Methods, equipment, and storage media for wafer defect data alignment under dual inspection channels

Abstract

This invention discloses a method, device, and storage medium for aligning wafer defect data under dual detection channels. The method includes: acquiring defect masks from wafer images under two detection channels and taking their union to obtain a composite mask; performing region connectivity analysis on the composite mask to obtain connected components and connected component parameter information; based on the connected component parameter information, extracting corresponding defect regions from the defect masks under the two detection channels; and classifying defects within the same connected component on the corresponding composite mask into the same defect group. This invention can align defects identified from wafer images acquired from two different detection channels, thus more accurately classifying defects on the wafer surface.

Description

Technical Field

[0001] This application relates to the field of wafer inspection technology, and in particular to a method, device and storage medium for aligning wafer defect data under dual inspection channels. Background Technology

[0002] Research on third-generation semiconductor materials began in the 1990s. With the increasing demands for high performance, high efficiency, and high reliability in electronic devices, materials such as gallium nitride (GaN) and silicon carbide (SiC) have gradually become the focus of research. These materials, due to their superior electrical and thermal properties, are particularly suitable for applications in high-power, high-frequency, and high-temperature environments, such as electric vehicles, renewable energy systems, and 5G communications. In the manufacturing process of third-generation semiconductors, advancements in crystal growth technology have continuously improved the quality of GaN and SiC, but have also introduced various lattice defects, such as dislocations, vacancies, and impurities. These defects significantly affect the performance and reliability of devices; therefore, research on defect detection technology has become particularly important. For defect detection in third-generation semiconductors, the following methods are mainly used: 1. Dark-field detection channel: using the scattering principle to detect defects such as particles; 2. Bright-field detection channel: detecting defects on the wafer surface; 3. Photoluminescence detection channel: used to identify lattice defects. Since different defects emit different wavelengths, photoluminescence detection can be further divided into near-ultraviolet photoluminescence (NUVPL) detection and visible light photoluminescence (VISPL) detection.

[0003] When classifying defects, it is necessary to observe the imaging characteristics of defects on the wafer surface under different detection channels and classify them in combination with the imaging features under different detection channels. However, for detection channels constructed based on different physical mechanisms and hardware imaging systems, due to unavoidable differences in hardware geometry configuration (such as camera pose and optical path) and imaging physics principles (such as response mechanism to defects and depth sensitivity), the spatial position of the same wafer defect in images from different detection channels exhibits complex and difficult-to-model deviations (such as translation, rotation, scaling, and nonlinear distortion) and differences in feature representation. This deviation makes the process of automatically, robustly, and with high accuracy establishing cross-channel defect correspondence extremely difficult, becoming a major bottleneck hindering the achievement of high-precision and high-reliability defect classification using detection data from different detection channels. Summary of the Invention

[0004] In view of this, this application provides a method, device and storage medium for aligning wafer defect data under dual detection channels, so as to solve the problem that wafer defect data is difficult to accurately correspond under multiple detection channels.

[0005] To address the aforementioned technical problems, this application provides a method for aligning wafer defect data based on dual detection channels. This method includes: acquiring defect masks from wafer images under two detection channels and taking their union to obtain a composite mask; performing regional connectivity analysis on the composite mask to obtain connected components and their parameter information; extracting corresponding defect regions from the defect masks under the two detection channels based on the connected component parameter information; and classifying defects within the defect regions that correspond to the same connected component on the composite mask into the same defect group.

[0006] As a further improvement of this application, a region connectivity analysis is performed on the composite mask to obtain connected components and connected component parameter information, including: performing binarization processing on the composite mask to obtain a binarized image; traversing each pixel of the binarized image line by line, considering the region formed by adjacent pixels with the same pixel value as a connected component, and recording the position, shape and size of the connected component.

[0007] As a further improvement of this application, the corresponding defect regions are extracted from the defect masks under the two detection channels based on the connected component parameter information, including: defining the position and size of the region of interest corresponding to each connected component based on the connected component parameter information; and extracting the corresponding region from each defect mask according to the position and size of the region of interest, thereby obtaining the defect region corresponding to each connected component on the defect mask under the two detection channels.

[0008] As a further improvement of this application, defects within the same connected region on the composite mask that have defects are classified into the same defect group, including: pairing defect regions that correspond to the same connected region but belong to different defect masks; confirming the channel category of the detection channel corresponding to the defect mask to which the two paired defect regions belong, the channel category including a primary category and a secondary category; merging or splitting the defects corresponding to the two paired defect regions according to the channel category and then performing an alignment operation, and then classifying them into the same defect group.

[0009] As a further improvement of this application, after merging or splitting the defects corresponding to the two paired defect regions according to the channel category, an alignment operation is performed, and then they are classified into the same defect group. This includes: when the defect masks to which the two paired defect regions belong both to the main category or both to the secondary category, the defects corresponding to the two defect regions are merged respectively, and then the merged defects of the two defect regions are aligned and classified into the same defect group; when the defect masks to which the two paired defect regions belong to the main category and the secondary category respectively, the defects in the defect regions of the corresponding secondary category are merged or split according to the number and category of defects in the defect regions of the corresponding main category, and then aligned with the defects in the defect regions of the corresponding main category and classified into the same defect group.

[0010] As a further improvement of this application, when all defects within a defect region are merged into one defect, the defect category is the highest priority category among all defects within the defect region; when all defects within a defect region are split according to defects in another defect region, the category of the split defect is the category of the defect within the defect region.

[0011] As a further improvement of this application, defects within defect regions that exist and correspond to the same connected domain on the synthetic mask are classified into the same defect group. This includes: pairing defect regions that correspond to the same connected domain but belong to different defect masks; identifying the defects included in each of the paired defect regions and the corresponding categories of the defects; identifying the target defect region corresponding to the defect with the highest priority; and, based on the number and category of defects in the target defect region, merging or splitting the defects in another defect region, and then aligning them with the defects in the target defect region and classifying them into the same defect group.

[0012] As a further improvement of this application, based on the number and category of defects in the target defect area, defects in another defect area are merged or split, and then aligned with the defects in the target defect area and classified into the same defect group. This includes: when there is a single defect in the target defect area and multiple defects in the other defect area, the multiple defects in the other defect area are merged, and the category of the merged defect is recorded as the highest priority category among the multiple defects in the other defect area. Then, the merged defect is aligned with the single defect in the target defect area and classified into the same defect group; when there are multiple defects in the target defect area and a single defect in the other defect area, the single defect in the other defect area is split according to the multiple defects in the target defect area, and the category of the split defect is recorded as the category of the single defect in the other defect area. Then, the split defect is aligned with the multiple defects in the target defect area one by one and classified into the same defect group.

[0013] To address the aforementioned technical problems, another technical solution adopted in this application is: providing a wafer defect data alignment device based on dual detection channels, comprising: a mask generation module, used to acquire defect masks of wafer images under two detection channels respectively and take the union to obtain a composite mask; a connected component analysis module, used to perform regional connectivity analysis on the composite mask to obtain connected components and connected component parameter information; a region truncation module, used to truncate corresponding defect regions in the defect masks under the two detection channels based on the connected component parameter information; and a defect matching module, used to classify defects within the defect regions that exist and correspond to the same connected component on the composite mask into the same defect group.

[0014] To solve the above-mentioned technical problems, another technical solution adopted in this application is: to provide a computer device, the computer device including a processor and a memory coupled to the processor, the memory storing program instructions, and when the program instructions are executed by the processor, causing the processor to perform the steps of the wafer defect data alignment method under dual detection channels as described above.

[0015] To solve the above-mentioned technical problems, another technical solution adopted in this application is to provide a storage medium storing program instructions capable of implementing the wafer defect data alignment method under dual detection channels as described above.

[0016] The beneficial effects of this application are as follows: The wafer defect data alignment method under dual detection channels of this application obtains a composite mask by taking the union of the defect masks of wafer images under two different detection channels, thereby ensuring the integrity of the defect data in the composite mask. Then, connected component analysis is performed on the composite mask, and the corresponding defect regions are extracted from the defect masks under each detection channel based on the connected components under the composite mask. Then, the defects in the defect regions of different defect masks corresponding to the same connected component are matched, thereby aligning the defect data of the same defect under different detection channels. This fundamentally solves the core problem of difficulty in accurately matching the spatial coordinates of defects caused by differences in hardware configuration and imaging physics principles of different detection channels. It effectively accommodates the differences in defect visibility and manifestation under different channels, ensuring the complete and accurate grouping of data of the same physical defect under different detection channels, and providing support for the subsequent realization of high-precision and high-reliability automatic classification of wafer defects. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a wafer defect data alignment method with dual detection channels according to an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of the functional modules of the wafer defect data alignment device with dual detection channels according to an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of the structure of the storage medium according to an embodiment of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0022] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0023] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0024] Figure 1 This is a flowchart illustrating the wafer defect data alignment method with dual detection channels according to an embodiment of the present invention. It should be noted that if substantially the same result is obtained, the method of the present invention is not necessarily identical. Figure 1 The illustrated process sequence is limited. For example... Figure 1 As shown, the wafer defect data alignment method under dual detection channels includes the following steps:

[0025] Step S1: Obtain the defect masks of the wafer images under the two detection channels respectively and take the union to obtain the composite mask.

[0026] It should be noted that, in this embodiment, the detection channel includes, but is not limited to, a dark field detection channel, a bright field detection channel, a near-ultraviolet photoluminescence detection channel, and a visible light photoluminescence detection channel. Each detection channel may use different light sources, filters, and imaging parameters, resulting in differences in the types and locations of detected defects.

[0027] Specifically, after acquiring wafer images from two detection channels, the wafer images are binarized to obtain defect masks for both detection channels. Pixels in defective areas are marked as 1 (white), and pixels in background areas are marked as 0 (black). Then, the defect masks corresponding to the two detection channels are logically ORed to generate a composite mask. This composite mask contains all defect data found from all detection channels, ensuring data integrity.

[0028] Step S2: Perform regional connectivity analysis on the integrated mask to obtain connected components and connected component parameter information.

[0029] It should be noted that a connected component typically refers to a region in an image composed of adjacent pixels. For example, in a binary image, if two white pixels are adjacent (top, bottom, left, right, or diagonally), they belong to the same connected component.

[0030] Specifically, after obtaining the composite mask, the pixel value of each pixel in the composite mask is analyzed, and pixels with the same pixel value are connected to form a connected component. It can be understood that this connected component is the region composed of defects. After obtaining the connected component, the parameter information of the connected component is extracted. In this embodiment, the parameter information of the connected component includes the position, shape, and size of the connected component.

[0031] Furthermore, step S2 specifically includes:

[0032] 1. Perform binarization on the composite mask to obtain a binarized image.

[0033] 2. Iterate through each pixel of the binarized image row by row, treat the regions formed by adjacent pixels with the same pixel value as a connected component, and record the position, shape and size of the connected component.

[0034] It should be noted that "adjacent" in connected components can be defined according to different rules, with 4-connectivity and 8-connectivity being common. 4-connectivity only considers adjacent pixels in the four directions (up, down, left, and right), while 8-connectivity also includes four adjacent pixels in the diagonal direction. Clearly, 8-connectivity can more comprehensively capture complex shapes and structures, especially when defects may present irregular shapes. Therefore, in this embodiment, the 8-connectivity rule is used to label all connected components. Specifically, in the synthesis mask, the 8-connectivity rule is defined as follows:

[0035] Adjacent pixels: All 8 neighborhoods of a pixel (top, bottom, left, right, and 4 diagonal directions) are considered adjacent;

[0036] Connected region: The same region consisting of all pixels connected by adjacent paths.

[0037] The location of a connected component can be represented by the center of the connected component or the coordinates of the upper left corner of the circumscribed rectangle of the connected component. The shape of a connected component can be represented by the circumscribed rectangle or circumscribed polygon of the connected component. The size of a connected component can be represented by the area of ​​the circumscribed rectangle or circumscribed polygon of the connected component.

[0038] Step S3: Based on the connected component parameter information, extract the corresponding defect regions from the defect masks in the two detection channels respectively.

[0039] Specifically, after obtaining the connected component parameter information, based on the shape and size of the connected components, the corresponding defect regions are extracted from the defect masks under the two detection channels according to the positions of the connected components. By traversing each connected component, the corresponding defect region in the defect masks under the two detection channels for each connected component is obtained.

[0040] Furthermore, step S3 specifically includes:

[0041] 1. Define the position and size of the region of interest corresponding to each connected component based on the connected component parameter information.

[0042] Specifically, in this embodiment, the defect region is extracted based on the region of interest (ROI). The size of the ROI is set according to the shape and size of the connected components, for example, the size of the ROI is set according to the bounding rectangle of the connected components, and the position of the ROI is determined according to the position of the connected components. Each connected component corresponds to its own ROI.

[0043] 2. Based on the location and size of the region of interest, the corresponding region is extracted from each defect mask to obtain the defect region corresponding to each connected component on the defect mask under the two detection channels.

[0044] Specifically, after setting a corresponding region of interest for each connected component, the corresponding defect regions are extracted from the defect masks under the two detection channels using the regions of interest.

[0045] Step S4: Defects within the same connected region on the corresponding synthesis mask that have defects are classified into the same defect group.

[0046] Specifically, after obtaining the defect regions of the defect masks under the two detection channels, the defect regions corresponding to the same connected domain on the composite mask in different defect masks are divided into the same type of defect region. The defects in the same type of defect region are aligned and divided into the same defect group, thereby completing the classification of defect categories for the defects detected under the dual detection channels.

[0047] Furthermore, it should be noted that for wafer defect detection, the degree of dependence on different detection channels varies depending on the detection requirements. Therefore, the detection results under dual detection channels need to be prioritized. Thus, in some embodiments, step S4 specifically includes:

[0048] 1. Pair up defect regions that correspond to the same connected region but belong to different defect masks.

[0049] Specifically, after obtaining all defect regions of the defect mask under the two detection channels, the defect regions in the two defect masks that correspond to the same connected region under the composite mask are paired to obtain at least one pair of defect regions.

[0050] 2. Confirm the channel category of the detection channel corresponding to the defect mask to which the two paired defect areas belong. The channel category includes the primary category and the secondary category.

[0051] It should be noted that the category of each detection channel is preset, namely primary category and secondary category.

[0052] 3. After merging or splitting the defects corresponding to the two paired defect areas according to the channel category, perform an alignment operation and then classify them into the same defect group.

[0053] Specifically, in this embodiment, when aligning defects in two defect areas, the detection channel of the primary category is used as the main method, and the defects corresponding to the detection channels of the secondary category are merged or split according to the defects corresponding to the primary category. Then, the merged or split defects are aligned with the defects corresponding to the primary category and classified into the same defect group.

[0054] Furthermore, the steps of merging or splitting defects corresponding to two paired defect areas according to channel category, performing alignment operations, and then classifying them into the same defect group specifically include:

[0055] 3.1 When the defect masks of the two paired defect regions both correspond to the primary category or both correspond to the secondary category, the defects corresponding to the two defect regions are merged separately, and then the merged defects of the two defect regions are aligned and classified into the same defect group.

[0056] Specifically, the two paired defect areas correspond to the first detection channel and the second detection channel, respectively. When both the first and second detection channels are major categories or minor categories, assuming one defect area contains one defect, denoted as Defect A, and the other defect area contains three defects, denoted as Defect b1, Defect b2, and Defect b3 respectively, when the detection channels corresponding to the two defect areas are both major categories or minor categories, the three defects Defect b1, Defect b2, and Defect b3 in the other defect area need to be merged into one defect, denoted as Defect B. Then, Defect A and Defect B are aligned and classified into the same defect group.

[0057] 3.2 When the defect masks of the two paired defect regions correspond to the primary and secondary categories respectively, the defects in the defect regions of the corresponding secondary categories are merged or split according to the number and category of defects in the defect regions of the corresponding primary categories, and then aligned with the defects in the defect regions of the corresponding primary categories and classified into the same defect group.

[0058] Specifically, the cases where the defect masks of the two paired defect regions correspond to the primary and secondary categories respectively can be categorized as follows: 1. The defect region corresponding to the primary category includes one defect, and the defect region corresponding to the secondary category includes multiple defects; 2. The defect region corresponding to the primary category includes multiple defects, and the defect region corresponding to the secondary category includes one defect; 3. Both the defect region corresponding to the primary category and the defect region corresponding to the secondary category include one defect; 4. Both the defect region corresponding to the primary category and the defect region corresponding to the secondary category include multiple defects.

[0059] For the first case, multiple defects in the corresponding secondary category defect area are merged into one defect, and then this defect is aligned with the defects in the corresponding primary category defect area and classified into the same defect group.

[0060] For the second case, a defect in the corresponding secondary category defect area is split into multiple defects in the corresponding primary category defect area. Then, the multiple defects obtained from the splitting are aligned with the multiple defects in the corresponding primary category defect area and classified into the same defect group.

[0061] For the third case, the defects in the corresponding minor category defect area are aligned with the defects in the corresponding major category defect area and classified into the same defect group.

[0062] For the fourth case, firstly, multiple defects in the corresponding secondary category defect area are merged into one defect. Then, the merged defect is split according to multiple defects in the corresponding primary category defect area. Finally, the multiple defects obtained from the re-splitting are aligned with the multiple defects in the corresponding primary category defect area and classified into the same defect group.

[0063] It should be noted that during the above process of merging or splitting defects, when all defects within a defect area are merged into one defect, the defect category is the highest priority category among all defects within the defect area; when all defects within a defect area are split according to defects in another defect area, the category of the split defect is the category of the defect before the split within the defect area.

[0064] Specifically, when performing defect splitting, if all defects in a defect region are split according to the defects in another defect region, the category of the split defect is the same as the category of the defect before splitting in the defect region. Furthermore, the defect category of the remaining unmatched regions is marked as the general defect of that defect region.

[0065] Furthermore, in some other embodiments, defects can be split or merged according to their priority. Step S4 specifically includes:

[0066] 1. Pair up defect regions that correspond to the same connected region but belong to different defect masks.

[0067] 2. Confirm the defects included in each of the two paired defect areas and the corresponding categories of the defects.

[0068] 3. Identify the target defect area corresponding to the highest priority defect.

[0069] 4. Based on the number and type of defects in the target defect area, merge or split the defects in another defect area, then align them with the defects in the target defect area and classify them into the same defect group.

[0070] Specifically, when aligning defects within two defect regions, the category corresponding to each defect in each defect region is obtained. It should be noted that the priorities of different defect categories are pre-defined; for example, the priority of scratch defects > the priority of particle defects > the priority of other defects. For instance, if one defect region contains one defect, which is the highest priority scratch defect, while another defect region contains three defects, all with lower priorities than the scratch defect, then the three defects in the other defect region need to be merged into one defect, and the category of the merged defect is set to the highest priority category among the three defects. Similarly, if one detection channel's defect region contains one low-priority defect, and another detection channel's defect region contains three defects, and one of these three defects has a higher priority than the low-priority defect, then the low-priority defect in one detection channel's defect region is split into the three defects in the other detection channel's defect region, and the category of the three split defects is set to the low-priority defect category.

[0071] The wafer defect data alignment method proposed in this application aligns wafer defect data under dual detection channels by taking the union of the defect masks of wafer images under two different detection channels to obtain a composite mask, thereby ensuring the integrity of the defect data in the composite mask. Then, connected component analysis is performed on the composite mask, and the corresponding defect regions are extracted from the defect masks under each detection channel based on the connected components under the composite mask. The defects in the defect regions of different defect masks corresponding to the same connected component are then matched, thereby aligning the defect data of the same defect under different detection channels. This method fundamentally solves the core problem of difficulty in accurately matching the spatial coordinates of defects caused by differences in hardware configuration and imaging physics principles of different detection channels. It effectively accommodates the differences in defect visibility and manifestation under different channels, ensuring the complete and accurate grouping of data of the same physical defect under different detection channels, and providing support for the subsequent realization of high-precision and high-reliability automatic classification of wafer defects.

[0072] Figure 2 This is a functional module diagram of the wafer defect data alignment device with dual detection channels according to an embodiment of the present invention. Figure 2 As shown, the wafer defect data alignment device 20 with dual detection channels includes: a mask generation module 21, a connected component analysis module 22, a region extraction module 23, and a defect matching module 24.

[0073] The mask generation module 21 is used to acquire the defect masks of the wafer images under the two detection channels respectively and take the union to obtain the comprehensive mask;

[0074] The connected component analysis module 22 is used to perform regional connectivity analysis on the integrated mask to obtain connected components and connected component parameter information.

[0075] The region extraction module 23 is used to extract the corresponding defect region from the defect mask in the two detection channels based on the connected component parameter information.

[0076] The defect matching module 24 is used to classify defects that exist and are in the same connected region on the corresponding defect mask into the same defect group.

[0077] Optionally, the connected component analysis module 22 performs a region connectivity analysis on the composite mask to obtain connected components and connected component parameter information. Specifically, this includes: performing binarization processing on the composite mask to obtain a binarized image; traversing each pixel of the binarized image line by line, treating the region formed by adjacent pixels with the same pixel value as a connected component, and recording the position, shape, and size of the connected component.

[0078] Optionally, the region extraction module 23 performs the operation of extracting the corresponding defect region in the defect mask under the two detection channels based on the connected component parameter information. Specifically, this includes: defining the position and size of the region of interest corresponding to each connected component based on the connected component parameter information; and extracting the corresponding region in each defect mask according to the position and size of the region of interest, thereby obtaining the defect region corresponding to each connected component on the defect mask under the two detection channels.

[0079] Optionally, the defect matching module 24 performs the operation of classifying defects within the same connected region on the corresponding defect mask into the same defect group. This may include: pairing defect regions that correspond to the same connected region but belong to different defect masks; confirming the channel category of the detection channel corresponding to the defect mask to which the two paired defect regions belong, where the channel category includes a primary category and a secondary category; merging or splitting the defects corresponding to the two paired defect regions according to the channel category, performing an alignment operation, and then classifying them into the same defect group.

[0080] Optionally, the defect matching module 24 performs an alignment operation after merging or splitting the defects corresponding to the two paired defect regions according to the channel category, and then classifies them into the same defect group. Specifically, this includes: when the defect masks to which the two paired defect regions belong both to the main category or both to the secondary category, merging the defects corresponding to the two defect regions respectively, and then performing an alignment operation on the merged defects of the two defect regions and classifying them into the same defect group; when the defect masks to which the two paired defect regions belong to the main category and the secondary category respectively, merging or splitting the defects in the defect regions of the corresponding secondary category according to the number and category of defects in the defect regions of the corresponding main category, and then performing an alignment operation with the defects in the defect regions of the corresponding main category and classifying them into the same defect group.

[0081] Optionally, when all defects within a defect region are merged into one defect, the defect category is the highest priority category among all defects within the defect region; when all defects within a defect region are split according to defects in another defect region, the category of the split defect is the category of the defect before splitting within the defect region.

[0082] Optionally, the defect matching module 24 performs the operation of classifying defects within the same connected region on the corresponding defect mask into the same defect group. This may further include: pairing defect regions corresponding to the same connected region but belonging to different defect masks; confirming the defects included in each of the paired defect regions and the corresponding categories of the defects; confirming the target defect region corresponding to the defect with the highest priority; and merging or splitting the defects in another defect region according to the number and category of defects in the target defect region, and then aligning them with the defects in the target defect region and classifying them into the same defect group.

[0083] Optionally, the defect matching module 24 performs an operation to merge or split defects in another defect area based on the number and category of defects in the target defect area, and then aligns them with the defects in the target defect area and classifies them into the same defect group. Specifically, this includes: when there is a single defect in the target defect area and multiple defects in the other defect area, merging the multiple defects in the other defect area, and recording the category of the merged defect as the highest priority category among the multiple defects in the other defect area, and then aligning the merged defect with the single defect in the target defect area and classifying it into the same defect group; when there are multiple defects in the target defect area and a single defect in the other defect area, splitting the single defect in the other defect area according to the multiple defects in the target defect area, recording the category of the split defect as the category of the single defect in the other defect area, and then aligning the split defect with the multiple defects in the target defect area one by one and classifying them into the same defect group.

[0084] For other details regarding the implementation of the technical solutions of each module in the dual-detection-channel wafer defect data alignment device in the above embodiments, please refer to the description in the dual-detection-channel wafer defect data alignment method in the above embodiments, which will not be repeated here.

[0085] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0086] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 3 As shown, the computer device 30 includes a processor 31 and a memory 32 coupled to the processor 31. The memory 32 stores program instructions. When the program instructions are executed by the processor 31, the processor 31 performs the steps of the wafer defect data alignment method under dual detection channels described in any of the above embodiments.

[0087] The processor 31 can also be referred to as a Central Processing Unit (CPU). The processor 31 may be an integrated circuit chip with signal processing capabilities. The processor 31 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0088] See Figure 4 , Figure 4 This is a schematic diagram of the structure of the storage medium according to an embodiment of the present invention. The storage medium of this embodiment stores program instructions 41 capable of implementing the above-described wafer defect data alignment method under dual detection channels. These program instructions 41 can be stored in the storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or computer devices such as computers, servers, mobile phones, and tablets.

[0089] In the several embodiments provided in this application, it should be understood that the disclosed computer devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0090] Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for aligning wafer defect data under dual detection channels, characterized in that, It includes: Defect masks of wafer images from two detection channels are obtained separately and their union is taken to obtain a composite mask; Perform regional connectivity analysis on the composite mask to obtain connected domains and connected domain parameter information; Based on the connected component parameter information, the corresponding defect regions are extracted from the defect masks under the two detection channels respectively; Defects that exist within the same connected region on the composite mask are classified into the same defect group.

2. The wafer defect data alignment method under dual detection channels according to claim 1, characterized in that, The process of performing regional connectivity analysis on the integrated mask to obtain connected components and connected component parameter information includes: The composite mask is binarized to obtain a binarized image; The binary image is traversed line by line. The regions formed by adjacent pixels with the same pixel value are regarded as a connected component, and the position, shape and size of the connected component are recorded.

3. The wafer defect data alignment method under dual detection channels according to claim 1, characterized in that, The step of extracting the corresponding defect region from the defect mask in each of the two detection channels based on the connected component parameter information includes: Based on the connected component parameter information, define the position and size of the region of interest corresponding to each connected component; Based on the location and size of the region of interest, the corresponding region is extracted from each defect mask to obtain the defect region corresponding to each connected domain on the defect mask under the two detection channels.

4. The wafer defect data alignment method under dual detection channels according to claim 1, characterized in that, The step of classifying defects within the same connected region on the composite mask as the same defect group includes: Pair up defect regions that correspond to the same connected region but belong to different defect masks; Confirm the channel category of the detection channel corresponding to the defect mask to which the two paired defect regions belong, the channel category including a primary category and a secondary category; According to the channel category, the defects corresponding to the two paired defect areas are merged or split, and then aligned before being assigned to the same defect group.

5. The wafer defect data alignment method under dual detection channels according to claim 4, characterized in that, The step of merging or splitting defects corresponding to two paired defect regions according to the channel category, performing an alignment operation, and then classifying them into the same defect group includes: When the defect masks of the two paired defect regions both correspond to the primary category or both correspond to the secondary category, the defects corresponding to the two defect regions are merged separately, and then the merged defects of the two defect regions are aligned and classified into the same defect group. When the two paired defect regions belong to the primary and secondary categories of the defect mask respectively, the defects in the corresponding secondary category defect region are merged or split according to the number and category of defects in the defect region of the primary category, and then aligned with the defects in the defect region of the primary category and classified into the same defect group.

6. The wafer defect data alignment method under dual detection channels according to claim 5, characterized in that, When all defects within a defect region are merged into one defect, the defect category is the highest priority category among all defects within the defect region; when all defects within a defect region are split according to defects in another defect region, the category of the split defect is the category of the defect before the split within the defect region.

7. The wafer defect data alignment method under dual detection channels according to claim 1, characterized in that, The step of classifying defects within the same connected region on the composite mask as the same defect group includes: Pair up defect regions that correspond to the same connected region but belong to different defect masks; Identify the defects included in each of the two paired defect areas and the corresponding categories of the defects; Identify the target defect area corresponding to the highest priority defect; Based on the number and type of defects in the target defect area, defects in another defect area are merged or split, then aligned with the defects in the target defect area and classified into the same defect group.

8. The wafer defect data alignment method under dual detection channels according to claim 7, characterized in that, The step of merging or splitting defects in another defect region based on the number and type of defects in the target defect region, and then aligning them with the defects in the target defect region and classifying them into the same defect group, includes: When there is a single defect in the target defect area and multiple defects in another defect area, the multiple defects in the other defect area are merged, and the category of the merged defect is recorded as the highest priority category among the multiple defects in the other defect area. Then, the merged defect is aligned with the single defect in the target defect area and classified into the same defect group. When there are multiple defects in the target defect area and a single defect in another defect area, the single defect in the other defect area is split according to the multiple defects in the target defect area, and the category of the split defect is recorded as the category of the single defect in the other defect area. Then, the split defects are matched one-to-one with the multiple defects in the target defect area and aligned and divided into the same defect group.

9. A computer device, characterized in that, The computer device includes a processor and a memory coupled to the processor, the memory storing program instructions that, when executed by the processor, cause the processor to perform the steps of the wafer defect data alignment method under dual detection channels as described in any one of claims 1-8.

10. A storage medium, characterized in that, The system stores program instructions capable of implementing the wafer defect data alignment method under dual detection channels as described in any one of claims 1-8.

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