SEM image contour extraction method, system and terminal

Abstract

The invention provides an SEM image contour extraction method and system and a terminal, and the method comprises the steps: respectively extracting an outer contour line and an inner contour line of a to-be-measured pattern in a to-be-measured wafer according to an SEM image, and selecting the outer contour line or the inner contour line as an initial contour line of the to-be-measured pattern according to different properties of the to-be-measured pattern. Correcting the initial contour line according to a key dimension machine table measurement value output by an electronic scanning microscope machine table to obtain a target contour line of the to-be-measured graph; therefore, the precision and reliability of the target contour line are improved, the contour morphology characteristics of the to-be-measured graph are reserved, and the verification and calibration of the OPC model are facilitated. The technical problems of low measurement precision, poor reliability and critical dimension deviation of the contour output by an electronic scanning microscope machine in the prior art of extracting the two-dimensional contour of the to-be-measured pattern of the wafer from the SEM image are solved.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and in particular to a method, system and terminal for extracting contours from SEM images. Background Technology

[0002] During chip manufacturing, when the pattern on the photomask is projected onto the wafer by a photolithography machine, the actual image will deviate from the design pattern due to the diffraction effect of light. This manifests as shortened line ends, narrower linewidths, and rounded corners instead of right angles. Optical Proximity Correction (OPC) technology compensates for these optical errors by pre-adjusting the photomask pattern, ensuring that the actual image after exposure is as close as possible to the design pattern.

[0003] To validate and calibrate the OPC model, a scanning electron microscope (SEM) is typically used to acquire SEM images of the wafer pattern to be measured. The actual outline of the wafer pattern to be measured is extracted from the SEM images, and the linewidth (CD) difference between the actual outline and the design pattern is compared. Line end shortening and edge placement error (EPE) are also calculated to optimize the parameters of the OPC model and improve the accuracy of the OPC model prediction results.

[0004] Therefore, extracting the two-dimensional contour of the wafer to be measured pattern from SEM images is fundamental for calculating and analyzing key parameters. The accuracy and reliability of contour extraction have a significant impact on the improvement strategy and prediction accuracy of the OPC model, which in turn affects the accuracy of the actual image pattern in the lithography process, and ultimately the quality and performance of the final semiconductor product.

[0005] In existing technologies, extracting the two-dimensional contour of a wafer to be measured from SEM images mainly relies on digital image processing algorithms. Specifically, edge detection algorithms, such as threshold-based edge detection operators, are used to identify edge pixels in the SEM image. Multiple detected edge pixels are then connected, fitted, and smoothed to generate a continuous vector contour line. However, existing contour extraction techniques have significant shortcomings:

[0006] ①SEM images themselves have serious problems such as noise, blurred edges and uneven contrast, resulting in broken, rough contours and full of false edges extracted based on traditional edge detection algorithms.

[0007] ② The threshold-based edge detection operator is extremely sensitive to parameter selection, and morphological post-processing may introduce geometric distortion, affecting the measurement accuracy of the wafer pattern to be measured.

[0008] ③ The contour measurements obtained from SEM images deviate from the key contour dimensions output by the scanning electron microscope, making accurate matching impossible.

[0009] Currently, with the widespread application of deep learning models, there are attempts to extract the two-dimensional contours of wafers to be measured from SEM images based on deep learning models. However, this method heavily relies on a large amount of labeled data, and the model's generalization ability is limited. More importantly, the output of a purely data-driven deep learning model may violate physical laws, such as the phenomenon of contour self-intersection or the contour exhibiting a non-smooth jagged shape, resulting in a lack of interpretability in the obtained contour measurement values ​​and making it difficult to guarantee reliability under harsh measurement scenarios. Summary of the Invention

[0010] In view of the shortcomings of the prior art described above, the purpose of this application is to provide a SEM image contour extraction method, system and terminal to solve the technical problems of low measurement accuracy, poor reliability and deviation from the key dimensions of the contour output by the electron scanning microscope when extracting two-dimensional contours of wafers to be measured from SEM images.

[0011] To achieve the above and other related objectives, a first aspect of this application provides a method for contour extraction from an SEM image. The method includes: acquiring a wafer to be measured, and determining the measurement position and direction of a pattern to be measured on the wafer according to the measurement requirements of the wafer; using an electron scanning microscope, focusing an electron beam on the measurement position of the wafer and scanning the wafer along the measurement direction to obtain an SEM image of the pattern to be measured; performing a contour extraction operation on the SEM image to obtain an initial contour line of the pattern to be measured; acquiring key dimension measurements of the pattern to be measured output by the electron scanning microscope, and correcting the initial contour line based on the key dimension measurements to obtain a target contour line of the pattern to be measured.

[0012] In some embodiments of the first aspect of this application, the method of performing contour extraction on the SEM image includes: laying out multiple sampling lines parallel to the measurement direction along the graphic to be measured in the SEM image, and acquiring multiple grayscale waveform curves along the direction of each sampling line; based on the SEM image, locating one or more contour regions of interest of the graphic to be measured, and acquiring the peak points and trough points of each grayscale waveform curve in each contour region of interest, so as to draw the outer contour line of the graphic to be measured according to each peak point, and draw the inner contour line of the graphic to be measured according to each trough point; and selecting the outer contour line or the inner contour line as the initial contour line of the graphic to be measured according to the properties of the graphic to be measured.

[0013] In some embodiments of the first aspect of this application, after obtaining each grayscale waveform curve, the method further includes: flattening each grayscale waveform curve.

[0014] In some embodiments of the first aspect of this application, the method of locating the regions of interest of each contour of the graphic to be measured includes: obtaining one or more contour reference lines of the graphic to be measured, and based on each contour reference line, extending a preset measurement dimension to both sides along the measurement direction to obtain one or more contour regions of interest of the graphic to be measured.

[0015] In some embodiments of the first aspect of this application, the method of selecting an outer contour line or an inner contour line as the initial contour line of the graphic to be measured, based on the nature of the graphic to be measured, includes: if the graphic to be measured is solid, selecting the outer contour line as the initial contour line of the graphic to be measured; if the graphic to be measured is hollow, selecting the inner contour line as the initial contour line of the graphic to be measured.

[0016] In some embodiments of the first aspect of this application, the method of correcting the initial contour line based on the key dimension machine measurement value includes: obtaining the key dimension image measurement value of the graphic to be measured based on the initial contour line, and calculating the difference between the key dimension image measurement value and the key dimension machine measurement value and the key dimension correction coefficient; obtaining the contour edge point measurement value of multiple sampling positions of the graphic to be measured based on the initial contour line, and calculating the contour edge point correction value of each sampling position based on the key dimension correction coefficient, so as to draw the target contour line of the graphic to be measured.

[0017] In some embodiments of the first aspect of this application, the formula for calculating the critical dimension correction coefficient is as follows: ;in, The key dimension correction coefficient of the graphic to be measured; The difference between the key dimension image measurement value and the key dimension machine measurement value; The key dimension image measurement values ​​of the graphic to be measured; The key dimensions of the graphic to be measured are the machine measurement values.

[0018] In some embodiments of the first aspect of this application, the formula for calculating the contour edge point correction value is as follows: ;in, The key dimension correction coefficient of the graphic to be measured; The first of the measured patterns Measurement values ​​of contour edge points at each sampling location; The first of the measured patterns Correction values ​​for contour edge points at each sampling location.

[0019] To achieve the above and other related objectives, a second aspect of this application provides a SEM image contour extraction system, comprising: a measurement parameter determination module, used to acquire a wafer to be measured, and determine the measurement position and measurement direction of the pattern to be measured in the wafer to be measured according to the measurement requirements of the wafer to be measured; a SEM image acquisition module, connected to the measurement parameter determination module, used to focus an electron beam on the measurement position of the wafer to be measured using an electron scanning microscope, and scan the wafer to be measured along the measurement direction to obtain an SEM image of the pattern to be measured; a contour extraction module, connected to the SEM image acquisition module, used to perform a contour extraction operation on the SEM image to obtain an initial contour line of the pattern to be measured; and a contour correction module, connected to the contour extraction module, used to acquire the key dimension measurement values ​​of the pattern to be measured output by the electron scanning microscope, and correct the initial contour line according to the key dimension measurement values ​​to obtain a target contour line of the pattern to be measured.

[0020] To achieve the above and other related objectives, a third aspect of this application provides a SEM image contour extraction terminal, the SEM image contour extraction terminal comprising: a memory and a processor; the memory for storing a computer program; and the processor for executing the computer program stored in the memory to enable the terminal to perform the SEM image contour extraction method described in the above embodiments.

[0021] As described above, this application has the following beneficial effects: This application provides a SEM image contour extraction method, system, and terminal. By extracting the outer contour line and inner contour line of the pattern to be measured in the wafer under test from the SEM image, and selecting the outer contour line or inner contour line as the initial contour line of the pattern to be measured according to the different properties of the pattern to be measured, the initial contour line is corrected according to the key dimension measurement value output by the scanning electron microscope, thereby obtaining the target contour line of the pattern to be measured. This improves the accuracy and reliability of the target contour line, preserves the contour morphology features of the pattern to be measured, and helps to verify and calibrate the OPC model. It solves the technical problems of low measurement accuracy, poor reliability, and deviation from the key dimension of the contour output by the scanning electron microscope in the existing extraction of two-dimensional contours of wafer patterns to be measured from SEM images. Attached Figure Description

[0022] Figure 1 The diagram shown is a flowchart illustrating a SEM image contour extraction method in one embodiment of this application.

[0023] Figure 2 The image shown is a schematic diagram of an SEM image according to an embodiment of this application.

[0024] Figure 3 The diagram shown is a flowchart illustrating the contour extraction operation in one embodiment of this application.

[0025] Figure 4 The diagram shown is a schematic representation of a grayscale waveform curve in one embodiment of this application.

[0026] Figure 5 The diagram shown is a schematic representation of the region of interest in the outline of one embodiment of this application.

[0027] Figure 6 The diagram shown is a schematic representation of the inner and outer contours in one embodiment of this application.

[0028] Figure 7 The diagram shown is a flowchart illustrating the initial contour line correction process in one embodiment of this application.

[0029] Figure 8 The diagram shown is a structural schematic of an SEM image contour extraction system according to an embodiment of this application.

[0030] Figure 9 The diagram shown is a structural schematic of a SEM image contour extraction terminal in one embodiment of this application. Detailed Implementation

[0031] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0032] To address the problems mentioned above in the background technology, this application provides a SEM image contour extraction method, system, and terminal. The aim is to extract the outer and inner contour lines of the pattern to be measured from the SEM image, and select either the outer or inner contour line as the initial contour line based on the different properties of the pattern. The initial contour line is then corrected based on the key dimension measurement values ​​output by the scanning electron microscope (SEM) instrument, resulting in a high-precision target contour line for the pattern to be measured. This solves the technical problems of low measurement accuracy, poor reliability, and deviation from the key dimensions of the contour output by the SEM instrument in existing methods for extracting two-dimensional contours of wafer patterns from SEM images.

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application are further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application.

[0034] like Figure 1 The diagram illustrates a flowchart of a SEM image contour extraction method according to an embodiment of this application. The SEM image contour extraction method in this embodiment mainly includes the following steps.

[0035] Step S1: Obtain the wafer to be tested, and determine the measurement position and measurement direction of the pattern to be measured in the wafer to be tested according to the measurement requirements of the wafer to be tested.

[0036] Specifically, the measurement requirements include at least the design dimensions, measurement range, measurement position, measurement direction, and sampling density of the pattern to be measured in the wafer to be measured.

[0037] Step S2: Using an electron scanning microscope, focus the electron beam on the measurement position of the wafer to be measured, and scan the wafer to be measured along the measurement direction to obtain an SEM image of the pattern to be measured.

[0038] It should be understood that a scanning electron microscope (SEM) is a high-resolution imaging and analysis instrument that uses a focused, high-energy electron beam to scan the surface of a sample. By detecting various signals generated by the interaction between the electron beam and the sample, it obtains information on the microscopic morphology, composition, and structure of the sample surface. The SEM image obtained using a scanning electron microscope is a high-resolution grayscale image. The grayscale value of each pixel corresponds to the signal intensity excited by the electron beam at that point.

[0039] For example, a scanning electron microscope is used to scan a linear pattern to be measured, and the corresponding SEM image is obtained, such as... Figure 2 As shown, the initial contour line of the graphic to be measured is extracted based on the SEM image.

[0040] Step S3: Perform contour extraction on the SEM image to obtain the initial contour line of the graphic to be measured.

[0041] In one embodiment, before performing contour extraction on the SEM, a filtering algorithm can be used to perform denoising and enhancement operations on the SEM image to remove noise interference from the SEM image, preserve the true structural details of the SEM image, especially edge details, thereby improving the image quality of the SEM image and ensuring the accuracy of subsequent contour extraction.

[0042] Specifically, median filtering, Gaussian filtering, or frequency domain filtering algorithms can be used to perform denoising and enhancement operations on the SEM image. It should be noted that users can choose the filtering algorithm according to their needs; this application does not specifically limit it.

[0043] In one embodiment, such as Figure 3 As shown, step S3 includes the following steps.

[0044] Step S31: In the SEM image, lay out multiple sampling lines parallel to the measurement direction along the graphic to be measured, and obtain multiple grayscale waveform curves along the direction of each sampling line.

[0045] Specifically, each sampling line is parallel to the measurement direction and is laid out at equal intervals.

[0046] The measurement direction is determined by the measurement requirements of the graphic to be measured. Preferably, the measurement direction may be perpendicular to the length direction of the graphic to be measured, or form a preset angle with the length equation of the graphic to be measured; however, this application does not limit the specific direction.

[0047] Simultaneously, based on the measurement requirements of the graphic to be measured, the sampling density of the graphic to be measured at the measurement location can be determined, thereby determining the number of each sampling line and performing multi-point sampling on the graphic to be measured.

[0048] Based on multiple sampling lines, the grayscale waveform curves of the image to be measured at each sampling position are obtained. Specifically, on the SEM image, along the sampling lines, the grayscale values ​​of each pixel on the sampling lines are extracted and a two-dimensional relationship diagram is drawn to obtain the grayscale waveform curves of the image to be measured at the corresponding sampling positions, such as... Figure 4 As shown in the figure. The horizontal axis of the grayscale waveform represents the pixel coordinates of each pixel on the sampling line, and the vertical axis represents the grayscale value of each pixel.

[0049] In one embodiment, after acquiring each grayscale waveform curve, the process further includes flattening each grayscale waveform curve. Specifically, Savitzky-Golay filtering, moving average filtering, Gaussian filtering, or wavelet denoising algorithms can be used to flatten each grayscale waveform curve to suppress noise, improve the signal-to-noise ratio, and preserve as much of the true peak characteristics of the measured image as possible in each grayscale waveform curve. It should be noted that users can choose a specific flattening algorithm according to their needs, and this application is not specifically limited to it.

[0050] Step S32: Based on the SEM image, locate one or more regions of interest (ROIs) of the shape to be measured, and obtain the peaks and troughs of each grayscale waveform curve within each ROI, so as to draw the outer contour of the shape to be measured based on each peak and the inner contour of the shape to be measured based on each trough.

[0051] In one embodiment, the method for locating the regions of interest (ROIs) of each contour of the graphic to be measured includes: obtaining one or more contour baselines of the graphic to be measured, and based on each contour baseline, extending a preset measurement dimension to both sides along the measurement direction to obtain one or more ROIs of the graphic to be measured.

[0052] The method for obtaining the contour baselines of the graphic to be measured includes: using a threshold segmentation algorithm to identify multiple contour edge points of the graphic to be measured, and generating the contour baselines of the graphic to be measured.

[0053] It should be understood that threshold segmentation is an edge detection algorithm that divides an image into multiple regions with similar properties by setting one or more grayscale thresholds. This application uses a threshold segmentation algorithm to initially identify the edge points of each contour and construct the baselines for each contour. However, this application is not specifically limited; users can choose other edge detection algorithms to obtain the baselines for each contour of the image to be measured, according to their needs.

[0054] The method of obtaining the contour baselines of the graphic to be measured further includes: obtaining the design graphic of the graphic to be measured, aligning it with the SEM image, and using one or more contour lines of the design graphic as the contour baselines of the graphic to be measured.

[0055] Based on each contour baseline, a preset measurement dimension is extended to both sides along the measurement direction to obtain the corresponding contour region of interest. In a preferred embodiment, the measurement dimension can be designed to be 1 / 2 of the width design dimension of the graphic to be measured. In this case, the width of each contour region of interest is the width design dimension of the graphic to be measured, and the length of each contour region of interest is the length design dimension of the graphic to be measured.

[0056] For example, such as Figure 5 As shown, in the SEM image of the linear graphic to be measured, a threshold segmentation algorithm is used to identify multiple contour edge points of the graphic to be measured, and connect each contour edge point to form two contour baselines on the left and right. Based on the two contour baselines, extend 1 / 2 width design size to the left and right sides along the measurement direction to obtain the two contour regions of interest of the graphic to be measured, so as to further accurately extract the initial contour line of the graphic to be measured.

[0057] In this embodiment, after obtaining the regions of interest for each contour of the graphic to be measured, the grayscale waveform curves at each sampling position are truncated, such as... Figure 4 As shown, one or more peak points and trough points are obtained. The peak points at each sampling location are connected, fitted, and smoothed to obtain the outer contour line of the graphic to be measured; and the trough points at each sampling location are connected, fitted, and smoothed to obtain the inner contour line of the graphic to be measured, as shown. Figure 6 As shown.

[0058] The purpose of this design in this embodiment is to obtain high-quality outer and inner contour lines from the SEM image, effectively avoid contour disturbances caused by problems such as blurred edges and uneven contrast in the SEM image, greatly improve the accuracy of contour extraction, and obtain initial and target contour lines with better contrast and edge smoothness.

[0059] Step S33: Based on the properties of the graphic to be measured, select the outer contour line or the inner contour line as the initial contour line of the graphic to be measured.

[0060] In one embodiment, if the graphic to be measured is solid, the outer contour line is selected as the initial contour line of the graphic to be measured; if the graphic to be measured is hollow, the inner contour line is selected as the initial contour line of the graphic to be measured. For example, ... Figure 2 as well as Figure 5 As shown, for a linear graphic to be measured, the graphic is solid. In this case, its outer contour is closer to the real contour. Therefore, the outer contour is selected as the initial contour of the graphic to be measured, and correction is performed based on the initial contour to obtain a more accurate target contour of the graphic to be measured.

[0061] This application selects different contour lines as initial contour lines for correction based on the properties of the graphic to be measured, thereby achieving the use of different correction benchmarks according to different properties of the design graphics, ensuring the accuracy and reliability of the final target contour line.

[0062] Step S4: Obtain the key dimension measurement values ​​of the graphic to be measured output by the scanning electron microscope, and correct the initial contour line according to the key dimension measurement values ​​to obtain the target contour line of the graphic to be measured.

[0063] It should be understood that the OPC (Optical Proximity Correction) model is used to simulate and predict the pattern of each design pattern on the wafer after photolithography based on the actual wafer layout. Then, by comparing the predicted pattern with the design pattern, it automatically calculates how the mask pattern needs to be pre-adjusted, such as moving edges or adding auxiliary features, to make the actual image after photolithography as close as possible to the design pattern, thereby ensuring chip quality and performance. Therefore, in order to establish an accurate digital twin and ensure that the OPC model can truly reflect the real-world photolithography process, it is necessary to accurately match the initial contour line of the pattern to be measured extracted from the SEM image with the measurement values ​​output by the scanning electron microscope. This ensures that the obtained target contour line is closer to reality, thereby ensuring the accuracy of the input data to the OPC model and improving the verification and calibration accuracy of the OPC model.

[0064] It should be noted that the OPC model is constructed by the user using OPC software according to their needs, and for the sake of brevity, this application will not elaborate further.

[0065] In a preferred embodiment, the critical dimension measurement value is obtained by directly measuring the width of the critical position of the pattern to be measured at the wafer sample using the onboard software of the scanning electron microscope. Figure 2 The line-shaped graphic to be measured shown is defined as the line width of the graphic, where the key dimension is the machine measurement value.

[0066] In one embodiment, such as Figure 7 As shown, the method for correcting the initial contour line based on the machine tool measurement values ​​of the key dimensions includes the following steps.

[0067] Step S41: Based on the initial contour line, obtain the key dimension image measurement value of the graphic to be measured, and calculate the difference between the key dimension image measurement value and the key dimension machine measurement value, as well as the key dimension correction coefficient.

[0068] Wherein, the key dimension image measurement value is the image measurement value at the same key location as the key dimension machine measurement value. In one embodiment, the pixel distance between two sampling positions located at the key location can be obtained based on the initial contour line, and the pixel distance can be converted into an actual distance to serve as the key dimension image measurement value.

[0069] In one embodiment, the formula for calculating the difference between the critical dimension image measurement value and the critical dimension machine measurement value is as follows:

[0070] ;Formula (1)

[0071] The formula for calculating the critical dimension correction coefficient is as follows:

[0072] ;Formula (2)

[0073] in, The key dimension correction coefficient of the graphic to be measured; The difference between the key dimension image measurement value and the key dimension machine measurement value; The key dimension image measurement values ​​of the graphic to be measured; The key dimensions of the graphic to be measured are the machine measurement values.

[0074] Step S42: Based on the initial contour line, obtain the contour edge point measurement values ​​of multiple sampling positions of the graphic to be measured, and calculate the contour edge point correction value of each sampling position according to the key dimension correction coefficient, so as to draw the target contour line of the image to be measured.

[0075] Specifically, the formula for calculating the contour edge point correction value is as follows:

[0076] ;Formula (3)

[0077] in, The key dimension correction coefficient of the graphic to be measured; The first of the measured patterns Measurement values ​​of contour edge points at each sampling location; The first of the measured patterns Correction values ​​for contour edge points at each sampling location.

[0078] Based on the correction values ​​of each contour edge point, multiple corresponding corrected contour edge points are obtained, and each corrected contour edge point is connected, fitted, and smoothed to obtain the target contour line of the image to be measured.

[0079] This application improves the accuracy of the target contour by correcting the initial contour obtained based on the SEM image, preserving the contour morphology features of the graphic to be measured. More importantly, it makes the target contour match the key dimensions of the contour output by the scanning electron microscope, providing a basis for verifying and calibrating the OPC model.

[0080] like Figure 8 The diagram illustrates the structure of a SEM image contour extraction system according to an embodiment of this application. The SEM image contour extraction system 800 in this embodiment mainly includes: a measurement parameter determination module 801, an SEM image acquisition module 802, a contour extraction module 803, and a contour correction module 804, connected in sequence.

[0081] The measurement parameter determination module 801 is used to acquire the wafer to be measured and determine the measurement position and measurement direction of the pattern to be measured in the wafer to be measured according to the measurement requirements of the wafer to be measured.

[0082] The SEM image acquisition module 802 is used to focus an electron beam on the measurement position of the wafer under test using an electron scanning microscope, and scan the wafer under test along the measurement direction to obtain an SEM image of the pattern to be measured.

[0083] The contour extraction module 803 is used to perform contour extraction operation on the SEM image to obtain the initial contour line of the graphic to be measured.

[0084] The contour correction module 804 is used to acquire the key dimension measurement values ​​of the graphic to be measured output by the scanning electron microscope, and correct the initial contour line according to the key dimension measurement values ​​to obtain the target contour line of the graphic to be measured.

[0085] It should be understood that the specific process of each module performing the corresponding steps has been described in detail in the aforementioned method embodiments, and will not be repeated here for the sake of brevity.

[0086] It should also be understood that the division of modules or units in the embodiments of this application is illustrative and only represents a logical functional division. In actual implementation, there may be other division methods. Furthermore, the functional modules / units in the various embodiments of this application can be integrated into a single processor, exist as separate physical entities, or have two or more modules / units integrated into a single module or unit. The integrated modules or units described above can be implemented in hardware or as software functional modules.

[0087] Figure 9 This is a schematic diagram of the structure of the SEM image contour extraction terminal 900 provided in this embodiment of the application. Figure 9 As shown, the SEM image contour extraction terminal 900 includes: at least one processor 901, a memory 902, at least one network interface 903, and a user interface 905. The various components in the terminal are coupled together via a bus system 904. It is understood that the bus system 904 is used to implement communication between these components. In addition to a data bus, the bus system 904 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 9 The general will label all buses as bus systems.

[0088] The user interface 905 may include a monitor, keyboard, mouse, trackball, clicker, button, touchpad, or touch screen.

[0089] It is understood that memory 902 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM) or programmable read-only memory (PROM), used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable categories of memory.

[0090] In this embodiment, the memory 902 is used to store various types of data to support the operation of the SEM image contour extraction terminal 900. Examples of this data include: any executable program that operates on the SEM image contour extraction terminal 900, such as the operating system 9021 and application program 9022; the operating system 9021 contains various system programs, such as the framework layer, core library layer, driver layer, etc., for implementing various basic services and handling hardware-based tasks. The application program 9022 may contain various applications, such as media players, browsers, etc., for implementing various application services. The implementation of the SEM image contour extraction method provided in this embodiment can be included in the application program 9022.

[0091] The SEM image contour extraction method disclosed in the above embodiments of this application can be applied to, or implemented by, processor 901. Processor 901 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the SEM image contour extraction method can be completed by the integrated logic circuits in the hardware of processor 901 or by instructions in software form. The processor 901 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 901 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor 901 may be a microprocessor or any conventional processor. The steps of the SEM image contour extraction method provided in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory. The processor reads information from the memory and, in conjunction with its hardware, completes the steps of the aforementioned method.

[0092] In an exemplary embodiment, the SEM image contour extraction terminal 900 may be used by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), or complex programmable logic devices (CPLDs) to perform the aforementioned method.

[0093] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented using computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0094] In the embodiments provided in this application, the computer-readable and writable storage medium may include read-only memory, random access memory, EEPROM, CD-ROM or other optical disc storage devices, disk storage devices or other magnetic storage devices, flash memory, USB flash drive, portable hard drive, or any other medium capable of storing desired program code in the form of instructions or data structures and accessible by a computer. Additionally, any connection may be appropriately referred to as a computer-readable medium. For example, if instructions are transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. However, it should be understood that computer-readable and writable storage media and data storage media do not include connections, carrier waves, signals, or other transient media, but are intended for non-transient, tangible storage media. The disks and optical discs used in the application include compact optical discs (CDs), laser optical discs, optical discs, digital multifunction optical discs (DVDs), floppy disks, and Blu-ray discs, where disks typically copy data magnetically, while optical discs use lasers to copy data optically.

[0095] In summary, this application provides a method, system, and terminal for contour extraction from SEM images. It extracts the outer and inner contour lines of the pattern to be measured from the SEM image, and selects either the outer or inner contour line as the initial contour line based on the different properties of the pattern. The initial contour line is then corrected using the key dimension measurements output by the scanning electron microscope (SEM) to obtain the target contour line of the pattern. This improves the accuracy and reliability of the target contour line, preserves the contour morphology features of the pattern, and facilitates the verification and calibration of the OPC model. It solves the technical problems of low measurement accuracy, poor reliability, and deviation from the key dimensions of the contour output by the SEM image in existing methods for extracting two-dimensional contours of wafer patterns from SEM images. Therefore, this application effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0096] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method of SEM image contour extraction, characterized by, include: Obtain the wafer to be tested, and determine the measurement position and measurement direction of the pattern to be measured in the wafer to be tested according to the measurement requirements of the wafer to be tested; An electron scanning microscope is used to focus an electron beam on the measurement position of the wafer under test and scan the wafer under test along the measurement direction to obtain an SEM image of the pattern to be measured. Perform contour extraction on the SEM image to obtain the initial contour line of the graphic to be measured; The key dimensions of the graphic to be measured are obtained from the scanning electron microscope, and the initial contour line is corrected based on the key dimensions to obtain the target contour line of the graphic to be measured.

2. The SEM image contour extraction method according to claim 1, characterized by, The methods for performing contour extraction on the SEM image include: In the SEM image, multiple sampling lines parallel to the measurement direction are laid out along the graphic to be measured, and multiple grayscale waveform curves along each sampling line direction are obtained. Based on the SEM image, locate one or more contour regions of interest of the graphic to be measured, and obtain the peak points and trough points of each grayscale waveform curve in each contour region of interest, so as to draw the outer contour line of the graphic to be measured according to each peak point and draw the inner contour line of the graphic to be measured according to each trough point. Based on the properties of the graphic to be measured, the outer contour line or the inner contour line is selected as the initial contour line of the graphic to be measured.

3. The SEM image contour extraction method according to claim 2, characterized by, After obtaining the grayscale waveform curves, the following is also included: Each grayscale waveform curve is flattened.

4. The SEM image contour extraction method according to claim 2, wherein The methods for locating the regions of interest (ROIs) of each contour of the graphic to be measured include: Obtain one or more contour baselines of the graphic to be measured, and based on each contour baseline, extend a preset measurement dimension to both sides along the measurement direction to obtain one or more contour regions of interest of the graphic to be measured.

5. The SEM image contour extraction method of claim 2, wherein, Depending on the properties of the graphic to be measured, the methods for selecting the outer contour line or the inner contour line as the initial contour line of the graphic to be measured include: If the graphic to be measured is solid, the outer contour line is selected as the initial contour line of the graphic to be measured. If the graphic to be measured is hollow, the inner contour line is selected as the initial contour line of the graphic to be measured.

6. The SEM image contour extraction method of claim 1, wherein, The methods for correcting the initial contour line based on the machine tool measurements of the key dimensions include: Based on the initial contour line, obtain the key dimension image measurement values ​​of the graphic to be measured, and calculate the difference between the key dimension image measurement values ​​and the key dimension machine measurement values, as well as the key dimension correction coefficient. Based on the initial contour line, the contour edge point measurement values ​​of multiple sampling positions of the graphic to be measured are obtained, and the contour edge point correction value of each sampling position is calculated according to the key dimension correction coefficient, so as to draw the target contour line of the image to be measured.

7. The SEM image contour extraction method according to claim 6, wherein The formula for calculating the critical dimension correction coefficient is as follows: ； in, The key dimension correction coefficient of the graphic to be measured; The difference between the key dimension image measurement value and the key dimension machine measurement value; The key dimension image measurement values ​​of the graphic to be measured; The key dimensions of the graphic to be measured are the machine measurement values.

8. The SEM image contour extraction method according to claim 6, characterized in that, The formula for calculating the correction value of the contour edge points is: ； in, The key dimension correction coefficient of the graphic to be measured; The first of the measured patterns Measurement values ​​of contour edge points at each sampling location; The first of the measured patterns Correction values ​​for contour edge points at each sampling location.

9. A SEM image contour extraction system, characterized in that, include: The measurement parameter determination module is used to acquire the wafer to be measured and determine the measurement position and measurement direction of the pattern to be measured in the wafer to be measured according to the measurement requirements of the wafer to be measured. The SEM image acquisition module, connected to the measurement parameter determination module, is used to focus an electron beam on the measurement position of the wafer under test using an electron scanning microscope and scan the wafer under test along the measurement direction to obtain an SEM image of the pattern to be measured. The contour extraction module is connected to the SEM image acquisition module and is used to perform contour extraction operations on the SEM image to obtain the initial contour line of the graphic to be measured. The contour correction module, connected to the contour extraction module, is used to acquire the key dimensions of the graphic to be measured output by the scanning electron microscope, and correct the initial contour line according to the key dimensions to obtain the target contour line of the graphic to be measured.

10. A SEM image contour extraction terminal, characterized in that, include: Memory and processor; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory to cause the terminal to perform the SEM image contour extraction method as described in any one of claims 1 to 8.

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