SEM image correction method and device, equipment, medium and product
By straightening the contours of the SEM image and straightening the linear fit, the original SEM image is directly rotated and corrected, solving the problems of standard sample dependence and repeated scanning, and significantly improving the correction accuracy and accuracy.
Patent Information
- Application Number
- CN202411187369.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-27
- Publication Date
- 2024-12-13
AI Technical Summary
The existing SEM image correction methods rely on standard samples and are easily affected by changes in surface state caused by repeated scanning, resulting in low correction accuracy. The limitations of standard samples production process and material differences limit the accuracy and application range of correction effects.
By straightening the outline of the original SEM image, filtering the corrected edges with length greater than the preset length, performing straight line fitting, calculating the angle between the fitted straight line and the corrected edge, and directly rotating and correcting the original SEM image to obtain High-quality target images.
It has got rid of the dependence on high-precision standard samples, eliminated the problem of accuracy degradation caused by repeated scanning, significantly improved the correction accuracy of SEM images, and achieved higher clarity and accuracy.
Smart Images
Figure CN119130869A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of measurement technology, and in particular to a SEM image correction method, device, equipment, medium and product. Background Art
[0002] In the field of chip manufacturing, Scanning Electron Microscope (SEM) images are an important means of high-precision detection, and their imaging quality directly affects the evaluation of product quality. The current correction method of SEM images generally relies on standard samples. This method estimates and corrects the distortion and rotation angle of the SEM image by comparing the subtle differences between the standard sample and the SEM image. However, the existing correction method that relies on standard samples has multiple limitations. For example, the standard sample is easily affected by the changes in the surface state caused by repeated scanning, which leads to low accuracy of SEM image correction. Summary of the invention
[0003] The present application provides a SEM image correction method, device, equipment, medium and product, which can improve the correction accuracy of SEM images.
[0004] In a first aspect, an embodiment of the present application provides a SEM image correction method, the method comprising:
[0005] Straightening the image contour of the original SEM image to obtain a polygon corresponding to the image contour, wherein the straightening is used to extend each edge in the image contour along the axial direction of a preset coordinate axis, wherein the preset coordinate axis is determined according to each edge in the image contour;
[0006] Selecting edges whose length is greater than a preset length from multiple edges of the polygon to obtain at least one corrected edge;
[0007] For each corrected edge, respectively: obtaining the image contour position point corresponding to the corrected edge on the image contour; performing straight line fitting on the image contour position point to obtain a fitted straight line; and calculating the angle between the fitted straight line and the corrected edge;
[0008] The original SEM image is rotationally corrected according to an angle corresponding to at least one corrected edge to obtain a target SEM image.
[0009] In a second aspect, the present application provides a SEM image correction device, the device comprising:
[0010] A first processing module, configured to perform a straightening process on the image contour of the original SEM image to obtain a polygon corresponding to the image contour, wherein the straightening process is configured to extend each edge in the image contour along an axial direction of a preset coordinate axis, wherein the preset coordinate axis is determined according to each edge in the image contour;
[0011] A screening module, used for screening the edges whose length is greater than a preset length from the multiple edges of the polygon to obtain at least one corrected edge;
[0012] The second processing module is used to respectively perform, for each corrected edge, the following steps: obtaining an image contour position point on the image contour corresponding to the corrected edge; performing straight line fitting on the image contour position point to obtain a fitted straight line; and calculating an angle between the fitted straight line and the corrected edge.
[0013] The correction module is used to perform rotation correction on the original SEM image according to the angle corresponding to the at least one correction edge to obtain a target SEM image.
[0014] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising: a processor and a memory storing computer program instructions;
[0015] When the processor executes the computer program instructions, it implements the SEM image correction method in any one of the embodiments of the first aspect.
[0016] In a fourth aspect, an embodiment of the present application provides a computer storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, a SEM image correction method as in any one of the embodiments in the first aspect is implemented.
[0017] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the SEM image correction method in any one of the embodiments in the first aspect above.
[0018] In a SEM image correction method, device, equipment, medium and product provided in an embodiment of the present application, the contour of the original SEM image is directly flattened to obtain a polygonal representation of the image contour. Subsequently, a correction edge whose length is greater than a preset length is selected from multiple edges in the polygon, and a fitting straight line is obtained by performing a straight line fitting on the image contour position points corresponding to the correction edge, and then the angle between the fitting straight line and the correction edge is calculated. This angle directly reflects the rotational deviation of the original SEM image, so that the original SEM image can be directly and accurately rotationally corrected according to the angle, thereby obtaining a high-quality target SEM image. This method not only gets rid of the dependence on high-precision standard samples, but also fundamentally eliminates the problem of decreased accuracy caused by repeated scanning of standard samples, and significantly improves the correction accuracy of the SEM image. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0020] Figure 1 It is a schematic flow chart of a SEM image correction method provided by an embodiment of the present application;
[0021] Figure 2 This is one of the principle schematic diagrams of the SEM image correction method provided in the embodiments of the present application;
[0022] Figure 3 This is the second principle schematic diagram of the SEM image correction method provided in the embodiment of the present application;
[0023] Figure 4 This is the third principle schematic diagram of the SEM image correction method provided in the embodiment of the present application;
[0024] Figure 5 This is the fourth principle schematic diagram of the SEM image correction method provided in the embodiment of the present application;
[0025] Figure 6 This is the fifth principle schematic diagram of the SEM image correction method provided in the embodiment of the present application;
[0026] Figure 7 This is the sixth principle schematic diagram of the SEM image correction method provided in the embodiment of the present application;
[0027] Figure 8 This is the seventh principle schematic diagram of the SEM image correction method provided in the embodiment of the present application;
[0028] Fig. 9is a structural schematic diagram of a SEM image correction device provided in an embodiment of the present application;
[0029] Fig.10 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0030] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.
[0031] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.
[0032] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising" or any other variant thereof is 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 other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0033] Electron beam scanning measurement and detection equipment forms images by collecting secondary electrons. Since the electron gun and scanning circuit board are easily affected by mechanical vibration, electromagnetic field changes, manufacturing accuracy and other factors, the obtained scanning electron microscope (SEM) image will generally be distorted. Image distortion includes a variety of image distortions, one of which is that the SEM image will produce a small amount of rotation as a whole. In some cases, this small rotation will also affect the electron beam scanning measurement and detection results. Therefore, it is necessary to correct the rotation angle of the obtained SEM image. Especially when it is necessary to extract high-precision measurement information from the SEM image, accurate, reliable, timely and fast image rotation correction is necessary.
[0034] In the analysis and evaluation of scanning electron microscope (SEM) images, the correction of rotation angle is a crucial link, which directly affects the image quality and the subsequent product quality judgment. Traditional SEM image rotation angle correction technology mainly relies on the use of standard samples, which usually contain uniform periodic patterns with known parameters for comparison and analysis with the patterns in the SEM image.
[0035] In the specific implementation process, the SEM image of the standard sample needs to be taken first, and the distortion and rotation angle of the SEM image are calculated by comparing the size and direction of the graphics in the image with the design value of the standard sample. This calculation result provides a correction benchmark for the subsequent SEM image of the sample to be tested, aiming to reduce the distortion and adjust the rotation angle to ensure the accuracy and reliability of the image.
[0036] However, the existing correction methods have several significant limitations. First, the reuse of standard samples is an issue that cannot be ignored. Since multiple scans of the electron beam will change the physical state of the surface of the standard sample, thus affecting the imaging effect, this directly reduces the accuracy and stability of the correction. In order to mitigate this effect, although the standard sample is designed with a simple repetitive grating pattern and special marks are added to the edge for easy positioning, it is still difficult to completely avoid repeated scanning in actual operation.
[0037] Secondly, the state and accuracy of the standard sample itself are also key factors that limit the correction effect. The limitations of the manufacturing process mean that the standard sample may have slight differences from the theoretical design value, and this difference will be magnified during the correction process, affecting the accuracy of the final result. In addition, the differences in material and surface conditions between the standard sample and the actual test sample also lead to the correction parameters obtained on the standard sample not being fully applicable to the actual sample, thus limiting the effectiveness and scope of application of the correction method.
[0038] In order to solve the problems existing in the prior art, the embodiments of the present application provide a SEM image correction method, device, equipment, medium and product.
[0039] The present application embodiment provides a SEM image correction method, device, equipment, medium and product. The following first introduces the SEM image correction method provided by the present application embodiment. Figure 1 As shown, the method specifically comprises the following steps:
[0040] S100, straightening the image contour of the original SEM image to obtain a polygon corresponding to the image contour, wherein the straightening is used to extend each edge in the image contour along the axial direction of a preset coordinate axis, and the preset coordinate axis is determined according to each edge in the image contour.
[0041] Optionally, the original SEM image refers to an image directly obtained by SEM without any post-processing. The image contour of the original SEM image refers to a line or curve extracted from the original SEM image that represents the boundary of the sample surface morphology.
[0042] Optionally, in a feasible implementation of the present application, first, the original SEM image can be preprocessed using image processing software or algorithms, including but not limited to denoising, contrast enhancement, etc., to improve image quality and facilitate subsequent image contour extraction. Subsequently, an edge detection algorithm can be used to identify edge information in the original SEM image, which corresponds to the boundary of the object contour. After obtaining the edge pixel points, the contour tracking algorithm is used to connect these discrete edge pixel points into a continuous contour line to obtain the image contour of the original SEM image.
[0043] However, the image contour of the original SEM image directly extracted often contains many subtle twists and irregularities. Therefore, in S100, the image contour of the original SEM image needs to be further straightened. The core idea of the straightening process is to smooth or remove the small twists and irregularities in the contour line of the image contour that do not affect the overall shape, so that the contour line is closer to the ideal polygonal shape. This can be achieved through certain mathematical methods, such as using the least squares method to perform segmented fitting on the points on the contour line of the image contour, and then taking the midpoint or average position of each segment of the fitting straight line as the new contour point, thereby obtaining a smoother contour line.
[0044] In addition, the straightening process can also consider introducing a certain threshold control, that is, when the length or curvature of a certain tortuous or irregular part on the contour line of the image contour is less than the preset threshold, it is considered that the impact of this part on the overall shape can be ignored, so it is removed or smoothed. Through such processing, the image contour of the original SEM image is converted into a polygon composed of multiple relatively straight edges, which provides a good foundation for the correction edge screening and straight line fitting in the subsequent steps.
[0045] Optionally, in the embodiment of the present application, the straightening process specifically refers to geometrically transforming the irregular edges in the image contour so that they are as close to the horizontal or vertical direction as possible, that is, extending axially along a preset ideal coordinate axis (such as the X axis or the Y axis) to achieve a "horizontally flat and vertically straight" effect. The determination of the preset coordinate axis depends on the direction of the main edges in the image contour, and the direction of these main edges can be set by statistical analysis or identification of key feature points of the image contour to ensure that the polygons obtained by the straightening process can serve as a reliable reference for subsequent rotation correction.
[0046] S200, selecting edges whose length is greater than a preset length from multiple edges of the polygon to obtain at least one corrected edge.
[0047] Optionally, the correction edge refers to an edge selected from the polygonal contour after the straightening process and having a length greater than a preset length. These edges are considered to be representative line segments in the image contour, long enough and suitable for subsequent correction calculations.
[0048] Optionally, in a feasible implementation of the present application, first, each edge of the polygon corresponding to the image contour obtained in step S100 is traversed, and the length of each edge is measured and recorded. This process can be completed by calculating the Euclidean distance between adjacent vertices of the polygon. Then, the measured length of each edge is compared with a preset length threshold. The preset length threshold is set in advance according to the actual application scenario and image characteristics, and is used to screen out edges that are long enough, representative, and suitable for subsequent correction calculations.
[0049] During the comparison process, if the length of a certain edge in the polygon is greater than the preset length threshold, the edge is considered to be a valid correction edge and is retained; conversely, if the length of a certain edge is less than or equal to the preset length threshold, the edge is considered to be too short and may be greatly affected by factors such as noise and error, and is not suitable for subsequent correction calculations, so it is excluded. Through this screening process, at least one (or more, if there are multiple edges that meet the conditions) correction edge with a length greater than the preset length is finally obtained for the subsequent straight line fitting and angle calculation steps.
[0050] Optionally, the present application determines the longer straight line pattern edge as the correction edge, which is determined by the strict mask manufacturing and photolithography manufacturing processes in chip production. The mask manufacturing process and photolithography process in chip production can achieve a manufacturing accuracy of tens of nanometers, and patterns with a length of hundreds of nanometers exist in large quantities in the actual chip layout. Therefore, the longer straight lines designed are also easy to be accurately processed into straight lines in the same direction during the chip production process, so they are also easy to be used as the basis for image correction.
[0051] Optionally, in other embodiments of the present application, the simple polygons in the design layout file of the sample corresponding to the original SEM image can be directly used to select the correction edge. This is logically similar to the method of obtaining the simple polygon by straightening the image contour of the original SEM image and selecting the correction edge in the present application, except that the data source is different.
[0052] S300, for each corrected edge, respectively executing: obtaining an image contour position point on the image contour corresponding to the corrected edge; performing straight line fitting on the image contour position point to obtain a fitted straight line; and calculating an angle between the fitted straight line and the corrected edge.
[0053] Optionally, the image contour position points refer to pixel points constituting the image contour boundary. These image contour position points define the boundary of the object in the original SEM image.
[0054] Optionally, in a feasible implementation of the present application, for each selected correction edge, it is first necessary to determine the image contour position point on the image contour corresponding to the correction edge. Then, these image contour position points are processed using a straight line fitting algorithm (such as least squares method, Hough transform, etc.) to find a straight line that best represents the distribution trend of these image contour position points, that is, a fitting straight line. The selection of the fitting straight line should ensure that it can reflect the actual direction of the correction edge in the contour image as accurately as possible.
[0055] After getting the fitted line, the next step is to calculate the angle between the fitted line and the original corrected edge. You can do this by calculating the angle between the normals of the two lines. The normal is a line segment perpendicular to the line. By calculating the angle between the normals of the two lines, you can accurately get the angle difference between them.
[0056] S400, performing rotation correction on the original SEM image according to the angle corresponding to the at least one correction edge to obtain a target SEM image.
[0057] Optionally, after calculating the angle between the fitting line and the correction edge, the angle information will be used in the subsequent image correction step. This angle reflects the degree of inclination or distortion of the correction edge in the image and is an important basis for image correction. According to this angle, the original SEM image can be rotated, stretched or tilted to eliminate the distortion or distortion in the image, thereby obtaining a more accurate and clear target SEM image.
[0058] Specifically, for each correction edge, a correction matrix or transformation parameters can be calculated according to its corresponding angle. This correction matrix describes how to map the pixels in the original SEM image from one position to another to eliminate distortion caused by tilt, twist, etc. Then, this correction matrix is applied to the entire original SEM image, and each pixel in the original SEM image is transformed to obtain the corrected image coordinates. Finally, all the transformed pixels are recombined into a new image, namely the target SEM image.
[0059] Optionally, the target SEM image is a corrected image, which eliminates the tilt, distortion and other distortions that may exist in the original image, and more realistically reflects the morphological characteristics of the sample surface. Compared with the original SEM image, the target SEM image has higher clarity and accuracy, which is convenient for subsequent analysis, measurement and identification.
[0060] In the SEM image correction method provided in the embodiment of the present application, the contour of the original SEM image is directly straightened to obtain a polygonal representation of the image contour. Subsequently, the correction edge whose length is greater than the preset length is screened out from the multiple edges in the polygon, and a fitting straight line is obtained by performing a straight line fitting on the image contour position point corresponding to the correction edge, and then the angle between the fitting straight line and the correction edge is calculated. This angle directly reflects the rotational deviation of the original SEM image, so that the original SEM image can be directly and accurately corrected according to the angle, thereby obtaining a high-quality target SEM image. This method not only gets rid of the dependence on high-precision standard samples, but also fundamentally eliminates the problem of decreased accuracy caused by repeated scanning of standard samples, and significantly improves the correction accuracy of the SEM image.
[0061] In one embodiment, the step of obtaining the image contour position point on the image contour corresponding to the correction edge includes:
[0062] Acquire a target contour corresponding to the correction edge in the image contour;
[0063] Acquire a plurality of first contour position points of the target contour;
[0064] The step of performing straight line fitting on the image contour position points to obtain a fitting straight line includes:
[0065] Removing the first contour position point located at the end position of the target contour from the plurality of first contour position points to obtain a second contour position point;
[0066] A straight line fitting is performed on the second contour position points to obtain the fitting straight line.
[0067] Optionally, in a feasible implementation of the present application, first, the target contour directly associated with the correction edge is identified by image processing technology, specifically involving edge detection, contour tracking and other algorithms, to ensure that the target contour corresponding to the correction edge can be accurately extracted. Subsequently, all pixel points constituting the boundary of the target contour are sequentially obtained along the target contour, and these points are the first contour position points, which together define the shape and position of the target contour.
[0068] However, due to the noise, distortion or imperfection of the edge detection algorithm that may exist in the image acquisition process, the two ends of the target contour (i.e., the end positions) may contain some points that deviate from the ideal straight line shape. In order to improve the accuracy of straight line fitting, it is necessary to remove the first contour position points of these end positions. This step can be achieved by setting certain thresholds or conditions, such as identifying and eliminating these points based on parameters such as the distance from the point to the straight line (hypothetical or preliminary fitting), the curvature change, the distance between adjacent points, etc., and the remaining points are the second contour position points.
[0069] After obtaining the second contour position points, a straight line fitting algorithm (such as least squares method, Hough transform, etc.) is used to process these second contour position points to find a straight line that can best describe the distribution trend of these points, that is, the fitting line. The parameters of the fitting line (such as slope and intercept) will be used to subsequently calculate the angle between the correction edge and the fitting line, and the original SEM image will be corrected accordingly.
[0070] In these optional embodiments, by accurately extracting the target contour corresponding to the correction edge and removing the noise points at its ends, the accuracy of the straight line fitting is effectively improved, so that the deviation between the correction edge and the fitting straight line can be calculated more accurately, providing a reliable basis for subsequent image correction, ensuring the clarity and accuracy of the corrected SEM image, and further improving the correction accuracy of the SEM image.
[0071] In one embodiment, removing the first contour position point at the end position of the target contour from the plurality of first contour position points to obtain the second contour position point includes:
[0072] The target position point at the end position of the target contour among the multiple first contour position points is removed to obtain a second contour position point, wherein the target position point is a first contour position point among the multiple first contour position points whose deviation degree is greater than a preset deviation threshold, and the deviation degree is used to characterize the deviation degree of the contour position point from the preset straight line.
[0073] Optionally, the degree of deviation refers to the vertical distance from a certain contour position point to a preset straight line (i.e., a theoretical, expected, or assumed straight line). The larger the distance, the higher the degree to which the position point deviates from the preset straight line, i.e., the greater the degree of deviation.
[0074] Optionally, in a specific implementation of the present application, the preset straight line can be a theoretical straight line set according to factors such as image features, design data or lithography conditions, representing the expected position of the correction edge in the absence of errors. The determination of this preset straight line can indeed take into account the lithography conditions of the sample itself of the original SEM image, such as exposure time, focal length adjustment, etc., because these lithography conditions will directly affect the shape of the graphics in the image and the straightness of the edges. Therefore, by comprehensively considering the lithography conditions and image features of the sample, a preset straight line that is closer to reality can be set, so as to more accurately identify and remove the deviation points of the end position of the target contour, and improve the accuracy of the straight line fitting and the correction effect. Such processing helps to ensure that the corrected SEM image can more accurately reflect the true morphology of the sample.
[0075] Optionally, in a specific implementation of the present application, first, as Figure 2 As shown, the image outline is extracted from the original SEM image and output as a file in a design layout format such as gds for subsequent processing.
[0076] Then, if Figure 3 As shown, the extracted image contour is straightened and the complex image contour shape is simplified into a polygon so that the correction edge can be more easily identified and selected.
[0077] Then, if Figure 4 As shown in FIG. 1 , according to a preset length threshold, edges with suitable lengths are selected from the simplified polygons as correction edges. For example, Figure 4 As shown, three edges Edge1, Edge2 and Edge3 are selected as correction edges.
[0078] Then, if Figure 5 As shown, for each corrected edge, the position information of all points on the target contour corresponding to the corrected edge (ie, the first contour position points) is obtained.
[0079] However, due to the noise or irregularity that may exist at both ends of the correction edge, directly fitting the first contour position points with a straight line may not be accurate. Figure 6 As shown, the graphic contour points (ie, target position points) corresponding to the head and tail parts of the image contour corresponding to the correction edge that deviate from the straight line are removed, and only the contour point position information corresponding to the straight part (ie, the second contour position point) is retained.
[0080] Then, if Figure 7 As shown, a straight line fitting is performed on the image contour points (ie, the second contour position points) left by each corrected edge to obtain a fitting straight line.
[0081] Optionally, in another implementation of the present application, firstly, the lithography conditions of the sample corresponding to the original SEM image are obtained, and then, a preset mapping relationship is used to establish a direct connection between different lithography conditions and corresponding removal lengths, so that the range of contour points to be removed for the current lithography conditions can be quickly determined. Based on this removal length, the parts of the target contour ends corresponding to the removal lengths are directly removed to obtain the second contour position points of the contour after the removal.
[0082] In these optional embodiments, by setting a deviation threshold and removing contour position points (i.e., target position points) that deviate too much from the preset straight line, noise or abnormal points at the end of the target contour can be automatically filtered out, thereby retaining more accurate and stable contour data points for straight line fitting. Such processing not only improves the accuracy of straight line fitting, but also enhances the robustness and reliability of the image correction algorithm.
[0083] In one embodiment, the at least one correction edge is a plurality of edges, and the rotation correction is performed on the original SEM image according to the angle corresponding to the at least one correction edge to obtain the target SEM image, including:
[0084] For any corrected edge, respectively: calculate the angle difference between the corrected edge and the fitting line corresponding to the corrected edge;
[0085] The average value of the angle differences corresponding to the plurality of corrected edges is determined as the corrected angle of the original SEM image;
[0086] The original SEM image is rotationally corrected according to the correction angle to obtain the target SEM image.
[0087] Optionally, in another implementation of the present application, first, multiple correction edges existing in the original SEM image are processed one by one. For each correction edge, Figure 8 As shown, the angle difference between the corrected edge and the fitting straight line is calculated using a geometric calculation method, and the angle difference is the correction angle of the original SEM image.
[0088] Next, to determine the correction angle for the entire original SEM image, the algorithm calculates the average of the angle differences corresponding to all the correction edges. This step aims to comprehensively consider the distortion in multiple directions in the image and obtain a correction angle that can represent the overall distortion trend by taking the average. Optionally, when calculating the average, different weights can be assigned according to the importance and position of the correction edge to improve the accuracy and effectiveness of the correction.
[0089] After the correction angle is obtained, the original SEM image will be rotated or translated according to this angle to eliminate the distortion in the original SEM image. The corrected SEM image, i.e. the target SEM image, will have clearer edges, more accurate shapes and higher measurement accuracy, providing strong support for subsequent analysis and processing.
[0090] In these optional embodiments, the overall correction angle is determined by calculating the angle differences between multiple correction edges and the fitting straight line and taking the average, so that the distortion in the image can be more comprehensively considered and the accuracy and robustness of the SEM image correction can be improved.
[0091] In one embodiment, before performing rotation correction on the original SEM image according to the angle corresponding to the at least one correction edge, the method further comprises:
[0092] Removing a corrected edge that meets a preset condition from the at least one corrected edge to obtain a remaining corrected edge;
[0093] The preset conditions include any one of the following: the fitting residual of the fitting line corresponding to the correction edge is greater than or equal to the preset residual threshold, the roughness of the image contour corresponding to the correction edge is greater than or equal to the preset roughness threshold, and the length of the contour formed by the image contour position points corresponding to the correction edge is less than the preset length;
[0094] The rotation correction of the original SEM image according to the angle corresponding to the at least one correction edge comprises:
[0095] When the number of the remaining corrected edges is greater than 0, the original SEM image is rotationally corrected according to the angles corresponding to the remaining corrected edges.
[0096] Optionally, in an embodiment of the present application, since the edge position of the graphic in the SEM image obtained during the chip manufacturing process is often rough, when the roughness is large, it will affect the correction effect and reliability of the image rotation angle. Therefore, the present application sets a judgment on whether the roughness of the edge position of the graphic in the SEM image affects the final rotation angle. When the roughness of the image contour corresponding to the correction edge exceeds a certain threshold, the correction based on the angle difference determined by the correction edge can be abandoned to avoid the erroneous influence introduced by the wrong correction.
[0097] Optionally, in a feasible implementation of the present application, after calculating the angle differences between all the corrected edges and their respective fitting lines, not all corrected edges can provide reliable angle information for correction calculation. Therefore, a screening mechanism needs to be set to exclude those corrected edges that do not meet the preset conditions.
[0098] The screening process is based on three preset conditions: first, the fitting residual of the fitting line corresponding to the correction edge must be greater than or equal to the preset residual threshold to ensure the accuracy of the fitting; second, the roughness of the image contour corresponding to the correction edge must be greater than or equal to the preset roughness threshold to exclude contour irregularities caused by image quality problems; third, the contour length formed by the image contour position points corresponding to the correction edge must be less than the preset length threshold to ensure that the correction edge is sufficiently representative.
[0099] For the correction edges that do not meet any of the above conditions, their corresponding angle difference will be excluded from the calculation and will not be included in the calculation of the average value of the final correction angle. After the remaining correction edges are screened out, when only one correction edge that meets the conditions is left after screening, the angle difference corresponding to the correction edge will become the only basis for determining the correction angle of the original SEM image.
[0100] When two or more corrected edges that meet the conditions are obtained after screening, the average value is calculated based on the angle differences corresponding to these corrected edges to determine the corrected angle of the original SEM image.
[0101] Specifically, different weights can be assigned according to the importance or reliability of the correction edge, and then the weighted average angle can be calculated. The weight can be determined based on factors such as the length of the correction edge, the fitting residual, and the clarity of the image contour. This can more accurately reflect the combined impact of distortion in different areas of the image and improve the representativeness of the correction angle.
[0102] Alternatively, in order to cope with complex image distortion situations, the angle difference between the correction edge and the fitting straight line can be regarded as an error term, and the best fitting correction angle is determined by minimizing the sum of squares of these error terms.
[0103] In these optional embodiments, the correction edges are screened by preset conditions, thereby ensuring the quality of the data used for correction, avoiding correction errors caused by low-quality correction edges, ensuring the rationality and effectiveness of the correction process, and improving the accuracy and reliability of the final corrected image.
[0104] In one embodiment, the method further comprises:
[0105] When the number of the remaining corrected edges is equal to 0, the original SEM image is output.
[0106] Optionally, in a specific implementation of the present application, if the fitting residual of the obtained fitting straight line is greater than or equal to a preset residual threshold, and the length of the image contour corresponding to the correction edge after removing the two ends (that is, the length of the image contour formed by the second contour position points) is lower than a preset length threshold, or the roughness of the image contour corresponding to the correction edge exceeds a preset roughness threshold, then the corresponding rotation correction angle of the correction edge does not participate in the average calculation to ensure that the data source for the calculation of the final rotation correction angle is reliable.
[0107] If, after length screening, fitting residual screening, etc., there is no suitable data to obtain the final rotation correction, the original SEM image will not be corrected for image rotation angle, and will be output as the original SEM image in the final output.
[0108] In these optional embodiments, when data is insufficient or the quality does not meet the standards, correction is not performed and the original image is directly output, thereby avoiding image distortion caused by erroneous correction and ensuring the robustness of image processing and the availability of the final correction result.
[0109] Optionally, in the embodiment of the present application, when correcting the SEM image, the use of standard samples is avoided, and the import of reference objects such as design layouts is also avoided, so that each actual image to be corrected can be rotated and corrected separately, avoiding the situation in the prior art where a correction calculation is performed once and then applied to a batch of images. In this way, correcting each original SEM image separately helps to achieve higher rotation angle accuracy, especially when high-precision measurement requires high contour position accuracy, which can effectively reduce the edge position error of image contour extraction.
[0110] At the same time, due to the straight line fitting method used, when there is only a single-direction graphic in the actual SEM image, rotation angle correction can also be performed, and the actual graphic is not required to be a periodic graphic, which greatly expands the objects that can be corrected for image rotation angle. In addition, before applying the calculated rotation angle to correct the original SEM image, the application also considers the data reliability confirmation of the angle source corresponding to the correction edge. Only when it is confirmed that the data volume is sufficient and the data consistency is good, the calculated angle is applied to correct the SEM image, thereby avoiding the erroneous correction of the imported data with insufficient reliability and ensuring the availability of the final correction result.
[0111] Fig. 9 A schematic structural diagram of a SEM image correction device provided in another embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.
[0112] Reference Fig. 9 , the SEM image correction device may include:
[0113] A first processing module 901 is used to perform a straightening process on the image contour of the original SEM image to obtain a polygon corresponding to the image contour, wherein the straightening process is used to extend each edge in the image contour along the axial direction of a preset coordinate axis, and the preset coordinate axis is determined according to each edge in the image contour;
[0114] A screening module 902, configured to screen the edges whose length is greater than a preset length from the multiple edges of the polygon to obtain at least one corrected edge;
[0115] The second processing module 903 is used to respectively perform, for each corrected edge, the following steps: obtaining the image contour position point corresponding to the corrected edge on the image contour; performing straight line fitting on the image contour position point to obtain a fitted straight line; and calculating the angle between the fitted straight line and the corrected edge.
[0116] The correction module 904 is used to perform rotation correction on the original SEM image according to the angle corresponding to the at least one correction edge to obtain a target SEM image.
[0117] In one embodiment, the second processing module 903 includes:
[0118] A first acquisition submodule is used to acquire a target contour corresponding to the correction edge in the image contour;
[0119] A second acquisition submodule, used for acquiring a plurality of first contour position points of the target contour;
[0120] A first processing submodule is used to remove the first contour position point at the end position of the target contour from the plurality of first contour position points to obtain a second contour position point;
[0121] The first fitting submodule is used to perform straight line fitting on the second contour position points to obtain the fitting straight line.
[0122] In one embodiment, the first processing submodule includes:
[0123] The first processing unit is used to remove the target position point at the end position of the target contour from the multiple first contour position points to obtain a second contour position point, wherein the target position point is the first contour position point among the multiple first contour position points whose deviation degree is greater than a preset deviation threshold, and the deviation degree is used to characterize the deviation degree of the contour position point from the preset straight line.
[0124] In one embodiment, the at least one correction edge is multiple, and the correction module 904 includes:
[0125] The second processing submodule is used to respectively perform, for any corrected edge: calculating the angle difference between the corrected edge and the fitting straight line corresponding to the corrected edge;
[0126] A first determination submodule is used to determine the average value of the angle differences corresponding to the plurality of correction edges as the correction angle of the original SEM image;
[0127] The first correction submodule is used to perform rotation correction on the original SEM image according to the correction angle to obtain the target SEM image.
[0128] In one embodiment, the SEM image correction device may further include:
[0129] A third processing submodule, configured to remove a corrected edge that meets a preset condition from the at least one corrected edge to obtain a remaining corrected edge;
[0130] The preset conditions include any one of the following: the fitting residual of the fitting line corresponding to the correction edge is greater than or equal to the preset residual threshold, the roughness of the image contour corresponding to the correction edge is greater than or equal to the preset roughness threshold, and the length of the contour formed by the image contour position points corresponding to the correction edge is less than the preset length;
[0131] In one embodiment, the correction module 904 includes:
[0132] The second correction submodule is used to perform rotation correction on the original SEM image according to the angles corresponding to the remaining correction edges when the number of the remaining correction edges is greater than 0.
[0133] In one embodiment, the SEM image correction device may further include:
[0134] The second correction module is used to output the original SEM image when the number of the remaining corrected edges is equal to 0.
[0135] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application, and are devices corresponding to the above-mentioned battery thermal runaway warning method. All implementation methods in the above-mentioned method embodiment are applicable to the embodiments of the device. Its specific functions and technical effects can be found in the method embodiment part, which will not be repeated here.
[0136] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.
[0137] Fig.10 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.
[0138] The electronic device may include a processor 1001 and a memory 1002 storing program instructions.
[0139] When the processor 1001 executes the program, the steps in any of the above method embodiments are implemented.
[0140] Exemplarily, the program may be divided into one or more modules / units, one or more modules / units are stored in the memory 1002, and executed by the processor 1001 to complete the present application. One or more modules / units may be a series of program instruction segments capable of completing a specific function, and the instruction segments are used to describe the execution process of the program in the device.
[0141] Specifically, the processor 1001 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.
[0142] The memory 1002 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 1002 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 1002 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 1002 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 1002 is a non-volatile solid-state memory.
[0143] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software including computer executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.
[0144] The processor 1001 implements any one of the methods in the above embodiments by reading and executing program instructions stored in the memory 1002 .
[0145] In one example, the electronic device may further include a communication interface 1003 and a bus 1010. The processor 1001, the memory 1002, and the communication interface 1003 are connected via the bus 1010 and communicate with each other.
[0146] The communication interface 1003 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.
[0147] Bus 1010 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 1010 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.
[0148] In addition, in combination with the method in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores program instructions; when the program instructions are executed by a processor, any one of the methods in the above embodiment is implemented.
[0149] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.
[0150] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.
[0151] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the above-mentioned method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.
[0152] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.
[0153] The functional modules shown in the above block diagram can be implemented as hardware, software, firmware or their combination. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), suitable firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. Programs or code segments can be stored in machine-readable media, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable media" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. Code segments can be downloaded via computer grids such as the Internet, intranets, etc.
[0154] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.
[0155] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.
[0156] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.
Claims
1. A scanning electron microscope (SEM) image correction method, characterized in that: The method comprises: Performing a straightening process on the image contour of the original SEM image to obtain a polygon corresponding to the image contour, wherein the straightening process is used to extend each edge in the image contour along the axial direction of a preset coordinate axis, wherein the preset coordinate axis is determined according to each edge in the image contour; Selecting edges whose length is greater than a preset length from the multiple edges of the polygon to obtain at least one corrected edge; For each corrected edge, respectively: obtaining the image contour position point corresponding to the corrected edge on the image contour; performing straight line fitting on the image contour position point to obtain a fitted straight line; and calculating the angle between the fitted straight line and the corrected edge; The original SEM image is rotationally corrected according to the angle corresponding to the at least one corrected edge to obtain a target SEM image.
2. The method according to claim 1, characterized in that The obtaining of the image contour position point on the image contour corresponding to the correction edge includes: Acquire a target contour corresponding to the correction edge in the image contour; Acquire a plurality of first contour position points of the target contour; The step of performing straight line fitting on the image contour position points to obtain a fitting straight line includes: Removing the first contour position point located at the end position of the target contour from the plurality of first contour position points to obtain a second contour position point; A straight line fitting is performed on the second contour position points to obtain the fitting straight line.
3. The method according to claim 2, characterized in that The removing of the first contour position point located at the end position of the target contour from the plurality of first contour position points to obtain the second contour position point comprises: The target position point at the end position of the target contour among the multiple first contour position points is removed to obtain a second contour position point, wherein the target position point is a first contour position point among the multiple first contour position points whose deviation degree is greater than a preset deviation threshold, and the deviation degree is used to characterize the deviation degree of the contour position point from the preset straight line.
4. The method according to claim 1, characterized in that: The at least one correction edge is a plurality of edges, and the rotation correction is performed on the original SEM image according to the angle corresponding to the at least one correction edge to obtain the target SEM image, including: For any corrected edge, respectively: calculate the angle difference between the corrected edge and the fitting line corresponding to the corrected edge; The average value of the angle differences corresponding to the plurality of corrected edges is determined as the corrected angle of the original SEM image; The original SEM image is rotationally corrected according to the correction angle to obtain the target SEM image.
5. The method according to claim 4, characterized in that Before performing rotation correction on the original SEM image according to the angle corresponding to the at least one correction edge, the method further includes: Removing a corrected edge that meets a preset condition from the at least one corrected edge to obtain a remaining corrected edge; The preset conditions include any one of the following: the fitting residual of the fitting line corresponding to the correction edge is greater than or equal to the preset residual threshold, the roughness of the image contour corresponding to the correction edge is greater than or equal to the preset roughness threshold, and the length of the contour formed by the image contour position points corresponding to the correction edge is less than the preset length; The rotation correction of the original SEM image according to the angle corresponding to the at least one correction edge comprises: When the number of the remaining corrected edges is greater than 0, the original SEM image is rotationally corrected according to the angles corresponding to the remaining corrected edges.
6. The method according to claim 5, characterized in that The method further comprises: When the number of the remaining corrected edges is equal to 0, the original SEM image is output.
7. A SEM image correction device, characterized in that: The device comprises: A first processing module, configured to perform a straightening process on the image contour of the original SEM image to obtain a polygon corresponding to the image contour, wherein the straightening process is configured to extend each edge in the image contour along an axial direction of a preset coordinate axis, wherein the preset coordinate axis is determined according to each edge in the image contour; A screening module, used for screening the edges whose length is greater than a preset length from the multiple edges of the polygon to obtain at least one corrected edge; The second processing module is used to respectively perform, for each corrected edge, the following steps: obtaining an image contour position point on the image contour corresponding to the corrected edge; performing straight line fitting on the image contour position point to obtain a fitted straight line; and calculating an angle between the fitted straight line and the corrected edge. The correction module is used to perform rotation correction on the original SEM image according to the angle corresponding to the at least one correction edge to obtain a target SEM image.
8. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the SEM image correction method according to any one of claims 1 to 6 is implemented.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the SEM image correction method according to any one of claims 1 to 6 is implemented.
10. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the SEM image correction method as described in any one of claims 1 to 6.