Layout fuzzy matching method and device, storage medium and electronic equipment

Abstract

The invention discloses a layout fuzzy matching method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a target layout, carrying out the normalization processing of coordinate points of all polygons in the target layout, and obtaining a target coordinate; performing Fourier transform and frequency domain truncation processing based on the target coordinate to obtain a target frequency domain signal; sampling the target frequency domain signal to obtain sampling frequency spectrum data; encoding the sampling frequency spectrum data to generate an encoding value; and performing fuzzy matching on the target layout and the to-be-matched layout according to the coded value. According to the scheme, the fuzzy matching requirement in a complex layout environment can be met.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of semiconductor technology, and specifically to a layout fuzzy matching method, device, storage medium and electronic device. Background Art

[0002] In integrated circuit design and semiconductor manufacturing, layout fuzzy matching is a key technology that is widely used to detect similar circuit layouts, optimize layout design, and perform pattern recognition and defect detection.

[0003] Traditional layout fuzzy matching methods mainly rely on geometric feature comparison or template matching. Although these methods can provide high matching accuracy under ideal conditions, they are sensitive to noise, rotation, scaling and other transformations in actual applications, and it is difficult to meet the fuzzy matching requirements in complex layout environments. Summary of the invention

[0004] The embodiments of the present application provide a layout fuzzy matching method, device, storage medium and electronic device, which can meet the fuzzy matching requirements in a complex layout environment.

[0005] In a first aspect, an embodiment of the present application provides a layout fuzzy matching method, comprising: Acquire a target map, and normalize the coordinate points of all polygons in the target map to obtain target coordinates; Perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal; Sampling the target frequency domain signal to obtain sampled spectrum data; Encoding the sampled spectrum data to generate a coded value; The target layout is fuzzily matched with the layout to be matched according to the coding value.

[0006] In the layout fuzzy matching method provided in the embodiment of the present application, the Fourier transform and frequency domain truncation processing are performed based on the target coordinates to obtain the target frequency domain signal, including: Sorting all the target coordinates to generate an ordered coordinate sequence; Performing short-time Fourier transform on the ordered coordinate sequence to obtain a total frequency domain signal of the target layout; Perform frequency domain truncation processing on the total frequency domain signal to obtain a target frequency domain signal.

[0007] In the layout fuzzy matching method provided in the embodiment of the present application, encoding the sampled spectrum data to generate a coded value includes: Convert the sampled spectrum data into a character string; Encode the string to generate an encoded value.

[0008] In the layout fuzzy matching method provided in the embodiment of the present application, encoding the string to generate a coded value includes: The string is hashed using the BKDRHash algorithm to generate a unique hash value.

[0009] In the layout fuzzy matching method provided in the embodiment of the present application, the BKDRHash algorithm is used to hash the string to generate a unique hash value, including: Initialize the hash value to 0 and set the prime number as the multiplication factor; Each character in the string is traversed, and the ASCII code of each character is multiplied by the multiplication factor and then added to the hash value to generate a unique hash value.

[0010] In the layout fuzzy matching method provided in the embodiment of the present application, the coordinate points of all polygons in the target layout are normalized to obtain the target coordinates, including: Obtaining coordinate points of all polygons in the target map; Calculating a bounding box of the target layout; Taking the minimum coordinate point of the bounding box as a reference point, normalizing the coordinate points of all the polygons to obtain the target coordinates.

[0011] In the layout fuzzy matching method provided in the embodiment of the present application, the minimum coordinate point of the bounding box is used as a reference point, and the coordinate points of all the polygons are normalized to obtain the target coordinates, including: Obtaining the minimum coordinate point of the bounding box; The coordinate points of all the polygons are subtracted from the minimum coordinate point to obtain the target coordinates.

[0012] In a second aspect, an embodiment of the present application provides a layout fuzzy matching device, comprising: An acquisition unit is used to acquire a target layout, and normalize the coordinate points of all polygons in the target layout to obtain target coordinates; A transform unit, configured to perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal; A sampling unit, used for sampling the target frequency domain signal to obtain sampled spectrum data; An encoding unit, used for encoding the sampled spectrum data to generate an encoding value; A matching unit is used to perform fuzzy matching between the target layout and the layout to be matched according to the coding value.

[0013] In a third aspect, the present application provides a storage medium storing a plurality of instructions, wherein the instructions are suitable for loading by a processor to execute any of the above-mentioned layout fuzzy matching methods.

[0014] In a fourth aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described layout fuzzy matching methods when executing the computer program.

[0015] In summary, the layout fuzzy matching method provided in the embodiment of the present application includes obtaining a target layout, normalizing the coordinate points of all polygons in the target layout to obtain target coordinates; performing Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal; sampling the target frequency domain signal to obtain sampled spectrum data; encoding the sampled spectrum data to generate a coding value; and fuzzily matching the target layout with the layout to be matched according to the coding value. This solution converts layout features from the time domain to the frequency domain through Fourier transform, thereby improving the robustness of layout matching, and by combining feature optimization and coding strategies, it can quickly extract key features in complex environments and perform efficient comparisons, thereby meeting the fuzzy matching requirements in complex layout environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a schematic diagram of the application scenario of the layout fuzzy matching method provided in the embodiment of the present application.

[0018] Figure 2 It is a flow chart of the layout fuzzy matching method provided in the embodiment of the present application.

[0019] Figure 3 This is an example diagram of the target layout provided in the embodiment of the present application.

[0020] Figure 4 It is a structural schematic diagram of the layout fuzzy matching device provided in an embodiment of the present application.

[0021] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0023] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0024] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0026] In the description of the present application, it should be noted that the terms "upper", "lower", "left", "right", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present application. In addition, terms such as "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0027] Traditional layout fuzzy matching methods mainly rely on geometric feature comparison or template matching. Although these methods can provide high matching accuracy under ideal conditions, they are sensitive to noise, rotation, scaling and other transformations in actual applications, and it is difficult to meet the fuzzy matching requirements in complex layout environments.

[0028] Based on this, the embodiments of the present application provide a method, device, storage medium and electronic device for fuzzy matching of a layout. Specifically, the fuzzy matching device of the layout can be integrated in an electronic device, and the electronic device can be a server or a terminal or other device; wherein the terminal can include a mobile phone, a wearable smart device, a tablet computer, a laptop computer, and a personal computer (PC), etc.; the server can be a single server or a server cluster composed of multiple servers, and can be a physical server or a virtual server.

[0029] For example, Figure 1 As shown, after acquiring the target layout, the electronic device normalizes the coordinate points of all polygons in the target layout to obtain the target coordinates; then performs Fourier transform and frequency domain truncation processing based on the target coordinates to obtain the target frequency domain signal; then samples the target frequency domain signal to obtain sampled spectrum data; then encodes the sampled spectrum data to generate a coding value; finally, fuzzy match the target layout with the layout to be matched based on the coding value.

[0030] The technical solutions shown in the present application will be described in detail below through specific embodiments. It should be noted that the description order of the following embodiments is not intended to limit the priority order of the embodiments.

[0031] See also Figure 2 , Figure 2 : is a schematic diagram of the flow of the layout fuzzy matching method provided in the embodiment of the present application. The specific flow of the layout fuzzy matching method can be as follows: 101. Obtain a target map, normalize the coordinate points of all polygons in the target map, and obtain target coordinates.

[0032] version Figure 1 Generally, it is created by chip design software (such as Cadence, Mentor Graphics, Synopsys, etc.). In the semiconductor manufacturing industry, in order to ensure the standardization and compatibility of design data, specific file format standards such as GDS (Graphic Data System) or OASIS (Open Artwork System Interchange Standard) are usually used to save these layouts.

[0033] The target layout in the embodiment of the present application is a partial layout information cut out from the complete layout. The target layout may include at least one polygon. Figure 4 As shown, a target layout contains 3 polygons.

[0034] It can be understood that each polygon is composed of multiple coordinate points. For example, a polygon P can be represented as: P={(x1,y1),(x2,y2),...,(x n ,y n )}.

[0035] Among them, normalization processing refers to mapping the coordinate points of all polygons in the target layout to a relative coordinate system. Therefore, before normalization processing, it is necessary to find a coordinate point as a reference point.

[0036] Typically, one of the coordinate points of the bounding box of the target layout can be selected as a reference point. In some embodiments, the bounding box of the target layout can be a rectangle that surrounds all polygons in the target layout. The bounding box can be calculated as follows: First, calculate the minimum X and Y coordinates of the bounding box, that is: min =min(x1,x2,...,x n ), y min =min(y1,y2,...,y n ).

[0037] Then, calculate the maximum X and Y coordinates of the bounding box, that is: max =max(x1,x2,...,x n ), y max =max(y1,y2,...,y n ).

[0038] Finally, the bounding box is formed, that is: B=[(x min ,y min ),(x max ,y max )].

[0039] In some embodiments, the minimum coordinate point of the bounding box of the target layout can be selected as the reference point. That is, the step of "normalizing the coordinate points of all polygons in the target layout to obtain the target coordinates" can be specifically: obtaining the coordinate points of all polygons in the target layout; calculating the bounding box of the target layout; taking the minimum coordinate point of the bounding box as the reference point, normalizing the coordinate points of all polygons to obtain the target coordinates.

[0040] Among them, the step of "taking the minimum coordinate point of the bounding box as the reference point, normalizing the coordinate points of all polygons to obtain the target coordinates" can specifically be: obtaining the minimum coordinate point of the bounding box; subtracting the coordinate points of all polygons from the minimum coordinate point respectively to obtain the target coordinates.

[0041] For example, suppose one of the coordinate points is (x, y) and the target coordinate is (x′, y′). In this case, x′=xx min , y′=yy min .

[0042] In some embodiments, in order to further ensure the consistency of the scale of the target layout, the target coordinates can be normalized and scaled, that is, the coordinates are normalized to the range of [0,1] or [-1,1]: x′′=x′ / (x max −x min ), y′′=y′ / (y max −y min ). In this way, all coordinate points of the target layout are mapped to the unit interval to avoid matching errors caused by different sizes.

[0043] It can be understood that after normalization, no matter where the target layout is originally located in the complete layout, its coordinate points will become relative positions, so that different target layouts can be directly compared, improving the stability of Fourier transform matching.

[0044] 102. Perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal.

[0045] The Fourier transform may be a short-time Fourier transform (STFT) or a discrete-time Fourier transform (DTFT).

[0046] The embodiment of the present application takes the Fourier transform being a short-time Fourier transform as an example to explain step 102 in detail.

[0047] Since the short-time Fourier transform needs to process the coordinate points in a window, and the input of the Fourier transform needs to be an ordered data sequence. If the order of the coordinate points is disordered, the spectrum information after the Fourier transform may change with the order of the input data, resulting in unstable matching results. After sorting, the stability and accuracy of the matching can be improved.

[0048] Therefore, step 102 may specifically be: sorting all target coordinates to generate an ordered coordinate sequence; performing short-time Fourier transform on the ordered coordinate sequence to obtain a total frequency domain signal of the target layout; performing frequency domain truncation processing on the total frequency domain signal to obtain a target frequency domain signal.

[0049] In some embodiments, all target coordinates may be sorted by X axis, for example, first sorted by X coordinate in ascending order, and if X is the same, then sorted by Y coordinate in ascending order.

[0050] In some embodiments, a window function such as a Gaussian window or a Hamming window may be used to perform a short-time Fourier transform on the ordered coordinate sequence. It is understandable that the window width may be adjusted according to the density and accuracy requirements of the target layout.

[0051] The purpose of frequency domain truncation processing on the total frequency domain signal is to filter the total frequency domain signal to retain the main frequency components and remove high-frequency noise, further enhance the main features and reduce unimportant edge information, thereby improving the subsequent matching accuracy.

[0052] In some embodiments, a Gaussian window may be used to perform frequency domain truncation processing on the total frequency domain signal, which may be specifically as follows:

[0053] In the above formula, σ is the influencing factor of the window width.

[0054] 103. Sample the target frequency domain signal to obtain sampled spectrum data.

[0055] In some embodiments, the target frequency domain signal can be sampled at equal intervals according to a preset sampling step. It should be noted that the sampling step needs to be determined through experiments. If the sampling step is too large, detailed information will be lost and the matching effect will be poor. If the sampling step is too narrow, the amount of calculation will increase and the efficiency will be affected.

[0056] 104. Encode the sampled spectrum data to generate a coded value.

[0057] Specifically, the sampled spectrum data may be converted into a character string; and then the character string may be encoded to generate an encoded value.

[0058] In some embodiments, the BKDRHash algorithm may be used to hash the string to generate a unique hash value.

[0059] Specifically, the hash value may be initialized to 0, and a prime number may be set as a multiplication factor; then each character in the string is traversed, the ASCII code of each character is multiplied by the multiplication factor, and then added to the hash value to generate a unique hash value.

[0060] 105. Fuzzy matching is performed between the target layout and the layout to be matched according to the coding value.

[0061] It is understandable that the layout to be matched can also be converted into a coding value through the above steps. Then, the coding value of the target layout is compared with the coding value of the layout to be matched to determine whether the target layout is consistent with the layout to be matched.

[0062] When the encoding value is a unique hash value, the layout to be matched can also be converted into a unique hash value through the above steps. Then, the unique hash value of the target layout is compared with the unique hash value of the layout to be matched to determine whether the target layout is consistent with the layout to be matched.

[0063] It can be understood that when the encoding values ​​are completely consistent, it can be considered that the target layout and the to-be-matched layout are identical. Figure 1 To.

[0064] In summary, the layout fuzzy matching method provided in the embodiment of the present application includes obtaining the target layout, normalizing the coordinate points of all polygons in the target layout to obtain the target coordinates; performing Fourier transform and frequency domain truncation processing based on the target coordinates to obtain the target frequency domain signal; sampling the target frequency domain signal to obtain sampled spectrum data; encoding the sampled spectrum data to generate a coding value; and fuzzy matching the target layout with the layout to be matched according to the coding value. This scheme converts the layout features from the time domain to the frequency domain through Fourier transform, thereby improving the robustness of layout matching, and by combining feature optimization (i.e., frequency domain truncation processing and sampling) and coding strategies, it can quickly extract key features and perform efficient comparison in complex environments, reduce computational complexity, and improve matching efficiency, thereby meeting the fuzzy matching requirements in complex layout environments.

[0065] In order to better implement the layout fuzzy matching method provided in the embodiment of the present application, the embodiment of the present application also provides a layout fuzzy matching device. The meanings of the terms are the same as those in the above-mentioned layout fuzzy matching method, and the specific implementation details can refer to the description in the method embodiment.

[0066] See also Figure 4 , Figure 4 201 is a schematic diagram of the structure of a layout fuzzy matching device provided in an embodiment of the present application. The layout fuzzy matching device may include an acquisition unit 201, a transformation unit 202, a sampling unit 203, an encoding unit 204 and a matching unit 205. The acquisition unit 201 is used to acquire the target layout, normalize the coordinate points of all polygons in the target layout, and obtain the target coordinates; A transform unit 202 is used to perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal; The sampling unit 203 is used to sample the target frequency domain signal to obtain sampled spectrum data; The encoding unit 204 is used to encode the sampled spectrum data to generate a code value; The matching unit 205 is used to perform fuzzy matching between the target layout and the layout to be matched according to the coding value.

[0067] The specific implementation methods of the above-mentioned units can be found in the above-mentioned embodiments of the layout fuzzy matching method, which will not be described one by one here.

[0068] In summary, the layout fuzzy matching device provided in the embodiment of the present application obtains the target layout through the acquisition unit 201, normalizes the coordinate points of all polygons in the target layout, and obtains the target coordinates; the transformation unit 202 performs Fourier transform and frequency domain truncation processing based on the target coordinates to obtain the target frequency domain signal; the sampling unit 203 samples the target frequency domain signal to obtain the sampled spectrum data; the encoding unit 204 encodes the sampled spectrum data to generate a coding value; the matching unit 205 performs fuzzy matching on the target layout and the layout to be matched according to the coding value. This scheme converts the layout features from the time domain to the frequency domain through Fourier transform, improves the robustness of layout matching, and by combining feature optimization (i.e., frequency domain truncation processing and sampling) and coding strategies, it can quickly extract key features and perform efficient comparison in complex environments, reduce computational complexity, and improve matching efficiency, thereby meeting the fuzzy matching requirements in complex layout environments.

[0069] The present application also provides an electronic device, in which the layout fuzzy matching device of the present application can be integrated, such as Figure 5 As shown, it shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically: The electronic device may include one or more processors 301 of processing cores and one or more computer-readable storage media memories 302 and other components. Those skilled in the art will appreciate that Figure 5 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. The processor 301 is the control center of the electronic device, which uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing the software program and / or the present application stored in the memory 302, and calling the data stored in the memory 302, so as to monitor the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operation storage medium, user interface and application program, etc., and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0070] The memory 302 can be used to store software programs and the present application. The processor 301 executes various functional applications and data processing by running the software programs and the present application stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating storage medium, an application required for at least one function, etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0071] Although not shown, the electronic device may further include a display unit, an input unit, a power supply, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows: Obtain the target map, normalize the coordinate points of all polygons in the target map, and obtain the target coordinates; Perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain the target frequency domain signal; Sampling the target frequency domain signal to obtain sampled spectrum data; Encode the sampled spectrum data to generate a coded value; The target layout is fuzzily matched with the layout to be matched according to the coding value.

[0072] In summary, the electronic device provided by the embodiment of the present application can obtain the target layout, normalize the coordinate points of all polygons in the target layout, and obtain the target coordinates; perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain the target frequency domain signal; sample the target frequency domain signal to obtain sampled spectrum data; encode the sampled spectrum data to generate a coding value; and fuzzy match the target layout with the layout to be matched according to the coding value. This solution converts the layout features from the time domain to the frequency domain through Fourier transform, improves the robustness of layout matching, and by combining feature optimization (i.e., frequency domain truncation processing and sampling) and coding strategies, it can quickly extract key features and perform efficient comparison in complex environments, reduce computational complexity, and improve matching efficiency, thereby meeting the fuzzy matching requirements in complex layout environments.

[0073] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0074] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any method provided in the embodiment of the present application. For example, the instructions can execute the following steps: Obtain the target map, normalize the coordinate points of all polygons in the target map, and obtain the target coordinates; Perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain the target frequency domain signal; Sampling the target frequency domain signal to obtain sampled spectrum data; Encode the sampled spectrum data to generate a coded value; The target layout is fuzzily matched with the layout to be matched according to the coding value.

[0075] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0076] In summary, the storage medium provided in the embodiment of the present application can obtain the target layout, normalize the coordinate points of all polygons in the target layout, and obtain the target coordinates; perform Fourier transform and frequency domain truncation based on the target coordinates to obtain the target frequency domain signal; sample the target frequency domain signal to obtain sampled spectrum data; encode the sampled spectrum data to generate a coding value; and fuzzy match the target layout with the layout to be matched according to the coding value. This solution converts the layout features from the time domain to the frequency domain through Fourier transform, improves the robustness of layout matching, and by combining feature optimization (i.e., frequency domain truncation and sampling) and coding strategies, it can quickly extract key features and perform efficient comparison in complex environments, reduce computational complexity, and improve matching efficiency, thereby meeting the fuzzy matching requirements in complex layout environments.

[0077] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0078] Since the instructions stored in the storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects that can be achieved by any method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0079] The above respectively introduces in detail the layout fuzzy matching method, device, storage medium and electronic device provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the core idea of ​​the present application; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A layout fuzzy matching method, characterized in that: include: Acquire a target map, and normalize the coordinate points of all polygons in the target map to obtain target coordinates; Perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal; Sampling the target frequency domain signal to obtain sampled spectrum data; Encoding the sampled spectrum data to generate a coded value; The target layout is fuzzily matched with the layout to be matched according to the coding value.

2. The layout fuzzy matching method according to claim 1, characterized in that: The Fourier transform and frequency domain truncation processing are performed based on the target coordinates to obtain a target frequency domain signal, including: Sorting all the target coordinates to generate an ordered coordinate sequence; Performing short-time Fourier transform on the ordered coordinate sequence to obtain a total frequency domain signal of the target layout; Perform frequency domain truncation processing on the total frequency domain signal to obtain a target frequency domain signal.

3. The layout fuzzy matching method according to claim 1, characterized in that: The step of encoding the sampled spectrum data to generate a coded value comprises: Convert the sampled spectrum data into a character string; Encode the string to generate an encoded value.

4. The layout fuzzy matching method as claimed in claim 3, characterized in that: The encoding of the string to generate an encoded value includes: The string is hashed using the BKDRHash algorithm to generate a unique hash value.

5. The layout fuzzy matching method according to claim 4, characterized in that: The BKDRHash algorithm is used to perform hash encoding on the string to generate a unique hash value, including: Initialize the hash value to 0 and set the prime number as the multiplication factor; Each character in the string is traversed, and the ASCII code of each character is multiplied by the multiplication factor and then added to the hash value to generate a unique hash value.

6. The layout fuzzy matching method according to claim 1, characterized in that: The normalizing of the coordinate points of all polygons in the target layout to obtain the target coordinates includes: Obtaining coordinate points of all polygons in the target map; Calculating a bounding box of the target layout; Taking the minimum coordinate point of the bounding box as a reference point, normalizing the coordinate points of all the polygons to obtain the target coordinates.

7. The layout fuzzy matching method according to claim 6, characterized in that: The step of taking the minimum coordinate point of the bounding box as a reference point and normalizing the coordinate points of all the polygons to obtain the target coordinates includes: Obtaining the minimum coordinate point of the bounding box; The coordinate points of all the polygons are subtracted from the minimum coordinate point to obtain the target coordinates.

8. A layout fuzzy matching device, characterized in that: include: An acquisition unit is used to acquire a target layout, and normalize the coordinate points of all polygons in the target layout to obtain target coordinates; A transform unit, configured to perform Fourier transform and frequency domain truncation processing based on the target coordinates to obtain a target frequency domain signal; A sampling unit, used for sampling the target frequency domain signal to obtain sampled spectrum data; An encoding unit, used for encoding the sampled spectrum data to generate an encoding value; A matching unit is used to perform fuzzy matching between the target layout and the layout to be matched according to the coding value.

9. A storage medium, characterized in that: The storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the layout fuzzy matching method described in any one of claims 1-7.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the layout fuzzy matching method as described in any one of claims 1 to 7 when executing the computer program.

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