Building damage condition evaluation method and device, computer equipment and storage medium

Abstract

Embodiments of the present application disclose a building damage condition evaluation method and device, computer equipment and a storage medium. The method comprises: obtaining a multi-polarization SAR time series data set of a building before and after a disaster to obtain radar data; preprocessing the radar data to obtain a multi-polarization intensity time series data set; extracting texture information from the multi-polarization intensity time series data set; extracting a time point of building change and corresponding spatial location information from the multi-polarization intensity time series data set to obtain change information; calculating a change degree according to the change information and the texture information to obtain a building damage condition. The method of the embodiments of the present application can realize quantitative evaluation of the building damage degree and improve the evaluation accuracy of the building damage condition.

Description

Technical Field

[0001] The present invention relates to geological disasters, and more specifically to a method, device, computer equipment and storage medium for assessing building damage. Background Art

[0002] With the development of modern civilization, people are becoming more dependent on nature, and their demands for natural resources are increasing. Consequently, potential safety hazards, such as geological disasters, are becoming increasingly apparent, posing a serious threat to people's lives and property. China's diverse geological landscape contributes to the high incidence of geological disasters, including frequent collapses, landslides, and debris flows.

[0003] According to investigations and statistical data, disaster-stricken areas often have harsh natural conditions, making it impossible to quickly and comprehensively assess the disaster situation. Existing technologies usually use optical remote sensing data and classification methods to identify affected buildings, but due to meteorological conditions, they cannot quantitatively describe the extent of building damage, resulting in the inability to accurately assess the damage to buildings caused by geological disasters.

[0004] Therefore, it is necessary to design a new method to quantitatively evaluate the degree of building damage and improve the accuracy of building damage assessment. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the prior art and provide a building damage assessment method, device, computer equipment and storage medium.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a building damage assessment method, comprising:

[0007] Obtain multi-polarimetric SAR time series datasets of buildings before and after disasters to obtain radar data;

[0008] Preprocessing the radar data to obtain a multi-polarization intensity time series data set;

[0009] extracting texture information from the multi-polarization intensity time series data set;

[0010] Extracting the time points of building changes and corresponding spatial location information according to the multi-polarization intensity time series data set to obtain change information;

[0011] The degree of change is calculated according to the change information and the texture information to obtain the damage status of the building.

[0012] A further technical solution is: preprocessing the radar data to obtain a multi-polarization intensity time series data set, including:

[0013] Orbit correction and radiation calibration are performed on the radar data to obtain a multi-polarization intensity time series data set.

[0014] A further technical solution is: extracting texture information from the multi-polarization intensity time series data set includes:

[0015] A gray level co-occurrence matrix method is used to extract texture information from the multi-polarization intensity time series data set.

[0016] A further technical solution is: extracting the time point of building changes and the corresponding spatial position information based on the multi-polarization intensity time series data set to obtain change information, including:

[0017] A time series change detection algorithm is used to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information.

[0018] Its further technical solution is: the texture information includes the average value of the grayscale co-occurrence matrix of the multi-polarization intensity time series data set at 0° and 90°, and the statistics of the grayscale co-occurrence matrix at 0° and 90° include at least one of contrast, correlation, entropy, and energy indicators.

[0019] A further technical solution is: calculating the degree of change based on the change information and the texture information to obtain the damage status of the building, including:

[0020] The maximum value of the mean absolute error of the gray level co-occurrence matrix of different statistics before and after the time point of the building change is determined to obtain the building damage situation.

[0021] The present invention also provides a building damage assessment device, comprising:

[0022] A data acquisition unit is used to acquire a multi-polarization SAR time series data set of the building before and after the disaster to obtain radar data;

[0023] a preprocessing unit, configured to preprocess the radar data to obtain a multi-polarization intensity time series data set;

[0024] A texture information extraction unit, configured to extract texture information from the multi-polarization intensity time series data set;

[0025] a change information determining unit, configured to extract the time point of building change and the corresponding spatial position information according to the multi-polarization intensity time series data set to obtain change information;

[0026] The change degree calculation unit is used to calculate the change degree according to the change information and the texture information to obtain the building damage situation.

[0027] A further technical solution is: the pre-processing unit is used to perform orbit correction and radiation calibration processing on the radar data to obtain a multi-polarization intensity time series data set.

[0028] The present invention further provides a computer device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above method when executing the computer program.

[0029] The present invention also provides a storage medium, wherein the storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention obtains a multi-polarization SAR time series data set of buildings before and after a disaster, performs preprocessing, and extracts texture features in combination with a gray-level co-occurrence matrix method. The time series change detection algorithm determines the time point of building changes and the corresponding spatial position information. The texture features and change information are combined to calculate the degree of change to obtain the building damage situation, thereby achieving a quantitative assessment of the degree of building damage and improving the assessment accuracy of the building damage situation.

[0031] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 A schematic diagram of an application scenario of the building damage assessment method provided by an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of a flow chart of a building damage assessment method provided by an embodiment of the present invention;

[0035] Figure 3 A schematic block diagram of a building damage assessment device provided by an embodiment of the present invention;

[0036] Figure 4 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0038] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0039] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0040] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0041] See also Figure 1 and Figure 2 , Figure 1 A schematic diagram of an application scenario of the building damage assessment method provided by an embodiment of the present invention. Figure 2 This is a schematic flow chart of a building damage assessment method provided by an embodiment of the present invention. This building damage assessment method is applied to a server. The server exchanges data with a radar scanner, which scans buildings before and after a disaster, generating a multi-polarimetric SAR time-series dataset. After processing this dataset, the degree of texture feature change is calculated based on changes in texture information combined with mutation time, thereby quantitatively assessing the building damage.

[0042] Figure 2 FIG. 1 is a flow chart of a building damage assessment method according to an embodiment of the present invention. Figure 2 As shown, the method includes the following steps S110 to S150.

[0043] S110 , obtaining a multi-polarization SAR time series dataset of the building before and after the disaster to obtain radar data.

[0044] In this embodiment, the radar data refers to a multi-polarization SAR (Synthetic Aperture Radar) time series dataset of buildings before and after a disaster.

[0045] The use of radar data has good penetration and can be used for ground observation under adverse weather conditions, making this method applicable to a wider range of scenarios.

[0046] S120: Preprocess the radar data to obtain a multi-polarization intensity time series data set.

[0047] In this embodiment, the multi-polarization intensity time series data set refers to data obtained after orbit correction and radiation calibration processing are performed on radar data.

[0048] Specifically, orbit correction and radiation calibration processing are performed on the radar data to obtain a multi-polarization intensity time series data set.

[0049] In this embodiment, when radar data is generated, the radar scanner's sensor receives electromagnetic radiation energy from ground targets, which is affected by the characteristics of the remote sensing sensor itself, atmospheric effects, and ground lighting conditions, resulting in inconsistency between the remote sensing sensor's detection value and the actual spectral radiation value of the ground object, and grayscale distortion. Therefore, preprocessing is required to ensure the accuracy of the radar data.

[0050] S130. Extracting texture information from the multi-polarization intensity time series data set.

[0051] In this embodiment, the texture information includes the average value of the gray level co-occurrence matrix of the multi-polarization intensity time series data set at 0° and 90°, and the statistics of the gray level co-occurrence matrix at 0° and 90° include at least one of contrast, correlation, entropy, and energy indicators.

[0052] Specifically, a gray-level co-occurrence matrix method is used to extract texture information from the multi-polarization intensity time series dataset. The cropped dataset and change information from the building vector dataset are used as input signals and fed into the gray-level co-occurrence matrix method to extract the texture features of the buildings before and after the disaster.

[0053] Extracting texture features of radar data of each building under different polarization modes before and after the disaster by using methods such as gray-level co-occurrence matrix is ​​a prior art and will not be described in detail here.

[0054] S140 , extracting the time points of building changes and corresponding spatial position information according to the multi-polarization intensity time series data set to obtain change information.

[0055] In this embodiment, the change information refers to the time point when the building undergoes a sudden change and the corresponding spatial position information, and the spatial position information refers to the location where the building undergoes a sudden change.

[0056] In this embodiment, a time series change detection algorithm is used to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information.

[0057] Specifically, the time point of change and the corresponding spatial location information are extracted through time series change detection algorithms such as CCDC (Continuous Change Detection and Classification).

[0058] S150: Calculate the degree of change according to the change information and the texture information to obtain damage status of the building.

[0059] In this embodiment, the building damage condition refers to the degree of change of the building before and after the disaster.

[0060] Specifically, the maximum value of the mean absolute error of the gray-level co-occurrence matrix of different statistics before and after the building change is determined to obtain the building damage situation. The maximum value itself is the probability.

[0061] The damage degree information is obtained through the changes in the gray matrix, thereby converting the building damage into a quantitative assessment method.

[0062] The above-mentioned building damage assessment method obtains a multi-polarization SAR time series dataset of buildings before and after a disaster, performs preprocessing, and combines the gray-level co-occurrence matrix method to extract texture features. The time series change detection algorithm determines the time point of building changes and the corresponding spatial position information. The texture features and change information are combined to calculate the degree of change to obtain the building damage situation, realize quantitative assessment of the degree of building damage, and improve the accuracy of building damage assessment.

[0063] Figure 3 FIG. 3 is a schematic block diagram of a building damage assessment device 300 provided by an embodiment of the present invention. Figure 3 As shown, corresponding to the above building damage assessment method, the present invention also provides a building damage assessment device 300. The building damage assessment device 300 includes a unit for executing the above building damage assessment method, and the device can be configured in a server. Figure 3 The building damage assessment device 300 includes a data acquisition unit 301 , a pre-processing unit 302 , a texture information extraction unit 303 , a change information determination unit 304 , and a change degree calculation unit 305 .

[0064] The data acquisition unit 301 is used to obtain a multi-polarization SAR time series data set of the building before and after the disaster to obtain radar data; the preprocessing unit 302 is used to preprocess the radar data to obtain a multi-polarization intensity time series data set; the texture information extraction unit 303 is used to extract texture information from the multi-polarization intensity time series data set; the change information determination unit 304 is used to extract the time point of the building change and the corresponding spatial position information based on the multi-polarization intensity time series data set to obtain change information; the change degree calculation unit 305 is used to calculate the change degree based on the change information and the texture information to obtain the building damage situation.

[0065] In one embodiment, the pre-processing unit 302 is configured to perform orbit correction and radiation calibration processing on the radar data to obtain a multi-polarization intensity time series data set.

[0066] In one embodiment, the texture information extraction unit 303 is configured to extract texture information from the multi-polarization intensity time series dataset using a gray level co-occurrence matrix method.

[0067] In one embodiment, the change information determining unit 304 is configured to extract the time points of building changes and corresponding spatial position information from the multi-polarization intensity time series data set using a time series change detection algorithm to obtain change information.

[0068] In one embodiment, the change degree calculation unit 305 is used to determine the maximum value of the mean absolute error of the gray level co-occurrence matrix of different statistics before and after the time point of the building change to obtain the building damage status.

[0069] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned building damage assessment device 300 and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and brevity of description, it will not be repeated here.

[0070] The above-mentioned building damage assessment device 300 can be implemented in the form of a computer program. The computer program can be used in Figure 4 Runs on the computer equipment shown.

[0071] See also Figure 4 , Figure 4 1 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0072] See Figure 4The computer device 500 includes a processor 502 , a memory, and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0073] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, which, when executed, can enable the processor 502 to execute a building damage assessment method.

[0074] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500.

[0075] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a building damage assessment method.

[0076] The network interface 505 is used to communicate with other devices through the network. Figure 4 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0077] The processor 502 is configured to execute a computer program 5032 stored in the memory to implement the following steps:

[0078] Acquire a multi-polarization SAR time series dataset of the building before and after the disaster to obtain radar data; preprocess the radar data to obtain a multi-polarization intensity time series dataset; extract texture information from the multi-polarization intensity time series dataset; extract the time points of building changes and corresponding spatial position information based on the multi-polarization intensity time series dataset to obtain change information; calculate the degree of change based on the change information and the texture information to obtain the building damage situation.

[0079] The texture information includes the average value of the gray level co-occurrence matrix of the multi-polarization intensity time series data set at 0° and 90°, and the statistics of the gray level co-occurrence matrix at 0° and 90° include at least one of contrast, correlation, entropy, and energy indicators.

[0080] In one embodiment, when the processor 502 implements the step of preprocessing the radar data to obtain a multi-polarization intensity time series dataset, the processor 502 specifically implements the following steps:

[0081] Orbit correction and radiation calibration are performed on the radar data to obtain a multi-polarization intensity time series data set.

[0082] In one embodiment, when the processor 502 implements the step of extracting texture information from the multi-polarization intensity time series data set, the processor 502 specifically implements the following steps:

[0083] A gray level co-occurrence matrix method is used to extract texture information from the multi-polarization intensity time series data set.

[0084] In one embodiment, when the processor 502 implements the step of extracting the time points of building changes and the corresponding spatial location information based on the multi-polarization intensity time series dataset to obtain the change information, the processor 502 specifically implements the following steps:

[0085] A time series change detection algorithm is used to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information.

[0086] In one embodiment, when the processor 502 calculates the degree of change based on the change information and the texture information to obtain the building damage status, the processor 502 specifically implements the following steps:

[0087] The maximum value of the mean absolute error of the gray level co-occurrence matrix of different statistics before and after the time point of the building change is determined to obtain the building damage situation.

[0088] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0089] Those skilled in the art will appreciate that all or part of the steps in the method of the above-described embodiment can be implemented by instructing the relevant hardware through a computer program. The computer program includes program instructions, which can be stored in a storage medium that is computer-readable. The program instructions are executed by at least one processor in the computer system to implement the steps in the method of the above-described embodiment.

[0090] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein when the computer program is executed by a processor, the processor performs the following steps:

[0091] Acquire a multi-polarization SAR time series dataset of the building before and after the disaster to obtain radar data; preprocess the radar data to obtain a multi-polarization intensity time series dataset; extract texture information from the multi-polarization intensity time series dataset; extract the time points of building changes and corresponding spatial position information based on the multi-polarization intensity time series dataset to obtain change information; calculate the degree of change based on the change information and the texture information to obtain the building damage situation.

[0092] The texture information includes the average value of the gray level co-occurrence matrix of the multi-polarization intensity time series data set at 0° and 90°, and the statistics of the gray level co-occurrence matrix at 0° and 90° include at least one of contrast, correlation, entropy, and energy indicators.

[0093] In one embodiment, when the processor executes the computer program to implement the step of preprocessing the radar data to obtain a multi-polarization intensity time series dataset, the processor specifically implements the following steps:

[0094] Orbit correction and radiation calibration are performed on the radar data to obtain a multi-polarization intensity time series data set.

[0095] In one embodiment, when the processor executes the computer program to implement the step of extracting texture information from the multi-polarization intensity time series data set, the processor specifically implements the following steps:

[0096] A gray level co-occurrence matrix method is used to extract texture information from the multi-polarization intensity time series data set.

[0097] In one embodiment, when the processor executes the computer program to implement the step of extracting the time points of building changes and the corresponding spatial location information based on the multi-polarization intensity time series dataset to obtain change information, the processor specifically implements the following steps:

[0098] A time series change detection algorithm is used to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information.

[0099] In one embodiment, when the processor executes the computer program to implement the step of calculating the degree of change based on the change information and the texture information to obtain the building damage status, the processor specifically implements the following steps:

[0100] The maximum value of the mean absolute error of the gray level co-occurrence matrix of different statistics before and after the time point of the building change is determined to obtain the building damage situation.

[0101] The storage medium may be any computer-readable storage medium that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk.

[0102] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0103] In the several embodiments provided herein, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the various units is merely a logical functional division, and actual implementation may employ other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0104] The steps in the methods of the embodiments of the present invention may be adjusted in order, combined, or deleted as needed. The units in the devices of the embodiments of the present invention may be combined, divided, or deleted as needed. Furthermore, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0105] If this integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, terminal, or network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present invention.

[0106] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A building damage assessment method, characterized in that: include: Obtain multi-polarimetric SAR time series datasets of buildings before and after disasters to obtain radar data; Preprocessing the radar data to obtain a multi-polarization intensity time series data set; extracting texture information from the multi-polarization intensity time series data set; Extracting the time points of building changes and corresponding spatial location information according to the multi-polarization intensity time series data set to obtain change information; Calculating a degree of change according to the change information and the texture information to obtain a damage condition of the building; Extracting texture information from the multi-polarization intensity time series data set includes: Extracting texture information from the multipolarization intensity time series dataset using a gray level co-occurrence matrix method; the texture information includes an average value of the gray level co-occurrence matrix of the multipolarization intensity time series dataset at 0° and 90°, and the statistics of the gray level co-occurrence matrix at 0° and 90° include at least one of contrast, correlation, entropy, and energy indicators; Calculating the degree of change according to the change information and the texture information to obtain the damage condition of the building includes: Determine the maximum value of the mean absolute error of the gray level co-occurrence matrix of different statistics before and after the time point of the building change to obtain the building damage situation; Extracting the time point of building changes and corresponding spatial location information according to the multi-polarization intensity time series data set to obtain change information includes: A time series change detection algorithm is used to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information.

2. The building damage assessment method according to claim 1, wherein: The preprocessing of the radar data to obtain a multi-polarization intensity time series data set includes: Orbit correction and radiation calibration are performed on the radar data to obtain a multi-polarization intensity time series data set.

3. A building damage assessment device, characterized in that: include: A data acquisition unit is used to acquire a multi-polarization SAR time series data set of the building before and after the disaster to obtain radar data; a preprocessing unit, configured to preprocess the radar data to obtain a multi-polarization intensity time series data set; A texture information extraction unit, configured to extract texture information from the multi-polarization intensity time series data set; a change information determining unit, configured to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information; and extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set using a time series change detection algorithm to obtain change information; a change degree calculation unit, configured to calculate the change degree based on the change information and the texture information to obtain a building damage condition; Extracting texture information from the multi-polarization intensity time series data set includes: Extracting texture information from the multipolarization intensity time series dataset using a gray level co-occurrence matrix method; the texture information includes an average value of the gray level co-occurrence matrix of the multipolarization intensity time series dataset at 0° and 90°, and the statistics of the gray level co-occurrence matrix at 0° and 90° include at least one of contrast, correlation, entropy, and energy indicators; Calculating the degree of change according to the change information and the texture information to obtain the damage condition of the building includes: Determine the maximum value of the mean absolute error of the gray level co-occurrence matrix of different statistics before and after the time point of the building change to obtain the building damage situation; Extracting the time point of building changes and corresponding spatial location information according to the multi-polarization intensity time series data set to obtain change information includes: A time series change detection algorithm is used to extract the time points of building changes and the corresponding spatial position information from the multi-polarization intensity time series data set to obtain change information.

4. The building damage assessment device according to claim 3, characterized in that: The pre-processing unit is used to perform orbit correction and radiation calibration processing on the radar data to obtain a multi-polarization intensity time series data set.

5. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 2 when executing the computer program.

6. A storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 2 is implemented.

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