A method and device for locating reference points in a measurement area

Abstract

The present application discloses a method and device for locating reference points of a measurement area. Through geometric methods, geometric data is directly operated, and characteristic values ​​are extracted, and points suitable for being reference points of the measurement area, such as AP and / or AFP, are gradually screened out, which shortens the time consumption, improves the efficiency, and more efficiently realizes the measurement of critical dimensions (CD) and the positioning of target areas such as EP areas. At the same time, the problem of increasing the operation time with the increase in the image size is avoided.

Description

Technical Field

[0001] The present application relates to but is not limited to semiconductor integrated circuit technology, and in particular to a method and device for locating reference points in a measurement area. Background Art

[0002] To meet the demand for higher speed and higher integration of semiconductor devices, circuit patterns are becoming more and more refined. In order to ensure the accuracy of the production process, resolution enhancement function (RET) and optical proximity correction (OPC) are introduced. However, these finer masks increase the complexity of manufacturing, making it more difficult to predict the transmission shape through simulation. Therefore, the measurement requirements of critical dimension scanning electron microscope (CD-SEM, Critical Dimension Scanning ElectronMicroscopy) have also become more complex and diverse, especially when characterizing critical OPC models, the number of measurement area points (EP, Evaluation Points) required has increased dramatically.

[0003] In the semiconductor manufacturing process, in order to measure critical dimensions on the wafer (such as the width or spacing of tiny circuits), engineers use images taken from the wafer as reference templates. These images are usually taken with an optical microscope or a scanning electron microscope (SEM). In order to use a CD-SEM for measurement, the operator needs to align the microscope's field of view (FOV) to the target area. This alignment process is done manually, requiring the operator to adjust the position of the sample under the microscope so that the designated measurement area is accurately located in the center of the microscope's field of view. Because the operator needs to manually align the CD-SEM to specify the FOV at the position, it usually takes several minutes to collect the image template each time. Therefore, it usually takes several hours to create a CD-SEM image template that contains a large number of strategies.

[0004] In order to deal with this time-consuming manual operation problem, the industry has gradually introduced automation-based technical methods. These methods mainly identify image features through image matching and pixel traversal, especially based on the image features of the autofocus point (AFP) and the addressing point (AP), automatically find the corresponding point near the EP, that is, through the AFP and AP features in the image, use automation technology to quickly determine the position of the measurement area EP. However, the time complexity of image conversion increases exponentially with the increase of image size. When processing larger images, the time required for calculation will be much longer than expected, resulting in low efficiency.

[0005] To ensure reliable measurements, engineers usually select appropriate AP and AFP to ensure accurate correction of the imaging position and focusing of the electron beam. Traditionally, the selection of these points mainly relies on the experience of engineers, which is time-consuming and inefficient, and the calculation time will increase significantly with the increase in image size. Summary of the invention

[0006] The present application provides a method and device for locating reference points in a measurement area, which can shorten the time consumption, improve efficiency, and avoid the problem of increasing calculation time as the image size increases.

[0007] The present application provides a method for locating a reference point in a measurement area, including:

[0008] The search range is set with the measurement area point EP as the center, and the geometric line segments and their segmentation points within the search range are extracted. The segmentation points are several candidate points obtained by segmenting the geometric line segments at equal distances.

[0009] Extract the basic geometric features of each candidate point;

[0010] According to the extracted basic geometric features, the feature value of each candidate point is calculated;

[0011] Obtaining a screening weight value according to the obtained feature value of each candidate point;

[0012] After sorting by the screening weighted eigenvalues, the candidate points are screened according to the screening conditions, and the reference points of the positioning measurement area have been obtained.

[0013] In an exemplary embodiment, the basic geometric features include:

[0014] Width width, indicating the shortest distance from the candidate point to the inner geometric shape;

[0015] Space, representing the shortest distance from the candidate point to the outer geometric shape;

[0016] Length, which indicates the total length of the geometric line segment where the candidate point is located;

[0017] Among them, width=width×(-1 / length), space=space×(-1 / length).

[0018] In an exemplary embodiment, the positioning measurement area reference point is an addressing point AP;

[0019] The feature value of each candidate point includes a distance feature value and a symmetry feature value between each candidate point and EP.

[0020] In an exemplary embodiment, a Gaussian function is used to calculate the distance feature value between each candidate point and the EP, and ensure that a preset distance requirement is met.

[0021] In an exemplary embodiment, the calculation of symmetry features includes, for example:

[0022] Calculate the first symmetric eigenvalue in the length direction;

[0023] Calculate the second symmetry eigenvalue in the width / space direction;

[0024] The first symmetry eigenvalue and the second symmetry eigenvalue are combined to obtain the symmetry feature.

[0025] In an exemplary embodiment, the positioning measurement area reference point is an automatic focus point AFP;

[0026] The feature value of each candidate point also includes: a geometric complexity feature.

[0027] In an exemplary embodiment, calculating the geometric complexity feature includes:

[0028] Calculate the number of connected components of the line segment where the candidate point is located;

[0029] Count the number of holes in a geometry, which are closed geometric shapes formed by line segments or polygonal boundaries;

[0030] The geometric complexity characteristic value is calculated according to the calculated number of connected components and the number of holes.

[0031] In an exemplary embodiment, the screening condition is that the weighted feature value is the largest;

[0032] After the sorting according to the screening weighted eigenvalues, the candidate points are screened according to the screening conditions to obtain the reference points of the positioning measurement area, including:

[0033] Eliminate the candidate points within the EP range; and from the remaining candidate points, use the point with the largest weighted eigenvalue as the reference point of the positioning measurement area.

[0034] In an exemplary embodiment, the screening condition further includes that the angle between the candidate point and the EP is reasonable;

[0035] Also includes:

[0036] Find the candidate point with the smallest weighted eigenvalue, regard the candidate point as the reference point, and define the direction of the line connecting the reference point and EP as 0 degrees;

[0037] For each candidate point, calculating the angle between the line connecting the candidate point and the EP and the reference point;

[0038] Among the remaining candidate points, the point with the largest weighted eigenvalue and a reasonable angle between the candidate point and the EP is used as the reference point of the positioning measurement area.

[0039] An embodiment of the present application further provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute any of the above methods for locating reference points in a measurement area.

[0040] An embodiment of the present application further provides a computer device, including a memory and a processor, wherein the memory stores the following instructions executable by the processor: used to execute the steps of the method for locating reference points in a measurement area as described in any one of the above.

[0041] The embodiment of the present application further provides a device for locating reference points in a measurement area, comprising a first extraction module, a second extraction module, a calculation module, an acquisition module, and a determination module; wherein:

[0042] The first extraction module is used to set a search range with EP as the center, extract geometric line segments and their segmentation points within the search range, and the segmentation points are a number of candidate points obtained by segmenting the geometric line segments at equal distances;

[0043] The second extraction module is used to extract the basic geometric features of each candidate point;

[0044] A calculation module is used to calculate the feature value of each candidate point according to the extracted basic geometric features;

[0045] An acquisition module, used for acquiring a screening weight value according to the acquired feature value of each candidate point;

[0046] The determination module is used to screen the candidate points according to the screening conditions after sorting the candidate points according to the screening weighted eigenvalues ​​to obtain the reference points of the positioning measurement area.

[0047] The method for locating reference points of the measurement area provided in the embodiment of the present application directly operates on geometric data through geometric methods, extracts characteristic values, and gradually selects points suitable as reference points of the measurement area, such as AP and / or AFP, thereby shortening the time consumption, improving efficiency, and more efficiently measuring the critical dimension (CD) and locating the target area such as the EP area. At the same time, the problem of increasing the operation time as the image size increases is avoided.

[0048] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide further understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0050] Figure 1 A schematic diagram of a flow chart of a method for locating reference points in a measurement area in an embodiment of the present application;

[0051] Figure 2 Schematic diagram of the structure of the device for locating reference points in the measurement area in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present application more clear, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other arbitrarily without conflict.

[0053] In a typical configuration of the present application, a computing device includes one or more processors (CPU), an input / output interface, a network interface, and a memory.

[0054] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0055] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory media such as modulated data signals and carrier waves.

[0056] The steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described can be performed in a sequence different from that shown here.

[0057] In order to improve the measurement efficiency, certain specific feature points in the image (such as AFP and AP) are used as references. Through the image features of these points, the specific position near EP is automatically identified. AFP is a specific point used to adjust and optimize the focus of the electron beam. The image features of AFP (such as brightness changes, edge clarity, etc.) are extracted to guide the focus of the instrument to ensure clear imaging and accurate measurement. AP is a reference point for alignment and positioning. By identifying the features of these points (such as geometric shape or texture information), the position of the measurement area can be accurately located. In other words, EP is the key area that needs to be measured, and AFP and AP are reference points used to assist in positioning. By analyzing the image features of AFP and AP, the positional relationship between these reference points and the template is automatically matched, so as to quickly find the exact position of EP.

[0058] The inventor of the present application believes that searching for AP and AFP near EP is essentially searching for the point with the most obvious features. The method using images is also to search for feature vectors through images. The significance of feature vectors is actually to represent the geometric shape around the point. In order to shorten the time consumption, improve efficiency, and avoid the problem of increasing computing time as the image size increases, in the embodiment of the present application, the problem of excessive computation caused by images is avoided by not using images, and a graphical method is used for processing, because graphics are simpler and more convenient for geometric shape calculations. Moreover, geometry is composed of topological structures, and the data structure is simple. As the image size increases, the time complexity will also change less.

[0059] Figure 1 FIG. 1 is a flow chart of a method for locating reference points in a measurement area in an embodiment of the present application. Figure 1 As shown, it may include:

[0060] Step 100: Set a search range with EP as the center, extract geometric line segments and their segmentation points within the search range, where the segmentation points are several candidate points obtained by segmenting the geometric line segments at equal distances.

[0061] In the embodiment of the present application, EP is a known target point and is the core position of the inspection. AP is an addressing point used to uniquely locate EP and AFP. AFP is an automatic focus point used to ensure a clear focus position.

[0062] When the reference point of the positioning measurement area is AP, the distance between AP and EP needs to meet the distance requirement, such as about 4 to 8 microns (μm). The distance between AP and EP is used as the characteristic value, and the points that meet the distance requirement can be screened by distance. AP is the addressing point in the drawing, which is used as an index to find the location index of EP and AFP. AP is the index of the unique address, and what is needed is uniqueness and uniqueness.

[0063] When the reference point of the positioning measurement area is AFP, the distance between AFP and AP and EP needs to meet the distance requirement, that is, the distance needs to be far enough to avoid overlapping or being too close. In one embodiment, AFP can be closer to EP, such as about 4 μm, and AFP can be farther from EP, such as about 8-10 μm.

[0064] In an exemplary embodiment, the search range may be set to a range with a radius of 10 μm and EP as the center.

[0065] It should be noted that extracting geometric line segments within the search range is a well-known technology for those skilled in the art, and the specific implementation is not intended to limit the protection scope of this application.

[0066] Step 101: Extract basic geometric features of each candidate point.

[0067] In an exemplary instance, basic geometric features may include but are not limited to: width (width) represents the shortest distance from the candidate point to the inner geometric shape; space (space) represents the shortest distance from the candidate point to the outer geometric shape; length (length), represents the total length of the geometric segment where the candidate point is located; and so on.

[0068] In one embodiment, width=width×(-1 / length).

[0069] In one embodiment, space=space×(-1 / length).

[0070] Step 102: Calculate the feature value of each candidate point based on the extracted basic geometric features.

[0071] In an exemplary embodiment, the feature value of each candidate point may include a distance feature value and a symmetry feature value between each candidate point and the EP.

[0072] In an exemplary embodiment, a Gaussian function may be used to calculate the distance feature value between each candidate point and the EP, and ensure that a preset distance requirement is met.

[0073] In one embodiment, the distance characteristic value is calculated as shown in formula (1):

[0074] (1)

[0075] In formula (1), μ represents the optimal distance, that is, the ideal distance between the candidate point and the EP, μ is the center value of the Gaussian function, corresponding to the location of the peak of the Gaussian distribution. σ represents the standard deviation, which determines the width or diffusion of the Gaussian function. The larger σ is, the wider the Gaussian distribution is; the smaller σ is, the narrower the Gaussian distribution is.

[0076] In an exemplary embodiment, the selection of σ depends on actual needs. For example, if the distance range of candidate points needs to be strictly limited, a smaller σ (such as 1 μm) can be selected; if a looser screening range is desired, a larger σ (such as 2~3 μm) can be selected.

[0077] In an exemplary embodiment, the calculation of the symmetry feature in step 102 may include, for example:

[0078] Calculate the first symmetry eigenvalue in the length direction. The symmetry in the length direction reflects the uniformity of the distribution of the geometric line segment in the length direction. For example, when the candidate point is in the middle of the set line segment, the symmetry is high; when it is close to one end of the set line segment, the symmetry is low;

[0079] Calculate the second symmetry eigenvalue in the width / space direction. The symmetry in the width and space directions reflects whether the distance distribution around the candidate point (inner width and outer space) is balanced. For example, if the difference between the inner and outer distances is small, the symmetry is high; if the difference is large, the symmetry is low.

[0080] The first symmetry eigenvalue in the length direction and the second symmetry eigenvalue in the width / space direction are combined to obtain the symmetry feature.

[0081] In one embodiment, the first symmetry eigenvalue= , where d1 represents the distance from the candidate point to the starting point of the geometric segment, and d2 represents the distance from the candidate point to the end point of the geometric segment. When d1 = d2 (the candidate point is located in the middle of the geometric segment), the maximum symmetry eigenvalue is 1. When d1 or d2 is close to 0, the symmetry eigenvalue is close to 0.

[0082] In one embodiment, the second symmetry eigenvalue= , when width = space (candidate points are evenly distributed inside and outside), the symmetry eigenvalue is the largest, which is 1. When width or space is significantly larger than the other, the symmetry eigenvalue is close to 0.

[0083] In one embodiment, the first symmetry eigenvalue in the length direction and the second symmetry eigenvalue in the width / space direction are combined to obtain a symmetry feature, which may include: symmetry eigenvalue = α1·first symmetry eigenvalue + β1·second symmetry eigenvalue, where and are weight coefficients for adjusting the contribution of the two directions to the comprehensive symmetry. In this step, the two symmetry eigenvalues ​​are combined into a comprehensive value as a quantitative expression of the candidate point symmetry for subsequent sorting and screening.

[0084] In an exemplary embodiment, when the reference point of the positioning measurement area is AFP, points with simpler geometric shapes and smoother edges tend to be selected because these points are easier to be recognized and processed by the program during the autofocus process. When the space value of a point (i.e., the shortest distance from the point to the outer geometric shape) is large, it usually indicates that the space around this point is relatively open and far away from other geometric elements, indicating that the edge may be smoother. In this scenario, the feature value of each candidate point in step 102 also includes a geometric complexity feature. In one embodiment, the geometric complexity feature may include analyzing the topological information of the geometric segment where the candidate point is located, as follows:

[0085] Count the number of connected components of the line segment where the candidate point is located; in geometry, a group of connected line segments constitutes a connected component. If a line segment can be connected to another point through a series of other line segments, these line segments belong to the same connected component.

[0086] Counts the number of holes (enclosed regions) in a geometry. Holes (enclosed regions) are closed geometric shapes formed by line segments or polygonal boundaries.

[0087] The geometric complexity eigenvalue is calculated based on the calculated number of connected components and the number of holes.

[0088] The higher the geometric complexity eigenvalue, the more complex the shape; the lower the geometric complexity eigenvalue, the simpler the shape. In one embodiment, calculating the geometric complexity eigenvalue may include: geometric complexity eigenvalue = α2·number of connected components + β2·number of holes, where α2 and β2 are weight coefficients that can be adjusted according to actual needs. In one embodiment, the number of total line segments representing the total number of line segments in the connected component to which the candidate point belongs, and the average line segment length representing the total length of the line segments in the connected component divided by the number of line segments can be further considered. At this time, calculating the geometric complexity eigenvalue may include: geometric complexity eigenvalue = α3·number of connected components + β3·number of holes + γ1·number of total line segments + δ1·average line segment length, where α3, β3, γ1 and δ1 are weight coefficients that can be adjusted according to actual needs.

[0089] It should be noted that how to calculate the number of connected components of the line segment where the candidate point is located and the number of holes (closed areas) in the geometry are well-known techniques for those skilled in the art, and the specific implementation is not intended to limit the scope of protection of this application.

[0090] Step 103: Obtain a screening weight value according to the obtained feature value of each candidate point.

[0091] In an exemplary instance, for the case where the reference point of the positioning measurement area is AP, the screening weighted value is as follows: screening weighted value = α4·width+β4·space+γ2·distance eigenvalue+δ2·symmetry eigenvalue, where α4, β4, γ2 and δ2 are weight coefficients and can be adjusted according to actual needs.

[0092] In an exemplary instance, for the case where the reference point of the positioning measurement area is AFP, the screening weighted value is as follows: screening weighted value = α5·width+β5·space+γ3·distance eigenvalue+δ3·symmetry eigenvalue+ε·geometric complexity eigenvalue, where α5, β5, γ3, δ3 and ε are weight coefficients and can be adjusted according to actual needs.

[0093] Step 104: After sorting by the screening weighted eigenvalues, the candidate points are screened according to the screening conditions to obtain reference points in the positioning measurement area.

[0094] In an exemplary embodiment, the screening condition is that the weighted feature value is the largest, and step 104 may include:

[0095] Exclude candidate points within the EP range: set a certain protection range around the EP (such as 0.5 μm radius) and exclude all candidate points within the range to avoid selecting points that are too close to the EP; select the candidate point with the largest weighted eigenvalue: from the remaining candidate points, use the point with the largest weighted eigenvalue as the reference point of the positioning measurement area.

[0096] In one embodiment, in order to ensure that the selected reference point of the positioning measurement area has the best characteristics, the screening condition also includes that the angle between the candidate point and the EP is reasonable, and step 104 may also include:

[0097] Sort each candidate point by its weighted eigenvalue from small to large;

[0098] Find the candidate point with the smallest weighted eigenvalue, regard the candidate point as the reference point, and define the direction of the line connecting the reference point and EP as 0 degrees (the direction of the reference coordinate system);

[0099] For each candidate point, calculate the angle between the candidate point and the EP relative to the reference point. The angle can be normalized to the range of [0, 360] degrees and converted to a floating point value by dividing it by 360;

[0100] Among the remaining candidate points, if the weighted eigenvalues ​​of two candidate points are very close, in order to ensure that the angle between the final reference point of the positioning measurement area and the EP has a certain directional advantage (such as avoiding too concentrated or repeated directions), the point with the largest weighted eigenvalue and a reasonable angle between the candidate point and the EP is used as the reference point of the positioning measurement area.

[0101] It should be noted that reasonableness means ensuring that the direction of the reference point of the positioning measurement area is associated with the geometric characteristics of the EP (such as the directionality or symmetry of the overall figure), avoiding candidate points that are too close to the EP or have repeated directions, and ensuring that the reference point of the positioning measurement area finally selected is unique in a geometric sense.

[0102] The method for locating reference points of the measurement area provided in the embodiment of the present application realizes the effective identification of reference points of the measurement area such as AP and AFP based on geometric features without using image calculation, thereby shortening the time consumption, improving efficiency, and reducing the calculation complexity, while avoiding the problem of increasing calculation time as the image size increases.

[0103] The method for locating reference points of the measurement area provided in the embodiment of the present application directly operates on geometric data through geometric methods, extracts characteristic values, and gradually selects points suitable as reference points of the measurement area, such as AP and / or AFP, thereby shortening the time consumption, improving efficiency, and more efficiently measuring the critical dimension (CD) and locating the target area such as the EP area. At the same time, the problem of increasing the operation time as the image size increases is avoided.

[0104] The present application also provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute any of the above methods for locating reference points in a measurement area.

[0105] The present application further provides a computer device, including a memory and a processor, wherein the memory stores the following instructions executable by the processor: used to execute the steps of the method for locating reference points in a measurement area as described in any one of the above items.

[0106] Figure 2 Schematic diagram of the structure of the device for locating the reference point of the measurement area in the embodiment of the present application. Figure 2 As shown, it includes: a first extraction module, a second extraction module, a calculation module, an acquisition module, and a determination module; wherein,

[0107] The first extraction module is used to set a search range with EP as the center, extract geometric line segments and their segmentation points within the search range, and the segmentation points are a number of candidate points obtained by segmenting the geometric line segments at equal distances;

[0108] The second extraction module is used to extract the basic geometric features of each candidate point;

[0109] A calculation module is used to calculate the feature value of each candidate point according to the extracted basic geometric features;

[0110] An acquisition module, used for acquiring a screening weight value according to the acquired feature value of each candidate point;

[0111] The determination module is used to screen the candidate points according to the screening conditions after sorting the candidate points according to the screening weighted eigenvalues ​​to obtain the reference points of the positioning measurement area.

[0112] The device for locating reference points of the measurement area provided in the embodiment of the present application directly operates geometric data through geometric methods, extracts characteristic values, and gradually selects points suitable as reference points of the measurement area, such as AP and / or AFP, thereby shortening the time consumption, improving efficiency, and more efficiently measuring the critical dimension (CD) and locating the target area such as the EP area. At the same time, the problem of increasing the operation time as the image size increases is avoided.

[0113] Although the embodiments disclosed in this application are as above, the contents described are only embodiments adopted to facilitate understanding of this application and are not intended to limit this application. Any technician in the field to which this application belongs can make any modifications and changes in the form and details of implementation without departing from the spirit and scope disclosed in this application, but the scope of patent protection of this application shall still be based on the scope defined in the attached claims.

Claims

1. A method for locating a reference point of a measurement area, characterized in that: include: The search range is set with the measurement area point EP as the center, and the geometric line segments and their segmentation points within the search range are extracted. The segmentation points are several candidate points obtained by segmenting the geometric line segments at equal distances. Extract the basic geometric features of each candidate point; According to the extracted basic geometric features, the feature value of each candidate point is calculated; Obtaining a screening weight value according to the obtained feature value of each candidate point; After sorting by the screening weighted eigenvalues, the candidate points are screened according to the screening conditions, and the reference points of the positioning measurement area are obtained; Wherein, the basic geometric features include: Width width, indicating the shortest distance from the candidate point to the inner geometric shape; Space, representing the shortest distance from the candidate point to the outer geometric shape; Length, which indicates the total length of the geometric line segment where the candidate point is located; in, , ; The characteristic value of each candidate point includes a distance characteristic value and a symmetry characteristic value between each candidate point and EP; Wherein, a Gaussian function is used to calculate the distance characteristic value between each candidate point and the EP, and ensure that the preset distance requirement is met; Wherein, the computational symmetry features include: Calculate the first symmetric eigenvalue in the length direction; Calculate the second symmetry eigenvalue in the width / space direction; The first symmetry eigenvalue and the second symmetry eigenvalue are combined to obtain the symmetry feature.

2. The method according to claim 1, wherein: The reference point of the positioning measurement area is the addressing point AP.

3. The method according to claim 1, wherein: The reference point of the positioning measurement area is the automatic focus point AFP; The feature value of each candidate point also includes: a geometric complexity feature.

4. The method according to claim 3, wherein: Calculating the geometric complexity feature includes: Calculate the number of connected components of the line segment where the candidate point is located; Count the number of holes in a geometry, which are closed geometric shapes formed by line segments or polygonal boundaries; The geometric complexity characteristic value is calculated according to the calculated number of connected components and the number of holes.

5. The method according to claim 2, wherein: The screening condition is that the weighted eigenvalue is the largest; After the sorting according to the screening weighted eigenvalues, the candidate points are screened according to the screening conditions to obtain the reference points of the positioning measurement area, including: Eliminate the candidate points within the EP range; and from the remaining candidate points, use the point with the largest weighted eigenvalue as the reference point of the positioning measurement area.

6. The method according to claim 5, wherein the screening condition further comprises that the angle between the candidate point and the EP is reasonable; Also includes: Find the candidate point with the smallest weighted eigenvalue, regard the candidate point as the reference point, and define the direction of the line connecting the reference point and EP as 0 degrees; For each candidate point, calculating the angle between the line connecting the candidate point and the EP and the reference point; Among the remaining candidate points, the point with the largest weighted eigenvalue and a reasonable angle between the candidate point and the EP is used as the reference point of the positioning measurement area.

7. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the method for locating reference points in a measurement area according to any one of claims 1 to 6.

8. A computer device comprising a memory and a processor, wherein: The memory stores the following instructions executable by the processor: used to execute the steps of the method for locating reference points of a measurement area as described in any one of claims 1-6.

9. A device for locating reference points in a measurement area, characterized in that: It includes a first extraction module, a second extraction module, a calculation module, an acquisition module, and a determination module; wherein, The first extraction module is used to set a search range with EP as the center, extract geometric line segments and their segmentation points within the search range, and the segmentation points are a number of candidate points obtained by segmenting the geometric line segments at equal distances; The second extraction module is used to extract the basic geometric features of each candidate point; A calculation module is used to calculate the feature value of each candidate point according to the extracted basic geometric features; An acquisition module, used for acquiring a screening weight value according to the acquired feature value of each candidate point; A determination module is used to screen the candidate points according to the screening conditions after sorting the screening weighted eigenvalues ​​to obtain the reference points of the positioning measurement area; Wherein, the basic geometric features include: Width width, indicating the shortest distance from the candidate point to the inner geometric shape; Space, representing the shortest distance from the candidate point to the outer geometric shape; Length, which indicates the total length of the geometric line segment where the candidate point is located; in, , ; The characteristic value of each candidate point includes a distance characteristic value and a symmetry characteristic value between each candidate point and EP; Wherein, a Gaussian function is used to calculate the distance characteristic value between each candidate point and the EP, and ensure that the preset distance requirement is met; The computational symmetry features include: Calculate the first symmetric eigenvalue in the length direction; Calculate the second symmetry eigenvalue in the width / space direction; The first symmetry eigenvalue and the second symmetry eigenvalue are combined to obtain the symmetry feature.

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