Alignment method, alignment apparatus, program, and storage medium

Abstract

To provide an alignment method, an alignment device, a program, and a storage medium capable of more easily aligning an image of a design layout and an image obtained by photographing.SOLUTION: An alignment method according to an embodiment causes a computer to acquire a first preparatory image showing a design layout of a structure and a second preparatory image obtained by imaging the structure. A first parameter to be used in the first processing and a second parameter to be used in the second processing are determined based on the similarity between the first preparation image subjected to the first processing and the second preparation image subjected to the second processing. A first processed image is acquired by performing first processing on a first image showing a design layout using a first parameter. A second processed image is acquired by performing second processing on a second image obtained by photographing, using a second parameter. The first processed image and the second processed image are aligned based on the similarity between the first processed image and the second processed image.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] FIELD Embodiments of the present invention relate to a registration method, a registration apparatus, a program, and a storage medium. [Background technology]

[0002] A photograph of a structure is taken and then aligned with an image of the design layout. There is a need for a technology that can more easily align the two images. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2020 / 246149 Summary of the Invention [Problem to be solved by the invention]

[0004] The problem to be solved by the embodiments of the present invention is to provide an alignment method, an alignment device, a program, and a storage medium that can more easily align an image of a design layout with an image obtained by photographing. [Means for solving the problem]

[0005] An alignment method according to an embodiment causes a computer to acquire a first preparatory image showing a design layout of a structure and a second preparatory image obtained by photographing the structure. The alignment method causes the computer to determine first parameters to be used in a first process and second parameters to be used in a second process based on a similarity between the first preparatory image subjected to the first process and the second preparatory image subjected to the second process. The alignment method causes the computer to acquire a first processed image by performing the first process on the first image showing the design layout of the structure using the first parameters. The alignment method causes the computer to acquire a second processed image by performing the second process on a second image obtained by photographing the structure using the second parameters. The alignment method causes the computer to align the first processed image and the second processed image based on a similarity between the first processed image and the second processed image. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a flowchart showing an outline of the alignment method according to the embodiment. [Figure 2] FIG. 2 is a flowchart showing a part of the alignment method according to the embodiment. [Figure 3] FIG. 3 is a flowchart showing a part of the alignment method according to the embodiment. [Figure 4] FIG. 4 is a flowchart showing a part of the alignment method according to the first modified example of the embodiment. [Figure 5] FIG. 5 is a flowchart showing a part of the alignment method according to the first modified example of the embodiment. [Figure 6] FIG. 6 is a flowchart showing a part of an alignment method according to a second modified example of the embodiment. [Figure 7] FIG. 7 is a flowchart showing a part of an alignment method according to a third modified example of the embodiment. [Figure 8]FIG. 8 is a flowchart showing a part of an alignment method according to a fourth modified example of the embodiment. [Figure 9] FIG. 9 is a flowchart showing a part of the alignment method according to the second modified example of the embodiment. [Figure 10] FIG. 10 is a schematic diagram for explaining the processing shown in FIG. [Figure 11] Fig. 11(a) is an example of a first partial image, Fig. 11(b) is an example of a second partial image, and Fig. 11(c) is an example of a first preliminary image. [Figure 12] FIG. 12 is an example of the second preparation image. [Figure 13] FIG. 13 is a graph showing the relationship between the amount of change in resizing and the number of image pairs. [Figure 14] FIG. 14 is a graph showing the relationship between the rotation angle and the number of image pairs. [Figure 15] FIG. 15 is a graph showing the relationship between the size of the smoothing filter and the similarity. [Figure 16] Fig. 16(a) is an example of a first processed image after the first processing has been performed, and Fig. 16(b) is an example of a second processed image after the second processing has been performed. [Figure 17] FIG. 17 is an example of an image showing the test results. [Figure 18] FIG. 18 is a schematic diagram showing the configuration of a computer. DETAILED DESCRIPTION OF THE INVENTION

[0007] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the present specification and the drawings, elements similar to those already described are designated by the same reference numerals, and detailed descriptions thereof will be omitted where appropriate.

[0008] When a structure is manufactured, it may be inspected. In the inspection, electrical properties, thermal properties, mechanical properties, etc. are examined. For example, in an electrical property inspection, the electrical properties (electrical resistance, electrical capacitance, etc.) of each point within a specific area of ​​the structure are measured. In a thermal property inspection, the thermal properties (thermal conductivity, heat capacity, etc.) of each point within a specific area of ​​the structure are measured. For example, the inspection results in an image in which the properties of each point are mapped.

[0009] During the inspection, photographs of the structure are also taken. The photographs can be optical, electronic, X-ray, or ultrasonic images. The inspection images showing the inspection results do not fully show the shape of the structure. For this reason, it is difficult to determine which parts of the structure are abnormal using only the inspection images. The photographs of the structure can be used to identify abnormal parts of the structure. By referring to the photographs, it becomes easier to identify the abnormal parts.

[0010] However, when a structure is small, it may be difficult to identify which part of the structure has an abnormality using only a photograph. In particular, when the structure is a semiconductor device, each component is minute, and the structure's configuration is difficult to clearly see in a photograph. Depending on the manufacturing process, the manufactured shape may differ from the designed shape. For this reason, it may be difficult to identify the abnormality using only a photograph.

[0011] If it is difficult to identify the abnormality from the photograph, the design layout is further referenced. For example, the photograph is compared with an image of the design layout. It is determined which area of ​​the design layout corresponds to the area shown in the photograph. Next, based on the result of aligning the photograph with the design layout, it is determined which part of the design layout the abnormality in the inspection image corresponds to. In this way, the abnormality on the design layout is identified. The results of identifying the abnormality are used in design or development to prevent the occurrence of the abnormality.

[0012] In recent years, miniaturization of semiconductor devices has progressed further. As a result, features such as shapes and patterns tend to become blurred in photographs. The more blurred the features in a photograph, the more difficult it becomes to align the photograph with a design layout. Embodiments of the present invention are used to align an image showing a design layout with a photographed image of a structure with higher accuracy.

[0013] FIG. 1 is a flowchart showing an outline of the alignment method according to the embodiment. As shown in FIG. 1, the alignment method according to the embodiment mainly includes determining parameters (step S10) and aligning (step S20). In step S10, parameters required for alignment are determined. In step S20, an image of a design layout and a photograph of a structure are aligned. In step S20, the parameters determined in step S10 are used. Steps S10 and S20 are executed by a computer.

[0014] FIG. 2 is a flowchart showing a part of the alignment method according to the embodiment. FIG. 2 shows details of step S10 in FIG. 1. First, the computer acquires a first preparatory image showing a design layout of a structure (step S11a). The first preparatory image is obtained by converting the design layout into image data. For example, the first preparatory image is prepared by converting two-dimensional Computer Aided Design (CAD) data or three-dimensional CAD data into an image. The computer may acquire the first preparatory image by acquiring CAD data and converting it into an image. The first preparatory image may be prepared in advance, and the computer may acquire the prepared first preparatory image.

[0015] The computer acquires a second preparatory image obtained by photographing the structure (step S11b). The first and second preparatory images relate to the same structure. For example, a camera photographs the structure and acquires a photograph (image) of the structure. The photograph may be an RGB color image or a grayscale image. For example, the camera receives infrared light and generates a grayscale image based on the infrared light. The computer acquires an optical image of the structure as the second preparatory image. If the structure is minute, the camera is preferably attached to an optical microscope. Instead of an optical image, an electron image may be acquired. For example, an electron image of the structure may be acquired by a scanning electron microscope (SEM). In that case, the computer acquires the electron image as the second preparatory image.

[0016] The area of ​​the structure shown in the first preliminary image is approximately the same as the area of ​​the structure shown in the second preliminary image. The area shown in the image of the design layout may be slightly larger than the area included in the photograph of the structure. It is preferable that the entire area included in the photograph is included in the image of the design layout.

[0017] When the resolution of the first preparatory image and the resolution of the second preparatory image are different, it is preferable to adjust the resolution of at least one of the first preparatory image and the second preparatory image in advance. Generally, an image of a design layout depicts a more detailed shape of a structure than a photograph. In other words, the resolution of the image of a design layout is higher than the resolution of a photograph. For this reason, it is preferable to reduce the size of the first preparatory image in advance to reduce the difference in resolution between the first preparatory image and the second preparatory image.

[0018] The order of steps S11a and S11b can be changed as appropriate. Step S11b may be performed before step S11a, or steps S11a and S11b may be performed simultaneously.

[0019] The computer sets first parameters to be used in the first process and second parameters to be used in the second process (step S11c). The first process is image processing performed on an image of the design layout. The second process is image processing performed on an image of the structure.

[0020] For example, at least one of the first and second processes includes a smoothing process. In this case, at least one of the first and second parameters is the size of a smoothing filter. In the smoothing process, pixel values ​​are smoothed between adjacent pixels. The "smoothing filter" indicates the range over which pixel values ​​are smoothed. The larger the size of the smoothing filter, the wider the range over which pixel values ​​are smoothed. An averaging filter, a Gaussian filter, or the like can be used as the smoothing filter.

[0021] At least one of the first and second processes may include resizing (enlarging or reducing) the image. In this case, at least one of the first and second parameters is the amount of change in resizing. At least one of the first and second processes may include rotating the image. In this case, at least one of the first and second parameters is an angle. The first process may include multiple image processes. In this case, a first parameter is set for each image process. The second process may include multiple image processes. In this case, a second parameter is set for each image process.

[0022] In step S11c, the first and second parameters are set to initial values, which may be preset by a computer user or may be randomly set by the computer.

[0023] The computer performs a first process on the first preparatory image using the first parameter, and a second process on the second preparatory image using the second parameter (step S11d).The computer calculates a similarity between the first preparatory image that has been subjected to the first process and the second preparatory image that has been subjected to the second process (step S11e).

[0024] As a specific example, template matching is used to calculate the similarity. The processed second preparatory image is used as the template image. A range for calculating the similarity with the template image is set in the processed first preparatory image. The similarity between the set range in the first preparatory image and the second preparatory image is calculated. The computer repeats the similarity calculation while changing the range for calculating the similarity in the first preparatory image. In this way, the similarity is calculated for the entire area of ​​the processed first preparatory image. The computer extracts the maximum similarity from the multiple similarities. The maximum similarity is associated with the first and second parameters when step S11e was executed and saved. Feature point matching may be used to calculate the similarity instead of template matching.

[0025] The computer determines whether the entire range of the first parameter and the entire range of the second parameter have been searched (step S11f). For example, the ranges to be searched are set in advance for each of the first and second parameters. The computer determines whether the entire set ranges have been searched.

[0026] If it is determined that the entire range has not been searched, the computer changes the first parameter or the second parameter (step S11g). At this time, only one of the first and second parameters may be changed, or both the first and second parameters may be changed.

[0027] After step S11g, step S11d is executed again. As a result, the first and second processes are executed using the changed first and second parameters. Then, the similarity is calculated. Steps S11d to S11g are repeated until the entire range of the first parameter has been searched and the entire range of the second parameter has been searched.

[0028] Instead of searching the entire range, the loop of steps S11d to S11g may be terminated by setting the number of times the loop is executed. In this case, the computer terminates the loop when the number of times the loop is executed reaches a predetermined value. A threshold value for the similarity may also be set as the termination condition. In this case, the computer compares the similarity obtained in step S11e with a preset threshold value. If the similarity exceeds the threshold value, the computer terminates the loop. The loop is repeated until the similarity exceeds the threshold value or the number of times the loop is executed reaches a predetermined value.

[0029] Furthermore, in steps S11f and S11g, an optimization method other than a full search may be used. For example, in the initial stage of the search, the similarity is calculated while greatly changing at least one of the first and second parameters. From the results, the computer calculates an approximate expression that expresses the relationship between the first parameter and the similarity, and an approximate expression that expresses the relationship between the second parameter and the similarity. From these approximate expressions, the computer determines a range in which the optimal first parameter is estimated to be obtained and a range in which the optimal second parameter is estimated to be obtained. Within these ranges, the computer calculates the similarity while slightly changing at least one of the first and second parameters.

[0030] If it is determined in step S11f that the entire range has been searched, the computer refers to the multiple similarities obtained so far. The computer extracts the maximum similarity from the multiple similarities. The computer refers to the first and second parameters that were used when the maximum similarity was obtained. The computer determines the first and second parameters as the parameters to be used in the first and second processes (step S11h).

[0031] According to steps S11d to S11h, the first parameter and the second parameter are determined based on the similarity between the first preparatory image that has been subjected to the first processing and the second preparatory image that has been subjected to the second processing. More specifically, the first parameter and the second parameter are determined so that the first preparatory image that has been subjected to the first processing and the second preparatory image that has been subjected to the second processing are similar.

[0032] FIG. 3 is a flowchart showing a part of the alignment method according to the embodiment. FIG. 3 shows details of step S20 in FIG. 1. First, the computer acquires a first image showing a design layout of a structure (step S21a). The first preliminary image and the first image relate to the same structure. The extent of the design layout in the first image may be the same as the extent of the design layout in the first preliminary image, or may be different from the extent of the design layout in the first preliminary image. If the extent of the design layout in the first preliminary image is the same as the extent of the design layout in the first image, the first image may be the same as the first preliminary image.

[0033] The computer performs a first process on the first image to generate a first processed image (step S21b). In the first process in step S21b, the first parameters determined in step S11h are used.

[0034] The computer acquires a second image obtained by photographing the structure (step S21c). The second preparatory image and the second image relate to the same structure. The range of the structure depicted in the second image may be the same as the range of the structure depicted in the second preparatory image, or may be different from the range of the structure depicted in the second preparatory image.

[0035] The computer performs second processing on the second image to generate a second processed image (step S21d). In the second processing in step S21d, the second parameters determined in step S11h are used.

[0036] The order of steps S21a to S21d can be changed as appropriate. For example, step S21c may be performed before step S21a, or steps S21b and S21d may be performed after steps S21a and S21c.

[0037] In order to calculate the similarity, the computer sets, in one of the first processed image and the second processed image, the position of the other of the first processed image and the second processed image (step S21e). For example, in the first processed image, a position at which the similarity with the second processed image is calculated is set.

[0038] The computer performs template matching at the set position and calculates the similarity between the first processed image and the second processed image (step S21f).

[0039] The computer determines whether the entire range of one of the first processed image and the second processed image has been searched (step S21g). For example, if the similarity has been calculated at all positions in the first processed image, it is determined that the entire range has been searched.

[0040] If it is determined that the entire range has not been searched, the computer changes the position of the first processed image or the second processed image in one of the first processed image or the second processed image (step S21h). For example, a position in the first processed image where the similarity has not yet been calculated is adopted.

[0041] After step S21h, step S21f is executed again. As a result, the similarity is calculated again at the changed position. Steps S21f to S21h are repeated until the entire range of one of the first processed image and the second processed image has been searched.

[0042] If it is determined that the entire range has been searched, the computer references the multiple similarities obtained so far and extracts the maximum similarity. The computer references the position where the maximum similarity was obtained. The computer determines that position as the position where the first processed image and the second processed image best match (step S21i).

[0043] If an inspection image is also acquired when the second image is captured, the inspection image may be aligned. For example, if an abnormality in a structure is captured in the inspection image, the computer aligns the inspection image with the first image. As a result, the coordinates of the abnormality in the first image are calculated. The computer outputs the calculated coordinates (step S21j). This allows the computer user to easily determine at which coordinates in the design layout the abnormality occurs.

[0044] The advantages of the embodiment will be described. Conventionally, there is a technology that uses artificial intelligence (AI) to process images of design layouts in order to align the images with photographs of structures. With this technology, the images of the design layout are processed by AI, and an image similar to the photograph of the structure is output. This makes it easy to align the photograph of the structure with the image output by the AI. However, training the AI ​​requires a large amount of training data. This requires a great deal of effort in advance preparation.

[0045] In an embodiment of the present invention, instead of using AI, a first image of a design layout and a second image of a photograph of a structure are each subjected to image processing. The first image is subjected to a first processing to generate a first processed image. The second image is subjected to a second processing to generate a second processed image. The first parameters used in the first processing and the second parameters used in the second processing are determined in advance so that the first processed image and the second processed image are similar to each other. For example, if only one of the first image and the second image is processed, it is difficult to make the two images sufficiently similar. By processing the first image and the second image, respectively, it is possible to obtain a first processed image and a second processed image that are similar to each other. Then, alignment is performed using the first processed image and the second processed image. According to the embodiment, an image of a design layout and a photograph of a structure can be aligned more easily without using AI.

[0046] At least one of the first and second processes preferably includes a smoothing process. Photographs generally include image blur due to insufficient resolution. When the first process includes a smoothing process, blur is imparted to the image of the design layout, making the image of the design layout closer to a photograph. When the second process includes a smoothing process, random noise contained in the photograph is suppressed.

[0047] The size of the structure shown in the design layout may differ from the size of the structure included in the photograph. For this reason, the second processing may include resizing. Also, the orientation of the structure shown in the design layout may differ from the orientation of the structure included in the photograph. For this reason, the second processing may include rotation.

[0048] When both the first and second processes include smoothing processes, the parameters of only one of the smoothing processes may be optimized in step S10. For example, the first image is subjected to smoothing, and the second image is subjected to smoothing, resizing, and rotation. In this case, the parameters of the smoothing process for the first image, the resizing parameters for the second image, and the rotation parameters for the second image may be optimized in step S10. The parameters of the smoothing process for the second image are set to arbitrary values ​​as appropriate.

[0049] (First Modification) An image of the design layout may be generated by blending multiple images. A semiconductor device generally has a multilayer structure consisting of multiple layers. Specifically, a semiconductor device includes a substrate, a wiring layer, a contact layer, etc. The substrate includes n-type or p-type semiconductor regions, insulating regions for electrically or spatially isolating the semiconductor regions, etc. For example, multiple circuit elements such as diodes, capacitors, and transistors are formed on the substrate. The wiring layer includes wiring for electrically connecting the semiconductor regions and wiring for electrically connecting the semiconductor regions to external circuits. The contact layer includes contact plugs for electrically connecting the wiring and the semiconductor regions, or vias for electrically connecting the wiring. Multiple wiring layers and multiple contact layers may be formed alternately in the thickness direction of the substrate.

[0050] When photographing a structure, the structure may be irradiated with light. The wavelength of the irradiated light can be selected appropriately. In this case, depending on the combination of the irradiation position and wavelength of the light, a structure with multiple layers may be captured in the image.

[0051] As an example, infrared light is irradiated onto a semiconductor device from the substrate side. Infrared light is less easily absorbed by semiconductors than light with short wavelengths such as green or blue. Therefore, a photograph based on reflected infrared light may include not only the structure of the substrate, but also the structure of the contact layer and the wiring layer. Furthermore, if the substrate is sufficiently thin, even with visible light, the photograph may include the structure of the substrate, the structure of the contact layer, the structure of the wiring layer, and the like. In such cases, an image showing the design layout of the substrate may be blended with an image showing the design layout of the contact layer or an image showing the design layout of the wiring layer.

[0052] As another example, visible light is irradiated onto the semiconductor device from the wiring layer side. If the semiconductor device includes multiple wiring layers and the insulating layers included in the wiring layers are transparent, the light may be reflected by the multiple wiring layers. A photograph based on the reflected visible light may include the structure of the multiple wiring layers. In this case, an image of the design layout of the top wiring layer may be blended with images of the design layout of other wiring layers.

[0053] FIG. 4 is a flowchart showing a part of the alignment method according to the first modified example of the embodiment. In a first modified example of the embodiment, step S10a shown in FIG. 4 is executed instead of step S10 shown in FIG. 2. First, the computer acquires a first partial image and a second partial image (step S12a). The first partial image shows a design layout of a first layer of the structure. The second partial image shows a design layout of a second layer of the structure. The range of the design layout of the first partial image and the range of the design layout of the second partial image are selected so as to overlap each other when viewed from the shooting direction of the camera. For example, the range of the design layout of the first partial image and the range of the design layout of the second partial image overlap each other in the stacking direction of the structure.

[0054] The computer acquires a second preliminary image (step S12b). The computer sets first and second weights (step S12c). In a first variant, the first preliminary image is generated by blending a first partial image and a second partial image. The first weight is a weight parameter of the first partial image in the blending. The second weight is a weight parameter of the second partial image in the blending. In step S12c, the first and second weights are set to initial values. The initial values ​​may be set in advance by a user of the computer or may be set randomly by the computer.

[0055] The computer generates a first preliminary image by blending the first partial image and the second partial image (step S12d), using the weights that were set immediately before.

[0056] The computer calculates the similarity between the first and second preparatory images (step S12e). Template matching can be used to calculate the similarity.

[0057] The computer determines whether the entire range of the first weight and the entire range of the second weight have been searched (step S12f). For example, the ranges to be searched are set in advance for each of the first and second weights. The computer determines whether the entire set ranges have been searched.

[0058] If it is determined that the entire range has not been searched, the computer changes the first or second weight (step S12g). At this time, only one of the first weight and the second weight may be changed, or both the first weight and the second weight may be changed.

[0059] After step S12g, step S12d is executed again. As a result, a first preliminary image is generated again using the changed weights. The similarity between the newly generated first preliminary image and the second preliminary image is calculated. Steps S12d to S12g are repeated until the entire range of each weight has been searched.

[0060] Instead of searching the entire range, the loop of steps S12d to S12g may be terminated by setting the number of times the loop is executed. A threshold value for the similarity may also be set as the termination condition. For example, if the similarity obtained in step S12e exceeds the threshold value, the computer terminates the loop. The loop is repeated until the similarity exceeds the threshold value or the number of times the loop is executed reaches a predetermined value.

[0061] Furthermore, in steps S12f and S12g, an optimization method other than a full search may be used. For example, in the initial stage of the search, the similarity is calculated while greatly changing at least one of the first and second weights. From the results, the computer calculates an approximate expression that expresses the relationship between the first weight and the similarity, and an approximate expression that expresses the relationship between the second weight and the similarity. From these approximate expressions, the computer determines a range in which an optimal first weight is estimated to be obtained and a range in which an optimal second weight is estimated to be obtained. Within these ranges, the computer calculates the similarity while making small changes to at least one of the first and second weights.

[0062] If it is determined in step S12f that the entire range has been searched, the computer refers to the multiple similarities obtained by repeating steps S12d to S12g. The computer extracts the maximum similarity from the multiple similarities. The computer refers to the first and second weights used when the maximum similarity was obtained. The computer determines the first and second weights as weights to be used in blending the images (step S12h).

[0063] After the weights are determined, the computer sets first and second parameters (step S12i). The first and second parameters are values ​​used in the first and second processes, respectively. In step S12i, the first and second parameters are set to initial values. The initial values ​​may be set in advance by a user of the computer, or may be set randomly by the computer.

[0064] The computer performs a first process on the first preparatory image using the first parameter, and a second process on the second preparatory image using the second parameter (step S12j). The computer calculates the similarity between the first preparatory image that has been subjected to the first process and the second preparatory image that has been subjected to the second process (step S12k). Template matching can be used to calculate the similarity.

[0065] The computer determines whether the entire range of the first parameter and the entire range of the second parameter have been searched (step S121). For example, the ranges to be searched are set in advance for each of the first and second parameters.

[0066] If it is determined that the entire range has not been searched, the computer changes the first or second parameter (step S12m). At this time, only one of the first parameter and the second parameter may be changed, or both the first parameter and the second parameter may be changed.

[0067] After step S12m, step S12j is executed again. As a result, the first and second processes are executed using the changed first and second parameters. Then, the similarity is calculated again. Steps S12j to S12m are repeated until the entire range of each parameter has been searched.

[0068] Instead of searching the entire range, the loop of steps S12j to S12m may be terminated by setting the number of times the loop is executed. A threshold value for the similarity may also be set as the termination condition. For example, if the similarity obtained in step S12k exceeds the threshold value, the computer terminates the loop. The loop is repeated until the similarity exceeds the threshold value or the number of times the loop is executed reaches a predetermined value.

[0069] If it is determined in step S12l that the entire range has been searched, the computer refers to the multiple similarities obtained by repeating steps S12j to S12m. The computer extracts the maximum similarity from the multiple similarities. The computer refers to the first and second parameters that were used when the maximum similarity was obtained. The computer determines the first and second parameters as parameters to be used in the first and second processes (step S12n).

[0070] According to steps S12d to S12g, weights are set for each partial image so that the blended first preliminary image resembles a photograph of the structure. Also, according to steps S12j to S12m, the first and second parameters are determined so that the first preliminary image subjected to the first processing resembles the second preliminary image subjected to the second processing.

[0071] FIG. 5 is a flowchart showing a part of the alignment method according to the first modified example of the embodiment. In the first modified example, step S20a shown in Fig. 5 is executed instead of step S20 shown in Fig. 3. In step S20a, first, the computer acquires a third partial image (step S22a). The third partial image acquired in step S22a and the first partial image acquired in step S12a show the same design layout in the first layer. The range of the design layout in the third partial image may be the same as or different from the range of the design layout in the first partial image.

[0072] The computer acquires a fourth partial image (step S22b). The fourth partial image acquired in step S22b and the second partial image acquired in step S12b show the same design layout on the second layer. The extent of the design layout in the fourth partial image may be the same as the extent of the design layout in the second partial image, or may be different from the extent of the layout depicted in the second partial image. The extent of the design layout in the third partial image and the extent of the design layout in the fourth partial image are selected so as to overlap each other when viewed from the shooting direction of the camera.

[0073] The computer generates the first image by blending the third and fourth partial images (step S22c). At this time, the weight of the third partial image is set to the first weight determined in step S12h. The weight of the fourth partial image is set to the second weight determined in step S12h.

[0074] The computer performs a first process on the first image to generate a first processed image (step S22d). In the first process in step S22d, the first parameters determined in step S12n are used.

[0075] The computer acquires a second image obtained by photographing the structure (step S22e). The computer generates a second processed image by performing a second process on the second image (step S22f). In the second process of step S22f, the second parameters determined in step S12n are used.

[0076] The computer sets the position of the other of the first processed image and the second processed image in one of the first processed image and the second processed image (step S22g), and performs template matching at the set position to calculate the similarity between the first processed image and the second processed image (step S22h).

[0077] The computer determines whether the entire range of one of the first processed image and the second processed image has been searched (step S22i). If it is determined that the entire range has not been searched, the computer changes the position of the other of the first processed image and the second processed image (step S22j). After step S22j, step S22h is executed again. As a result, the similarity is calculated again at the changed position.

[0078] If it is determined that the entire range has been searched, the computer references the multiple similarities obtained so far and extracts the maximum similarity. The computer references the position where the maximum similarity was obtained. The computer determines that position as the position where the first processed image and the second processed image best match (step S22k). The computer may then output the coordinates of the abnormality (step S22m).

[0079] According to the first modification, when a photograph includes a structure of multiple layers, the image of the design layout and the photograph of the structure can be aligned with higher accuracy.

[0080] (Second Modification) In a first modification, when the first or second processing includes resizing, the amount of change in resizing may be determined using a plurality of first preliminary images and a plurality of second preliminary images. In a second modification, the amount of change in resizing is determined using a plurality of first preliminary images and a plurality of second preliminary images.

[0081] Fig. 6 is a flowchart showing a part of an alignment method according to a second modification of the embodiment. In the second modification, step S10b shown in Fig. 6 is executed instead of step S10 shown in Fig. 2. First, a plurality of pairs of a first partial image and a second partial image are prepared. The plurality of pairs represent different areas of the same structure. In addition, a second preliminary image corresponding to each pair is prepared.

[0082] The computer acquires a plurality of pairs (first partial images and second partial images) (step S13a). Next, the computer acquires a plurality of second preparation images corresponding to the plurality of pairs (step S13b). This results in a plurality of combinations of the first partial images, the second partial images, and the second preparation images.

[0083] The computer selects a combination to be used to determine the weights from the plurality of combinations (step S13c), and executes the same processes as steps S12c to S12h shown in Fig. 4 to determine the first and second weights (step S13d).

[0084] The computer generates a plurality of first preliminary images from the plurality of pairs acquired in step S13a using the determined first and second weights (step S13e), thereby obtaining a plurality of pairs of the first preliminary image and the second preliminary image.

[0085] The computer selects a pair of a first and a second preliminary image to be used to determine the amount of change in resizing (step S13f). The computer sets the amount of change (step S13g). In step S13g, the amount of change is set to an initial value. The amount of change may be set in advance by the computer user or may be set randomly by the computer.

[0086] The computer resizes one of the first and second preparatory images using the set amount of change (step S13h). Here, an example will be described in which the second preparatory image is resized. The computer calculates the similarity between the first preparatory image and the resized second preparatory image (step S13i). Template matching can be used to calculate the similarity.

[0087] The computer determines whether the entire range of the amount of change has been searched (step S13j). If it is determined that the entire range has not been searched, the computer changes the amount of change (step S13k). After step S13k, step S13h is executed again. As a result, the second preparation image is resized again using the changed amount of change. Steps S13h to S13k are repeated until the entire range of the amount of change has been searched.

[0088] If it is determined in step S13j that the entire range has been searched, the computer refers to the multiple similarities obtained by repeating steps S13h to S13k, and selects the amount of change that yields the maximum similarity (step S13l).

[0089] The computer determines whether all pairs of first and second preliminary images have been selected in step S13f (step S13m). If there are any pairs that have not been selected, step S13f is executed again. This selects a pair that has not yet been selected. Steps S13g to S13k are executed again using that pair.

[0090] If it is determined in step S13m that all pairs have been selected, the computer determines the amount of change to be used in resizing based on the amounts of change selected in the previous multiple steps S13l (step S13n). For example, the computer determines the amount of change that has been selected most frequently as the parameter to be used in resizing. The computer may also determine the average or median of the selected amounts of change as the parameter to be used in resizing.

[0091] The parameter for the amount of change is easily affected by noise. When the amount of change is determined using only a single pair of first and second preliminary images, noise may cause the determined amount of change to deviate from the optimal amount of change. According to the second modification, the amount of change is determined using multiple pairs. This allows the amount of change for resizing to be determined to a more appropriate value. By performing resizing using the determined amount of change, the first preliminary image and the second preliminary image can be aligned more accurately.

[0092] The amount of change in the horizontal direction of the image and the amount of change in the vertical direction of the image may be determined separately. In this case, in the first step S10b, the image is resized in one of the vertical direction and the horizontal direction. This determines the amount of change in one of the vertical direction and the horizontal direction. Thereafter, steps S13f to S13n are executed again. The image is resized in the other of the vertical direction and the horizontal direction, and the amount of change in the other of the vertical direction and the horizontal direction is determined.

[0093] (Third Modification) In a first variant, if the first or second processing includes rotation, the angle of rotation may be determined using a plurality of first preparatory images and a plurality of second preparatory images. In a third variant, the angle of rotation is determined using a plurality of first preparatory images and a plurality of second preparatory images.

[0094] Fig. 7 is a flowchart showing a part of an alignment method according to a third modified example of the embodiment. In the third modified example, step S10c shown in Fig. 7 is executed instead of step S10 shown in Fig. 2. The process in step S10c is generally similar to the process in step S10b.

[0095] First, similar to step S10b, the computer acquires a plurality of pairs (first and second partial images) (step S14a), and acquires a plurality of second preparation images corresponding to the plurality of pairs (step S14b). The computer selects a combination to be used for determining weights (step S14c), and determines first and second weights (step S14d).

[0096] The computer generates a plurality of first preparatory images from the plurality of pairs acquired in step S14a (step S14e). The computer selects a pair of the first preparatory image and the second preparatory image to be used for determining the angle of rotation (step S14f). The computer sets the angle to an initial value (step S14g).

[0097] The computer rotates one of the first and second preliminary images by the set angle (step S14h). Here, an example in which the second preliminary image is rotated will be described. The computer calculates the similarity between the first preliminary image and the rotated second preliminary image (step S14i).

[0098] The computer determines whether the entire range of angles has been searched up to that point (step S14j). If it is determined that the entire range has not been searched, the computer changes the angle (step S14k). After step S14k, step S14h is executed again. Steps S14h to S14k are repeated until the entire range of angles has been searched.

[0099] If it is determined in step S14j that the entire range has been searched, the computer refers to the multiple similarities obtained by repeating steps S14h to S14k, and selects the angle at which the maximum similarity is obtained (step S14l).

[0100] The computer determines whether all pairs of first and second preparatory images have been selected in the previous step S14f (step S14m). If there are any pairs that have not been selected, step S14f is executed again. If it is determined that all pairs have been selected, the computer determines the angle to be used in the rotation based on the angles selected in the previous multiple steps S14l (step S14n). For example, the computer determines the angle that has been selected most frequently as the parameter to be used in the rotation. The computer may also determine the average or median of the multiple selected angles as the parameter to be used in the rotation.

[0101] Angle parameters are susceptible to noise. If an angle is determined using only a single pair of first and second preliminary images, noise may cause the determined angle to deviate from the optimal angle. According to the third modification, the angle used in the rotation is determined using multiple pairs. This allows the angle of rotation to be determined to a more appropriate value. By performing the rotation using the determined angle, the first and second preliminary images can be aligned more accurately.

[0102] If the first or second process includes both resizing and rotation, steps S10b and S10c are executed in combination. For example, after step S10b shown in FIG. 6 is executed, steps S14f to S14n of step S10c are executed. This allows the resizing change amount and rotation angle to be determined using multiple pairs. If the first or second process includes smoothing, after the change amount and angle are determined, the size of the smoothing filter may be searched for using any pair of the first and second preliminary images.

[0103] (Fourth Modification) In each of the above-described embodiments, images are aligned based on the similarity between the images. The similarity is calculated using pixel values. That is, in the above-described methods, images are aligned at the pixel level. In a fourth modification of the embodiment, after the alignment at the pixel level, alignment at a level smaller than the pixel (sub-pixel level) is performed.

[0104] FIG. 8 is a flowchart showing a part of an alignment method according to a fourth modified example of the embodiment. Step S25 shown in Fig. 8 is executed after aligning the first processed image and the second processed image. When the process shown in Fig. 3 is executed, step S25 is executed after step S21i. When the process shown in Fig. 5 is executed, step S25 is executed after step S22k.

[0105] First, the computer enlarges the first processed image (step S25a) and then enlarges the second processed image (step S25b). The enlargement magnification of the second processed image is the same as that of the first processed image. The larger the enlargement magnification, the more accurate the alignment at the sub-pixel level becomes. For example, the enlargement magnification is preferably 2x or more, more preferably 5x or more, and most preferably 10x or more. Here, the enlarged first processed image is referred to as the "first enlarged image." The enlarged second processed image is referred to as the "second enlarged image."

[0106] The computer sets the position of the first enlarged image or the second enlarged image in one of the first enlarged image or the second enlarged image (step S25c), and performs template matching at the set position to calculate the similarity between the first enlarged image and the second enlarged image (step S25d).

[0107] The computer determines whether the entire range of one of the first enlarged image and the second enlarged image has been searched (step S25e). If it is determined that the entire range has not been searched, the computer changes the position of the other of the first enlarged image and the second enlarged image in one of the first enlarged image and the second enlarged image (step S25f). After step S25f, step S25d is executed again. As a result, the similarity is calculated again at the changed position.

[0108] If it is determined that the entire range has been searched, the computer references the multiple similarities obtained so far and extracts the maximum similarity. The computer references the position where the maximum similarity was obtained. The computer determines that position as the position where the first enlarged image and the second enlarged image best match (step S25g). The coordinates after alignment are then output.

[0109] Step S25 aligns the images at the sub-pixel level, further improving the alignment accuracy. For example, if an anomaly is found in the inspection image, more accurate coordinates of the anomaly in the design layout can be obtained.

[0110] Note that alignment at the pixel level may be omitted and alignment at the sub-pixel level may be performed. For example, in the flowchart shown in Fig. 3, steps S21e to S21i may be omitted and steps S25a to S25g may be performed instead. When the positional deviation between the first image and the second image is small, omitting alignment at the pixel level can shorten the time required for alignment.

[0111] FIG. 9 is a flowchart showing a part of the alignment method according to the second modified example of the embodiment. In the sub-pixel level alignment, the process shown in Fig. 9 may be executed instead of the process shown in Fig. 8. In step S26, first, the computer generates a similarity map (step S26a). The similarity map is generated using a plurality of similarities obtained by the loop of steps S21f to S21h or the loop of steps S22h to S22j.

[0112] FIG. 10 is a schematic diagram for explaining the processing shown in FIG. FIG. 10 is a schematic diagram showing an enlarged portion of the first processed image. In the example shown in FIG. 10, 25 pixels in the first processed image are shown. The numerical value for each pixel indicates the similarity when the position of the second processed image is set to that pixel. By repeating the calculation of the similarity, the pixel px 11 ~px 55 In the example shown, the similarity at each coordinate of pixel px is calculated. 33 The maximum similarity is obtained.

[0113] The computer uses the maximum similarity and the similarities of the surrounding pixels to create the similarity map shown in Figure 10. The similarity map is created by dividing the pixel px 11 ~px 55 and the similarity at each coordinate.

[0114] Next, the computer calculates the position where the similarity is maximized at the sub-pixel level using the multiple similarities included in the similarity map (step S26b). Gaussian fitting can be used to calculate the position. The distribution of similarity is generally a normal distribution. Therefore, by using Gaussian fitting, it is possible to calculate the coordinate where the similarity is maximized. As a result, the pixel px 33 The computer outputs coordinate c1 as the position where the first processed image and the second processed image most closely match.

[0115] Instead of Gaussian fitting, the computer may calculate the centroid position of the multiple similarities, and output the centroid position as the position where the first processed image and the second processed image best match.

[0116] (Example) An example of the alignment method according to the embodiment will be described. In the example, the structure is a semiconductor device. The first process includes a smoothing process. The second process includes resizing and rotation.

[0117] Fig. 11(a) is an example of a first partial image, Fig. 11(b) is an example of a second partial image, and Fig. 11(c) is an example of a first preliminary image. Fig. 11(a) is an image IMG1 showing the design layout of the substrate. Fig. 11(b) is an image IMG2 showing the design layout of the contact layer. The images in Fig. 11(a) and Fig. 11(b) show the design layout in an area of ​​approximately 183 μm × 183 μm.

[0118] The computer executes steps S12c to S12h shown in FIG. 4 to determine a weight for image IMG1 in FIG. 11(a) and a weight for image IMG2 in FIG. 11(b). The computer blends images IMG1 and IMG2 using these weights. As a result, a first preliminary image IMG3 in FIG. 11(c) is generated. In the illustrated example, the weight for image IMG1 is much greater than the weight for image IMG2. Therefore, image IMG3 in FIG. 11(c) is similar to image IMG1 in FIG. 11(a). For example, it can be seen that the shape of portion A shown in FIG. 11(a) has changed to the shape of portion C shown in FIG. 11(c) as a result of blending.

[0119] The computer similarly blends multiple pairs of partial images other than those shown in Figures 11(a) and 11(b), thereby generating multiple first preliminary images.

[0120] FIG. 12 is an example of the second preparation image. The image IMG4 in Fig. 12 is obtained by photographing the semiconductor device in the middle of manufacturing from the substrate side using infrared light. The second preparation image IMG4 in Fig. 12 is a photograph of an area of ​​approximately 183 μm × 183 μm.

[0121] The computer determines each parameter in the first and second processes using multiple pairs of first and second preliminary images. The order of determining each parameter for the resizing, rotation, and smoothing processes can be set appropriately. In this embodiment, first, the amount of change in resizing in the second process is determined. Next, the angle of rotation in the second process is determined. Finally, the filter size for the smoothing process in the first process is determined.

[0122] First, the computer performs a smoothing process on the second preliminary image. In this smoothing process, a smoothing filter is applied to the second preliminary image so as to remove high-order spatial frequencies specific to the optical image. In this embodiment, the size of the smoothing filter for the optical image is preset and is not searched.

[0123] Next, the computer resizes the second preliminary image. Figure 13 is a graph showing the relationship between the amount of change in resizing and the number of image pairs. As a result of performing step S10b shown in Figure 6 on the second preliminary image, the results shown in Figure 13 are obtained. In Figure 13, the horizontal axis represents the amount of increase or decrease in the number of pixels. The vertical axis represents the number of pairs for which the maximum similarity was obtained at each amount of change. The solid line represents the relationship between the amount of change in the number of pixels in the vertical direction and the number of pairs. The dashed line represents the relationship between the amount of change in the number of pixels in the horizontal direction and the number of pairs.

[0124] In the results shown in Figure 13, the number of pairs with the highest similarity was greatest for "0.999 times" in both the vertical and horizontal directions. Therefore, the computer determines the amount of resizing of the second preliminary image in the vertical direction to be "0.999 times." The computer also determines the amount of resizing of the second preliminary image in the horizontal direction to be "0.999 times."

[0125] Next, the computer rotates the resized second preliminary image. Figure 14 is a graph showing the relationship between the angle of rotation and the number of image pairs. As a result of performing steps S14f to S14n of step S10c shown in Figure 7 on the second preliminary image, the results shown in Figure 14 are obtained. In Figure 14, the horizontal axis represents the angle of rotation, and the vertical axis represents the number of pairs for which the maximum similarity was obtained at each angle.

[0126] 14, the number of pairs with the maximum similarity was greatest at "-0.04 degrees." Therefore, the computer determines the angle of rotation of the second preliminary image to be "-0.04 degrees."

[0127] Finally, the computer performs a smoothing process on the first preliminary image. Figure 15 is a graph showing the relationship between the size of the smoothing filter and the similarity. In Figure 15, the horizontal value represents the size of the Gaussian filter in the X direction of the image. The vertical value represents the size of the Gaussian filter in the Y direction of the image. Figure 15 shows the results of calculating the similarity for each combination of the filter size in the X direction and the filter size in the Y direction.

[0128] 15, the similarity between the smoothed first preliminary image and the resized and rotated second preliminary image was greatest when the filter size in the X direction was 435 pixels and the filter size in the Y direction was 389 pixels. Therefore, the computer determines the filter size in the X direction to be 435 pixels and the filter size in the Y direction to be 389 pixels.

[0129] Through the above processing, the filter size for the smoothing processing in the first processing is determined, and the amount of change in resizing and the angle of rotation in the second processing are determined.

[0130] Next, the computer executes step S20a shown in Fig. 5 using the determined parameters. Fig. 16(a) is an example of a first processed image IMG5 after the first processing. Fig. 16(b) is an example of a second processed image IMG6 after the second processing. The computer aligns the second processed image IMG6 shown in Fig. 16(b) with the first processed image IMG5 shown in Fig. 16(a).

[0131] The computer then executes the process shown in Fig. 8 or 9. This aligns the second processed image IMG6 with the first processed image IMG5 at the sub-pixel level.

[0132] FIG. 17 is an example of an image showing the inspection results. The inspection image IMG7 shown in FIG. 17 is obtained together with the image that served as the basis for the second processed image IMG6. FIG. 17 shows the inspection results for electrical resistance. In this inspection, a voltage is applied to the probe while scanning the structure in the in-plane direction. In areas where the electrical resistance is low, current flows and is displayed in white. In the example shown in FIG. 17, current flows in the upper left area. This area is determined to be abnormal.

[0133] The computer calculates the amount of movement required to align the second processed image with the first processed image. The computer resizes and rotates the inspection result image in the same manner as the second image, and aligns it with the first processed image. The computer then obtains the coordinates of the abnormality after alignment. If the coordinate system of the design layout image is different from the coordinate system of the inspection result image, the coordinate system of the inspection result image may be converted to the coordinate system of the design layout image. This outputs the location of the abnormality in the design layout. The abnormality can be easily identified based on the inspection results.

[0134] The computer may output the position where the photograph of the structure best fits in the image of the design layout after alignment. The computer may output the resizing change, rotation angle, or smoothing filter size determined by the alignment method.

[0135] FIG. 18 is a schematic diagram showing the configuration of a computer. The registration method according to the embodiment is executed by, for example, a computer 90 shown in Fig. 18. The computer 90 that executes the registration method is used as a registration device. The computer 90 includes a processing circuit (CPU or GPU) 91, a ROM 92, a RAM 93, a storage device 94, an input interface 95, an output interface 96, and a communication interface 97.

[0136] The ROM 92 stores a program that controls the operation of the computer 90. The ROM 92 stores a program necessary for causing the computer 90 to perform each of the above-described processes. The RAM 93 functions as a storage area in which the programs stored in the ROM 92 are expanded.

[0137] The CPU 91 includes a processing circuit. The CPU 91 uses a RAM 93 as a work memory and executes a program stored in at least one of a ROM 92 and a storage device 94. During program execution, the CPU 91 controls each component via a system bus 98 and executes various processes.

[0138] The storage device 94 stores data necessary for executing the program and data obtained by executing the program.

[0139] The input interface (I / F) 95 can connect the computer 90 to an input device 95a. The input I / F 95 is, for example, a serial bus interface such as USB. The CPU 91 can read various data from the input device 95a via the input I / F 95.

[0140] The output interface (I / F) 96 can connect the computer 90 and an output device 96a. The output I / F 96 is, for example, a video output interface such as a Digital Visual Interface (DVI) or a High-Definition Multimedia Interface (HDMI (registered trademark)). The CPU 91 can transmit data to the output device 96a via the output I / F 96 and cause the output device 96a to display an image.

[0141] The communication interface (I / F) 97 can connect the computer 90 to a server 97a external to the computer 90. The communication I / F 97 is, for example, a network card such as a LAN card. The CPU 91 can read various data from the server 97a via the communication I / F 97.

[0142] The storage device 94 includes one or more selected from a hard disk drive (HDD) and a solid state drive (SSD). The input device 95a includes one or more selected from a mouse, a keyboard, a microphone (voice input), and a touchpad. The output device 96a includes one or more selected from a monitor, a projector, a printer, and a speaker. A device having the functions of both the input device 95a and the output device 96a, such as a touch panel, may also be used.

[0143] The processing required for alignment may be executed by one computer 90 or by multiple computers 90.

[0144] The various data processing operations described above may be recorded as a computer-executable program on a magnetic disk (such as a flexible disk or hard disk), an optical disk (such as a CD-ROM, CD-R, CD-RW, DVD-ROM, DVD±R, or DVD±RW), a semiconductor memory, or other non-transitory computer-readable storage medium.

[0145] For example, data from a recording medium is read by a computer (or an embedded system). The recording medium may have any recording format (storage format). For example, the computer reads a program from the recording medium and causes a CPU to execute instructions based on the program. The computer may also acquire (or read) the program via a network.

[0146] According to the embodiments described above, an alignment method, an alignment device, a program, and a storage medium are provided that are capable of aligning an image of a design layout with a photograph of a structure with higher accuracy.

[0147] As used herein, "or" indicates that "at least one or more" of the items listed in the sentence may be employed.

[0148] Embodiments of the invention include the following features. (Feature 1) On the computer, acquiring a first preliminary image showing a design layout of a structure and a second preliminary image obtained by photographing the structure; determining a first parameter to be used in a first process and a second parameter to be used in a second process based on a similarity between the first preparatory image that has been subjected to the first process and the second preparatory image that has been subjected to the second process; performing the first processing on a first image showing a design layout of the structure using the first parameters to obtain a first processed image; performing the second processing using the second parameters on a second image obtained by photographing the structure, thereby obtaining a second processed image; aligning the first processed image with the second processed image based on a similarity between the first processed image and the second processed image; Alignment method. (Feature 2) at least one of the first processing and the second processing includes a smoothing processing; 2. The registration method according to Feature 1, wherein at least one of the first parameter and the second parameter includes a size of a smoothing filter. (Feature 3) 3. The alignment method of feature 1 or 2, wherein the first preliminary image is generated by blending a first partial image showing a design layout in a first layer of the structure and a second partial image showing a design layout in a second layer of the structure. (Feature 4) The alignment method described in Feature 3, wherein the computer determines a first weight for the first partial image and a second weight for the second partial image based on the similarity between the first preliminary image and the second preliminary image. (Feature 5) the first image is generated by blending a third partial image showing a design layout of the structure in the first layer and a fourth partial image showing a design layout of the structure in the second layer; The alignment method described in Feature 4, wherein in generating the first image, the weight of the third partial image is set to the first weight, and the weight of the fourth partial image is set to the second weight. (Feature 6) at least one of the first processing and the second processing includes resizing; 6. The registration method according to any one of features 1 to 5, wherein at least one of the first parameter and the second parameter includes a change amount of the resizing. (Feature 7) at least one of the first process and the second process includes rotation; 7. The alignment method according to any one of Features 1 to 6, wherein at least one of the first parameter and the second parameter includes an angle of the rotation. (Feature 8) at least one of the first processing and the second processing includes resizing; acquiring a plurality of pairs of the first partial image and the second partial image; blending the first partial image and the second partial image using the first weight and the second weight for each pair to generate a plurality of the first preliminary images; 5. The registration method according to Feature 4, further comprising determining the amount of change in resizing based on a degree of similarity between the plurality of first preliminary images and the plurality of second preliminary images. (Feature 9) at least one of the first process and the second process includes rotation; acquiring a plurality of pairs of the first partial image and the second partial image; blending the first partial image and the second partial image using the first weight and the second weight for each pair to generate a plurality of the first preliminary images; 5. The registration method of claim 4, further comprising determining the angle of rotation based on a degree of similarity between the plurality of first preliminary images and the plurality of second preliminary images. (Feature 10) After the first processed image and the second processed image are aligned, the computer sub-pixel alignment of the enlarged first processed image and the enlarged second processed image based on a similarity between the enlarged first processed image and the enlarged second processed image; or aligning the first processed image and the second processed image at a sub-pixel level using a similarity map based on the similarity between the first processed image and the second processed image; 10. The alignment method according to any one of features 1 to 9. (Feature 11) The computer, an inspection image showing an inspection result of the structure is acquired, the range shown in the inspection image is the same as the range shown in the second image; aligning the inspection image with the first processed image based on a result of aligning the first processed image with the second processed image; 11. The alignment method according to any one of Features 1 to 10. (Feature 12) Feature 12. The alignment method according to Feature 11, wherein, if the inspection image shows an abnormal part of the structure, the inspection image is aligned with the first processed image, and then the computer is caused to output coordinates of the abnormal part in the first image. (Feature 13) On the computer, performing a smoothing process on a first image showing a design layout of the structure to obtain a first processed image; performing a smoothing process on a second image obtained by photographing the structure, thereby obtaining a second processed image; aligning the first processed image with the second processed image based on a similarity between the first processed image and the second processed image; Alignment method. (Feature 14) 14. The alignment method according to any one of Features 1 to 13, wherein the structure is a semiconductor device. (Feature 15) A processing unit is provided, An alignment device that performs the alignment method according to any one of Features 1 to 13. (Feature 16) A program that causes a computer to execute the alignment method according to any one of features 1 to 13. (Feature 17) A storage medium storing the program according to feature 16.

[0149] Although several embodiments of the present invention have been described above, these embodiments are presented by way of example only and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, modifications, etc. can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as set forth in the claims. Furthermore, the above-described embodiments can be implemented in combination with each other. [Explanation of symbols]

[0150] IMG1: First partial image, IMG2: Second partial image, IMG3: First preparatory image, IMG4: Second preparatory image, IMG5: First processed image, IMG6: Second processed image, IMG7: Inspection image

Claims

1. On the computer, acquiring a first preliminary image showing a design layout of a structure and a second preliminary image obtained by photographing the structure; determining a first parameter to be used in the first processing and a second parameter to be used in the second processing based on a similarity between the first preparatory image that has been subjected to the first processing and the second preparatory image that has been subjected to the second processing; performing the first processing on a first image showing a design layout of the structure using the first parameters to obtain a first processed image; performing the second processing using the second parameters on a second image obtained by photographing the structure, thereby obtaining a second processed image; aligning the first processed image with the second processed image based on a similarity between the first processed image and the second processed image; Alignment method.

2. at least one of the first processing and the second processing includes a smoothing processing; The registration method according to claim 1 , wherein at least one of the first parameter and the second parameter includes a size of a smoothing filter.

3. 2. The alignment method of claim 1, wherein the first preliminary image is generated by blending a first partial image showing a design layout at a first layer of the structure and a second partial image showing a design layout at a second layer of the structure.

4. The registration method of claim 3 , further comprising causing the computer to determine a first weight for the first partial image and a second weight for the second partial image based on a similarity between the first preliminary image and the second preliminary image.

5. the first image is generated by blending a third partial image showing a design layout of the structure at the first layer and a fourth partial image showing a design layout of the structure at the second layer; The registration method according to claim 4 , wherein in generating the first image, a weight of the third partial image is set to the first weight, and a weight of the fourth partial image is set to the second weight.

6. at least one of the first processing and the second processing includes resizing; The registration method according to claim 1 , wherein at least one of the first parameter and the second parameter includes a change amount of the resizing.

7. at least one of the first process and the second process includes rotation; The method of claim 1 , wherein at least one of the first parameter and the second parameter includes an angle of the rotation.

8. at least one of the first processing and the second processing includes resizing; acquiring a plurality of pairs of the first partial image and the second partial image; generating a plurality of the first preliminary images by blending the first partial image and the second partial image for each pair using the first weight and the second weight; The registration method according to claim 4 , further comprising determining the amount of change in the resizing based on a degree of similarity between the plurality of first preliminary images and the plurality of second preliminary images.

9. at least one of the first process and the second process includes rotation; acquiring a plurality of pairs of the first partial image and the second partial image; generating a plurality of the first preliminary images by blending the first partial image and the second partial image for each pair using the first weight and the second weight; The method of claim 4 , further comprising determining the angle of rotation based on a degree of similarity between the first plurality of preliminary images and the second plurality of preliminary images.

10. After the first processed image and the second processed image are aligned, the computer Aligning the enlarged first processed image and the enlarged second processed image at a sub-pixel level based on a similarity between the enlarged first processed image and the enlarged second processed image; or aligning the first processed image and the second processed image at a sub-pixel level using a similarity map based on the similarity between the first processed image and the second processed image; The alignment method according to claim 1 .

11. The computer, acquiring an inspection image showing an inspection result of the structure, the range shown in the inspection image being the same as the range shown in the second image; aligning the inspection image with the first processed image based on a result of aligning the first processed image with the second processed image; The alignment method according to claim 1 .

12. 12. The alignment method according to claim 11, wherein, if an abnormality in the structure is captured in the inspection image, the inspection image is aligned with the first processed image, and then the computer is caused to output coordinates of the abnormality in the first image.

13. On the computer, performing a smoothing process on a first image showing a design layout of the structure to obtain a first processed image; performing a smoothing process on a second image obtained by photographing the structure, thereby obtaining a second processed image; aligning the first processed image with the second processed image based on a similarity between the first processed image and the second processed image; Alignment method.

14. The alignment method according to any one of claims 1 to 13, wherein the structure is a semiconductor device.

15. A processing unit is provided, An alignment device that performs the alignment method according to any one of claims 1 to 13.

16. A program that causes a computer to execute the alignment method according to any one of claims 1 to 13.

17. A storage medium storing the program according to claim 16.

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