CN117173157A - Patterning process quality detection method, patterning process quality detection device, patterning process quality detection equipment and storage medium - Google Patents
Patterning process quality detection method, patterning process quality detection device, patterning process quality detection equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a patterning process quality detection method, a patterning process quality detection device, patterning process quality detection equipment and a storage medium, wherein the patterning process quality detection method comprises the following steps: acquiring a first image and a second image, and performing edge extraction processing to obtain a first graph and a second graph; placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph; performing coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph; and comparing the edge positions of the target graph and the first graph to determine graph deviation information between the target graph and the first graph. The method determines graph deviation information among graphs in a graph translation overlapping mode, efficiently completes deviation confirmation of batch points in the graphs, provides more comprehensive layout correction data for photoetching process development, and ensures the improvement effect of the graphical process.
Description
Technical Field
The embodiment of the application relates to the technical field of image processing, in particular to a patterning process quality detection method, a patterning process quality detection device, patterning process quality detection equipment and a storage medium.
Background
At present, in integrated circuit manufacturing, a patterning process is used for transferring a design layout to the surface of a wafer, and is a key link in a chip manufacturing process, wherein the patterning process comprises photoetching and etching, in order to control the quality of a finished product of the layout transfer process, a pattern image after development and a pattern image after etching are determined by using a scanning electron microscope, etching deviation is determined by comparing pattern line width information and edge difference information of the two pattern images, layout correction data is provided for subsequent photoetching process development based on the etching deviation, and errors between the pattern image after etching and an expected design layout are reduced.
However, in the prior art, the etching deviation between the developed pattern image and the etched pattern image is usually determined by an engineer through single-point measurement by using a scanning electron microscope, and only the pattern linewidth deviation can be determined.
Disclosure of Invention
The embodiment of the application provides a patterning process quality detection method, a patterning process quality detection device, patterning process quality detection equipment and a patterning process quality detection storage medium, solves the problems of single deviation information and low efficiency caused by determining etching deviation based on single-point measurement, realizes that corresponding patterns are obtained by carrying out edge extraction on images processed by different patterning processes, determines pattern deviation information among the patterns in a pattern translation overlapping mode, efficiently completes deviation confirmation of batch point positions in the patterns, can support determination of line width deviation and edge placement deviation in a photoetching process, provides more comprehensive layout correction data for photoetching process development, and ensures patterning process improvement effect.
In a first aspect, an embodiment of the present application provides a method for detecting quality of a patterning process, including:
acquiring a first image and a second image, wherein the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process;
performing edge extraction processing on the first image and the second image to obtain a first graph and a second graph;
placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph;
Performing coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph;
and comparing the edge positions of the target graph and the first graph to determine graph deviation information between the target graph and the first graph.
The edge extraction processing is performed on the first image and the second image to obtain a first graph and a second graph, which includes:
filtering the first image and the second image to obtain a first filtered image and a second filtered image;
performing binarization processing on the first filter image based on a set first global threshold to obtain a first characteristic image, and performing binarization processing on the second filter image based on a set second global threshold to obtain a second characteristic image;
and carrying out edge extraction on the first characteristic image and the second characteristic image based on a preset extraction algorithm to obtain a first graph and a second graph.
The first global threshold and the second global threshold are fixed thresholds, or the calculation results of the first filtering image and the second filtering image are based on a preset global threshold algorithm.
The calculating the target offset of the second graph relative to the first graph by performing frequency domain transformation on the first graph and the second graph in the same coordinate system includes:
performing Fourier transform on the first graph and the second graph to obtain first spectrum information and second spectrum information;
calculating mutual energy spectrum information of the first graph and the second graph based on the first spectrum information and the second spectrum information;
performing inverse Fourier transform on the mutual energy spectrum information to obtain the Dirichlet function distribution of the offset of the second graph relative to the first graph;
and taking peak position information obtained by carrying out the most value solving on the Dirichlet function distribution as the target offset of the second graph relative to the first graph.
Wherein the target offset includes an offset direction and an offset size;
the coordinate translation of the second graph based on the target offset is performed to obtain a target graph forming a position overlapping relation with the first graph, and the method comprises the following steps:
and carrying out coordinate translation corresponding to the offset size on each pixel point in the second graph according to the offset direction to obtain a target graph forming a position overlapping relation with the first graph.
The comparing the edge positions of the target graph and the first graph to determine graph deviation information of the target graph and the first graph includes:
acquiring a first coordinate position and a graph reference position corresponding to each pixel point in the target graph;
determining a matched pixel point corresponding to each pixel point from the pixel points of the first graph based on the graph reference position, and taking the coordinate position of the corresponding matched pixel point as a second coordinate position corresponding to each pixel point;
and calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain the target graph and graph deviation information between the first graph.
Wherein the graphic deviation information comprises a coordinate deviation direction and a coordinate deviation size;
calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain the target graph and graph deviation information between the first graph, wherein the method comprises the following steps:
determining the coordinate deviation direction of the first coordinate position corresponding to each pixel point relative to the second coordinate position;
And calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point.
In a second aspect, an embodiment of the present application further provides a patterning process quality detection apparatus, including
The image acquisition unit is configured to acquire a first image and a second image, wherein the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process;
the image extraction unit is configured to perform edge extraction processing on the first image and the second image to obtain a first image and a second image;
the offset determining unit is configured to place the first graph and the second graph into the same coordinate system, and perform frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph;
a graph translation unit configured to coordinate translate the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph;
and the deviation determining unit is configured to compare the edge positions of the target graph and the first graph to determine graph deviation information of the target graph and the first graph.
Wherein, the figure draws the unit, includes:
the filtering processing module is configured to perform filtering processing on the first image and the second image to obtain a first filtered image and a second filtered image;
the binarization module is configured to perform binarization processing on the first filter image based on a set first global threshold value to obtain a first characteristic image, and perform binarization processing on the second filter image based on a set second global threshold value to obtain a second characteristic image;
and the edge extraction module is configured to perform edge extraction on the first characteristic image and the second characteristic image based on a preset extraction algorithm to obtain a first graph and a second graph.
The first global threshold and the second global threshold are fixed thresholds, or the calculation results of the first filtering image and the second filtering image are based on a preset global threshold algorithm.
Wherein the offset determination unit includes:
the frequency spectrum calculation module is configured to perform Fourier transform on the first graph and the second graph to obtain first frequency spectrum information and second frequency spectrum information;
the energy spectrum calculation module is configured to calculate mutual energy spectrum information of the first graph and the second graph based on the first spectrum information and the second spectrum information;
The frequency spectrum inverse transformation module is configured to carry out inverse Fourier transformation on the mutual energy spectrum information to obtain the Dirichlet function distribution of the offset of the second graph relative to the first graph;
and the offset calculation module is configured to take peak position information obtained by carrying out the most value solving on the Dirichlet function distribution as the target offset of the second graph relative to the first graph.
Wherein the target offset includes an offset direction and an offset size;
a graphics translation unit comprising:
and the graph translation module is configured to translate the coordinates of each pixel point in the second graph corresponding to the offset according to the offset direction to obtain a target graph which is in a position overlapping relation with the first graph.
Wherein the deviation determining unit includes:
the first coordinate determining module is configured to acquire a first coordinate position corresponding to each pixel point in the target graph and a graph reference position;
a second coordinate determining module configured to determine a matching pixel point corresponding to each pixel point from among the pixel points of the first graph based on the graph reference position, and take a coordinate position of the corresponding matching pixel point as a second coordinate position corresponding to each pixel point;
And the graph deviation determining module is configured to calculate the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain graph deviation information between the target graph and the first graph.
Wherein the graphic deviation information comprises a coordinate deviation direction and a coordinate deviation size;
a deviation determining unit comprising:
the deviation direction determining module is configured to determine a coordinate deviation direction of the first coordinate position corresponding to each pixel point relative to the second coordinate position;
and the deviation determining module is configured to calculate the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
one or more processors;
a storage device configured to store one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the patterning process quality detection method according to the embodiments of the present application.
In a fourth aspect, embodiments of the present application also provide a non-volatile storage medium storing computer-executable instructions that, when executed by a computer processor, are configured to perform the patterning process quality detection method of embodiments of the present application.
In the embodiment of the application, a first image and a second image are acquired; then, carrying out edge extraction processing on the first image and the second image to obtain a first graph and a second graph; then placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph; then, carrying out coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph; and finally, comparing the edge positions of the target graph and the first graph to determine graph deviation information between the target graph and the first graph. The method has the advantages that the corresponding patterns are obtained by extracting the edges of the images processed by different patterning processes, the pattern deviation information between the patterns is determined by the pattern translation and overlapping mode, the deviation confirmation of batch point positions in the patterns is efficiently completed, the line width deviation and the edge placement deviation in the photoetching process can be supported, more comprehensive layout correction data is provided for photoetching process development, and the improvement effect of patterning process is ensured.
Drawings
FIG. 1 is a flow chart of a patterning process quality detection method provided by an embodiment of the application;
FIG. 2 is a flowchart of a method for obtaining a first pattern and a second pattern through edge extraction processing according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for calculating a target offset of a second pattern relative to a first pattern according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a target pattern shifted and overlapped with a first pattern in a position according to an embodiment of the present application;
FIG. 5 is a flowchart of a method for determining graphic deviation information of a target graphic and a first graphic according to an embodiment of the present application;
FIG. 6 is a block diagram of a patterning process quality detection device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in further detail below with reference to the drawings and examples. It should be understood that the particular embodiments described herein are illustrative only and are not limiting of embodiments of the application. It should be further noted that, for convenience of description, only some, but not all of the structures related to the embodiments of the present application are shown in the drawings.
The terms first, second and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type, and are not limited to the number of objects, such as the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.
The main execution body of each step of the patterning process quality detection method provided by the embodiment of the application can be computer equipment, and the computer equipment refers to any electronic equipment with data calculation, processing and storage capabilities, such as detection equipment, control equipment and the like, and also can be equipment such as a server and the like.
Fig. 1 is a flowchart of a patterning process quality detection method according to an embodiment of the present application, where the patterning process quality detection method may be implemented by using a patterning process quality detection device as an execution body. As shown in fig. 1, the patterning process quality detection method specifically includes the following steps:
Step S101, a first image and a second image are obtained, wherein the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process.
The first patterning process and the second patterning process may be different processing links with a sequence related to patterning process in the chip manufacturing process, taking a photolithography process as an example, and the pattern finally formed on the substrate needs to undergo the following pattern transfer process: the method comprises the steps of designing a layout, correcting an optical proximity effect (pattern on a mask plate), predicting a developed pattern, developing the pattern and etching the pattern by a photoetching model, wherein photoetching and etching processes aim to accurately transfer the designed layout to a substrate, which is equivalent to determining a process effect by measuring pattern deviation of the etched pattern and the designed layout, and particularly, as the deviation of the designed layout and the developed pattern is tiny, whether the etched pattern meets product requirements or not can be determined by comparing the developed pattern and the etched pattern, thereby the first patterning process can be development, the second patterning process can be etching, and the first image of residual photoresist on the surface of the developed substrate and the second image of the surface of the etched substrate can be used as reference data for determining deviation information between the developed pattern and the etched pattern later, so that the line width after etching can be accurately controlled within a specification range, and the edge deviation of the etched pattern and the designed pattern can be ensured within the specification range; in addition, for patterns with line widths smaller than exposure wavelength, diffraction effect is easy to occur during exposure, so that the developed patterns are distorted relative to the designed patterns, in order to improve the effectiveness and efficiency of lithography model verification, the first patterning process treatment can also be the prediction of the developed patterns by the lithography model, the second patterning process treatment can also be the development, and whether the line width difference value is in the specification range or not can be confirmed to perform model verification by acquiring a first image predicted by the lithography model and a second image of residual photoresist on the surface of the developed substrate, so that the follow-up improvement of model precision and product yield is facilitated.
In addition, in order to evaluate the effect of applying different materials or different devices in the same processing link related to the patterning process in the chip manufacturing process, the first patterning process and the second patterning process may be comparison processing tests performed by applying different materials or different devices in the same processing link, for example, the performance of the spare photoresist may be evaluated, and correspondingly, the first patterning process may be development by applying the spare photoresist, the second patterning process may be development by applying the baseline photoresist, and by acquiring the first image after development by applying the spare photoresist and the second image after development by applying the baseline photoresist, the difference between the spare photoresist and the detail of the baseline photoresist on the two-dimensional graph may be determined as a follow-up, thereby being beneficial to reducing the risk of using the spare photoresist and improving the safety factor of the supply chain. For example, the process effect of different lithography machines can be evaluated, the corresponding first patterning process can be performed by using a new machine, the second patterning process can be performed by using a baseline machine, the exposure difference of the new machine and the baseline machine to the complex graph can be evaluated by acquiring a first image after the development by using the new machine and a second image after the development by using the baseline machine, the difference between the new machine and the baseline machine can be accurately detected and corrected, the matching degree of the new machine and the baseline machine can be improved, and the consistency and the yield of products can be improved. For example, the use effects of different photomasks can be evaluated, corresponding to the first patterning process, the development can be performed by using a spare photomask, the second patterning process can be performed by using a base line photomask, and the pattern deviation between the spare photomask and the base line photomask can be obtained by acquiring a first image after the development by using the spare photomask and a second image after the development by using the base line photomask, so that the manufacturing difference of the spare photomask factory and the base line photomask for two-dimensional patterns can be evaluated, the spare photomask factory can be authenticated more accurately, the risk of using the spare photomask is reduced, and the safety coefficient of a supply chain is improved. Of course, the above-listed several application scenarios are merely exemplary and explanatory, and in practical applications, the patterning process quality detection method may also be used in patterning process under other scenarios, which is not limited in this embodiment of the present application.
And step S102, performing edge extraction processing on the first image and the second image to obtain a first graph and a second graph.
The first image and the second image may be captured images of a scanning electron microscope, and since the edges of the residual photoresist pattern after development or the edges of the substrate pattern after etching have a high jump, the brightness of the edge position in the captured images is relatively higher than that of other positions, so that the first pattern and the second pattern after the first patterning process treatment and the second patterning process treatment can be obtained by performing edge extraction treatment, which is beneficial to the subsequent detection and analysis of process quality parameters such as line width deviation, edge placement deviation and the like.
Specifically, fig. 2 is a flowchart of a method for obtaining a first graph and a second graph through edge extraction processing according to an embodiment of the present application, where, as shown in fig. 2, a specific implementation process for obtaining the first graph and the second graph through edge extraction processing includes:
step S1021, filtering the first image and the second image to obtain a first filtered image and a second filtered image.
The filtering process can adopt filtering algorithms such as mean filtering, median filtering, gaussian filtering and the like. The filtering processing is performed on the first image and the second image, so that high-frequency noise, low-frequency noise or other types of noise in the images can be effectively reduced, the quality and definition of the images are improved, in addition, in order to facilitate edge extraction in subsequent steps, details and irregular edges in the images can be smoothed through the filtering processing, the images are more uniform and continuous, edge features in the images are highlighted, and the edges of the images are clearer and more obvious.
Step S1022, performing binarization processing on the first filtered image based on the set first global threshold to obtain a first feature image, and performing binarization processing on the second filtered image based on the set second global threshold to obtain a second feature image.
Under the condition that the difference between the filtered images is small, the global threshold of the filtered images can be a set fixed threshold, binarization is carried out by using the same global threshold, and the global threshold can be formulated based on statistical characteristics such as the average value, the median and the like of the historical filtered images; under the condition of large difference between the filtered images, in order to improve the binarization precision, the global threshold of the filtered images can be the calculation result of the first filtered image and the second filtered image based on a preset global threshold algorithm, which is equivalent to that each filtered image is calculated to obtain the corresponding global threshold, and the specific algorithm for calculating the global threshold can be based on the maximized inter-class variance, based on the gray histogram or the image segmentation algorithm and the like, so that the highlighting effect of the binarized edges is effectively ensured, and the edge extraction of the images is facilitated.
Step S1023, performing edge extraction on the first feature image and the second feature image based on a preset extraction algorithm to obtain a first graph and a second graph.
The preset extraction algorithm can be a Canny edge detection algorithm, an edge detection algorithm based on a Sobel, rewitt, laplacian operator, a LoG algorithm and the like, and the first graph and the second graph can be obtained by effectively extracting edges of the first characteristic image and the second characteristic image based on the preset extraction algorithm. In addition, the first pattern and the second pattern can be further processed into image edge curves with single pixels, which is beneficial to pattern overlay and deviation measurement between patterns in subsequent steps.
And step 103, placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain the target offset of the second graph relative to the first graph.
In order to complete the graphic overlay through the coordinate translation operation, the first graphic and the second graphic need to be placed in the same coordinate system, and the relative offset between the first graphic and the second graphic needs to be determined. The embodiment of the application calculates the target offset of the second graph relative to the first graph by adopting the technical thought of frequency domain transformation calculation, and it can be understood that in the same coordinate system, the coordinate position of the first graph is fixed, and the second graph can be regarded as a translation result of the first graph as the second graph is similar to the first graph, and the calculation of the target offset is completed by combining the Fourier transformation and the inverse Fourier transformation of the frequency domain.
Specifically, fig. 3 is a flowchart of a method for calculating a target offset of a second graph relative to a first graph according to an embodiment of the present application, and as shown in fig. 3, a specific implementation process for calculating a target offset of a second graph relative to a first graph includes:
step S1031, placing the first pattern and the second pattern in the same coordinate system.
Step S1032, performing Fourier transform on the first graph and the second graph to obtain first spectrum information and second spectrum information.
Wherein, the two images are set in the same coordinate system,representing a first graphic>Representing a second graph, according to a correlation calculation formula of Fourier transform, the second graph is known:
the frequency domain expression after the first graph is fourier transformed is:
the frequency domain expression after the second graph is subjected to Fourier transform is:
because the first pattern is similar to the second pattern, the first pattern and the second pattern can be considered to be only different by one translation amount in the same coordinate system,/>) Thus, a first pattern can be obtained>And a second pattern->The functional relationship of (2) is:
correspondingly, a first patternAnd a second pattern->The frequency domain relation of (2) is:
thus, in the calculationAnd +.>In the case of (a) can be achieved by p- >Performing inverse Fourier transform to obtain translation (>，/>)。
Step S1033, calculating the mutual energy spectrum information of the first graph and the second graph based on the first spectrum information and the second spectrum information.
Wherein, according to the first spectrum information and the second spectrum information calculated in the step S1032, the translation amount is set as #，/>) In the case of (1) calculating the mutual energy spectrum of the first pattern and the second pattern +.>The calculation formula of (2) is as follows:
wherein the method comprises the steps ofIs->Is a conjugate of (c).
Step S1034, performing inverse fourier transform on the mutual energy spectrum information to obtain a dirac function distribution of the offset of the second pattern relative to the first pattern.
Wherein, for mutual energy spectrumThe inverse fourier transform can be obtained:
it is obvious that the process is not limited to,for a pulse function, i.e. a dirk function distribution, the peak occurs where the second pattern is optimally offset with respect to the first pattern due to the proximity of the first pattern to the second pattern.
And step S1035, using peak position information obtained by carrying out the optimal solution on the Dirichlet function distribution as the target offset of the second graph relative to the first graph.
Wherein, because the first pattern is similar to the second pattern, the peak value is the optimal offset of the second pattern relative to the first pattern, thereby determining the translation amount by searching the position of the peak value ，/>) Specifically, the peak position information can be obtained by performing the optimal solution on the dirk function distribution.
Therefore, the target offset of the second graph relative to the first graph can be effectively determined through the frequency domain transformation calculation mode, the accuracy of graph overlapping is improved, and the image deviation determination of the subsequent steps is facilitated.
And step S104, carrying out coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph.
Optionally, the target offset is a vector, and may include an offset direction and an offset size, and in the same coordinate system, the specific translation process of the second graph may include:
and carrying out coordinate translation corresponding to the offset size on each pixel point in the second graph according to the offset direction to obtain a target graph which forms a position overlapping relation with the first graph.
Specifically, in step S103, the translation amount is determined，/>) After that, second figure->Subtracting the translation amount from each pixel coordinate of (2) to obtain the target graph +.>The correlation calculation formula is:
then the target patternCan be +.>The best overlapping of the graphics is realized, wherein fig. 4 is a schematic diagram of overlapping the position formed by the target graphics after translation and the first graphics, and as shown in fig. 4, after the target graphics and the first graphics are overlapped through translation, the edge position deviation of the two graphics can be effectively reflected, so that the subsequent determination of the graphics deviation information is facilitated.
Step S105, comparing the edge positions of the target graph and the first graph to determine graph deviation information of the target graph and the first graph.
The second pattern is translated to obtain a target pattern overlapped with the first pattern, and although the target pattern is similar to the first pattern, a shape deviation may exist, and the reference information can be provided for the corresponding graphic process improvement by determining the shape deviation. The specific edge position comparison comprises edge position deviation determination of a target pattern and a first pattern, width measurement of adjacent edges representing line width information in the patterns, and the like, the first patterning process is used as development, the second patterning process is used as etching, and the pattern deviation information can be line width deviation information obtained by comparing line width information obtained by measuring the developed pattern and the etched pattern, edge placement deviation information obtained by stacking the developed pattern and the etched pattern, and the like.
Specifically, fig. 5 is a flowchart of a method for determining graphic deviation information of a target graphic and a first graphic according to an embodiment of the present application, where, as shown in fig. 5, a specific implementation process of determining the graphic deviation information of the target graphic and the first graphic includes:
Step S1051, obtain the first coordinate position and the graphics reference position corresponding to each pixel point in the target graphics.
The reference position of the pattern may be a relative position of each pixel point in the target pattern, and when the processing effect of the patterning process reaches an ideal state, the shape of the target pattern is the same as that of the first pattern, after the pattern overlapping, the coordinates of the pixel points are the same corresponding to the same relative position in the target pattern and the first pattern, if the processing effect of the patterning process does not conform to the expected one, the coordinates of the pixel points deviate, and the improvement of the patterning process can be facilitated by determining the deviation. Specifically, the graph reference position can be determined by determining the proportion position of the pixel point in the whole graph or by taking the set marking point as a reference center, and the association relationship of the corresponding pixel point between the target graph and the first graph can be established through the graph reference position, so that the determination of graph deviation information is facilitated. Of course, the pattern deviation is confirmed by setting the pattern key points, and the pattern deviation information is confirmed by comparing the coordinate deviations of the key points of the target pattern and the first pattern in the subsequent steps, so that the data processing amount can be reduced, and the operation efficiency can be improved.
Step S1052, determining a matched pixel point corresponding to each pixel point from the pixel points of the first graph based on the graph reference position, and taking the coordinate position of the corresponding matched pixel point as a second coordinate position corresponding to each pixel point;
the corresponding matching pixel point is determined from the first graph based on the graph reference position of the current pixel point of the target graph by traversing the pixel points of the target graph, and the coordinate position of the matching pixel point is correspondingly obtained, and the coordinate position can be used as a second coordinate position for comparing with the first coordinate position of the current pixel point in the target graph.
Step S1053, calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain the target graph and the graph deviation information between the first graphs.
It should be noted that, in the case that the patterning process treatment effect reaches the ideal state, the coordinate values of the first coordinate position and the second coordinate position corresponding to each pixel point obtained in step S1052 should be the same, if the patterning process treatment effect does not conform to the expectation, a coordinate deviation may occur between the first coordinate position and the second coordinate position of the pixel point, so that the graphic deviation information corresponding to each pixel point may be determined by calculating the coordinate deviation, and optionally, the graphic deviation information includes a coordinate deviation direction and a coordinate deviation magnitude, and a specific implementation process of calculating the coordinate deviation includes: determining the coordinate deviation direction of the first coordinate position corresponding to each pixel point relative to the second coordinate position, and calculating the coordinate deviation of the first coordinate position corresponding to each pixel point and the second coordinate position, so as to obtain the target graph and graph deviation information between the first graph. By taking the first patterning process as development and the second patterning process as etching as an example, based on the pattern deviation information, not only the line width deviation of the developed pattern and the etched pattern can be determined, but also the deviation direction of the line width deviation of the etched pattern relative to the developed pattern can be determined, so that the pattern design before development is improved, such as line width compensation and the like in the deviation direction, good consistency between the etched pattern and the design layout is ensured, and the product yield is improved.
According to the method, the corresponding patterns are obtained by extracting the edges of the images processed by different patterning processes, the pattern deviation information between the patterns is determined in a pattern translation and overlapping mode, the deviation confirmation of batch point positions in the patterns is efficiently completed, the line width deviation and the edge placement deviation in the photoetching process can be determined, more comprehensive layout correction data is provided for photoetching process development, and the improvement effect of the patterning process is ensured.
Fig. 6 is a block diagram of a patterning process quality detection device according to an embodiment of the present application, where the device is configured to execute the patterning process quality detection method according to the foregoing embodiment, and has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 6, the apparatus specifically includes:
an image acquisition unit 101 configured to acquire a first image and a second image, where the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process;
a graph extraction unit 102, configured to perform edge extraction processing on the first image and the second image to obtain a first graph and a second graph;
An offset determining unit 103, configured to place the first graph and the second graph in a same coordinate system, and perform frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph;
a graph translation unit 104, configured to perform coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relationship with the first graph;
and a deviation determining unit 105 configured to determine the image deviation information of the target image and the first image by comparing the edge positions of the target image and the first image.
The first image and the second image are acquired; then, carrying out edge extraction processing on the first image and the second image to obtain a first graph and a second graph; then placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph; then, carrying out coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph; and finally, comparing the edge positions of the target graph and the first graph to determine graph deviation information between the target graph and the first graph. The method has the advantages that the corresponding patterns are obtained by extracting the edges of the images processed by different patterning processes, the pattern deviation information between the patterns is determined by the pattern translation and overlapping mode, the deviation confirmation of batch point positions in the patterns is efficiently completed, the line width deviation and the edge placement deviation in the photoetching process can be supported, more comprehensive layout correction data is provided for photoetching process development, and the improvement effect of patterning process is ensured.
In one possible embodiment, the graphics extraction unit 102 comprises:
the filtering processing module is configured to perform filtering processing on the first image and the second image to obtain a first filtered image and a second filtered image;
the binarization module is configured to perform binarization processing on the first filter image based on a set first global threshold value to obtain a first characteristic image, and perform binarization processing on the second filter image based on a set second global threshold value to obtain a second characteristic image;
and the edge extraction module is configured to perform edge extraction on the first characteristic image and the second characteristic image based on a preset extraction algorithm to obtain a first graph and a second graph.
In a possible embodiment, the first global threshold and the second global threshold are fixed thresholds that are set, or are calculated based on a preset global threshold algorithm for the first filtered image and the second filtered image.
In one possible embodiment, the offset determining unit 103 includes:
the frequency spectrum calculation module is configured to perform Fourier transform on the first graph and the second graph to obtain first frequency spectrum information and second frequency spectrum information;
The energy spectrum calculation module is configured to calculate mutual energy spectrum information of the first graph and the second graph based on the first spectrum information and the second spectrum information;
the frequency spectrum inverse transformation module is configured to carry out inverse Fourier transformation on the mutual energy spectrum information to obtain the Dirichlet function distribution of the offset of the second graph relative to the first graph;
and the offset calculation module is configured to take peak position information obtained by carrying out the most value solving on the Dirichlet function distribution as the target offset of the second graph relative to the first graph.
In one possible embodiment, the target offset includes an offset direction and an offset size;
a graphics translation unit 104 comprising:
and the graph translation module is configured to translate the coordinates of each pixel point in the second graph corresponding to the offset according to the offset direction to obtain a target graph which is in a position overlapping relation with the first graph.
In one possible embodiment, the deviation determining unit 105 comprises:
the first coordinate determining module is configured to acquire a first coordinate position corresponding to each pixel point in the target graph and a graph reference position;
A second coordinate determining module configured to determine a matching pixel point corresponding to each pixel point from among the pixel points of the first graph based on the graph reference position, and take a coordinate position of the corresponding matching pixel point as a second coordinate position corresponding to each pixel point;
and the graph deviation determining module is configured to calculate the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain graph deviation information between the target graph and the first graph.
In one possible embodiment, the graphic deviation information includes a coordinate deviation direction and a coordinate deviation magnitude;
the deviation determining unit 105 includes:
the deviation direction determining module is configured to determine a coordinate deviation direction of the first coordinate position corresponding to each pixel point relative to the second coordinate position;
and the deviation determining module is configured to calculate the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in fig. 7, the device includes a processor 201, a memory 202, an input device 203, and an output device 204; the number of processors 201 in the device may be one or more, one processor 201 being taken as an example in fig. 7; the processor 201, memory 202, input devices 203, and output devices 204 in the apparatus may be connected by a bus or other means, for example in fig. 7. The memory 202 is a computer readable storage medium configured to store a software program, a computer executable program, and modules, such as program instructions/modules corresponding to the patterning process quality detection method in the embodiment of the present application. The processor 201 executes various functional applications of the device and data processing, i.e., implements the above-described quality detection method of patterning process, by running software programs, instructions, and modules stored in the memory 202. The input device 203 may be configured to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the apparatus. The output device 204 may include a display device such as a display screen.
The electronic equipment provided by the application can be used for executing the patterning process quality detection method provided by any embodiment, and has corresponding functions and beneficial effects.
The embodiments of the present application also provide a non-volatile storage medium containing computer-executable instructions that, when executed by a computer processor, are configured to perform a patterning process quality detection method described in the above embodiments, comprising: acquiring a first image and a second image, wherein the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process; performing edge extraction processing on the first image and the second image to obtain a first graph and a second graph; placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph; performing coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph; and comparing the edge positions of the target graph and the first graph to determine graph deviation information between the target graph and the first graph.
Storage media-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, lanbas (Rambus) RAM, etc.; nonvolatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a second, different computer system connected to the first computer system through a network such as the internet. The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media residing in different locations (e.g., in different computer systems connected by a network). The storage medium may store program instructions (e.g., embodied as a computer program) executable by one or more processors.
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present application is not limited to the patterning process quality detection method described above, and may also perform the related operations in the patterning process quality detection method provided in any embodiment of the present application.
It should be noted that, in the embodiment of the patterning process quality detection device, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for convenience of distinguishing from each other, and are not configured to limit the protection scope of the embodiments of the present application.
It should be noted that, the numbers of the steps in the solution are only used to describe the overall design framework of the solution, and do not represent the necessary sequence relationship between the steps. On the basis that the whole implementation process accords with the whole design framework of the scheme, the method belongs to the protection scope of the scheme, and the literal sequence during description is not an exclusive limit on the specific implementation process of the scheme. It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (10)
1. The patterning process quality detection method is characterized by comprising the following steps:
acquiring a first image and a second image, wherein the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process;
performing edge extraction processing on the first image and the second image to obtain a first graph and a second graph;
placing the first graph and the second graph in the same coordinate system, and performing frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph;
performing coordinate translation on the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph;
and comparing the edge positions of the target graph and the first graph to determine graph deviation information between the target graph and the first graph.
2. The method for detecting the quality of a patterning process according to claim 1, wherein performing edge extraction processing on the first image and the second image to obtain a first pattern and a second pattern comprises:
Filtering the first image and the second image to obtain a first filtered image and a second filtered image;
performing binarization processing on the first filter image based on a set first global threshold to obtain a first characteristic image, and performing binarization processing on the second filter image based on a set second global threshold to obtain a second characteristic image;
and carrying out edge extraction on the first characteristic image and the second characteristic image based on a preset extraction algorithm to obtain a first graph and a second graph.
3. The method according to claim 2, wherein the first global threshold and the second global threshold are fixed thresholds, or are calculated for the first filtered image and the second filtered image based on a preset global threshold algorithm.
4. The method for detecting the quality of a patterning process according to claim 1, wherein performing frequency domain transform calculation on a first pattern and a second pattern in the same coordinate system to obtain a target offset of the second pattern relative to the first pattern includes:
performing Fourier transform on the first graph and the second graph to obtain first spectrum information and second spectrum information;
Calculating mutual energy spectrum information of the first graph and the second graph based on the first spectrum information and the second spectrum information;
performing inverse Fourier transform on the mutual energy spectrum information to obtain the Dirichlet function distribution of the offset of the second graph relative to the first graph;
and taking peak position information obtained by carrying out the most value solving on the Dirichlet function distribution as the target offset of the second graph relative to the first graph.
5. The patterning process quality detection method of claim 1, wherein the target offset includes an offset direction and an offset magnitude;
the coordinate translation of the second graph based on the target offset is performed to obtain a target graph forming a position overlapping relation with the first graph, and the method comprises the following steps:
and carrying out coordinate translation corresponding to the offset size on each pixel point in the second graph according to the offset direction to obtain a target graph forming a position overlapping relation with the first graph.
6. The method for detecting the quality of a patterning process according to claim 1, wherein the comparing the edge positions of the target pattern and the first pattern to determine the pattern deviation information of the target pattern and the first pattern includes:
Acquiring a first coordinate position and a graph reference position corresponding to each pixel point in the target graph;
determining a matched pixel point corresponding to each pixel point from the pixel points of the first graph based on the graph reference position, and taking the coordinate position of the corresponding matched pixel point as a second coordinate position corresponding to each pixel point;
and calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain the target graph and graph deviation information between the first graph.
7. The patterning process quality detection method of claim 6, wherein the pattern deviation information includes a coordinate deviation direction and a coordinate deviation magnitude;
calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point to obtain the target graph and graph deviation information between the first graph, wherein the method comprises the following steps:
determining the coordinate deviation direction of the first coordinate position corresponding to each pixel point relative to the second coordinate position;
and calculating the coordinate deviation of the first coordinate position and the second coordinate position corresponding to each pixel point.
8. Patterning process quality detection device, characterized in that includes:
the image acquisition unit is configured to acquire a first image and a second image, wherein the first image is a product surface image processed by a first patterning process, and the second image is a product surface image processed by a second patterning process;
the image extraction unit is configured to perform edge extraction processing on the first image and the second image to obtain a first image and a second image;
the offset determining unit is configured to place the first graph and the second graph into the same coordinate system, and perform frequency domain transformation calculation on the first graph and the second graph in the same coordinate system to obtain a target offset of the second graph relative to the first graph;
a graph translation unit configured to coordinate translate the second graph based on the target offset to obtain a target graph forming a position overlapping relation with the first graph;
and the deviation determining unit is configured to compare the edge positions of the target graph and the first graph to determine graph deviation information of the target graph and the first graph.
9. An electronic device, the device comprising: one or more processors; a storage device configured to store one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the patterning process quality detection method of any one of claims 1-7.
10. A non-transitory storage medium storing computer-executable instructions which, when executed by a computer processor, are configured to perform the patterning process quality detection method of any one of claims 1-7.
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