Wafer defect detection method and system based on image segmentation and image difference

Abstract

The invention provides a wafer defect detection method and system based on image segmentation and image difference, and relates to the technical field of defect detection, and the method comprises the following steps: firstly, obtaining a difference image based on a detection image and a template image; then carrying out gray value extraction on the detection image and the template image based on the difference image, and calculating the penetration rate of the defect area according to a gray value extraction result; performing line segmentation processing on the detection image, and performing intersection positioning on a line segmentation image based on the difference image to obtain an intersection area image; performing geometric operation on the difference image and the intersection area image to obtain a defect width and a line width, and calculating a coverage ratio of a defect area based on the defect width and the line width; and finally, comprehensively judging the severity of the defect according to the penetration rate and the coverage rate of the defect area. The problems that the influence degree of the defect cannot be measured in the existing wafer appearance defect detection and over-detection is easy to occur are solved.

Description

Technical Field

[0001] The present invention relates to the field of defect detection technology, and in particular to a wafer defect detection method and system based on image segmentation and image difference. Background Art

[0002] Defect detection of wafer products is the process of automatic defect detection by automatic optical inspection equipment (AOI equipment) during the wafer production process. The AOI equipment uses industrial cameras to capture images of wafer products, and then uses computer vision algorithms (CV, Computer Vision) to detect possible defects in the images. However, the CV algorithm has the shortcoming of being difficult to accurately classify defects, and it is impossible to calculate the degree of impact of defects on background targets. Therefore, the use of AOI equipment for defect detection of wafer products generally has a high pass rate, requires manual re-judgment, and has high labor costs. Summary of the invention

[0003] The present invention provides a wafer defect detection method and system based on image segmentation and image difference, which solves the problem that the existing wafer appearance defect detection cannot measure the defect impact degree and is prone to over-inspection.

[0004] In a first aspect, an embodiment of the present invention provides a method for detecting wafer cutting defects, the method comprising the following process: Performing pixel difference processing on the inspection image of the wafer product and the template image to obtain a differential image; Extracting grayscale values ​​of defective areas of the inspection image and the template image based on the differential image to obtain defective grayscale values ​​and normal grayscale values, and calculating the penetration rate of the defective area according to the defective grayscale values ​​and the normal grayscale values; Performing line segmentation processing on the inspection image of the wafer product to obtain a line segmentation image; and performing intersection positioning on the line areas of the line segmentation image based on the differential image to obtain an intersection area image; Performing geometric operations on the difference image and the intersection area image to obtain geometric parameters of the defect and the geometric parameters of the line, and calculating the coverage ratio of the defect area based on the geometric parameters of the defect and the geometric parameters of the line; The severity of the defect is comprehensively judged based on the penetration rate and coverage ratio of the defect area to obtain a comprehensive detection result of the impact of the wafer defect.

[0005] In the above embodiment, the present invention uses a combination of image difference technology and image segmentation technology to process the inspection image and template image of the wafer product to obtain a differential image containing a defect area and an intersection area image containing a line area; and combines the light transmittance characteristics and geometric characteristics of the wafer product to perform transmittance verification and geometric verification on the differential image containing the defect area and the intersection area image containing the line area to quantify the degree of influence of the wafer product defects on the route, so as to more accurately determine whether the defects need to be detected, effectively reducing the pass rate of the AOI equipment and reducing the cost of manual re-judgment in the later stage.

[0006] As some optional implementations of the present application, the process of performing pixel difference processing on the inspection image of the wafer product and the template image to obtain the difference image is as follows: Acquire a test image and a template image of a wafer product, and pre-process the acquired test image and template image; Performing image registration on the preprocessed detection image and the template image so that the detection image and the template image are spatially aligned; Performing pixel difference processing on the spatially aligned detection image and the template image to obtain a difference image, and acquiring position information of the defect area according to the difference image; The calculation formula for the pixel difference processing is as follows: ; in, Indicates the detection image at pixel point The pixel value of the position, Indicates the template image at pixel point The pixel value at the location.

[0007] In the above-mentioned embodiments, the present invention uses pixel difference technology to quickly and accurately detect wafer defects.

[0008] As some optional implementations of the present application, the grayscale value extraction of the defective area of ​​the detection image and the template image based on the differential image to obtain the defect grayscale value and the normal grayscale value is as follows: Performing regional positioning on the inspection image and the template image based on the position information of the defect area to obtain a regional positioning result; Based on the regional positioning results, the grayscale values ​​of the defective areas of the detection image and the template image are extracted and the grayscale values ​​are averaged to obtain the defect grayscale value and the normal grayscale value.

[0009] In the above embodiment, the present invention can obtain the grayscale value difference between the test image and the template image in the defect area by extracting the grayscale value of the defect area of ​​the test image and the template image, which facilitates the subsequent calculation of the penetration rate based on the grayscale value difference.

[0010] As some optional implementations of the present application, the formula for calculating the penetration rate of the defect area is as follows: ; in, , Indicates the relatively larger and smaller values ​​among the defective grayscale values ​​and the normal grayscale values.

[0011] In the above embodiment, the present invention accurately quantifies the penetration rate of the defect area by obtaining the gray value difference between the detection image and the template image in the defect area.

[0012] As some optional implementations of the present application, the process of performing line segmentation processing on the inspection image of the wafer product to obtain the line segmentation image is as follows: Use edge detection algorithm to perform line segmentation processing on the inspection image of wafer products to obtain line areas; The line area is subjected to feature extraction, morphological processing and image post-processing to obtain a line segmentation image.

[0013] In the above embodiment, the present invention uses image segmentation technology to quickly and accurately segment the line from the background.

[0014] As some optional implementations of the present application, the process of performing intersection positioning on the line regions of the line segmentation image based on the differential image to obtain the intersection region image is as follows: According to the position information of the defect area, the line area of ​​the line segmentation image is intersected and located to obtain a line intersection location result; According to the line intersection positioning result, the intersecting lines are extracted from the line segmentation image to obtain the intersection area image of the defect and the line.

[0015] In the above-mentioned embodiment, the present invention adopts the intersection positioning method to extract the intersecting lines, thereby quickly and accurately obtaining the intersection area image of the defect and the line.

[0016] As some optional implementations of the present application, the process of performing geometric operations on the difference image and the intersection area image to obtain the geometric parameters of the defect and the geometric parameters of the line is as follows: Calculate the width of the line area of ​​the intersection area image to obtain the line width; Performing image registration on the difference image and the intersection area image so as to align the difference image and the intersection area image in space; A logical operation is performed on the spatially aligned difference image and the intersection area image to retain the pixel point area with the same pixel value in the two images, and the width of the pixel point area with the same pixel value is calculated to obtain the defect width.

[0017] In the above-mentioned embodiment, the present invention can quantify the defect width and the width of the intersecting lines by performing geometric operations on the difference image and the intersection area image.

[0018] As some optional implementations of the present application, the calculation formula for the coverage ratio of the defect area is as follows: ; in, represents the defect width, Indicates the line width.

[0019] In the above embodiment, the present invention accurately quantifies the coverage ratio of the defect area by calculating the ratio of the defect width to the line width.

[0020] As some optional implementations of the present application, the defect severity is comprehensively determined according to the penetration rate and coverage ratio of the defect area to obtain a comprehensive detection result of the impact of the wafer defect, and the process is as follows: Preset a verification threshold corresponding to the penetration rate of the defect area and a verification threshold for the coverage ratio of the defect area; The penetration rate of the defective area and the coverage ratio of the defective area are graded and checked according to the verification threshold to obtain a comprehensive detection result of the impact degree of wafer defects.

[0021] In the above embodiment, the present invention combines the light transmittance characteristics and geometric characteristics of the wafer product to perform transmittance verification and geometric verification on the differential image containing the defect area and the intersection area image containing the line area, and comprehensively measures the impact of defects on the wafer product from multiple angles to improve the accuracy of wafer defect detection and reduce the problem of over-inspection.

[0022] In a second aspect, the present invention provides a wafer defect detection system based on image segmentation and image difference, the system comprising: A pixel difference processing unit, the pixel difference processing unit is used to perform pixel difference processing on the detection image of the wafer product and the template image to obtain a difference image; A penetration rate calculation unit, wherein the penetration rate calculation unit extracts grayscale values ​​of defective areas of the detection image and the template image based on the differential image to obtain defective grayscale values ​​and normal grayscale values, and calculates the penetration rate of the defective area according to the defective grayscale values ​​and the normal grayscale values; A line intersection positioning unit, the line intersection positioning unit is used to perform line segmentation processing on the inspection image of the wafer product to obtain a line segmentation image; and to perform intersection positioning on the line area of ​​the line segmentation image based on the differential image to obtain an intersection area image; A coverage ratio calculation unit, the coverage ratio calculation unit is used to perform geometric operations on the difference image and the intersection area image to obtain geometric parameters of the defect and the geometric parameters of the line, and calculate the coverage ratio of the defect area based on the geometric parameters of the defect and the geometric parameters of the line; A defect comprehensive detection unit is used to comprehensively determine the severity of the defect according to the penetration rate and coverage ratio of the defect area to obtain a comprehensive detection result of the impact degree of the wafer defect.

[0023] In a third aspect, the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the wafer defect detection method based on image segmentation and image differentiation when executing the computer program.

[0024] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for wafer defect detection based on image segmentation and image difference is implemented.

[0025] The beneficial effects of the present invention are as follows: the present invention uses a combination of image difference technology and image segmentation technology to process the inspection image and template image of the wafer product to obtain a differential image containing the defect area and an intersection area image containing the line area; and combines the light transmittance characteristics and geometric characteristics of the wafer product to perform transmittance verification and geometric verification on the differential image containing the defect area and the intersection area image containing the line area, and comprehensively measures the impact of defects on the wafer product from all angles to improve the accuracy of wafer defect detection, so as to reduce the problem of over-inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 is a schematic diagram of the computer device structure of the hardware operating environment described in the embodiment of the present invention; Figure 2 is a flow chart of a wafer defect detection method according to an embodiment of the present invention; Figure 3 is an example diagram of pixel difference processing according to an embodiment of the present invention; Figure 4 is an example diagram of a line segmentation image according to an embodiment of the present invention; Figure 5 is a schematic diagram of an intersection area image according to an embodiment of the present invention; Figure 6 is a diagram showing an example of quantifying the degree of influence of defects on a circuit according to an embodiment of the present invention; Figure 7 It is a structural block diagram of the wafer defect detection system described in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0029] In order to solve the problem that the existing wafer appearance defect detection cannot measure the degree of defect impact and is prone to over-inspection, the present application provides a wafer defect detection method, system, device and storage medium based on image segmentation and image difference. Before introducing the specific technical solution of the present application, the hardware operating environment involved in the embodiment of the present application is first introduced.

[0030] See also Figure 1 , Figure 1 A schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0031] like Figure 1 As shown, the computer device may include: a processor, such as a central processing unit (CPU), a communication bus, a user interface, a network interface, and a memory. Among them, the communication bus is used to realize the connection and communication between these components. The user interface may include a display screen (Display), an input unit such as a keyboard (Keyboard), and optionally, the user interface may also include a standard wired interface and a wireless interface. The network interface may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity interface). The memory may be a high-speed random access memory (Random Access Memory, RAM) memory, or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory may optionally be a storage device independent of the aforementioned processor.

[0032] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0033] like Figure 1 As shown, a memory as a storage medium may include an operating system, a network communication module, a user interface module, and an electronic program module.

[0034] exist Figure 1 In the computer device shown, the network interface is mainly used for data communication with the network server; the user interface is mainly used for data interaction with the user; the processor and memory in the computer device of the present application can be set in the computer device, and the computer device calls the electronic program module to store the software product through the processor, and executes the wafer defect detection method provided in the embodiment of the present application.

[0035] Based on the hardware environment of the above-mentioned embodiment, the embodiment of the present application provides a wafer defect detection method based on image segmentation and image difference, please refer to Figure 2 , Figure 2 The flowchart of the wafer defect detection method is as follows: (1) Perform pixel difference processing on the inspection image of the wafer product and the template image to obtain a differential image.

[0036] In the embodiment of the present invention, the template image includes but is not limited to a defect-free inspection image, a design image, etc.; preferably, the embodiment of the present invention uses a design image as a template image. Since the physical wafer product is produced in a one-to-one ratio according to the design image, defects can be detected by comparing the design image. The inspection image is an image of a wafer product that is inspected in real time by an AOI device.

[0037] See also Figure 3 , Figure 3 is an example diagram of the pixel difference processing, Figure 3 -a is a schematic diagram of the detection image, Figure 3 -b is a schematic diagram of the template image, and 3-c is a schematic diagram of the difference image.

[0038] Specifically, the process of performing pixel difference processing on the inspection image of the wafer product and the template image to obtain the difference image is as follows: (1.1) Obtaining a test image and a template image of a wafer product, and preprocessing the obtained test image and template image. Specifically, the preprocessing includes but is not limited to image filtering, histogram equalization, contrast enhancement, and binarization, etc.; the preprocessing can be adjusted according to actual conditions.

[0039] (1.2) Perform image registration on the preprocessed detection image and template image so that the detection image and the template image are spatially aligned.

[0040] In the embodiment of the present invention, first, feature extraction is performed on the preprocessed detection image and template image to obtain their respective feature points. These feature points include but are not limited to unique and stable points such as corner points, edges, contours, and line intersections of the image; preferably, the embodiment of the present invention selects the corner points of the image as feature points. Then, the matching feature point pairs in the detection image and the template image are obtained by similarity measurement. Finally, the detection image and the template image are spatially aligned according to the matching feature points.

[0041] (1.3) Performing pixel difference processing on the spatially aligned detection image and the template image to obtain a difference image; and obtaining position information of the defect area according to the difference image, wherein the position information of the defect area includes coordinate information of pixel points corresponding to the defect.

[0042] Specifically, the calculation formula for the pixel difference processing is as follows: ; in, Indicates the detection image at pixel point The pixel value of the position, Indicates the template image at pixel point The pixel value at the location.

[0043] (2) Based on the differential image, the grayscale values ​​of the defective areas of the inspection image and the template image are extracted to obtain the defective grayscale value and the normal grayscale value, and the penetration rate of the defective area is calculated based on the defective grayscale value and the normal grayscale value.

[0044] Specifically, the AOI device will illuminate the wafer product from the bottom upward when acquiring the inspection image. Therefore, when there are defects on the surface of the wafer product, the light transmittance of the defective area will be reduced. Therefore, the transmittance can be used to measure whether the defect meets the detection standard.

[0045] In an embodiment of the present invention, the process of extracting grayscale values ​​of defect areas of the detection image and the template image based on the differential image is as follows: (2.1) Based on the position information of the defective area, the inspection image and the template image are regionally located to obtain a regional positioning result. Specifically, the defective area of ​​the inspection image and the template image is reversely located according to the coordinate information of the pixel points corresponding to the defective area on the differential image.

[0046] (2.2) Based on the regional positioning results, the grayscale values ​​of the defective areas of the test image and the template image are extracted and the grayscale values ​​are averaged to obtain the defective grayscale values ​​and normal grayscale values ​​corresponding to the test image and the test image. That is, according to the positioning of the defective areas corresponding to the test image and the template image, specifically, the grayscale values ​​of the defective areas are first extracted to obtain the grayscale values ​​of the defective areas corresponding to the two images, and then all the grayscale values ​​are averaged to obtain the defective grayscale values ​​and normal grayscale values ​​corresponding to the test image and the test image.

[0047] Specifically, the calculation formula for the penetration rate of the defect area is as follows: ; Where P represents the penetration rate of the defect area, , It represents the relatively larger and smaller values ​​between the defect grayscale value and the normal grayscale value. The penetration rate of the defect interval ranges from 0 to 1.

[0048] (3) Perform line segmentation processing on the inspection image of the wafer product to obtain a line segmentation image, and perform intersection positioning on the line areas of the line segmentation image based on the differential image to obtain an intersection area image. Please refer to Figure 4 , Figure 5 , Figure 4 is a schematic diagram of the line segmentation image, Figure 5 It is a schematic diagram of the intersection area image.

[0049] In an embodiment of the present invention, the process of performing line segmentation processing on the inspection image of the wafer product to obtain the line segmentation image is as follows: (3.1) Use an edge detection algorithm or a threshold segmentation algorithm to perform line segmentation processing on the inspection image of the wafer product to obtain the line area. Among them, the edge detection algorithm and the threshold segmentation algorithm are both existing image segmentation algorithms, and the steps of the algorithm are not repeated in the embodiment of the present invention. At the same time, the embodiment of the present invention can also use a trained AI segmentation model to perform line segmentation processing on the inspection image of the wafer product. The AI ​​segmentation model can use the instance algorithm of the YOLO framework to implement line segmentation processing.

[0050] (3.2) Perform feature extraction, morphological processing and image post-processing on the line area to obtain a line segmentation image. Specifically, the morphological processing includes but is not limited to expansion and corrosion. The image post-processing includes but is not limited to removing burrs, filling holes, etc. to improve the quality of the image.

[0051] (4) Performing geometric operations on the difference image and the intersection area image to obtain geometric parameters of the defect and the geometric parameters of the line, and calculating the coverage ratio of the defect area based on the geometric parameters of the defect and the geometric parameters of the line.

[0052] In an embodiment of the present invention, the process of performing geometric operations on the difference image and the intersection area image to obtain the geometric parameters of the defect and the geometric parameters of the line is as follows: (4.1) Calculate the width of the line area in the intersection area image to obtain the line width. Specifically, obtain the coordinate information of the edge pixel points of the line area in the intersection area image, construct a minimum bounding rectangle based on the coordinate information, and use the width of the minimum bounding rectangle as the line width.

[0053] (4.2) Perform image registration on the difference image and the intersection area image to spatially align the difference image and the intersection area image. First, perform feature extraction on the difference image and the intersection area image to obtain their respective feature points. These feature points include but are not limited to unique and stable points such as corner points, edges, contours, and line intersection points of the image; preferably, the embodiment of the present invention selects the corner points of the image as feature points. Then, the matching feature point pairs in the difference image and the intersection area image are obtained by a similarity measurement method. Finally, the difference image and the intersection area image are spatially aligned according to the matching feature points.

[0054] (4.3) Perform logical operations on the spatially aligned differential image and the intersection area image to retain the pixel areas with the same pixel values ​​in the two images, and calculate the width of the pixel areas with the same pixel values ​​to obtain the defect width. Specifically, first perform logical operations on the spatially aligned differential image and the intersection area image to retain the overlapping pixels with pixel values ​​of 255 in both images, that is, the intersection area of ​​the defect and the line can be extracted, and then obtain the coordinate information of the edge pixel points corresponding to the intersection area of ​​the defect and the line, construct the minimum bounding rectangle based on the coordinate information, and use the width of the minimum bounding rectangle as the defect width.

[0055] Specifically, the calculation formula of the coverage ratio of the defect area is as follows: ; in, represents the defect width, Represents the line width, and the coverage ratio of the defect area ranges from 0 to 1.

[0056] (5) Comprehensively judge the severity of defects based on the penetration rate and coverage ratio of the defect area to obtain a comprehensive test result of the impact of wafer defects. Please refer to Figure 6 , Figure 6The following is an example diagram that quantifies the impact of the defect on the line.

[0057] In the embodiment of the present invention, the process of comprehensively determining the severity of the defect based on the penetration rate and coverage ratio of the defect area is as follows: (5.1) A verification threshold corresponding to the penetration rate of the preset defect area and a verification threshold corresponding to the coverage ratio of the preset defect area.

[0058] For example, according to the actual verification index of the wafer product of the factory, a verification threshold T1 corresponding to the penetration rate of the defective area and a verification threshold T2 corresponding to the coverage ratio of the defective area are preset.

[0059] (5.2) The penetration rate of the defective area and the coverage ratio of the defective area are graded and checked according to the verification threshold to obtain a comprehensive test result of the impact degree of the wafer defect.

[0060] For example, if the penetration rate of the defective area is greater than the verification threshold T1, and the coverage ratio is less than the verification threshold T2, the impact of the wafer defect is judged to be slight and can be ignored; if the penetration rate of the defective area is greater than the verification threshold T1, and the coverage ratio is greater than the verification threshold T2, the impact of the wafer defect is judged to be moderate and needs to be detected; if the penetration rate of the defective area is less than the verification threshold T1, and the coverage ratio is greater than the verification threshold T2, the impact of the wafer defect is judged to be severe and needs to be detected and focused on. At the same time, the wafer can be detected only when the penetration rate of the defective area is less than the verification threshold T1 and the coverage ratio is greater than the verification threshold T2.

[0061] In summary, the present invention adopts a combination of image difference technology and image segmentation technology to process the inspection image and template image of the wafer product, so as to obtain a differential image containing the defect area and an intersection area image containing the line area; and in combination with the light transmittance characteristics and geometric characteristics of the wafer product, the differential image containing the defect area and the intersection area image containing the line area are subjected to transmittance verification and geometric verification, and the degree of influence of defects on the wafer product is comprehensively measured from all angles to improve the accuracy of wafer defect detection, so as to reduce the problem of over-inspection.

[0062] In addition, in one embodiment, based on the same inventive concept as the above embodiment, the embodiment of the present invention provides a wafer defect detection system based on image segmentation and image difference, and the system corresponds to the method of embodiment 1 one by one, please refer to Figure 7 , Figure 7 The structure block diagram of the wafer defect detection system is as follows: A pixel difference processing unit, the pixel difference processing unit is used to perform pixel difference processing on the detection image of the wafer product and the template image to obtain a difference image; A penetration rate calculation unit, wherein the penetration rate calculation unit extracts grayscale values ​​of defective areas of the detection image and the template image based on the differential image to obtain defective grayscale values ​​and normal grayscale values, and calculates the penetration rate of the defective area according to the defective grayscale values ​​and the normal grayscale values; A line intersection positioning unit, the line intersection positioning unit is used to perform line segmentation processing on the inspection image of the wafer product to obtain a line segmentation image; and to perform intersection positioning on the line area of ​​the line segmentation image based on the differential image to obtain an intersection area image; A coverage ratio calculation unit, the coverage ratio calculation unit is used to perform geometric operations on the difference image and the intersection area image to obtain geometric parameters of the defect and the geometric parameters of the line, and calculate the coverage ratio of the defect area based on the geometric parameters of the defect and the geometric parameters of the line; A defect comprehensive detection unit is used to comprehensively determine the severity of the defect according to the penetration rate and coverage ratio of the defect area to obtain a comprehensive detection result of the impact degree of the wafer defect.

[0063] It should be noted that each unit in the wafer defect detection system in this embodiment corresponds one-to-one to each step in the wafer defect detection method in the aforementioned embodiment. Therefore, the specific implementation method and technical effects achieved by this embodiment can refer to the implementation method of the aforementioned wafer defect detection method, which will not be repeated here.

[0064] In addition, in one embodiment, the present application also provides a computer device, which includes a processor, a memory, and a computer program stored in the memory, and the computer program implements the method in the aforementioned embodiment when executed by the processor.

[0065] In addition, in one embodiment, the present application further provides a computer storage medium, on which a computer program is stored, and the computer program implements the method in the aforementioned embodiment when executed by a processor.

[0066] In some embodiments, the computer readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or various devices including one or any combination of the above memories. The computer may be various computing devices including intelligent terminals and servers.

[0067] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0068] As an example, executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file storing other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0069] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0070] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0071] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0072] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a multimedia terminal device (which can be a mobile phone, a computer, a television receiver, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0073] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A wafer defect detection method based on image segmentation and image difference, characterized in that: The method comprises the following steps: Performing pixel difference processing on the inspection image of the wafer product and the template image to obtain a differential image; Extracting grayscale values ​​of defective areas of the inspection image and the template image based on the differential image to obtain defective grayscale values ​​and normal grayscale values, and calculating the penetration rate of the defective area according to the defective grayscale values ​​and the normal grayscale values; Performing line segmentation processing on the inspection image of the wafer product to obtain a line segmentation image; and performing intersection positioning on the line areas of the line segmentation image based on the differential image to obtain an intersection area image; Performing geometric operations on the difference image and the intersection area image to obtain geometric parameters of the defect and the geometric parameters of the line, and calculating the coverage ratio of the defect area based on the geometric parameters of the defect and the geometric parameters of the line; The severity of the defect is comprehensively judged based on the penetration rate and coverage ratio of the defect area to obtain a comprehensive detection result of the impact of the wafer defect.

2. The wafer defect detection method based on image segmentation and image difference according to claim 1, characterized in that: The process of performing pixel difference processing on the inspection image of the wafer product and the template image to obtain the difference image is as follows: Acquire a test image and a template image of a wafer product, and pre-process the acquired test image and template image; Performing image registration on the preprocessed detection image and the template image so that the detection image and the template image are spatially aligned; Performing pixel difference processing on the spatially aligned detection image and the template image to obtain a difference image, and acquiring position information of the defect area according to the difference image; The calculation formula for the pixel difference processing is as follows: ; in, Indicates the detection image at pixel point The pixel value of the position, Indicates the template image at pixel point The pixel value at the location.

3. The wafer defect detection method based on image segmentation and image difference according to claim 2, characterized in that: The process of extracting the grayscale values ​​of the defective areas of the inspection image and the template image based on the differential image to obtain the defect grayscale value and the normal grayscale value is as follows: Performing regional positioning on the inspection image and the template image based on the position information of the defect area to obtain a regional positioning result; Based on the regional positioning results, the grayscale values ​​of the defective areas of the detection image and the template image are extracted and the grayscale values ​​are averaged to obtain the defect grayscale value and the normal grayscale value.

4. The wafer defect detection method based on image segmentation and image difference according to claim 3 is characterized in that: The formula for calculating the penetration rate of the defect area is as follows: ； in, , Indicates the relatively larger and smaller values ​​among the defective grayscale values ​​and the normal grayscale values.

5. The wafer defect detection method based on image segmentation and image difference according to claim 1, characterized in that: The process of performing line segmentation processing on the inspection image of the wafer product to obtain the line segmentation image is as follows: Use edge detection algorithm to perform line segmentation processing on the inspection image of wafer products to obtain line areas; The line area is subjected to feature extraction, morphological processing and image post-processing to obtain a line segmentation image.

6. The wafer defect detection method based on image segmentation and image difference according to claim 1, characterized in that: The process of intersecting and locating the line area of ​​the line segmentation image based on the differential image to obtain the intersection area image is as follows: According to the position information of the defect area, the line area of ​​the line segmentation image is intersected and located to obtain a line intersection location result; According to the line intersection positioning result, the intersecting lines are extracted from the line segmentation image to obtain the intersection area image of the defect and the line.

7. The wafer defect detection method based on image segmentation and image difference according to claim 1, characterized in that: The process of performing geometric operations on the difference image and the intersection area image to obtain the geometric parameters of the defect and the geometric parameters of the line is as follows: Calculate the width of the line area of ​​the intersection area image to obtain the line width; Performing image registration on the difference image and the intersection area image so as to align the difference image and the intersection area image in space; A logical operation is performed on the spatially aligned difference image and the intersection area image to retain the pixel point area with the same pixel value in the two images, and the width of the pixel point area with the same pixel value is calculated to obtain the defect width.

8. The wafer defect detection method based on image segmentation and image difference according to claim 7, characterized in that: The calculation formula of the coverage ratio of the defect area is as follows: ； in, represents the defect width, Indicates the line width.

9. The wafer defect detection method based on image segmentation and image difference according to claim 1, characterized in that: The process of comprehensively judging the severity of defects based on the penetration rate and coverage ratio of the defect area to obtain a comprehensive test result of the impact of wafer defects is as follows: Preset a verification threshold corresponding to the penetration rate of the defect area and a verification threshold for the coverage ratio of the defect area; The penetration rate of the defective area and the coverage ratio of the defective area are graded and checked according to the verification threshold to obtain a comprehensive detection result of the impact degree of wafer defects.

10. A wafer defect detection system based on image segmentation and image difference, characterized in that: The system comprises: A pixel difference processing unit, the pixel difference processing unit is used to perform pixel difference processing on the detection image of the wafer product and the template image to obtain a difference image; A penetration rate calculation unit, wherein the penetration rate calculation unit extracts grayscale values ​​of defective areas of the detection image and the template image based on the differential image to obtain defective grayscale values ​​and normal grayscale values, and calculates the penetration rate of the defective area according to the defective grayscale values ​​and the normal grayscale values; A line intersection positioning unit, the line intersection positioning unit is used to perform line segmentation processing on the inspection image of the wafer product to obtain a line segmentation image; and to perform intersection positioning on the line area of ​​the line segmentation image based on the differential image to obtain an intersection area image; A coverage ratio calculation unit, the coverage ratio calculation unit is used to perform geometric operations on the difference image and the intersection area image to obtain geometric parameters of the defect and the geometric parameters of the line, and calculate the coverage ratio of the defect area based on the geometric parameters of the defect and the geometric parameters of the line; A defect comprehensive detection unit is used to comprehensively determine the severity of the defect according to the penetration rate and coverage ratio of the defect area to obtain a comprehensive detection result of the impact degree of the wafer defect.

11. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the wafer defect detection method based on image segmentation and image difference as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for wafer defect detection based on image segmentation and image difference as described in any one of claims 1 to 9 is implemented.

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