Method, device and equipment for determining defects of mask, medium and product

Abstract

The invention discloses a mask defect determination method and device, equipment, a medium and a product, and the method comprises the steps: obtaining an image of a mask, the image comprising a plurality of image contours; obtaining a scattering bar pattern layer in the design layout of the mask; aligning the image with the scattering bar layer, and determining the overlapping degree of each image contour and a graph in the scattering bar layer; and determining the image contour of which the overlapping degree with the pattern in the scattering bar layer is smaller than the preset threshold value as the defect image contour. The accuracy of a mask defect detection result can be improved.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and in particular relates to a method, device, equipment, medium and product for determining mask defects. Background Art

[0002] The mask is an indispensable and important component in wafer production. The yield of the mask directly affects the yield of the wafer, so defect detection of the mask is particularly important.

[0003] Currently, in defect detection of masks, defect detection in opaque areas of the mask is often performed by determining the defect area through the superimposed image of the mask's reflection image and the transmission pattern. However, since some scattering strips in the mask are small in size or have special shapes, the signal of the scattering strips may be collected in the reflection pattern but not in the transmission pattern. Therefore, when determining the defect area based on the superimposed pattern, the scattering strips may be misjudged as the defect area, affecting the defect detection results of the mask and making the defect detection results less accurate. Summary of the Invention

[0004] The embodiments of the present application provide a method, apparatus, device, medium, and product for determining mask defects, which can improve the accuracy of mask defect detection results.

[0005] In a first aspect, an embodiment of the present application provides a method for determining a reticle defect, comprising:

[0006] acquiring an image of the reticle, the reticle including scattering strips, the image including a plurality of image profiles;

[0007] Obtain a scattering stripe layer in the design layout of the mask;

[0008] Align the image and scatter strips layers and determine the degree of overlap between each image outline and the pattern in the scatter strips layer;

[0009] An image contour whose overlap with the pattern in the scattering stripe layer is less than a preset threshold is determined as a defective image contour.

[0010] In a second aspect, an embodiment of the present application provides a device for determining a reticle defect, comprising:

[0011] An acquisition module, configured to acquire an image of the mask, the image including a plurality of image contours;

[0012] The acquisition module is also used to obtain the scattering stripe layer in the design layout of the mask;

[0013] an alignment module, for aligning the image and the scattering strip layer, and determining the degree of overlap between each image outline and the pattern in the scattering strip layer;

[0014] The determination module is used to determine an image contour whose overlap with the pattern in the scattering stripe layer is less than a preset threshold as a defective image contour.

[0015] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising:

[0016] a processor and a memory storing computer program instructions;

[0017] When the processor executes the computer program instructions, it is used to perform the mask defect determination method of the first aspect.

[0018] In a fourth aspect, an embodiment of the present application provides a computer storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the method for determining mask defects according to the first aspect described above is implemented.

[0019] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when processed by a processor, implements the method for determining mask defects according to the first aspect.

[0020] The methods, devices, equipment, media, and products for determining mask defects provided by the embodiments of the present application obtain an image of the mask and a layer of scattering strips, align the image with the scattering strip layer, determine the degree of overlap between each image contour and the pattern in the scattering strip layer through the aligned image and scattering strip layer, and determine an image contour whose degree of overlap with the pattern in the scattering strip layer is less than a threshold value as a defective image contour. This method can filter out image contours of scattering strips from multiple image contours, avoid misjudging scattering strips as particle defects, and improve the accuracy of mask defect detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1A A schematic diagram of a transmission image of a mask provided in some embodiments of the present application.

[0023] Figure 1B A schematic diagram of a reflection image of a mask provided in some embodiments of the present application.

[0024] Figure 1C A schematic diagram of an overlay image of a mask provided in some embodiments of the present application.

[0025] Figure 2A flowchart of a method for determining mask defects provided in some embodiments of the present application.

[0026] Figure 2A A schematic diagram of an exemplary superimposed image provided in an embodiment of the present application.

[0027] Figure 2B A schematic diagram of an exemplary mask image provided in an embodiment of the present application.

[0028] Figure 3 A flowchart of a method for determining mask defects provided in some embodiments of the present application.

[0029] Figure 3A A schematic diagram of an exemplary scattering stripe layer provided in an embodiment of the present application.

[0030] Figure 3B A schematic diagram of an exemplary scattering stripe layer area provided in an embodiment of the present application.

[0031] Figure 3C A schematic diagram of an exemplary aligned mask image and a scattering stripe layer area provided in an embodiment of the present application.

[0032] Figure 4 A schematic diagram of a mask defect determination device provided in some embodiments of the present application.

[0033] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0035] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0036] Before describing the technical solutions provided by the embodiments of the present application, in order to facilitate understanding of the embodiments of the present application, the present application first specifically describes the problems existing in the related art:

[0037] During wafer fabrication, multiple scattering strips are often incorporated into the mask to compensate for optical aberrations and diffraction effects during photolithography and improve image resolution. These strips are created by etching the designed pattern within the opaque areas of the mask. Because masks play a crucial role in wafer manufacturing, defect detection is particularly important.

[0038] At present, the defects of the mask are mainly divided into two types, one is the defect in the light-transmitting area, and the other is the defect in the opaque area. When detecting defects in the opaque area, it is often done by Figure 1A The transmission image of the mask shown and Figure 1B The grayscale values ​​of the pixels of the reflected image of the mask shown are superimposed to obtain the following Figure 1C As shown in the grayscale image, in the transmission image 1A, the bright area 10 corresponds to the light-transmitting area of ​​the mask, and the dark area 11 corresponds to the opaque area of ​​the mask. Figure 1A The grayscale value of the pixel point of the bright area 10 corresponding to the light-transmitting area of ​​the mask is higher, while the grayscale value of the pixel point of the dark area 11 corresponding to the opaque area is lower. On the contrary, Figure 1B As shown, in the reflected image 1B, the dark area 12 corresponds to the translucent area of ​​the mask, and the bright area 13 corresponds to the opaque area of ​​the mask. The grayscale value of the pixel point in the dark area 12 corresponding to the translucent area is lower, while the grayscale value of the pixel point in the bright area 13 corresponding to the opaque area is higher.

[0039] Due to the different imaging principles of transmission images and reflection images, particle defects in opaque areas cannot be observed in transmission images, but they can be seen in Figure 1BThe defect image 101 can be directly observed on the reflected image, but the observation of the defect image in the reflected image is not obvious, so the defect image is observed by superimposing the image as shown in FIG. Figure 1C As shown in FIG. 1 , the defect image 101 of the opaque area can be clearly observed. However, due to the special shape or size of some scattering strips, the image of the scattering strips may be observed in the reflected image, for example, Figure 1C The scattering strip image 102 is included in the superimposed image, so the images of multiple opaque areas may include both the defect image 101 and the scattering strip image 102, which may cause the scattering strip to be misjudged as a defect, affecting the accuracy of defect detection of the mask.

[0040] Based on this, embodiments of the present application provide a method, apparatus, device, medium, and product for determining a mask defect, which can solve the above-mentioned problem.

[0041] In some embodiments, as Figure 2 As shown, an embodiment of the present application provides a method for determining a mask defect, the method comprising the following steps S210-S250:

[0042] S210: Acquire an image of the mask, where the image includes a plurality of image contours.

[0043] Here, an image of the mask may be acquired, the image of the mask being a surface image of the mask collected by an optical detection device, and the multiple image profiles may include a defect image profile to be determined and a scattering stripe image profile to be determined.

[0044] In some examples, such as Figure 2A As shown, Figure 2A The schematic diagram of an exemplary superimposed image is generated by superimposing the grayscale values ​​of the pixels of the reflection image and the transmission image of the mask. The superimposed image includes multiple images 201. The contour of the superimposed image can be extracted, for example, Figure 2A The contours of the multiple images 201 in the superimposed image shown are extracted to obtain the following Figure 2B The image of the mask shown includes a plurality of image contours 202. Here, the transmission image is generated based on the transmitted light passing through the mask, and the reflection image is generated based on the reflected light reflected from the surface of the mask.

[0045] In some examples, when the transmission image and the reflection image are superimposed as described above, the transmission image and the reflection image can first be aligned one by one based on an image registration algorithm to align at least some feature points in the transmission image and the reflection image, and the grayscale values ​​of the corresponding pixel points in the aligned transmission image and the reflection image can be superimposed to obtain a superimposed image.

[0046] S220: Obtain a scattering stripe layer in the design layout of the mask.

[0047] A scattering stripe layer may be obtained. Here, the scattering stripe layer may be obtained from a design layout of a mask based on a scattering stripe layer identifier. The scattering stripe layer includes a plurality of patterns.

[0048] S230: Align the image and the scattering strip layer, and determine the degree of overlap between each image outline and the graphics in the scattering strip layer.

[0049] At least two feature points of the image and the design layout can be aligned one by one in the same coordinate system. The feature points can be center points, vertices, etc., to obtain the aligned image and scattering stripe layer.

[0050] Based on the aligned image and scatter strip design layout, the overlap between multiple image outlines and the graphics in the scatter strip layer can be detected. For any image outline and corresponding graphic, the overlap can be determined based on the ratio of their intersection area to their union area. Alternatively, the overlap can be determined based on the ratio of the minimum circumscribed rectangle of their intersection area to their union area.

[0051] It is conceivable that the above-mentioned method of calculating overlap is only exemplary, and the overlap degree may also be determined based on other calculation methods.

[0052] S240: Determine an image contour whose overlap with the pattern in the scattering stripe layer is less than a preset threshold as a defective image contour.

[0053] Here, the calculated multiple overlaps can be compared with preset thresholds to determine that the image contour with an overlap less than the preset threshold is a defect image contour. It is understood that the image contour with an overlap greater than or equal to the preset threshold is a scattering stripe image contour.

[0054] It can be imagined that the above defective image contours include two categories: the first category is image contours that do not overlap with the graphics, and the second category is image contours that at least partially overlap with the graphics but the degree of overlap is less than a preset threshold.

[0055] In some embodiments, in order to improve the accuracy of determining the defect image contour, the preset threshold may be determined based on the degree of overlap between the historical mask image contour and the corresponding pattern in the scattering stripe layer.

[0056] The embodiment of the present application obtains an image of a mask including multiple image contours and a scattering strip layer, aligns the image with the scattering strip layer, determines the degree of overlap between each image contour and the pattern in the scattering strip layer, and determines the image contour whose overlap with the pattern is less than a preset threshold as a defective image contour. Determining the defective image contour by the degree of overlap can not only determine the defective image contour, but also filter out the image contour of the scattering strips from the multiple image contours, thereby avoiding misjudging the scattering strips as particle defects, and can improve the accuracy of defect detection of the mask.

[0057] In some embodiments, as Figure 3 As shown, obtaining the image of the mask may include the following steps S310-S320:

[0058] S310: Acquire a superimposed image of the mask, where the superimposed image is generated by superimposing the grayscale values ​​of the pixels of the transmission image and the grayscale values ​​of the pixels of the reflection image of the mask.

[0059] A transmission image and a reflection image of the mask can be obtained, and after registering multiple feature points in the transmission image and the reflection image, the grayscale values ​​of the registered transmission image and the reflection image are superimposed to obtain a superimposed image.

[0060] S320: Deleting multiple graphics with areas larger than a threshold value from the superimposed image to obtain a mask image.

[0061] Here, the mask image is obtained by deleting a plurality of patterns with an area larger than a preset area in the first image. The value of the preset area is selected according to a rule that patterns with an area larger than a threshold are definitely scattering stripes.

[0062] The area of ​​each graphic can be determined based on the number of pixels and the area of ​​the pixels in the superimposed image. After deleting multiple partial graphics with an area greater than a threshold in the superimposed image, the outline of the superimposed image after deleting the partial graphics can be extracted to obtain an image of the mask.

[0063] The embodiment of the present application obtains an overlay image, deletes multiple graphics with an area greater than a threshold in the overlay image, and obtains an image of the mask. This can filter out graphics with larger sizes that do not meet the size of defects, which is beneficial for reducing the amount of calculation required for subsequently determining the overlap between the image contour and the graphics in the scattering strip layer, and can also improve the accuracy of the determined defects.

[0064] In some embodiments, aligning the image and the scattering stripe layer and determining the degree of overlap between each image outline and the pattern in the scattering stripe layer includes:

[0065] At least two feature points of the image are aligned with at least two feature points in the scattering strip layer to obtain an aligned image and the scattering strip layer; based on the aligned image and the scattering strip layer, the overlap degree of each image contour and the pattern in the scattering strip layer is determined.

[0066] The image can be aligned with at least two feature points in the scattering strip layer. Here, the FLANN matching algorithm can be used to find multiple matching feature point pairs in the image and the scattering strip layer, and the at least two matching feature point pairs are aligned to obtain the aligned image and the scattering strip layer.

[0067] Then, based on the aligned image and the scattering strip layer, the overlap between each image contour and the graphics in the scattering strip layer is determined. For example, the overlap can be determined based on the value of the image contour and the coordinate value of the graphics in the scattering strip layer.

[0068] The embodiment of the present application aligns the image and the scattering strip layer based on at least two feature points, and determines the overlap between the image contour and the graphics in the scattering strip layer based on the aligned image and scattering strip layer, thereby improving the accuracy of the overlap and further improving the accuracy of determining the defect image contour.

[0069] It can be imagined that in order to improve the accuracy of determining the defect image, the above-mentioned mask image may be a local image of the mask, so it is necessary to determine the area matching the mask image in the scattering stripe layer.

[0070] In some embodiments, the image carries coordinate values ​​of the mask, and aligning the image and at least two feature points in the scattering stripe layer to obtain the aligned image and scattering stripe layer includes:

[0071] Based on the coordinate values ​​of the mask, determining coordinate values ​​corresponding to the coordinate values ​​of the mask in the scattering strip layer; based on the coordinate values ​​corresponding to the coordinate values ​​of the mask in the scattering strip layer, cropping the scattering strip layer to obtain a scattering strip layer area that matches the position of the mask; aligning at least two feature points of the image and the scattering strip layer area to obtain an aligned image and the scattering strip layer area;

[0072] Based on the aligned images and the scatter strip layer, the degree of overlap between each image outline and the pattern in the scatter strip layer is determined, including:

[0073] Based on the aligned images and the scattering stripe layer area, a degree of overlap between each image contour and a pattern in the scattering stripe layer area is determined.

[0074] The above image can carry the coordinate values ​​of the mask. It can be imagined that the coordinate values ​​of the mask have a preset correspondence with the coordinate values ​​in the scattering strip layer. The coordinate values ​​corresponding to the coordinate values ​​of the mask can be determined in the scattering strip layer based on the coordinate values ​​of the mask. Then, based on the coordinate values ​​in the scattering strip layer corresponding to the coordinate values ​​of the mask, the scattering strip layer can be cropped to obtain a scattering strip layer area that matches the position of the mask.

[0075] In some examples, the coordinate values ​​of each boundary point of the mask are obtained by exporting the image of the mask to obtain an integrated circuit design file format (GDS) file. Similarly, the coordinate values ​​of each boundary point of the mask are obtained by exporting the image of the mask to obtain an integrated circuit design file format (GDS). Figure 3A The scatter strip layer shown is exported to obtain a GDS file, such as Figure 3A As shown, the scattering stripe layer includes multiple images 301, and the coordinate values ​​corresponding to the coordinate values ​​of the mask can be determined based on the GDS file of the scattering stripe layer. Figure 3A The scattered stripe layer shown in the figure is obtained as Figure 3B In some examples, the image and at least two feature points of the scattering stripe layer area can be aligned, and based on the aligned image and scattering stripe layer area, the overlap degree of each image contour and the pattern in the scattering stripe layer area can be determined. Figure 2B The image of the mask shown is similar to Figure 3B Align the scattered stripe layer area shown in the figure to obtain Figure 3C The mask image and the scattering stripe layer area after alignment are shown, and the overlap degree of each image outline and the pattern in the scattering stripe layer area is determined based on the mask image and the scattering stripe layer area after alignment. Figure 3C As shown, based on multiple overlap degrees, the contour image 302 can be determined to be a defect contour image.

[0076] In an embodiment of the present application, corresponding coordinate values ​​are determined in a scattering strip layer based on the coordinate values ​​of a mask, the scattering strip layer is cropped based on the coordinate values ​​in the scattering strip layer, and a scattering strip layer area corresponding to the image of the mask is determined. This can avoid the problem of a computing system crashing due to excessive memory usage by the scattering strip layer file. Subsequently, alignment is performed based on the image and the scattering strip layer area, and a degree of overlap is determined based on the aligned image and the scattering strip layer area. By performing alignment after determining the scattering strip layer area corresponding to the image in the scattering strip layer, the difficulty of alignment can be reduced and the efficiency of alignment can be improved.

[0077] In some embodiments, the image outline carries coordinate values ​​of the image outline, and the scattering stripe layer carries coordinate values ​​of the pattern;

[0078] Determines how much each image outline overlaps the graphics in the scatter strips layer, including:

[0079] The degree of overlap is determined based on the coordinate values ​​of each image contour and the coordinate values ​​of the graphics in the scatter strip layer.

[0080] Here, the coordinate values ​​of each image contour and the coordinate values ​​of the graphic can be obtained based on the GDS file of the image and the GDS file of the scattering strip layer. Based on the coordinate values ​​of each image contour and the coordinate values ​​of the graphic, the ratio of the intersection area and the union area of ​​any image contour and the graphic can be determined to obtain the overlap degree.

[0081] The embodiment of the present application determines the degree of overlap based on the coordinate values ​​of each image contour and the coordinate values ​​of the graphics in the scattering strip layer, thereby improving the accuracy of the determined degree of overlap and further improving the accuracy of the determined defect image contour.

[0082] In some embodiments, determining the degree of overlap based on the coordinate values ​​of each image contour and the coordinate values ​​of the patterns in the scatter stripe layer includes:

[0083] The pixel coordinate value of each image contour is determined in the binarized image of each image contour, and the pixel coordinate value of the graphic is determined in the binarized image based on the scattered stripe layer; and the overlap degree is determined based on the pixel coordinate value of each image contour and the pixel coordinate value of the graphic.

[0084] Here, the image and design layout can be converted into binary images. The pixel coordinate values ​​of the image outline can be determined based on the binary image of the image outline, and the pixel coordinate values ​​of the pattern can be determined based on the binary image of the scatter stripe layer. Here, the pixel coordinate values ​​are the specific row and column coordinate values ​​of each pixel point in the binary image. The degree of overlap can be determined based on the pixel coordinate values ​​of each image outline and the pixel coordinate values ​​of the pattern.

[0085] In some examples, the ratio of the intersection area and the union area may be determined based on the pixel coordinate values ​​of the image outline, the pixel coordinate values ​​of the graphic, and the pixel area.

[0086] The embodiment of the present application determines the degree of overlap based on the pixel coordinate values ​​of the image contour and the pixel coordinate values ​​of the graphics in the scattering stripe layer, thereby improving the accuracy of the determined degree of overlap.

[0087] In some embodiments, the degree of overlap includes an intersection-over-union (IoU) ratio, which is the ratio of the intersection area of ​​the image outline and the pattern to the union area. By determining the IoU ratio, the degree of overlap between the image outline and the pattern in the scattering stripe layer can be intuitively reflected, thereby enabling the identification of defective image outlines among multiple image outlines, thereby improving the accuracy of reticle defect determination.

[0088] In some embodiments, after determining that an image contour having an overlap with the design layout of the scattering strips less than a preset threshold is a defective image contour, the method further includes:

[0089] A prompt message carrying the identification of the defective image contour is sent to the user device, where the prompt message is used to prompt the user to modify the process parameters for mask manufacturing based on the identification of the defective image contour.

[0090] Here, the image outline of the above-mentioned defect can be marked on the display interface of the user device, and a prompt message carrying the identification of the image outline of the defect can be sent to the user device to indicate the presence of defects in the mask. The user can be prompted to modify the process parameters of the mask manufacturing based on the identification of the image outline of the defect to improve the yield of the mask.

[0091] The embodiment of the present application can promptly remind the user of the defects included in the mask by sending prompt information with the identification of the image contour carrying the defect to the user device, so that the user can modify the process parameters based on the above prompt information, which is conducive to improving the yield of the mask.

[0092] Based on the same inventive concept, an embodiment of the present application also provides a device for determining mask defects.

[0093] In some embodiments, as Figure 4 As shown, an embodiment of the present application provides a device for determining mask defects, comprising:

[0094] An acquisition module 401 is configured to acquire an image of a mask, wherein the image includes a plurality of image contours;

[0095] The acquisition module 401 is further used to acquire a scattering stripe layer in the design layout of the mask;

[0096] an alignment module 402 for aligning the image and the scattering strip layer, and determining the degree of overlap between each image outline and the pattern in the scattering strip layer;

[0097] The determination module 403 is configured to determine an image contour whose overlap with the pattern in the scattering stripe layer is less than a preset threshold as a defective image contour.

[0098] In an embodiment of the present application, an acquisition module is used to acquire an image of a mask and a scattering strip layer, an alignment module is used to align the image with the scattering strip layer, and a degree of overlap between each image contour and a pattern in the scattering strip layer is determined. An image contour having an overlap with the pattern pattern less than a preset threshold is determined by a determination module as a defective image contour. This allows the image contour of the scattering strips to be screened out from multiple image contours, thereby avoiding misjudging the scattering strips as particle defects and improving the accuracy of defect detection on the mask.

[0099] In some embodiments, the acquisition module may be specifically configured to:

[0100] Acquire a superimposed image of the mask, where the superimposed image is generated based on the grayscale values ​​of the pixels of the transmission image and the grayscale values ​​of the pixels of the reflection image of the mask;

[0101] A plurality of patterns with an area greater than a preset area threshold are deleted from the superimposed image to obtain an image of the mask.

[0102] In some embodiments, the alignment module may be specifically configured to:

[0103] Aligning at least two feature points in the image and the scattering stripe layer to obtain an aligned image and scattering stripe layer;

[0104] Based on the aligned images and the scatter strips layer, the degree of overlap of each image outline with the pattern in the scatter strips layer is determined.

[0105] In some embodiments, the image carries the coordinate values ​​of the mask, and the alignment module can be used to:

[0106] Based on the coordinate values ​​of the mask, determining coordinate values ​​corresponding to the coordinate values ​​of the mask in the scattering stripe layer;

[0107] Based on the coordinate values ​​in the scattering strip layer corresponding to the coordinate values ​​of the mask, the scattering strip layer is clipped to obtain a scattering strip layer area that matches the position of the mask;

[0108] Aligning at least two feature points of the image and the scattering stripe layer area to obtain an aligned image and the scattering stripe layer area;

[0109] Determine the module, which can be used for:

[0110] Based on the aligned images and the scattering stripe layer area, a degree of overlap between each image contour and a pattern in the scattering stripe layer area is determined.

[0111] In some embodiments, the image outline carries coordinate values ​​of the image outline, and the scattering stripe layer carries coordinate values ​​of the pattern;

[0112] Determine the module, which can be used for:

[0113] The degree of overlap is determined based on the coordinate values ​​of each image contour and the coordinate values ​​of the graphics in the scatter strip layer.

[0114] In some embodiments, the determination module may be specifically configured to:

[0115] Determining pixel coordinate values ​​of each image contour in the binarized image of each image contour, and determining pixel coordinate values ​​of the pattern in the binarized image based on the scattered stripe layer;

[0116] The degree of overlap is determined based on the pixel coordinate values ​​of each image contour and the pixel coordinate values ​​of the pattern in the scatter bar.

[0117] In some embodiments, the device further comprises a prompt module for:

[0118] A prompt message carrying the identification of the defective image contour is sent to the user device, where the prompt message is used to prompt the user to modify the process parameters for mask manufacturing based on the identification of the defective image contour.

[0119] The apparatus of the above embodiment is used to implement the corresponding mask defect determination method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0120] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the application.

[0121] The electronic device 500 may include a processor 501 and a memory 502 storing computer program instructions.

[0122] Specifically, the processor 501 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0123] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 502 may include removable or non-removable (or fixed) media. Where appropriate, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0124] In certain embodiments, memory 502 includes read-only memory (ROM). The ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM), or flash memory, or a combination of two or more thereof, where appropriate.

[0125] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to the first aspect of the present application.

[0126] The processor 501 reads and executes computer program instructions stored in the memory 502 to implement any one of the methods for determining mask defects in the above embodiments.

[0127] In one example, the electronic device may further include a communication interface 503 and a bus 504. Figure 5 The processor 501, the memory 502, and the communication interface 503 are connected via a bus 504 and communicate with each other.

[0128] The communication interface 503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0129] Bus 504 includes hardware, software or both, and the parts of online data flow metering equipment are coupled to each other. For example, but not limitation, bus can include accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 504 can include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0130] The electronic device of the above embodiment is used to implement the corresponding mask defect determination method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0131] In addition, in conjunction with the methods for determining mask defects in the above embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the methods for determining mask defects in the above embodiments is implemented.

[0132] In addition, in combination with the mask defect determination method in the above embodiments, the present application can provide a computer program product to implement the above embodiments. When the computer program product instructions are executed by a processor of an electronic device, any of the mask defect determination methods in the above embodiments is implemented.

[0133] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. Within the scope of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0134] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0135] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or devices based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0136] The present invention has been described above with reference to the flowchart and / or block diagram of the method, device (device) and computer program product according to the embodiments of the present application.It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be realized by computer program instructions.These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed via the processor of the computer or other programmable data processing device enable the realization of the function / action specified in one or more boxes of the flowchart and / or block diagram.Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit.It is also understood that each box in the block diagram and / or the flowchart and the combination of the boxes in the block diagram and / or the flowchart can also be realized by the dedicated hardware that performs the specified function or action, or can be realized by the combination of dedicated hardware and computer instructions.

[0137] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the devices, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A method for determining a mask defect, characterized in that: include: acquiring an image of the reticle, the image comprising a plurality of image contours; Obtaining a scattering stripe layer in the design layout of the mask; Aligning the image with the scattering stripe layer, and determining the degree of overlap between each image outline and the pattern in the scattering stripe layer; An image contour whose overlap with the pattern in the scattering stripe layer is less than a preset threshold is determined as a defective image contour.

2. The method for determining a mask defect according to claim 1, wherein: The step of obtaining an image of the mask includes: Acquiring a superimposed image of the mask, where the superimposed image is generated based on the grayscale values ​​of the pixels of the transmission image and the grayscale values ​​of the pixels of the reflection image of the mask; A plurality of graphics having an area greater than a preset area threshold are deleted from the superimposed image to obtain an image of the mask.

3. The method for determining a mask defect according to claim 1, wherein: The step of aligning the image with the scattering stripe layer and determining the degree of overlap between each image outline and the graphics in the scattering stripe layer comprises: Aligning at least two feature points in the image and the scattering stripe layer to obtain the aligned image and scattering stripe layer; Based on the aligned image and the scattering stripe layer, the degree of overlap between each image outline and the pattern in the scattering stripe layer is determined.

4. The method for determining a mask defect according to claim 3, wherein: The image carries coordinate values ​​of the mask, and aligning the image and at least two feature points in the scattering stripe layer to obtain the aligned image and scattering stripe layer includes: determining, based on the coordinate values ​​of the mask, coordinate values ​​corresponding to the coordinate values ​​of the mask in the scattering stripe layer; Based on the coordinate values ​​of the scattering stripe layer corresponding to the coordinate values ​​of the mask, the scattering stripe layer is clipped to obtain a scattering stripe layer region that matches the position of the mask; Aligning at least two feature points of the image and the scattering stripe layer area to obtain the aligned image and scattering stripe layer area; Determining the degree of overlap between each image outline and a pattern in the scattering stripe layer based on the aligned image and the scattering stripe layer includes: Based on the aligned image and the scattering stripe layer area, the degree of overlap between each image outline and the pattern in the scattering stripe layer area is determined.

5. The method for determining a mask defect according to claim 1, wherein: The image outline carries the coordinate value of the image outline, and the scattering stripe layer carries the coordinate value of the graphic; Determining the degree of overlap between each image contour and the graphics in the scattering stripe layer includes: The degree of overlap is determined based on the coordinate values ​​of each image contour and the coordinate values ​​of the patterns in the scattering stripe layer.

6. The method for determining a mask defect according to claim 5, wherein: The determining the degree of overlap based on the coordinate values ​​of each image contour and the coordinate values ​​of the graphics in the scattering stripe layer includes: Determining pixel coordinate values ​​of each image contour in the binarized image of each image contour, and determining pixel coordinate values ​​of the pattern based on the binarized image of the scattering stripe layer; The degree of overlap is determined based on the pixel coordinate values ​​of each of the image contours and the pixel coordinate values ​​of the patterns in the scattering strips.

7. The method for determining a mask defect according to claim 1, wherein: After determining the image contour having a degree of overlap with the pattern in the scattering stripe layer less than a preset threshold as a defective image contour, the method further includes: Prompt information carrying the identification of the defective image contour is sent to the user device, where the prompt information is used to prompt the user to modify the process parameters for mask manufacturing based on the identification of the defective image contour.

8. An electronic device, characterized in that: The device includes: a processor, and a memory storing computer program instructions; The processor reads and executes the computer program instructions to implement the method for determining a mask defect according to any one of claims 1 to 7.

9. A readable storage medium, characterized in that The readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining a mask defect according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is processed by a processor, the method for determining a mask defect according to any one of claims 1 to 7 is implemented.

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