Critical dimension measurement method, system and device and storage medium
By performing image recognition and grayscale processing on scanning electron microscope images, combined with a parabolic fitting model, efficient critical dimension measurement was achieved without GDS, solving the problem of low efficiency in traditional methods and meeting the mass production requirements of advanced semiconductor processes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-21
- Publication Date
- 2026-03-13
AI Technical Summary
Traditional critical dimension measurement methods based on Design-gauge and GDS face problems such as low measurement efficiency, long program debugging cycle and high equipment load in the process of semiconductor process evolution to 7nm and more advanced nodes, making it difficult to adapt to the needs of large-scale mass production.
By acquiring scanning electron microscope images and performing image recognition processing, structural graphics are identified and key dimensions are measured. Key dimensions are accurately determined using grayscale processing and parabolic fitting models, and the location of minimum values is marked, achieving efficient measurement under GDS-free conditions.
It improves the efficiency of critical dimension measurement, enabling rapid identification and labeling of minimum critical dimensions without relying on GDS, thus meeting the mass production requirements of advanced processes.
Smart Images
Figure CN121655434A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of semiconductor manufacturing, and more specifically to a method, system, device, and storage medium for measuring critical dimensions. Background Technology
[0002] In the semiconductor manufacturing industry, critical dimension (CD) measurement is a core step in ensuring chip pattern stability and controlling product performance and yield. By accurately measuring CD parameters such as pattern width and spacing formed by processes such as photolithography and etching, process deviations can be corrected in a timely manner, preventing chip malfunctions caused by pattern distortion.
[0003] Currently, design gauges and GDS (graphic design system) are the mainstream technologies for building CD-SEM (critical dimension scanning electron microscope) measurement programs. Design gauges can preset measurement areas and judgment criteria, while GDS provides design data for chip patterns. The combination of the two can quickly match the actual wafer pattern with the design layout, achieving efficient measurement under traditional processes (such as 28nm and above), and has become a common solution in the industry.
[0004] However, as semiconductor processes evolve towards 7nm, 5nm, and more advanced nodes, chip pattern complexity increases significantly, and the number of CD measurement points that need to be monitored to meet performance requirements grows exponentially. Traditional measurement methods based on Design-gauge and GDS face problems such as a significant decrease in measurement efficiency, extended program debugging cycles, and excessive equipment load, making it difficult to adapt to the large-scale mass production requirements of advanced processes. There is an urgent need to break through existing technological bottlenecks and develop a more efficient CD measurement program construction solution. Summary of the Invention
[0005] This application provides a method, system, device, and storage medium for measuring critical dimensions, which can complete the measurement of a large number of critical dimensions without using GDS, thereby improving measurement efficiency.
[0006] In a first aspect, embodiments of this application provide a method for measuring critical dimensions, including: S1: Acquire several scanning electron microscope images; S2: For each of the scanning electron microscope images, perform image recognition processing; wherein, the image recognition processing includes: S21: Identify all structural patterns in the scanning electron microscope image; S22: Measure the key dimensions of all the structural graphics to obtain several key dimensions; S23: Identify the minimum critical dimension from all the critical dimensions; S24: Mark the position of the minimum value of the key dimension in the scanning electron microscope image.
[0007] In some embodiments, the step of identifying all structural patterns in the scanning electron microscope image includes: The scanning electron microscope image is processed to obtain a binary grayscale image by performing grayscale processing according to the set grayscale threshold. The structural graphics in the grayscale image are displayed as white parts.
[0008] In some embodiments, the step of measuring key dimensions of all the structural graphics to obtain several key dimensions includes: Identify the outline boundary of the target structural graphic, wherein the target structural graphic is any one of all structural graphics; Based on the outline boundary, identify the centerline of the target structural graphic; Using the center line as a reference, the pixel positions of the contour boundary are identified to obtain several measurement lines, and the distance between adjacent measurement lines is a preset spacing. The key dimensions corresponding to the measurement lines are obtained.
[0009] In some embodiments, the processing of each of the measurement lines in the step of obtaining the key dimensions corresponding one-to-one with the measurement lines includes: By identifying the boundary pixel positions at both ends of the measurement line, the initial integer pixel-level boundary for critical dimension measurement is determined; Identify the grayscale change region corresponding to the initial integer pixel-level boundary, locate the position with the largest grayscale gradient within the region, and the position with the largest grayscale gradient is the interval where the actual physical boundary of the measurement line is located, and the interval is located between two adjacent integer pixel points; Extract grayscale data from ±2~3 pixels near each initial integer pixel-level boundary to form two grayscale sample sets; Based on each of the grayscale sample sets, a quadratic differential function is defined respectively; A parabolic fitting model is constructed based on each of the aforementioned quadratic differential functions, and the vertex of the parabolic fitting model corresponds to the zero point of the differential at the position of the maximum gradient of the gray value. The grayscale sample set is fitted using the parabolic fitting model to obtain the coordinates of the vertex of the parabola, which are used as the sub-pixel positions of the endpoint boundaries of the measurement line. The key dimensions of the measurement line are obtained based on the sub-pixel positions of the two endpoint boundaries of the measurement line.
[0010] In some embodiments, in the step of identifying the contour boundary of the target structure graphic based on the centerline, the contour detection algorithm used is the OpenCV findContours algorithm.
[0011] Secondly, embodiments of this application provide a critical dimension measurement system, including: The image acquisition module is used to acquire several scanning electron microscope images; The image processing module is used to perform image recognition processing on each of the scanning electron microscope images; In the image recognition process, the image processing module performs the following processing: Identify all structural patterns in the scanning electron microscope image; Key dimensions were measured for all the structural graphics to obtain several key dimensions; Identify the minimum critical dimension from all the critical dimensions described; The location of the minimum critical dimension is marked in the scanning electron microscope image.
[0012] Thirdly, embodiments of this application provide an intelligent device, which includes a processor and a memory. The memory stores a computer program, and when the processor executes the computer program, it implements the key dimension measurement method as described in the first aspect.
[0013] Fourthly, embodiments of this application provide a storage medium storing a program, which, when executed by a processor, is used to implement the critical dimension measurement method as described in the first aspect.
[0014] The technical solution of this application has at least the following advantages: 1. By acquiring several scanning electron microscope (SEM) images and performing image recognition processing on each SEM image using a preset image recognition technology, the structural patterns in each SEM image are first identified. Then, key dimensions are measured on all structural patterns to obtain several key dimensions. Finally, the minimum value of the key dimension is identified from all the key dimensions, and the position of the minimum value is marked on the SEM image. This method enables the measurement of a large number of key dimensions without using GDS, thus improving measurement efficiency. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0016] Figure 1 This is a flowchart of a key dimension measurement method provided in an exemplary embodiment of this application; Figure 2 This is a schematic diagram of a grayscale scanning electron microscope image provided in an exemplary embodiment of this application; Figure 3 This is a schematic diagram of a scanning electron microscope image processed by step S222, provided in an exemplary embodiment of this application; Figure 4 This is a schematic diagram provided by an exemplary embodiment of the present application for illustrating measurement lines in a target structure graphic; Figure 5 This is a schematic diagram provided by an exemplary embodiment of the present application for illustrating a scanning electron microscope image showing the location of a graphic marked with the minimum value of a critical dimension; Figure 6 This is a structural block diagram of a smart device provided in an exemplary embodiment of this application. Detailed Implementation
[0017] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0018] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0019] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal connection of two components; and they can refer to a wireless connection or a wired connection. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.
[0020] Furthermore, the technical features involved in the different embodiments of this application described below can be combined with each other as long as they do not conflict with each other.
[0021] This application provides a method for measuring critical dimensions, referring to... Figure 1 The method includes the following steps: S1: Obtain several scanning electron microscope images.
[0022] In practice, semiconductor devices can be scanned using a high-resolution electron beam scanning device, resulting in a large number of scanning electron microscope (SEM) images. These images cover all structures within the semiconductor device that require critical dimensional measurements. The processing terminal then acquires these SEM images uploaded by the electron beam scanning device.
[0023] S2: Perform image recognition processing on each scanning electron microscope image separately.
[0024] In practice, the processing terminal performs further image recognition processing on each scanning electron microscope image.
[0025] Image recognition processing may include the following steps: S21: Identify all structural patterns in scanning electron microscope images.
[0026] During implementation, the processing terminal will identify all structural patterns in the scanning electron microscope image, facilitating further processing.
[0027] Furthermore, the processing steps in this step may include: According to the set grayscale threshold, the scanning electron microscope image is processed to obtain a binarized grayscale image, in which the structural graphics are displayed as white parts.
[0028] The preset grayscale threshold can be set as needed, enabling the processing terminal to distinguish between microstructures requiring critical size measurement (such as etched trenches) and other background.
[0029] In practice, the processing terminal performs grayscale processing on the scanning electron microscope image according to a pre-set grayscale threshold, obtaining a binarized grayscale image. For example, referring to... Figure 2 The grayscale image shown has microstructures that require critical dimension measurements displayed in white, while other parts are displayed in black.
[0030] S22: Measure the critical dimensions of all structural graphics to obtain several critical dimensions.
[0031] In practice, the processing terminal measures the key dimensions of all identified structural graphics to obtain several key dimensions.
[0032] Furthermore, this step may include the following processing: S221: Identify the outline boundary of the target structural graphic, where the target structural graphic is any one of all structural graphics.
[0033] In this step, the contour detection algorithm used can be OpenCV's findContours algorithm.
[0034] Reference Figure 2 It displays several structural patterns in a scanning electron microscope image, with the target structural pattern being any one of them. In implementation, for the target structural pattern, the processing terminal can first identify its contour boundary.
[0035] S222: Identify the centerline of the target structural graphic based on the contour boundary.
[0036] In implementation, for a target structural graphic, the processing terminal can further identify its centerline in a preset direction based on its contour boundary. Figure 2 In this context, the preset direction is the length direction of the target structural graphic, and the recognition result can be as follows: Figure 3 As shown.
[0037] S223: Using the center line as a reference, identify the pixel position of the contour boundary to obtain several measurement lines. The distance between adjacent measurement lines is a preset spacing.
[0038] In implementation, the processing terminal can start from the centerline and further identify the pixel positions of the contour boundaries, obtaining several measurement lines perpendicular to the centerline direction. (Refer to...) Figure 4 Each green line segment represents a measurement line, with the two ends of the measurement line representing the pixel position of the contour boundary. For the preset acquisition interval, the closer the interval, the more comprehensive the measurement, and the less likely it is to miss weak points. The densest interval can be set to measure every single pixel.
[0039] S224: Obtain the critical dimensions that correspond one-to-one with the measurement lines.
[0040] In practice, the processing terminal can process each measurement line separately to obtain the critical dimensions corresponding to each measurement line.
[0041] Furthermore, in this step, more accurate key dimensions can be obtained using grayscale gradients and parabolic approximation. The processing procedure for each measurement line can be as follows: By identifying the boundary pixel positions at both ends of the measurement line, the initial integer pixel-level boundaries for critical dimension measurements are determined.
[0042] Identify the grayscale change region corresponding to the initial integer pixel-level boundary, locate the position with the largest grayscale gradient within the region, and the position with the largest grayscale gradient is the interval where the actual physical boundary of the measurement line is located, and this interval is located between two adjacent integer pixel points.
[0043] In practice, because the grayscale values at structural boundaries in scanning electron microscope images change abruptly, such as from dark to light or from light to dark, this characteristic can be used to determine the actual physical boundary. The processing terminal can identify the grayscale change region corresponding to the initial integer pixel-level boundary, locate the position with the largest grayscale gradient within that region, and the position with the largest grayscale gradient is the interval where the actual physical boundary of the measurement line is located, and this interval lies between two adjacent integer pixels. Extract grayscale data from ±2 to 3 pixels near the boundary of each initial integer pixel level to form two grayscale sample sets.
[0044] For each grayscale sample set, a quadratic differential function is defined.
[0045] A parabolic fitting model is constructed based on each quadratic differential function. The vertex of the parabolic fitting model corresponds to the zero point of the differential at the position where the gray value gradient is maximum.
[0046] In practice, the differential of the grayscale change curve at the maximum gradient is equal to 0, which conforms to the characteristics of a parabola. Therefore, the processing terminal can construct a parabolic fitting model based on each quadratic differential function. The vertex of the parabolic fitting model corresponds to the zero point of the differential at the maximum gradient of the grayscale value.
[0047] By fitting the grayscale sample set using a parabolic fitting model, the coordinates of the parabola's vertex are obtained and used as the sub-pixel positions of the measurement line's endpoint boundaries.
[0048] The key dimensions of the measurement line are obtained based on the sub-pixel positions of the two endpoints of the measurement line.
[0049] For example, the processing terminal calculates the length of the measurement line based on the sub-pixel positions of the two endpoint boundaries of the measurement line, which corresponds to the critical dimension of the measurement line.
[0050] S23: Identify the minimum critical dimension from all critical dimensions.
[0051] In practice, for any given scanning electron microscope image, the processing terminal can identify the minimum critical dimension from all the critical dimensions.
[0052] S24: Mark the location of the minimum critical dimension in the scanning electron microscope image.
[0053] In implementation, refer to Figure 5 The processing terminal can mark the graphic location (highlighted in blue) of the minimum critical dimension in the scanning electron microscope image. When multiple minimum critical dimensions exist simultaneously, the graphic locations of all minimum critical dimensions will be marked.
[0054] Furthermore, after all the scanning electron microscope (SEM) images have been processed, the processing results are stored in the database of the processing terminal, which can then identify the minimum critical dimensions in all the SEM images.
[0055] The critical dimension measurement method provided in this application acquires several scanning electron microscope (SEM) images and performs image recognition processing on each SEM image using a preset image recognition technology. In the image recognition process, the structural pattern in each SEM image is first identified, and then the critical dimensions of all structural patterns are measured to obtain several critical dimensions. Finally, the minimum critical dimension is identified from all the critical dimensions, and the position of the minimum critical dimension is marked on the SEM image. This method enables the measurement of a large number of critical dimensions without using GDS, thus improving measurement efficiency.
[0056] This application also provides a critical dimension measurement system, including: The image acquisition module is used to acquire several scanning electron microscope images.
[0057] The image processing module is used to perform image recognition processing on each of the scanning electron microscope images.
[0058] In the image recognition process, the image processing module performs the following processing: Identify all structural patterns in the scanning electron microscope image; Key dimensions were measured for all the structural graphics to obtain several key dimensions; Identify the minimum critical dimension from all the critical dimensions described; The location of the minimum critical dimension is marked in the scanning electron microscope image.
[0059] refer to Figure 6This application also provides an intelligent device, which includes a processor 610 and a memory 620.
[0060] Processor 610 may include one or more processing cores. Processor 610 connects various parts of the device using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 620, and by calling data stored in memory 620. Optionally, processor 610 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). Processor 610 may integrate one or more of a Central Processing Unit (CPU) and a modem. The CPU primarily handles the operating system and applications; the modem is used for wireless communication. It is understood that the modem may also not be integrated into processor 610 and may be implemented as a separate chip.
[0061] Optionally, when the processor 610 executes the program instructions in the memory 620, it implements the key dimension measurement methods provided in the above-described method embodiments.
[0062] The memory 620 may include random access memory (RAM) or read-only memory. Optionally, the memory 620 may include a non-transitory computer-readable storage medium. The memory 620 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 620 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the various method embodiments described above, etc.; the data storage area may store data created according to the use of the device, etc.
[0063] Optionally, this application also provides a storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or instruction set is loaded and executed by the processor to implement the key dimension measurement method provided in the above method embodiments.
[0064] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this application.
Claims
1. A method for measuring critical dimensions, characterized in that, include: S1: Acquire several scanning electron microscope images; S2: For each of the scanning electron microscope images, perform image recognition processing; wherein, the image recognition processing includes: S21: Identify all structural patterns in the scanning electron microscope image; S22: Measure the key dimensions of all the structural graphics to obtain several key dimensions; S23: Identify the minimum critical dimension from all the critical dimensions; S24: Mark the position of the minimum value of the key dimension in the scanning electron microscope image.
2. The critical dimension measurement method according to claim 1, characterized in that, The step of identifying all structural patterns in the scanning electron microscope image includes: The scanning electron microscope image is processed to obtain a binary grayscale image by performing grayscale processing according to the set grayscale threshold. The structural graphics in the grayscale image are displayed as white parts.
3. The critical dimension measurement method according to claim 2, characterized in that, The step of measuring key dimensions of all the structural graphics to obtain several key dimensions includes: Identify the outline boundary of the target structural graphic, wherein the target structural graphic is any one of all structural graphics; Based on the outline boundary, identify the centerline of the target structural graphic; Using the center line as a reference, the pixel positions of the contour boundary are identified to obtain several measurement lines, and the distance between adjacent measurement lines is a preset spacing. The key dimensions corresponding to the measurement lines are obtained.
4. The critical dimension measurement method according to claim 3, characterized in that, In the step of obtaining the critical dimensions corresponding one-to-one with the measurement lines, the processing of each measurement line includes: By identifying the boundary pixel positions at both ends of the measurement line, the initial integer pixel-level boundary for critical dimension measurement is determined; Identify the grayscale change region corresponding to the initial integer pixel-level boundary, locate the position with the largest grayscale gradient within the region, and the position with the largest grayscale gradient is the interval where the actual physical boundary of the measurement line is located, and the interval is located between two adjacent integer pixel points; Extract grayscale data from ±2 to 3 pixels near each initial integer pixel-level boundary to form two grayscale sample sets; For each of the grayscale sample sets, a quadratic differential function is defined respectively; A parabolic fitting model is constructed based on each of the aforementioned quadratic differential functions, and the vertex of the parabolic fitting model corresponds to the zero point of the differential at the position of the maximum gradient of the gray value. The grayscale sample set is fitted using the parabolic fitting model to obtain the coordinates of the vertex of the parabola, which are used as the sub-pixel positions of the endpoint boundaries of the measurement line. The key dimensions of the measurement line are obtained based on the sub-pixel positions of the two endpoint boundaries of the measurement line.
5. The critical dimension measurement method according to claim 1, characterized in that, In the step of identifying the contour boundary of the target structure graphic based on the center line, the contour detection algorithm used is OpenCV's findContours algorithm.
6. A critical dimension measurement system, characterized in that, include: The image acquisition module is used to acquire several scanning electron microscope images; The image processing module is used to perform image recognition processing on each of the scanning electron microscope images; In the image recognition process, the image processing module performs the following processing: Identify all structural patterns in the scanning electron microscope image; Key dimensions were measured for all the structural graphics to obtain several key dimensions; Identify the minimum critical dimension from all the critical dimensions described; The location of the minimum critical dimension is marked in the scanning electron microscope image.
7. A smart device, characterized in that, The smart device includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the method of any one of claims 1 to 5.
8. A storage medium storing a program that, when executed by a processor, implements the method as claimed in any one of claims 1 to 5.