error area, obtain the first inspection coordinate information, also obtain the feature coordinate information to be compared in the error area, obtain the second inspection coordinate information, send the first inspection coordinate information and the second inspection coordinate information to the inspection equipment, the inspection equipment includes an inspection robot and an inspection drone, receive data collected by the inspection robot and the inspection drone, obtain real-time inspection image data, compare the real-time inspection image data with the features to be compared in the error area and the standard features of the error area, obtain a real-time inspection error comparison result, if the image feature deformation in the real-time inspection error comparison result is greater than the preset maximum deformation value, then generate rural cultural heritage protection early warning information.

2. The rural cultural heritage protection method according to claim 1, characterized in that: The S102 includes: The historical rural cultural heritage data is matched in the preset digital twin model knowledge base to obtain the digital twin modeling corresponding to the historical rural cultural heritage data. The collected historical rural cultural heritage data is combined with digital twin technology to construct a digital twin model of the rural cultural heritage. On the basis of the digital twin model, the digital image of the rural cultural heritage is generated through rendering technology. The digital image of the rural cultural heritage includes color, texture and size.

3. The rural cultural heritage protection method according to claim 1, characterized in that: The S103 includes: Extract coordinate point data from the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system; Merge the coordinate point data of the standard rural cultural heritage digital image coordinate system and the real-time rural cultural heritage digital image coordinate system into the dataset; Import the coordinate data merged into the dataset into the database table, set the database access permissions, back up the database at a preset time period, and monitor the database operation information, including CPU usage, memory usage, and query response time.

4. The rural cultural heritage protection method according to claim 1, characterized in that: The S104 includes: For the coordinate points where the comparison image coordinate data matches the standard image coordinate data, the spatial distance between the comparison image coordinate data and the standard image coordinate data is calculated as the coordinate data comparison error; An error threshold is set. When the coordinate data comparison error exceeds the error threshold, the coordinate points whose errors exceed the difference threshold in the coordinate data of the image to be compared are marked, and the coordinate point marks whose errors exceed the difference threshold are located in the real-time rural cultural heritage digital image to form an error area of ​​the real-time rural cultural heritage digital image; The area corresponding to the coordinate point marks exceeding the difference threshold is located in the standard rural cultural heritage digital image to form the error area of ​​the standard rural cultural heritage digital image.

5. The rural cultural heritage protection method according to claim 4, characterized in that: The S104 includes: In the error area of ​​the real-time rural cultural heritage digital image, the feature extraction method is applied to obtain the image features to constitute the features to be compared in the error area; Using the same feature extraction method as that of real-time images, image features are extracted within the error region of the standard rural cultural heritage digital image to obtain standard features of the error region; The extracted features to be compared in the error area and the standard features in the error area are sorted, and the sorted feature information is output for visual display of the error area and the extracted features on the image.

6. The rural cultural heritage protection method according to claim 1, characterized in that: The S105 includes: Extracting coordinate information from the standard features of the error area to form first inspection coordinate information, and extracting coordinate information from the features to be compared in the error area to form second inspection coordinate information; Integrate the first inspection coordinate information and the second inspection coordinate information, and send the integrated coordinate information to the inspection robot and the inspection drone via wireless communication; Inspection robots and inspection drones move to the locations corresponding to the coordinate information for inspection based on the received coordinate information. After completing the task, the inspection equipment will transmit the collected real-time inspection image data back via wireless communication; Perform necessary preprocessing on the received real-time inspection image data, and compare the preprocessed real-time inspection image data with the extracted error area features to be compared and the error area standard features one by one; The deformation degree of the image features in the real-time inspection image is evaluated by a machine learning algorithm, and the calculated deformation degree is compared with the preset maximum deformation value; If the real-time inspection error comparison results show that the deformation of the image features exceeds the preset maximum deformation value, there is a potential risk of damage to the rural cultural heritage.

7. The rural cultural heritage protection method according to claim 6, characterized in that: The S105 includes: If the image feature deformation in the real-time inspection error comparison result is less than the preset maximum deformation value, there is no potential risk of damage to the rural cultural heritage. The real-time inspection error comparison result and the historical rural cultural heritage data are used to optimize the rural cultural heritage digital image using a genetic algorithm to obtain an optimized rural cultural heritage digital image, which is then used to replace the original rural cultural heritage digital image.

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