Method and device for detecting compliance of homestead

Abstract

The present application relates to the field of digital processing technology, and discloses a method and device for detecting compliance of homesteads, comprising: first obtaining information of preset indicators of a homestead to be detected, and performing image comparison between an image of the homestead to be detected at a current moment and an image of the homestead to be detected at a specified moment before the current moment, and then adjusting the information of the preset indicators of the homestead to be detected according to the result of the image comparison, and then determining abnormal information of the indicators of the homestead to be detected based on the adjustment result and a pre-trained least squares support vector machine model, and then continuing to determine whether the homestead to be detected is compliant based on the abnormal information of the indicators and a pre-trained classification function, thereby accurately judging whether the homestead is compliant, making the land use of rural housing reform more reasonable.

Description

Technical Field

[0001] The present application relates to the field of digital processing technology, and in particular to a method and device for detecting compliance of homesteads. Background Art

[0002] The "one household, one house" principle is the basis for farmers to obtain homestead use rights and for rural collectives to reclaim the use rights of multiple homesteads. Currently, phenomena such as multiple houses per household, homesteads exceeding the designated area, and the illegal occupation and use of farmland for housing are common in rural areas. Existing technologies primarily rely on humans to determine whether homesteads are legally compliant, without specific standards or requirements for compliance. This results in inaccurate results for determining whether homesteads exceed the designated area. Therefore, there is a need to address the difficulty in accurately determining homestead compliance due to the complex characteristics of homesteads. Summary of the Invention

[0003] The embodiments of the present application provide a method and device for detecting compliance of homesteads, thereby accurately determining whether homesteads are compliant, making the use of land for rural housing reform more reasonable.

[0004] In a first aspect, an embodiment of the present application provides a method for detecting compliance of a homestead, the method comprising:

[0005] Obtaining information on preset indicators of the homestead to be detected, and performing image comparison between an image of the homestead to be detected at a current moment and an image of the homestead to be detected at a specified moment before the current moment;

[0006] Adjusting the preset indicator information of the homestead to be detected according to the result of the image comparison;

[0007] Determine abnormal information of the indicators of the homestead to be detected based on the adjustment result and the pre-trained least squares support vector machine model;

[0008] Based on the abnormal information of the indicators and the pre-trained classification function, determine whether the homestead to be inspected is compliant.

[0009] Compared with the existing technology, this application combines the information of the preset indicators of the homestead to be detected and the comparison results of the images of the homestead to be detected over a period of time, which can make use of more judgment basis to determine whether the homestead to be detected is compliant. At the same time, using the image comparison results to adjust the information of the preset indicators of the homestead to be detected can make the information used more accurate, and thus can more accurately determine whether the homestead to be detected is compliant using the classification function.

[0010] In one possible design, before obtaining information on preset indicators of the homestead to be detected, the method further includes:

[0011] Define the preset indicators of the homestead to be detected.

[0012] By defining indicators in a standard way, information can be collected more reasonably based on the defined indicators.

[0013] In one possible design, comparing an image of the homestead to be detected at a current moment with an image of the homestead to be detected at a specified moment before the current moment includes:

[0014] The image of the homestead to be detected at the current moment and the image of the homestead to be detected at a specified moment before the current moment are respectively subjected to noise reduction processing and input into a pre-trained convolutional neural network.

[0015] By performing noise reduction on the image, the image comparison results can be made more accurate. Using a pre-trained convolutional neural network, information such as the height of the homestead to be detected can be obtained more accurately.

[0016] In one possible design, when the image comparison result includes the height of the homestead, adjusting the information of the preset indicator of the homestead to be detected according to the image comparison result includes:

[0017] The weighted sum of the height of the homestead in the image comparison result and the obtained height of the homestead to be detected is used as the final height of the homestead to be detected.

[0018] By combining the results of image comparison with the information of preset indicators of the homestead to be detected, more accurate data information of the homestead to be detected can be obtained.

[0019] In one possible design, the abnormal information based on the indicator and the pre-trained classification function is used to determine whether the homestead to be inspected is compliant, including:

[0020] Mapping the abnormal information of the indicator into a hyperplane, and dividing the hyperplane according to a pre-trained classification function;

[0021] Based on the division results, determine whether the homestead to be inspected is compliant.

[0022] By mapping the abnormal information of the indicators to a hyperplane and dividing the housing reform points in the hyperplane, we can obtain more accurate housing reform information of the homestead to be tested, and determine whether the homestead to be tested is compliant based on the housing reform information.

[0023] In a second aspect, an embodiment of the present application provides a device for detecting compliance of a homestead, the device comprising:

[0024] An acquisition module is used to obtain information of preset indicators of the homestead to be detected, and to compare an image of the homestead to be detected at a current moment with an image of the homestead to be detected at a specified moment before the current moment;

[0025] A processing module, configured to adjust information on preset indicators of the homestead to be detected based on the result of the image comparison;

[0026] A first determination module is used to determine abnormal information of the indicators of the homestead to be detected based on the adjustment result and a pre-trained least squares support vector machine model;

[0027] The second determination module is used to determine whether the homestead to be inspected is compliant based on the abnormal information of the indicators and a pre-trained classification function.

[0028] In one possible design, the acquisition module is further configured to:

[0029] Define the preset indicators of the homestead to be detected.

[0030] In one possible design, the second determining module is specifically configured to:

[0031] Mapping the abnormal information of the indicator into a hyperplane, and dividing the hyperplane according to a pre-trained classification function;

[0032] Based on the division results, determine whether the homestead to be inspected is compliant.

[0033] In one possible design, the acquisition module is specifically configured to:

[0034] The image of the homestead to be detected at the current moment and the image of the homestead to be detected at a specified moment before the current moment are respectively subjected to noise reduction processing and input into a pre-trained convolutional neural network.

[0035] In one possible design, when the image comparison result includes the height of the homestead, the processing module is specifically configured to:

[0036] The weighted sum of the height of the homestead in the image comparison result and the obtained height of the homestead to be detected is used as the final height of the homestead to be detected.

[0037] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0038] processor;

[0039] a memory for storing instructions executable by the processor;

[0040] In which, the processor is configured to execute the instructions to implement the method for detecting homestead compliance as described in the first aspect.

[0041] In a fourth aspect, an embodiment of the present application provides a storage medium, which, when the instructions in the storage medium are executed by a processor, enables the execution of the method for detecting homestead compliance as described in the first aspect.

[0042] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device executes a method for implementing the above-mentioned various aspects of the embodiment of the present disclosure and any possible design involved in each aspect.

[0043] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. Obviously, the drawings introduced below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 A schematic diagram of an application scenario of the method for detecting homestead compliance provided in an embodiment of the present application;

[0046] Figure 2 A flowchart of a method for detecting compliance with homestead land provided in an embodiment of the present application;

[0047] Figure 3 A schematic diagram of image comparison provided in the embodiments of the present application;

[0048] Figure 4 A schematic diagram of the structure of the least squares support vector machine model provided in the embodiment of the present application;

[0049] Figure 5 A schematic diagram of a process for determining whether a homestead is inheritable based on an improved genetic algorithm provided in an embodiment of the present application;

[0050] Figure 6 A schematic diagram of the structure of an apparatus for detecting homestead compliance provided in an embodiment of the present application;

[0051] Figure 7 A schematic diagram of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to enable ordinary people in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0053] It should be noted that the terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0054] Below, some terms used in the embodiments of the present application are explained to facilitate understanding by those skilled in the art.

[0055] (1) In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar to it.

[0056] (2) “And / or” describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character “ / ” generally indicates that the related objects are in an “or” relationship.

[0057] (3) The server serves the terminal. The service content includes comparing the image of the homestead to be detected at the current moment sent by the terminal with the image of the homestead to be detected at a specified moment before the current moment. The server corresponds to the application installed on the terminal and runs in conjunction with the application on the terminal.

[0058] (4) Terminal device, which can refer to both software applications (APPs) and clients. It has a visual display interface and can interact with users. It corresponds to the server and provides local services to customers. For software applications, except for some applications that only run locally, they are generally installed on ordinary client terminals and need to cooperate with the server to operate.

[0059] The "one household, one house" principle is the basis for farmers to obtain homestead use rights and for rural collectives to reclaim the use rights of multiple homesteads. Currently, phenomena such as multiple houses per household, homesteads exceeding the designated area, and the illegal occupation and use of farmland for housing are common in rural areas. Existing technologies primarily rely on humans to determine whether homesteads are legally compliant, without specific standards or requirements for compliance. This results in inaccurate results for determining whether homesteads exceed the designated area. Therefore, there is a need to address the difficulty in accurately determining homestead compliance due to the complex characteristics of homesteads.

[0060] To this end, this application proposes a method and device for detecting compliance of homesteads. By combining the information of preset indicators of the homestead to be detected and the comparison results of images of the homestead to be detected over a period of time, it is possible to use more judgment basis to determine whether the homestead to be detected is compliant. At the same time, using the image comparison results to adjust the information of the preset indicators of the homestead to be detected can make the information used more accurate, and thus the classification function can be used to more accurately determine whether the homestead to be detected is compliant.

[0061] After introducing the design concepts of the embodiments of this application, the following briefly introduces the application scenarios to which the technical solutions of the embodiments of this application can be applied. It should be noted that the application scenarios introduced below are only used to illustrate the embodiments of this application and are not limiting. In specific implementations, the technical solutions provided by the embodiments of this application can be flexibly applied according to actual needs.

[0062] refer to Figure 1 , which is a schematic diagram of an application scenario of the method for detecting compliance of homesteads provided in an embodiment of the present application. The application scenario includes multiple terminal devices 101 (including terminal device 101-1, terminal device 101-2, ... terminal device 101-n) and a server 102. Among them, the terminal device 101 and the server 102 are connected via a wireless or wired network, and the terminal device 101 includes but is not limited to electronic devices such as desktop computers, mobile phones, mobile computers, tablet computers, media players, smart wearable devices, smart TVs, etc. The server 102 can be a single server, a server cluster consisting of several servers, or a cloud computing center. The server 102 can be an independent physical server, or a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0063] Take the interaction between the terminal device 101-1 and the server 102 as an example for explanation. First, the user sends the homestead to be detected to the server 102 through the terminal device 101-1, and then obtains the information of the preset indicators of the homestead to be detected through the server 102, and compares the image of the homestead to be detected at the current moment with the image of the specified moment before the current moment of the homestead to be detected. According to the result of the image comparison, the information of the preset indicators of the homestead to be detected is adjusted. Then, based on the adjustment result and the pre-trained least squares support vector machine model, the server 102 determines the abnormal information of the indicators of the homestead to be detected, and then continues to determine whether the homestead to be detected is compliant based on the abnormal information of the indicators and the pre-trained classification function. Finally, the server 102 sends the result of whether the homestead to be detected is compliant to the terminal device 101-1 and displays it in the terminal device 101-1.

[0064] Here, the steps executed in the server 102 can also be executed by the terminal device 101-1. This is just an example, and the specific execution entity of each step can be adjusted according to actual conditions.

[0065] Of course, the method provided in the embodiment of the present application is not limited to Figure 1 The application scenarios shown can also be used in other possible application scenarios, and the embodiments of the present application are not limited thereto. Figure 1 The functions that can be implemented by each device in the application scenario shown will be described in subsequent method embodiments and will not be described in detail here.

[0066] To further illustrate the technical solutions provided by the embodiments of the present application, the following is a detailed description of the technical solutions in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of the present application provide method operation steps as shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative work. In steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided in the embodiments of the present application.

[0067] The following combination Figure 1 The application scenario shown illustrates the technical solution provided by the embodiment of this application.

[0068] refer to Figure 2 , this embodiment of the application provides a method for detecting compliance of homestead land, comprising the following steps:

[0069] S201, obtaining information on preset indicators of the homestead to be detected, and performing image comparison between an image of the homestead to be detected at a current moment and an image of the homestead to be detected at a specified moment before the current moment.

[0070] Optionally, before obtaining the information of the preset indicators of the homestead to be inspected, the preset indicators of the homestead to be inspected may be defined.

[0071] For example, we can define the "one household, one house" indicator rule, meaning that each registered household can only share one piece of homestead land. We can also define indicators for the residential type of a homestead land, which can be either owner-occupied or transferable. Transfers can include leasing, exchange, gifting, family inheritance, and equity investment. We can also define indicators for per capita homestead land area, total homestead land area, whether the homestead land has a rural construction planning license number and rural homestead land approval number, the type of building constructed on the homestead land, whether the homestead land complies with rural planning requirements, whether the method for obtaining the homestead land is standardized, whether the homestead land application is reviewed and approved, whether the land is measured and approved, and whether the land is inspected and approved after completion.

[0072] After the preset indicators are defined, the preset indicator information of the homestead to be tested can be obtained. For example, the geographical location information of the homestead to be tested, the name of the head of household corresponding to the homestead, the ID number of the head of household corresponding to the homestead, the contact information of the head of household corresponding to the homestead, the building area of ​​the house on the homestead, the number of floors of the house on the homestead, the area of ​​the homestead, the area of ​​the house occupied by the house on the homestead, the orientation of the house, the start time of house construction, the completion time of house construction, the approved area of ​​the house, the per capita homestead area, and other information can be obtained.

[0073] Alternatively, an image of the homestead being inspected at the current moment and an image of the homestead at a specified time before the current moment can be subjected to noise reduction processing, and then input into a pre-trained convolutional neural network for image comparison. The image can also be scaled before noise reduction processing to facilitate better image processing. Image noise reduction processing can include operations such as image dehazing and image brightening.

[0074] For example, Figure 3 The middle left picture is an image of homestead B taken in Village A on November 14, 2021. According to the requirements, homestead B cannot arbitrarily renovate the house. Figure 3 The center-right image shows Homestead B in Village A, taken on June 10, 2022. By feeding both images into a convolutional neural network, the boundary of the houses on Homestead B remains unchanged. Information such as the house height (C) and house width (D) can also be obtained.

[0075] The specific training process of the convolutional neural network is not limited here and can be adjusted according to actual application conditions.

[0076] S202: Adjust the information of preset indicators of the homestead to be detected according to the result of image comparison.

[0077] Optionally, a weighted sum of the height of the homestead in the image comparison result and the obtained height of the homestead to be detected is used as the final height of the homestead to be detected.

[0078] For example, the height of the homestead in the image comparison result is H1, and the height of the homestead to be detected is H2, then (H1+H2) / 2 can be used as the final height of the homestead to be detected.

[0079] S203: Based on the adjustment result and the pre-trained least squares support vector machine model, determine the abnormal information of the indicators of the homestead to be detected.

[0080] Optionally, abnormal information of indicators may include: whether one household has multiple houses, whether the homestead is idle, whether construction has been carried out on the homestead without approval, whether construction has been carried out on the homestead after approval, whether the application for homestead has been reviewed and approved, whether the measurement and approval after the homestead has been approved have been carried out, whether the inspection after the construction of the building on the homestead has been completed has been carried out, whether the homestead has occupied basic farmland, and whether there have been any reports on the homestead.

[0081] The least squares support vector machine model is trained as follows:

[0082] Obtain training sample pairs, wherein the training sample pairs include indicator data after adjustment of the homestead to be tested and standard indicator data; input the training sample pairs into a least squares support vector machine model to obtain parameters corresponding to the indicator data after adjustment of the homestead to be tested and parameters corresponding to the standard indicator data output by the least squares support vector machine model; determine a first loss based on the parameters corresponding to the indicator data after adjustment of the homestead to be tested and the parameters corresponding to the standard indicator data; train the least squares support vector machine model according to the first loss.

[0083] For example, Figure 4 As shown, the least squares support vector machine model processes data for the homestead data set (i.e., the index data and standard index data after the homestead to be tested is adjusted). The first layer of the least squares support vector machine model can be set to three parameter indicators: compliance and non-compliance, non-compliance and others, and over-occupancy and over-standard. The second layer can be set to six parameter indicators: one household one house, idle and over-standard, one household multiple houses, unbuilt and others, abnormal warning, historical reasons and family household registration reasons. The third layer is set to two parameter indicators: illegal and in violation of regulations, and revitalizing and utilizing. The fourth layer is set to eleven parameter indicators: over-area, over-occupancy, construction without approval, violation of planning, occupation of farmland, leasing, equity investment, transfer, exchange, donation, and inheritance. This is just an example to illustrate the internal structure of the least squares support vector machine model. This application does not limit the specific internal structure of the least squares support vector machine model.

[0084] S204, based on the abnormal information of the indicators and the pre-trained classification function, determine whether the homestead to be inspected is compliant.

[0085] Optionally, the abnormal information of the indicator is mapped to a hyperplane, and the hyperplane is divided according to a pre-trained classification function; based on the division result, it is determined whether the homestead to be tested is compliant.

[0086] For example, first mark the abnormal information of the indicator in the hyperplane, and then use the classification function The hyperplane is used to divide the housing reform points, that is, by converting the abnormal information of the indicators into the coordinate values ​​of each dimension in the hyperplane, for example, the total building area of ​​the house in the homestead, the total area of ​​the homestead, ..., the per capita building area of ​​the homestead and other indicators are set as vectors Standard indicator data is set as a vector Therefore, we can get the pre-trained classification function Among them, the vector Adjust the values ​​of the trained parameters.

[0087] Furthermore, in order to improve the accuracy of the detection results, the data interval value on the above hyperplane can be adjusted to the maximum. For example, the maximum data interval value on the hyperplane can be determined by constructing a maximum interval classifier. It is a maximum margin classifier and needs to satisfy the following formula 1:

[0088]

[0089] According to the definition of geometric interval, let Thus, the target classification function is obtained, which is expressed by the following formula 2:

[0090]

[0091] Among them, st in Formula 2 is subject to, which means that the constraints are derived.

[0092] Through the above construction process, the classification function corresponding to the maximum margin classifier can be obtained, and then the housing reform points for the detected homesteads can be divided more accurately according to the classification function.

[0093] After testing whether the homestead to be tested is compliant, if the test result of the homestead to be tested is non-compliant, and the homestead to be tested is a household with multiple houses, it is possible to further determine whether the homestead to be tested is an inheritable homestead, so as to accurately determine the actual situation of the homestead to be tested.

[0094] Furthermore, after the compliance test is carried out on the homestead to be tested, a homestead form can be generated based on the test results. The form can be 18-digit data, the first 12 digits from left to right can be the national standard number of the administrative division, the 13th to 16th digits are the serial number, and the 17th to 18th digits are the status bits. For example, the form can be represented by 360827101200000101, where the 1st and 2nd digits represent the provincial number, the 3rd and 4th digits represent the municipal number, the 5th and 6th digits represent the county number, the 7th to 9th digits represent the township number, the 10th to 12th digits represent the community or village number, the 13th to 16th digits represent the serial number, and the 17th and 18th digits represent the status bit. For example, in the status bit, 01 indicates compliance, 02 indicates unlicensed, 03 indicates multiple houses per household, 04 indicates excessive land occupation, 05 indicates excessive construction, and 06 indicates illegal reconstruction.

[0095] Figure 5 A flow chart of determining whether a homestead is inheritable based on a modified genetic algorithm is shown, including the following steps:

[0096] S501, initialize pheromone and maximum number of iterations t.

[0097] S502, based on the household registration information of the homestead to be detected, generate a family homestead inheritance analysis task.

[0098] S503: Generate a solution space for inheritance analysis based on the household member information of each homestead to be detected.

[0099] S504: Whether there is a fitness value for each member. If yes, go to step S507; if not, go to step S505.

[0100] S505: Determine whether to file a complaint regarding the homestead to be inspected. If so, proceed to step S502; if not, proceed to step S506.

[0101] S506, releasing the solution space.

[0102] S507, number of iterations t=t+1.

[0103] S508: Determine whether the convergence condition is met or the maximum number of iterations is reached. If yes, execute step S5011; if not, execute steps S509 and S5010 and then continue to execute step S504.

[0104] S509, genetic operator operation.

[0105] S5010, updating pheromones, includes releasing and volatilizing pheromones.

[0106] S5011, output the optimal solution.

[0107] After determining whether the homestead to be tested is compliant and whether it is inheritable, the application can also publish the test results of the homestead to be tested in real time so that villagers can obtain updated results in a timely manner. This application is also conducive to improving the utilization rate of homesteads in rural areas.

[0108] Figure 6 An apparatus for detecting compliance of a homestead provided in an embodiment of the present application is shown. The apparatus 600 includes:

[0109] An acquisition module 601 is used to obtain information of preset indicators of the homestead to be detected, and to compare an image of the homestead to be detected at a current moment with an image of the homestead to be detected at a specified moment before the current moment;

[0110] Processing module 602, configured to adjust information on preset indicators of the homestead to be detected based on the result of the image comparison;

[0111] The first determination module 603 is used to determine abnormal information of the indicators of the homestead to be detected based on the adjustment result and the pre-trained least squares support vector machine model;

[0112] The second determination module 604 is used to determine whether the homestead to be inspected is compliant based on the abnormal information of the indicator and the pre-trained classification function.

[0113] In one possible design, the acquisition module 601 is further configured to:

[0114] Define the preset indicators for the homestead to be tested.

[0115] In one possible design, the acquisition module 601 is specifically configured to:

[0116] The image of the homestead to be detected at the current moment and the image of the homestead to be detected at a specified moment before the current moment are subjected to denoising processing respectively and then input into a pre-trained convolutional neural network.

[0117] In one possible design, when the image comparison result includes the height of the homestead, the processing module 602 is specifically configured to:

[0118] The weighted sum of the height of the homestead in the image comparison result and the obtained height of the homestead to be detected is used as the final height of the homestead to be detected.

[0119] In one possible design, the second determining module 604 is specifically configured to:

[0120] Map the abnormal information of the indicator to the hyperplane and divide the hyperplane according to the pre-trained classification function;

[0121] Based on the division results, determine whether the homestead to be inspected is compliant.

[0122] After introducing the method for detecting homestead compliance according to an exemplary embodiment of the present application, next, an electronic device according to another exemplary embodiment of the present application is introduced.

[0123] Those skilled in the art will appreciate that various aspects of the present application can be implemented as systems, methods, or program products. Therefore, various aspects of the present application can be specifically implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation that combines hardware and software aspects, which may be collectively referred to herein as a "circuit," "module," or "system."

[0124] In some possible implementations, the electronic device according to the present application may include at least one processor and at least one memory. The memory stores program code, and when the program code is executed by the processor, the processor performs the steps of the method for detecting homestead compliance according to various exemplary embodiments of the present application described above in this specification. For example, the processor may perform the steps in the method for detecting homestead compliance.

[0125] Refer to the following Figure 7 An electronic device 70 according to this embodiment of the present application will be described. Figure 7 The electronic device 70 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0126] like Figure 7 As shown, the electronic device 70 is a general electronic device. Components of the electronic device 70 may include, but are not limited to, the at least one processor 71, the at least one memory 72, and a bus 73 connecting different system components (including the memory 72 and the processor 71).

[0127] Bus 73 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, and a processor or local bus using any of a variety of bus architectures.

[0128] The memory 72 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 721 and / or a cache memory 722 , and may further include a read-only memory (ROM) 723 .

[0129] The memory 72 may also include a program / utility 725 having a set (at least one) of program modules 724, such program modules 724 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0130] The electronic device 70 can also communicate with one or more external devices 74 (e.g., a keyboard, pointing device, etc.), one or more devices that enable a user to interact with the electronic device 70, and / or any device that enables the electronic device 70 to communicate with one or more other electronic devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 75. Furthermore, the electronic device 70 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 76. As shown, the network adapter 76 communicates with other modules of the electronic device 70 via a bus 73. It should be understood that, although not shown, other hardware and / or software modules can be used in conjunction with the electronic device 70, including but not limited to microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0131] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 72 including instructions, and the instructions can be executed by the processor 71 to perform the above method. Alternatively, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0132] In an exemplary embodiment, a computer program product is also provided, comprising a computer program / instruction, which, when executed by the processor 71, implements any of the methods for detecting homestead compliance as provided in this application.

[0133] In an exemplary embodiment, various aspects of a method for detecting homestead compliance provided by the present application can also be implemented in the form of a program product, which includes program code. When the program product is run on a computer device, the program code is used to enable the computer device to execute the steps of a method for detecting homestead compliance according to various exemplary embodiments of the present application described above in this specification.

[0134] The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0135] The program product for determining text similarity of embodiments of the present application may be implemented as a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on an electronic device. However, the program product of the present application is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0136] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0137] Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0138] The program code for performing the operations of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user electronic device, partially on the user device, as a separate software package, partially on the user electronic device and partially on a remote electronic device, or entirely on the remote electronic device or server. In cases involving remote electronic devices, the remote electronic device can be connected to the user electronic device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external electronic device (for example, using an Internet service provider to connect through the Internet).

[0139] It should be noted that although several units or subunits of the device are mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, depending on the embodiment of the application, the features and functions of two or more units described above can be embodied in a single unit. Conversely, the features and functions of a single unit described above can be further divided and embodied by multiple units.

[0140] Furthermore, although the operations of the method of the present application are described in a particular order in the accompanying drawings, this does not require or imply that the operations must be performed in this particular order, or that all illustrated operations must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0141] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0142] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable electronic device to produce a machine, so that the instructions executed by the processor of the computer or other programmable electronic device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable electronic device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0144] These computer program instructions can also be loaded onto a computer or other programmable electronic device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0145] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0146] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for detecting compliance of homestead land, characterized in that: The method comprises: Obtaining information about preset indicators of the homestead to be detected, and performing noise reduction processing on an image of the homestead to be detected at a current moment and an image of the homestead to be detected at a specified moment before the current moment, respectively, and inputting the noise reduction processing into a pre-trained convolutional neural network to obtain image comparison results; Adjusting information on preset indicators of the homestead to be detected according to the result of the image comparison; Determine abnormal information of the indicators of the homestead to be detected based on the adjustment result and the pre-trained least squares support vector machine model; Determine whether the homestead to be inspected is compliant based on abnormal information of the indicators and a pre-trained classification function; When the result of the image comparison includes the height of the homestead, adjusting the information of the preset indicator of the homestead to be detected according to the result of the image comparison includes: The weighted sum of the height of the homestead in the image comparison result and the obtained height of the homestead to be detected is used as the final height of the homestead to be detected.

2. The method according to claim 1, characterized in that Before obtaining information on preset indicators of the homestead to be detected, the method further includes: Define the preset indicators of the homestead to be detected.

3. The method according to claim 1, characterized in that The abnormal information based on the indicators and the pre-trained classification function is used to determine whether the homestead to be inspected is compliant, including: Mapping the abnormal information of the indicator into a hyperplane, and dividing the hyperplane according to a pre-trained classification function; Based on the division results, determine whether the homestead to be inspected is compliant.

4. A device for detecting compliance of homestead land, characterized in that: The device comprises: An acquisition module is used to obtain information of preset indicators of the homestead to be detected, and to perform noise reduction processing on an image of the homestead to be detected at the current moment and an image of the homestead to be detected at a specified moment before the current moment, and then input the noise reduction processing into a pre-trained convolutional neural network to obtain an image comparison result; A processing module, configured to adjust information of preset indicators of the homestead to be detected according to a result of the image comparison; A first determination module is used to determine abnormal information of the indicators of the homestead to be detected based on the adjustment result and a pre-trained least squares support vector machine model; A second determination module is used to determine whether the homestead to be inspected is compliant based on abnormal information of the indicator and a pre-trained classification function; When the result of the image comparison includes the height of the homestead, the processing module is specifically configured to: The weighted sum of the height of the homestead in the image comparison result and the obtained height of the homestead to be detected is used as the final height of the homestead to be detected.

5. The device according to claim 4, characterized in that The acquisition module is further used for: Define the preset indicators of the homestead to be detected.

6. The device according to claim 4, characterized in that The second determining module is specifically configured to: Mapping the abnormal information of the indicator into a hyperplane, and dividing the hyperplane according to a pre-trained classification function; Based on the division results, determine whether the homestead to be inspected is compliant.

7. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method for detecting homestead compliance as described in any one of claims 1 to 3.

8. A computer storage medium, characterized in that When the instructions in the computer storage medium are executed by a processor, the method for detecting homestead compliance according to any one of claims 1 to 3 can be performed.

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