CN115641350A - SEM figure contour point analysis method, device, computer equipment and program product - Google Patents
SEM figure contour point analysis method, device, computer equipment and program product Download PDFInfo
- Publication number
- CN115641350A CN115641350A CN202211319742.1A CN202211319742A CN115641350A CN 115641350 A CN115641350 A CN 115641350A CN 202211319742 A CN202211319742 A CN 202211319742A CN 115641350 A CN115641350 A CN 115641350A
- Authority
- CN
- China
- Prior art keywords
- point
- contour
- sem
- principal point
- points
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Image Analysis (AREA)
Abstract
The invention relates to the technical field of computational lithography, in particular to an SEM (scanning electron microscope) graph contour point analysis method, a device, computer equipment and a program product, which comprise the following steps: acquiring an SE M image to be analyzed, and calculating a directional derivative of each pixel in the SE image; selecting a pixel point as a principal point, marking a principal point view in a preset range by taking the principal point as a center, and marking the pixel points except the principal point in the principal point view as slave points; and calculating the similarity between the principal point and the subordinate point according to the direction derivatives of the principal point and the subordinate point, and judging whether the principal point is a contour point according to the calculation result. The invention also provides various S EM figure outline analyzing devices, computer equipment and program products, which save unnecessary time cost in the layout design process and improve the efficiency of the design process.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of computational lithography, in particular to an SEM (scanning electron microscope) graph outline point analysis method, a device, computer equipment and a program product.
[ background of the invention ]
In modern very large scale integrated circuit manufacturing processes, since the dimension of the pattern on the surface of the silicon wafer after exposure and development is in the nanometer level, it has not been possible to image it with a common optical microscope, and SEM (scanning electron microscope) is applied to this field to improve the resolution and image such a micro-scale pattern. SEM (scanning electron microscope) emits electrons to the surface of an object (silicon wafer), the electrons touch the rugged surface of the object (silicon wafer), and reflect different amounts of electrons at different positions, the reflected electrons are called secondary electrons, and the SEM (scanning electron microscope) obtains images of the micro-scale patterns on the surface of the silicon wafer by detecting the secondary electrons.
At present, gradient operators are generally adopted in the SEM image contour algorithm, and there are several implementation modes, and a first-order differential operator of formula 1 is relatively common.
Similarly, sobel operator and Laplace operator which belong to the same first-order differential operator are also available, and both belong to a single convolution kernel algorithm. In the edge detection comprehensive algorithm, the Canny algorithm has a better effect, firstly, the noise of the original image is filtered out through low-pass filtering, then NMS (non-maximum suppression method) is used for further noise control, and finally, double-threshold detection is used for obtaining the contour edge. The Canny algorithm has no advantage in operation speed. The SEM image has poor contour acquisition effect by applying Canny algorithm, mainly because the quality of the SEM image is not high, and as shown in fig. 3, the contour of the microstructure is not visually obvious when the SEM image is enlarged.
After applying the traditional gradient operator or Canny algorithm commonly used in the image processing field, satisfactory image contours cannot be obtained.
It can be clearly seen that the conventional algorithm loses the image contour information which can be still recognized by naked eyes. This is because the quality of SEM image is poor, the signals of the edge and contour portions are weak in numerical representation, and the values are not much different from the background environment after the gradient operator is applied, and are not easily resolved, and the method for resolving the contour generally uses a threshold method, as shown in equation 2.
Contour i,j ＝f(I i,j )＝max(I i,j -threshold, 0) formula 2
The method adopts a certain floating point value as a threshold value as a standard for judging the contour: pixels above the threshold are identified as contour and edge, and pixels below it are excluded, which directly results in some contour regions with weak numerical signals in the SEM image being identified as non-contour regions.
[ summary of the invention ]
The invention provides a method, a device, computer equipment and a program product for analyzing SEM (scanning electron microscope) graph contour points, which aim to solve the problem that whether pixel points with weak numerical signals are contour points cannot be accurately judged in the traditional mode.
In order to solve the technical problems, the invention provides the following technical scheme: a SEM figure contour point analysis method comprises the following steps: obtaining an SEM image to be analyzed, and calculating the directional derivative of each pixel in the SEM image; selecting a pixel point as a principal point, marking a principal point view in a preset range by taking the principal point as a center, and marking the pixel points except the principal point in the principal point view as slave points; and calculating the similarity between the principal point and the subordinate point according to the direction derivatives of the principal point and the subordinate point, and judging whether the principal point is a contour point according to the calculation result.
Preferably, after the directional derivative of each pixel in the SEM image is obtained, the plurality of pixel points are marked as principal points, and whether each principal point is a contour point is determined in parallel.
Preferably, when the similarity is greater than a preset first threshold, the principal point is determined to be a contour point.
Preferably, the range of the principal point field of view does not exceed a circle with a radius of 10nm centered on the principal point.
Preferably, the similarity between the master point and the slave point is calculated by the following formula:
wherein Nrm represents the degree of similarity, N represents the number of slave points other than the master point in the master point view,
the vector represents the directional derivative, i and j represent the coordinates of the master point in a Cartesian coordinate system, and p and q represent the coordinates of the slave point relative to the master point.
Preferably, when calculating the similarity between the master point and the slave point, the similarity is calculated in a partial normalization or non-normalization manner, as follows:
partial normalization:
or
Unnormalization:
preferably, the directional derivatives include derivatives in X and Y directions perpendicular to each other.
In order to solve the above technical problems, the present invention provides another technical solution as follows: an SEM figure outline analysis apparatus, which can implement the steps of the SEM figure outline point analysis method, comprises: a receiving module: the SEM image analysis device is used for acquiring an SEM image to be analyzed; a marking module: for marking the principal point, the principal point view and the subordinate points; a calculation module: the method is used for calculating the directional derivative of the pixel points and the similarity of the principal point and the subordinate point and judging whether the principal point is the contour point.
In order to solve the above technical problems, the present invention provides another technical solution as follows: a computer device comprising a memory, a processor and a computer program stored on the memory, wherein the processor executes the computer program to implement the steps of the SEM figure outline point analysis method.
In order to solve the above technical problems, the present invention provides another technical solution as follows: a program product comprising computer program instructions which, when executed, implement the steps of the SEM graphical contour point analysis method as described above.
Compared with the prior art, the SEM figure outline point analysis method provided by the invention has the following beneficial effects:
1. the SEM figure outline point analysis method provided by the first embodiment of the present invention includes the following steps: obtaining an SEM image to be analyzed, and calculating the directional derivative of each pixel in the SEM image; selecting a pixel point as a principal point, marking a principal point view in a preset range by taking the principal point as a center, and marking the pixel points except the principal point in the principal point view as slave points; and calculating the similarity between the principal point and the subordinate point according to the direction derivatives of the principal point and the subordinate point, and judging whether the principal point is a contour point according to the calculation result. It can be understood that the scheme provided by the first embodiment of the present invention is different from the conventional threshold method, and for some contour regions with weak numerical signals, the conventional threshold method can easily determine the contour region as a non-contour region, while the scheme determines whether a certain pixel is a contour point based on the similarity between the certain pixel and an adjacent pixel, and does not affect the determination of whether the current pixel is a contour point even if the numerical signal of the current pixel is weak. Compared with the traditional threshold value method, the method can acquire richer contour points for drawing clear image contours.
2. In the SEM image contour point analysis method provided in the first embodiment of the present invention, after the directional derivative of each pixel in the SEM image is obtained, a plurality of pixel points are simultaneously marked as principal points, and whether each principal point is a contour point is determined in parallel. It can be understood that, in the conventional method, the judgment result of the previous pixel point is generally used as a reference or basis for judging whether the current pixel point is the threshold point, so that the whole process belongs to a serial process, and each pixel point needs to be judged in sequence, which results in too high time cost for analysis and judgment and affects the efficiency of the whole process flow. In the scheme, the analysis and judgment processes of each pixel point are independent and do not influence each other, so that a plurality of pixel points can be analyzed simultaneously and processed in parallel, time cost can be greatly saved, and the efficiency of the whole process flow is improved.
3. In the SEM image contour point analysis method according to the first embodiment of the present invention, when the similarity is greater than the preset first threshold, it is determined that the principal point is a contour point. It is understood that when the similarity is greater than the first threshold, it indicates that around the main point, the gray scale change direction of enough slave points is the same as or similar to the change direction of the main point, and the contour point identification characteristic is satisfied. Therefore, the scheme provided by the first embodiment of the invention has higher accuracy and higher reliability.
4. In the SEM figure contour point analysis method according to the first embodiment of the present invention, the range of the principal point visual field does not exceed a circle having a radius of 10nm and centered on the principal point. It can be understood that if the field of view of the master point is too small, the number of slave points for determining the similarity is not sufficient, and it is not possible to accurately determine whether the master point is a contour point based on the similarity with the existing slave points. If the field of view is too large, the number of samples is too large, which results in more resource and time costs for the calculation process. Therefore, the principal point view is set to be within the range, the reliability of calculating the similarity is guaranteed, meanwhile, the calculation cost is reduced, and the process efficiency is improved.
5. In the SEM figure contour point analysis method provided in the first embodiment of the present invention, when calculating the similarity between the master point and the slave point, the calculation is performed in a partial normalization or non-normalization manner, as follows:
partial normalization:
or
Unnormalization:
it can be understood that the operation steps of division can be reduced by adopting a partial normalization or non-normalization mode, and considerable calculation resources and time cost can be saved after the operation steps are amplified to the calculation process of all pixel points. Therefore, the technical scheme improves the operation efficiency of the technical process.
6. The second embodiment of the present invention further provides an SEM image outline analyzing apparatus, which has the same advantages as the SEM image outline point analyzing method described above, and will not be described herein again.
7. The third embodiment of the present invention further provides a computer device, which has the same beneficial effects as the SEM image contour point analysis method described above, and is not described herein again.
8. The fourth embodiment of the present invention further provides a program product, which has the same beneficial effects as the SEM image contour point analysis method described above, and is not described herein again.
[ description of the drawings ]
Fig. 1 is a schematic flowchart of a method for analyzing SEM image contour points according to a first embodiment of the present invention.
Fig. 2 is a schematic diagram of an SEM image to be analyzed according to the SEM picture outline point analysis method provided by the first embodiment of the present invention.
Fig. 3 is a diagram illustrating loss of edge contour information in a conventional method.
Fig. 4 is a schematic diagram of a pixel point direction derivative of the SEM image contour point analysis method according to the first embodiment of the present invention.
Fig. 5 is a schematic diagram of the influence of different normalization strategies on the threshold value in the SEM image contour point analysis method according to the first embodiment of the present invention.
FIG. 6 is a schematic diagram illustrating the comparison between the SEM image contour point analysis method provided by the first embodiment of the present invention and the conventional SEM image contour recognition rate.
Fig. 7 is a schematic diagram of contour information identified by the SEM image contour point analysis method according to the first embodiment of the present invention.
Fig. 8 is a schematic view of an SEM image profile analyzing apparatus according to a second embodiment of the present invention.
Fig. 9 is a schematic diagram of a computer device provided by a third embodiment of the present invention.
Fig. 10 is a schematic diagram of a program product provided by a fourth embodiment of the invention.
The attached drawings indicate the following:
1. SEM figure outline point analytical method; 2. SEM figure outline analytical equipment; 3. a computer device; 4. a program product;
20. a receiving module; 21. a marking module; 22 a calculation module; 30. a memory; 31. a processor; 40. program instructions;
300. a computer program.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, a first embodiment of the invention provides a method 1 for analyzing SEM image contour points, comprising the following steps:
s0: acquiring an SEM image to be analyzed (as shown in FIG. 2), and calculating the directional derivative of each pixel in the SEM image;
s1: selecting a pixel point as a principal point, marking a principal point view in a preset range by taking the principal point as a center, and marking the pixel points except the principal point in the principal point view as slave points;
s2: and calculating the similarity between the principal point and the slave point according to the directional derivatives of the principal point and the slave point, and judging whether the principal point is a contour point according to the calculation result.
It can be understood that the scheme provided by the first embodiment of the present invention is different from the conventional threshold method, and for some contour regions with weak numerical signals, the conventional threshold method easily determines the contour regions as non-contour regions, resulting in loss of contour edge information (as shown in fig. 3), while the scheme determines whether a certain pixel is a contour point based on the similarity between the pixel and its neighboring pixels, and even if the numerical signal of the current pixel is weak, the determination of whether the current pixel is a contour point is not affected. Compared with the traditional threshold value method, the method can acquire richer contour points for drawing clear image contours.
Further, the directional derivatives include derivatives in the X and Y directions perpendicular to each other.
In some embodiments, after the directional derivative of each pixel in the SEM image is obtained, a plurality of pixel points are simultaneously marked as principal points, and whether each principal point is a contour point is determined in parallel.
It can be understood that, in the conventional method, the judgment result of the previous pixel point is generally used as a reference or basis for judging whether the current pixel point is the threshold point, so that the whole process belongs to a serial process, and each pixel point needs to be judged in sequence, which results in too high time cost for analysis and judgment and affects the efficiency of the whole process flow. In the scheme, the analysis and judgment processes of each pixel point are independent and do not influence each other, so that a plurality of pixel points can be analyzed simultaneously and processed in parallel, time cost can be greatly saved, and the efficiency of the whole process flow is improved.
Further, when the similarity is greater than a preset first threshold, the principal point is judged to be the contour point. It is understood that when the similarity is greater than the first threshold, it indicates that around the main point, the gray scale change direction of enough slave points is the same as or similar to the change direction of the main point, and the contour point identification characteristic is satisfied. Therefore, the scheme provided by the first embodiment of the invention has higher accuracy and higher reliability.
It should be understood that the magnitude of the preset first threshold may depend on the specific process flow.
In some embodiments, the range of the principal point field of view does not exceed a circle centered at the principal point with a radius of 10 nm. It can be understood that if the field of view of the master point is too small, the number of slave points for determining the similarity is not sufficient, and it is not possible to accurately determine whether the master point is a contour point based on the similarity with the existing slave points. If the field of view is too large, the number of samples is too large, which results in more resource and time costs for the calculation process. Therefore, the principal point view is set to be within the range, the reliability of calculating the similarity is guaranteed, meanwhile, the calculation cost is reduced, and the process efficiency is improved.
Alternatively, the main point view may be determined according to a specific process flow, and is not limited to a circle, but may be a rectangle or other shapes.
In some embodiments, the similarity of the master point to the slave point is calculated by the following formula:
wherein Nrm represents the degree of similarity, N represents the number of slave points other than the master point in the master point view,
the vector represents the directional derivative, i and j represent the coordinates of the master point in a Cartesian coordinate system, and p and q represent the coordinates of the slave point relative to the master point.
Referring to FIG. 4, it can be understood that the directional derivatives of the pixels
The direction of the directional derivative of the non-contour point is disordered.
Preferably, when calculating the similarity between the master point and the slave point, the similarity is calculated in a partial normalization or non-normalization manner, as follows:
partial normalization:
or
Non-normalization:
it can be understood that the operation steps of division can be reduced by adopting a partial normalization or non-normalization mode, and considerable calculation resources and time cost can be saved after the operation steps are amplified to the calculation process of all pixel points. Therefore, the technical scheme improves the operation efficiency of the technical process.
It should be understood that for the case where different normalization strategies are used, different threshold schemes will be used, see fig. 5 in particular.
With reference to fig. 6 and 7, after the SEM image contour point analysis method 1 according to the first embodiment of the present invention is adopted, it can be clearly seen that the contour edges of the SEM image are richer, and the recognition rate of the SEM image contour obtained by the present invention is significantly improved compared to the conventional method.
Referring to fig. 8, a second embodiment of the present invention further provides an SEM image profile analyzing apparatus 2, which can implement the steps of the analysis method 1 according to the first embodiment, including:
the receiving module 20: the SEM image analysis device is used for acquiring an SEM image to be analyzed;
the marking module 21: for marking the principal point, the principal point view and the subordinate points;
the calculation module 22: the method is used for calculating the directional derivative of the pixel points and the similarity of the principal point and the subordinate point and judging whether the principal point is the contour point.
For example, after the receiving module 20 receives the SEM image to be analyzed, the calculating module 22 calculates a directional derivative of each pixel point in the SEM image to be analyzed, the marking module 21 then selects one pixel point to mark as a principal point and marks a principal point view according to the principal point, then marks the pixel point in the principal point view as a slave point, and finally, the calculating module 22 calculates a similarity between the principal point and the slave point according to the directional derivative of the principal point and the slave point, and determines whether the principal point is a contour point according to the similarity.
Referring to fig. 9, a computer apparatus 3 according to a third embodiment of the present invention includes a memory 30, a processor 31 and a computer program 300 stored in the memory 30, wherein the processor 31 executes the computer program 300 to implement the steps of the SEM figure outline point analyzing method 1 according to the first embodiment.
Referring to fig. 10, a program product 4 according to a fourth embodiment of the present invention is further provided, in which the program product 4 includes computer program instructions 40, and when the computer program instructions 40 are executed, the steps of the SEM picture outline point analyzing method 1 according to the first embodiment are implemented.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may also be determined from a and/or other information.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Those skilled in the art should also appreciate that the embodiments described in this specification are exemplary and alternative embodiments, and that the acts and modules illustrated are not required to practice the invention.
In various embodiments of the present invention, it should be understood that the sequence numbers of the above-mentioned processes do not imply an inevitable order of execution, and the execution order of the processes should be determined by their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
The flowchart and block diagrams in the figures of the present application illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Compared with the prior art, the SEM image contour point analysis method provided by the invention has the following beneficial effects:
1. the SEM image contour point analysis method provided by the first embodiment of the invention comprises the following steps: obtaining an SEM image to be analyzed, and calculating the directional derivative of each pixel in the SEM image; selecting a pixel point as a principal point, marking a principal point view in a preset range by taking the principal point as a center, and marking the pixel points except the principal point in the principal point view as slave points; and calculating the similarity between the principal point and the subordinate point according to the direction derivatives of the principal point and the subordinate point, and judging whether the principal point is a contour point according to the calculation result. It can be understood that the scheme provided by the first embodiment of the present invention is different from the conventional threshold method, and for some contour regions with weak numerical signals, the conventional threshold method can easily determine the contour region as a non-contour region, while the scheme determines whether a certain pixel is a contour point based on the similarity between the certain pixel and an adjacent pixel, and does not affect the determination of whether the current pixel is a contour point even if the numerical signal of the current pixel is weak. Compared with the traditional threshold value method, the method can acquire richer contour points for drawing clear image contours.
2. In the SEM image contour point analysis method provided in the first embodiment of the present invention, after the directional derivative of each pixel in the SEM image is obtained, a plurality of pixel points are simultaneously marked as principal points, and whether each principal point is a contour point is determined in parallel. It can be understood that, in the conventional method, the judgment result of the previous pixel point is generally used as a reference or basis for judging whether the current pixel point is the threshold point, so that the whole process belongs to a serial process, and each pixel point needs to be judged in sequence, which results in too high time cost for analysis and judgment and affects the efficiency of the whole process flow. In the scheme, the analysis and judgment processes of each pixel point are independent and do not influence each other, so that a plurality of pixel points can be analyzed simultaneously and processed in parallel, time cost can be greatly saved, and the efficiency of the whole process flow is improved.
3. In the SEM image contour point analysis method according to the first embodiment of the present invention, when the similarity is greater than the preset first threshold, it is determined that the principal point is a contour point. It is understood that when the similarity is greater than the first threshold, it indicates that around the main point, the gray scale change direction of enough slave points is the same as or similar to the change direction of the main point, and the contour point identification characteristic is satisfied. Therefore, the scheme provided by the first embodiment of the invention has higher accuracy and higher reliability.
4. In the SEM figure contour point analysis method according to the first embodiment of the present invention, the range of the principal point visual field does not exceed a circle having a radius of 10nm and centered on the principal point. It can be understood that if the field of view of the master point is too small, the number of slave points for determining the similarity is not sufficient, and it is not possible to accurately determine whether the master point is a contour point based on the similarity with the existing slave points. If the field of view is too large, the number of samples is too large, which results in more resource and time costs for the calculation process. Therefore, the principal point view is set to be within the range, the reliability of calculating the similarity is guaranteed, meanwhile, the calculation cost is reduced, and the process efficiency is improved.
5. In the SEM image contour point analysis method provided in the first embodiment of the present invention, when calculating the similarity between the master point and the slave point, the calculation is performed in a partial normalization or non-normalization manner, as follows:
partial normalization:
or
Unnormalization:
it can be understood that the operation steps of division can be reduced by adopting a partial normalization or non-normalization mode, and considerable calculation resources and time cost can be saved after the operation steps are amplified to the calculation process of all pixel points. Therefore, the technical scheme improves the operation efficiency of the technical process.
6. The second embodiment of the present invention further provides an SEM image contour analyzing apparatus, which has the same beneficial effects as the SEM image contour point analyzing method described above, and is not described herein again.
7. The third embodiment of the present invention further provides a computer device, which has the same beneficial effects as the SEM image contour point analysis method described above, and is not described herein again.
8. The fourth embodiment of the present invention further provides a program product, which has the same beneficial effects as the SEM image contour point analysis method described above, and is not described herein again.
The SEM figure outline point analysis method, apparatus, computer device and program product disclosed in the embodiments of the present invention are introduced in detail, and a specific example is applied in the present document to explain the principle and the implementation of the present invention, and the description of the above embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for the person skilled in the art, based on the idea of the present invention, there may be variations in the embodiments and applications, and in view of the above, the content of the present description should not be construed as a limitation to the present invention, and any modifications, equivalent substitutions and improvements made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A SEM figure contour point analysis method is characterized in that: the method comprises the following steps:
obtaining an SEM image to be analyzed, and calculating the directional derivative of each pixel in the SEM image;
selecting one pixel point as a principal point, marking a principal point view of a preset range by taking the principal point as a center, and marking the pixel points except the principal point in the principal point view as slave points;
and calculating the similarity between the principal point and the subordinate point according to the direction derivatives of the principal point and the subordinate point, and judging whether the principal point is a contour point according to the calculation result.
2. The method for analyzing SEM picture contour points of claim 1, wherein: and after the directional derivative of each pixel in the SEM image is obtained, simultaneously marking a plurality of pixel points as main points, and judging whether each main point is a contour point or not in parallel.
3. The method for analyzing SEM figure contour points of claim 1, wherein: and when the similarity is greater than a preset first threshold value, judging that the principal point is a contour point.
4. The method for analyzing SEM picture contour points of claim 1, wherein: the range of the main point view field does not exceed a circle with the main point as the center and the radius of 10 nm.
5. The method for analyzing SEM picture contour points of claim 1, wherein: the similarity between the master point and the slave point is calculated by the following formula:
wherein Nrm represents the degree of similarity, N represents the number of slave points other than the master point in the master point view,
the vector represents the directional derivative, i and j represent the coordinates of the master point in a Cartesian coordinate system, and p and q represent the coordinates of the slave point relative to the master point.
6. The method for analyzing SEM figure contour points of claim 5, wherein: when calculating the similarity between the master point and the slave point, calculating by adopting a partial normalization or non-normalization mode, as follows:
partial normalization:
or
Non-normalization:
7. the method for analyzing SEM figure contour points of claim 6, wherein: the directional derivatives include derivatives in the X and Y directions that are perpendicular to each other.
8. An SEM figure profile analysis device is characterized in that: the method is characterized in that: the SEM picture outline analyzing apparatus may perform the SEM picture outline point analyzing method according to claim 1, including:
a receiving module: the SEM image analysis device is used for acquiring an SEM image to be analyzed;
a marking module: for marking the principal point, the principal point view and the subordinate points;
a calculation module: the method is used for calculating the directional derivative of the pixel points and the similarity of the principal point and the subordinate point and judging whether the principal point is the contour point.
9. A computer device, characterized by: comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to implement the steps of the SEM picture outline point analysis method according to claim 1.
10. A program product, characterized in that: the program product comprising computer program instructions which, when executed, implement the steps of the SEM graphical contour points analysis method of claim 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211319742.1A CN115641350A (en) | 2022-10-26 | 2022-10-26 | SEM figure contour point analysis method, device, computer equipment and program product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211319742.1A CN115641350A (en) | 2022-10-26 | 2022-10-26 | SEM figure contour point analysis method, device, computer equipment and program product |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115641350A true CN115641350A (en) | 2023-01-24 |
Family
ID=84946528
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211319742.1A Pending CN115641350A (en) | 2022-10-26 | 2022-10-26 | SEM figure contour point analysis method, device, computer equipment and program product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115641350A (en) |
-
2022
- 2022-10-26 CN CN202211319742.1A patent/CN115641350A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10776953B2 (en) | Method for identification of candidate points as possible characteristic points of a calibration pattern within an image of the calibration pattern | |
| EP3176751B1 (en) | Information processing device, information processing method, computer-readable recording medium, and inspection system | |
| US20120099781A1 (en) | Method and apparatus of pattern inspection and semiconductor inspection system using the same | |
| US8538130B2 (en) | CD metrology system and method of classifying similar structural elements | |
| CN115861291B (en) | Chip circuit board production defect detection method based on machine vision | |
| CN111507055B (en) | Registering method and registering system for circuit design layout and electron microscope scanning image, circuit design layout and imaging error calculating method thereof | |
| CN112085709B (en) | Image comparison method and device | |
| CN114998227A (en) | Cloth printing and dyeing defect detection method and system based on image processing | |
| JP4262269B2 (en) | Pattern matching method and apparatus | |
| CN110348307B (en) | Path edge identification method and system for crane metal structure climbing robot | |
| CN115527049A (en) | High-precision measurement method for lead frame pin spacing | |
| JP2011007728A (en) | Method, apparatus and program for defect detection | |
| JPH06317414A (en) | Device and method for measuring dimension of pattern | |
| CN115641350A (en) | SEM figure contour point analysis method, device, computer equipment and program product | |
| CN115880303A (en) | Sub-pixel precision positioning detection method and system for PCB circular hole | |
| CN113744200B (en) | Camera dirt detection method, device and equipment | |
| CN115829943A (en) | Image difference region detection method based on super-pixel segmentation | |
| JPH11219435A (en) | White line detector for automobile | |
| JP4262288B2 (en) | Pattern matching method and apparatus | |
| JP2008027130A (en) | Object recognition apparatus, object recognition means, and program for object recognition | |
| CN113487589A (en) | Sub-pixel circle center detection method and system | |
| US20100303361A1 (en) | Pattern edge detecting method and pattern evaluating method | |
| WO2024100796A1 (en) | Signal processing circuit, signal processing method, and program | |
| JP4430179B2 (en) | Image extraction method | |
| CN118505802A (en) | Method, equipment and storage medium for positioning wafer measurement area |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |