Wafer microtube defect detection method and device, storage medium and computer equipment

Abstract

The invention discloses a wafer microtube defect detection method and device, a storage medium and computer equipment. The method comprises the following steps: acquiring a plurality of surface images corresponding to a wafer to be subjected to microtube defect detection under the same acquisition view angle; respectively determining the maximum gray value corresponding to each pixel point at the same position in the plurality of surface images, and determining a preprocessing image of the wafer area under the collection visual angle according to the maximum gray value of each pixel point at the position; performing microtube defect preliminary detection on the preprocessed image to obtain a suspected microtube defect area included in the preprocessed image; and for the surface image corresponding to each preset light source, determining a bright area and a dark area on the surface image, and verifying the suspected microtube defect area according to the bright area and the dark area of the surface image corresponding to each preset light source so as to determine whether the suspected microtube defect area is a real microtube defect area. According to the invention, rapid and efficient non-contact microtube defect detection can be carried out on the wafer, and the method is simple and easy to implement and high in automation degree.

Description

Technical Field

[0001] The present application relates to the technical field of semiconductor integrated circuit defect detection, and in particular to a method and device for detecting wafer micropipe defects, a storage medium, and a computer device. Background Art

[0002] Wafers are the basic raw materials for manufacturing semiconductor devices. The front-end manufacturing process of wafers includes multiple processes such as silicon ingot growth, cutting, polishing, and grinding. These processes are cumbersome and complicated, and the wafers may have defects such as scratches, edge collapse, and cracks during the process. Among them, micropipe defects mainly appear in the growth stage of silicon ingots. Micropipe defects may appear after the silicon ingots are cut after growth. Micropipe defects are a kind of defect that runs through the entire wafer product, and its size ranges from a few microns to tens of microns, large and small. The penetrating form of micropipe defects will directly affect the quality and subsequent yield of semiconductor products, and seriously affect the back-end process. Therefore, wafers need to be inspected after production and manufacturing to detect unqualified wafers in time and prevent them from flowing into subsequent processes.

[0003] In the prior art, when detecting micropipe defects on wafers, microscopic observation is mainly used. Inspectors can use a microscope to observe the surface of the wafer and measure the size, but this detection method requires manual observation, which is time-consuming and inefficient. In addition, the liquid penetration method can also be used. By taking advantage of the penetration characteristics of micropipe defects, the upper surface of the wafer is covered with liquid for detection, and the location and number of micropipe defects are determined by detecting whether there is liquid for detection on the lower surface. However, this method requires contact detection, which is easy to cause wafer contamination, and is also inefficient and not suitable for mass production. Summary of the invention

[0004] In view of this, the present application provides a method and device for detecting micropipe defects in wafers, a storage medium, and a computer device, which can perform fast, efficient, and non-contact micropipe defect detection on wafers under conventional imaging methods. This method is simple and easy to implement, and has a high degree of automation. At the same time, the detection scheme performs detection in the first process after the silicon ingot is cut, and realizes the control of micropipe defects in the front-end, thereby avoiding waste of resources in the wafer production stage.

[0005] According to one aspect of the present application, a method for detecting micropipe defects in a wafer is provided, comprising:

[0006] Acquire multiple surface images corresponding to the wafer to be inspected for micropipe defects under the same acquisition angle of view, wherein the multiple surface images include surface images acquired after each preset light source is turned on separately, and the setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect;

[0007] Determine respectively the maximum grayscale values ​​corresponding to the pixels at the same positions in the plurality of surface images, and determine the preprocessing image of the wafer area under the acquisition viewing angle according to the maximum grayscale values ​​of the pixels at each position;

[0008] Performing preliminary microtubule defect detection on the preprocessed image to obtain a suspected microtubule defect area included in the preprocessed image;

[0009] For the surface image corresponding to each preset light source, the bright area and the dark area on the surface image are determined, and each of the suspected microtube defect areas is verified based on the bright area and the dark area of ​​the surface image corresponding to each preset light source to determine whether the suspected microtube defect area is a real microtube defect area.

[0010] According to another aspect of the present application, a device for detecting micropipe defects in a wafer is provided, comprising:

[0011] A surface image acquisition module, used to acquire multiple surface images corresponding to the wafer to be inspected for micropipe defects under the same acquisition angle of view, wherein the multiple surface images include surface images acquired after each preset light source is turned on separately, and the setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect;

[0012] A pre-processing image generating module, used to respectively determine the maximum grayscale value corresponding to each pixel point at the same position in the plurality of surface images, and determine the pre-processing image of the wafer area under the acquisition viewing angle according to the maximum grayscale value of the pixel point at each position;

[0013] A preliminary defect detection module is used to perform preliminary micropipe defect detection on the preprocessed image to obtain a suspected micropipe defect area included in the preprocessed image;

[0014] The defect verification module is used to determine the bright area and the dark area on the surface image corresponding to each preset light source, and verify each suspected microtube defect area according to the bright area and the dark area of ​​the surface image corresponding to each preset light source to determine whether the suspected microtube defect area is a real microtube defect area.

[0015] According to another aspect of the present application, a storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned method for detecting wafer micropipe defects is implemented.

[0016] According to another aspect of the present application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the above-mentioned wafer micropipe defect detection method when executing the program.

[0017] By means of the above technical scheme, the present application provides a method and device for detecting micropipe defects on a wafer, a storage medium, and a computer device. First, a plurality of surface images corresponding to the same acquisition angle of view corresponding to the wafer to be detected for micropipe defects are obtained. Here, when the image acquisition device acquires the surface image, a preset light source is turned on separately each time, and the image acquisition device is controlled to acquire one or more surface images of the wafer, so that a plurality of surface images acquired by the wafer under each preset light source can be obtained. The setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect. After obtaining the plurality of surface images under each preset light source, the maximum grayscale value of each pixel at the same position in the plurality of surface images can be determined respectively, and then the pre-processing image of the wafer area under the acquisition angle of view of the acquisition of the surface image can be determined according to the maximum grayscale value of each pixel at each position. After obtaining the pre-processing image of the wafer area, the pre-processing image can be preliminarily detected for micropipe defects, so that the suspected micropipe defect area can be found from the pre-processing image. For the surface image corresponding to each preset light source acquired, the bright area and the dark area on the surface image are determined. After determining the bright and dark areas of the surface image under each preset light source, each suspected micropipe defect area in the preprocessing image can be verified according to the bright and dark areas of the surface image under each preset light source to determine whether the suspected micropipe defect area is bright or dark in the surface image of the preset light source. Finally, according to the corresponding light and dark judgment results under each preset light source, determine whether each suspected micropipe defect area is a real micropipe defect area. The embodiment of the present application can perform fast, efficient, and non-contact micropipe defect detection on wafers under conventional imaging methods. This method is simple and easy to implement with a high degree of automation. At the same time, the detection scheme performs detection in the first process after the silicon ingot is cut, and realizes the control of micropipe defects in the front-end, thereby avoiding waste of resources in the wafer production stage.

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0020] Figure 1 A schematic flow chart of a method for detecting micropipe defects on a wafer provided in an embodiment of the present application is shown;

[0021] Figure 2A top view showing a configuration method of a preset light source provided in an embodiment of the present application is shown;

[0022] Figure 3 A front view showing a setting method of a preset light source provided in an embodiment of the present application is shown;

[0023] Figure 4 shows the surface image corresponding to the light source 1 provided in the embodiment of the present application;

[0024] Figure 5 shows the surface image corresponding to the light source 2 provided in the embodiment of the present application;

[0025] Figure 6 shows the surface image corresponding to the light source 3 provided in the embodiment of the present application;

[0026] Figure 7 shows the surface image corresponding to the light source 4 provided in the embodiment of the present application;

[0027] Figure 8 An initial preprocessing diagram provided by an embodiment of the present application is shown;

[0028] Fig. 9 A schematic structural diagram of a wafer micropipe defect detection device provided in an embodiment of the present application is shown;

[0029] Fig.10 A schematic diagram of the device structure of a computer device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0030] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0031] In this embodiment, a method for detecting micro-pipe defects in a wafer is provided. Figure 1 As shown, the method includes:

[0032] Step 101, obtaining multiple surface images under the same acquisition angle corresponding to the wafer to be inspected for micropipe defects, wherein the multiple surface images include surface images acquired after each preset light source is turned on separately, and the setting position of each preset light source relative to the wafer is determined based on the physical properties of the micropipe defects.

[0033] A method for detecting micropipe defects on a wafer provided in an embodiment of the present application can automatically identify whether a wafer has a micropipe defect without contacting the wafer. Before performing micropipe defect detection on a wafer, an image acquisition device is set on one side of the wafer, and a plurality of preset light sources are set on the other side; or the image acquisition device and the plurality of preset light sources are set on the same side of the wafer. Among them, the setting position of the preset light source relative to the wafer can be determined according to the physical characteristics of the micropipe defect, so that by setting the preset light source at different positions, and the image acquisition device only turns on one preset light source at a time when collecting the surface image of the wafer, so that it can be determined whether the through defect is a micropipe defect based on the collected surface image later. It should be noted that one side and the other side of the wafer refer to the upper and lower surfaces of the wafer. When the preset light source and the image acquisition device are arranged on both sides of the wafer, if the preset light source is arranged on the upper surface side of the wafer, then the image acquisition device is arranged on the lower surface side of the wafer; if the preset light source is arranged on the lower surface side of the wafer, then the image acquisition device is arranged on the upper surface side of the wafer; when the preset light source and the image acquisition device are arranged on the same side of the wafer, the distance between the preset light source and the image acquisition device and the same surface of the wafer can be determined according to actual conditions, and is not limited here. Specifically, multiple surface images of the wafer can be acquired by the same image acquisition device, and the position of the image acquisition device relative to the wafer remains unchanged, so that the acquisition angle corresponding to the surface image acquired each time is the same. When the image acquisition device acquires the surface image, a preset light source is turned on separately each time, and the image acquisition device is controlled to acquire one or more surface images of the wafer, so that multiple surface images of the wafer acquired under each preset light source can be obtained. For example, if there are 4 preset light sources, then the multiple surface images acquired by the image acquisition device include at least 4. In one embodiment, the image acquisition device can be a linear array camera image sensor or a planar array camera image sensor. When it is a linear array camera image sensor or an area array camera image sensor, the collected surface image may be a grayscale image or a color image. Since the subsequent image processing is performed on the surface image, if the surface image is a color image, the color image can be converted into a grayscale image before performing subsequent operations.

[0034] Step 102, respectively determining the maximum grayscale values ​​corresponding to the pixels at the same position in the plurality of surface images, and determining a preprocessing image of the wafer area under the acquisition viewing angle according to the maximum grayscale values ​​of the pixels at each position.

[0035] In this embodiment, after obtaining multiple surface images under each preset light source, the maximum grayscale value of each pixel at the same position in the multiple surface images can be determined respectively, and then the pre-processing image of the wafer area under the acquisition viewing angle of the surface image can be determined according to the maximum grayscale value of each pixel at each position.i ,y i ), since the acquisition angles of multiple surface images are the same, the pixel point (x i ,y i ), and determine the pixel point (x i ,y i ) in different surface images, and the maximum gray value among these gray values ​​is taken as the pixel point (x i ,y i ) in the grayscale value of the pre-processing image. Here, due to the circular shape of the wafer, when the image acquisition device acquires the surface image of the wafer, some surface images under some acquisition viewing angles may be partly images of the wafer area, and the remaining part is images of the wafer placement surface area. Since the micropipe defects on the wafer are to be analyzed, it is only necessary to determine the pre-processing image of the wafer area.

[0036] Step 103 , performing preliminary detection of micropipe defects on the preprocessed image to obtain suspected micropipe defect regions included in the preprocessed image.

[0037] In this embodiment, after obtaining the pre-processing image of the wafer area, the pre-processing image can be subjected to a preliminary detection of micropipe defects, so that a suspected micropipe defect area can be found from the pre-processing image. Here, the suspected micropipe defect area can be a bright spot area in the pre-processing image, indicating a through defect. Because the micropipe defect itself is a through defect, the suspected micropipe defect area is first screened out according to the bright spot area in the pre-processing image, and then it is judged which are the real micropipe defect areas from the suspected micropipe defect areas.

[0038] Step 104, for each surface image corresponding to the preset light source, determine the bright area and the dark area on the surface image, and verify each of the suspected micropipe defect areas based on the bright area and the dark area of ​​the surface image corresponding to each preset light source to determine whether the suspected micropipe defect area is a real micropipe defect area.

[0039] In this embodiment, for each surface image corresponding to the preset light source obtained, the bright area and the dark area on the surface image are determined. Among them, when there are multiple surface images corresponding to a preset light source, these surface images can be merged first to obtain a merged surface image, and then the bright area and the dark area are determined according to the merged surface image; when there is only one surface image corresponding to a preset light source, the bright area and the dark area of ​​the surface image can be directly determined. After determining the bright area and the dark area of ​​the surface image under each preset light source, each suspected microtubule defect area in the preprocessing image can be verified according to the bright area and the dark area of ​​the surface image under each preset light source to determine whether the suspected microtubule defect area is bright or dark in the surface image of the preset light source, and finally, according to the corresponding light and dark judgment results under each preset light source, it is determined whether each suspected microtubule defect area is a real microtubule defect area.

[0040] By applying the technical solution of this embodiment, first, multiple surface images corresponding to the same acquisition angle of view corresponding to the wafer to be tested for micropipe defects are obtained. Here, when the image acquisition device performs surface image acquisition, a preset light source is turned on separately each time, and the image acquisition device is controlled to acquire one or more surface images of the wafer, so that multiple surface images of the wafer acquired under each preset light source can be obtained. The setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect. After obtaining multiple surface images under each preset light source, the maximum grayscale value of each pixel at the same position in the above multiple surface images can be determined respectively, and then the pre-processing image of the wafer area under the acquisition angle of view for acquiring the above surface image can be determined according to the maximum grayscale value of the pixel at each position. After obtaining the pre-processing image of the wafer area, the pre-processing image can be preliminarily detected for micropipe defects, so that the suspected micropipe defect area can be found from the pre-processing image. For the surface image corresponding to each preset light source acquired, the bright area and the dark area on the surface image are determined. After determining the bright and dark areas of the surface image under each preset light source, each suspected micropipe defect area in the preprocessing image can be verified according to the bright and dark areas of the surface image under each preset light source to determine whether the suspected micropipe defect area is bright or dark in the surface image of the preset light source. Finally, according to the corresponding light and dark judgment results under each preset light source, determine whether each suspected micropipe defect area is a real micropipe defect area. The embodiment of the present application can perform fast, efficient, and non-contact micropipe defect detection on wafers under conventional imaging methods. This method is simple and easy to implement with a high degree of automation. At the same time, the detection scheme performs detection in the first process after the silicon ingot is cut, and realizes the control of micropipe defects in the front-end, thereby avoiding waste of resources in the wafer production stage.

[0041] In an embodiment of the present application, optionally, the image acquisition device setting surface and the preset light source setting surface are distributed on both sides or the same side of the wafer, the preset light source is set on the preset light source setting surface, the distance between each preset light source and the projection point of the center of the wafer on the preset light source setting surface is the same, the angle between the line between each two adjacent preset light sources and the projection point is 90°, the irradiation direction of each preset light source is toward the wafer, and the angle formed between the irradiation direction of each preset light source and the wafer surface is equal.

[0042] In this embodiment, the wafer includes an upper and lower surface. Specifically, an image acquisition device setting surface can be determined on the outside of one surface of the wafer, and a preset light source setting surface can be determined on the outside of the other surface of the wafer. That is, the image acquisition device setting surface and the preset light source setting surface are distributed on both sides of the upper and lower surfaces of the wafer. In addition, the image acquisition device setting surface and the preset light source setting surface can also be set on the same side of the wafer surface. The image acquisition device can be set on the image acquisition device setting surface, and the preset light source can be set on the preset light source setting surface. The center of the wafer can be projected on the preset light source setting surface, and the distance between each preset light source and the projection point of the wafer center on the preset light source setting surface is equal, and the angle formed by the line between each two adjacent preset light sources and the above-mentioned projection points is 90 degrees, that is, four preset light sources are arranged on the preset light source setting surface. In addition, the irradiation direction of each preset light source is toward the wafer, and the angles formed between the irradiation directions of different preset light sources and the wafer surface are equal.

[0043] like Figure 2 As shown, a setting method of a preset light source is shown. Figure 2 It is a top view, and 4 preset light sources are set on a preset light source setting plane that is different from the upper and lower surfaces of the wafer, with setting angles of 0°, 90°, 180° and 270° respectively. It should be noted that the above angles are only relative angles, and the 0° direction can be set arbitrarily. The distance between each preset light source and the projection point of the wafer center on the preset light source setting plane is equal, and the angle formed by the line connecting every two adjacent preset light sources and the above projection points is 90 degrees. Figure 3 As shown, Figure 2 The main view of the setup mode, where Figure 3Only two preset light sources are shown, namely light source 1 and light source 3. The angle formed between each preset light source and the wafer surface is α, and the irradiation angle of the light source is toward the wafer. In the embodiment of the present application, a preset light source is set at each of the four angles. Each time a preset light source is turned on separately, an image is collected by an image acquisition device. This is because micropipe defects are through-defects. In order to capture micropipe defects, images are collected from four angles. Different angles will have different changes in brightness and darkness. This feature can be used to distinguish micropipe defects from other defects. At the same time, when only one surface image is collected under each preset light source, because the four surface images are only the changes of the preset light source, the image acquisition device does not move, so a group of surface images are obtained, and the position of each surface image is consistent and corresponding, and there is no offset, which is convenient for subsequent further processing.

[0044] In an embodiment of the present application, optionally, step 102 includes: respectively determining the maximum grayscale value corresponding to each pixel point at the same position in the multiple surface images, and obtaining an initial preprocessing image based on the maximum grayscale value of the pixel point at each position; selecting a target surface image from the multiple surface images, and for each pixel point in the target surface image, determining the relationship between the grayscale value corresponding to the pixel point in the target surface image and a first preset grayscale threshold and a second preset grayscale threshold, if the grayscale value is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, taking the pixel point as the first target pixel point, and determining the wafer area corresponding to the target surface image based on the first target pixel point, wherein the first preset grayscale threshold is less than the second preset grayscale threshold; aligning the initial preprocessing image with the target surface image, and intercepting the initial preprocessing image based on the wafer area in the target surface image to obtain a preprocessing image of the wafer area under the acquisition viewing angle.

[0045] In this embodiment, the preprocessing image of the wafer area under the acquisition viewing angle can be obtained in the following manner. First, in multiple surface images, for each pixel at the same position, the grayscale value of the pixel in each surface image is determined, and then the maximum grayscale value is determined from these grayscale values. Then, based on the maximum grayscale value of the pixel at each position, an initial preprocessing image is generated. This image reflects the maximum brightness or grayscale performance of the pixel at each position in all surface images. Figure 4 to Figure 7 As shown, Figure 2 In the preset light source setting mode, the surface image under each preset light source captured by the image acquisition device, Figure 8 is the initial pre-processed image obtained based on these four surface images. The gray area in these images is the wafer area.

[0046] Next, one of the multiple surface images is selected as the target surface image. Here, the target surface image can be any one of the multiple surface images, or a surface image selected based on factors such as image quality and clarity. Since the acquisition angles corresponding to the multiple surface images are the same, and only the preset light sources turned on are different, the wafer areas captured in the above surface images are the same. For each pixel in the target surface image, check whether its grayscale value is between two preset grayscale thresholds. Here, the two preset grayscale thresholds include a first preset grayscale threshold and a second preset grayscale threshold, and the first preset grayscale threshold is less than the second preset grayscale threshold. If the grayscale value of a pixel is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, the pixel is marked as a first target pixel. Subsequently, the wafer area in the target surface image is jointly formed according to the first target pixel selected. Afterwards, the initial preprocessing image generated previously is registered with the target surface image. Among them, registration refers to aligning two or more images in spatial position. After registration, the initial preprocessing image can be intercepted according to the wafer area determined in the target surface image, and only the part of the initial preprocessing image corresponding to the wafer area is retained, thereby obtaining a preprocessing image of the wafer area under the acquisition viewing angle. The embodiment of the present application synthesizes the initial preprocessing image by the maximum grayscale value of the pixel points at the same position in multiple surface images, so that the initial preprocessing image includes "bright spots" under the illumination angles of each preset light source, so that the initial preprocessing image effectively includes all through-defect areas, that is, includes all potential areas where micropipe defects may exist. Afterwards, the initial preprocessing image is intercepted using the wafer area of ​​the target surface image to obtain a preprocessing image of the wafer area. The micropipe defects are subsequently identified from the preprocessing image of the wafer area, which can effectively reduce the micropipe defect recognition range, thereby improving the accuracy and efficiency of micropipe defect recognition.

[0047] In an embodiment of the present application, optionally, step 102 includes: selecting a target surface image from multiple surface images, and for each pixel in the target surface image, determining the relationship between the grayscale value corresponding to the pixel in the target surface image and a first preset grayscale threshold and a second preset grayscale threshold; if the grayscale value is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, taking the pixel as the first target pixel, and determining the wafer area corresponding to the target surface image according to the first target pixel, wherein the first preset grayscale threshold is less than the second preset grayscale threshold; according to the wafer area corresponding to the target surface image, intercepting each surface image to obtain a surface image containing only the wafer area, and according to the maximum grayscale value corresponding to the pixel at the same position in the multiple surface images containing only the wafer area, obtaining a preprocessing image of the wafer area under the acquisition viewing angle.

[0048] In this embodiment, the preprocessing image of the wafer area under the acquisition viewing angle can also be obtained in the following manner. First, one of the multiple surface images is selected as the target surface image. Here, the target surface image can be any one of the multiple surface images, or a surface image selected based on factors such as image quality and clarity. Since the acquisition viewing angles corresponding to the multiple surface images are the same, only the preset light sources turned on are different, so the wafer area photographed in the above surface images is the same. For each pixel in the target surface image, check whether its grayscale value is between two preset grayscale thresholds. Here, the two preset grayscale thresholds include a first preset grayscale threshold and a second preset grayscale threshold, and the first preset grayscale threshold is less than the second preset grayscale threshold. If the grayscale value of a pixel is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, the pixel is marked as a first target pixel. Subsequently, the wafer area in the target surface image is jointly formed according to the first target pixel selected. Afterwards, the wafer area in the target surface image is used as a template or reference to intercept each surface image. Specifically, each surface image is registered with the target surface image, and then the portion corresponding to the wafer area in the target surface image is extracted from each surface image. In this way, multiple surface images containing only the wafer area can be obtained. For these surface images containing only the wafer area, for each pixel at the same position, the grayscale value of the pixel in the above-mentioned images is determined, and the maximum grayscale value is further determined from these grayscale values. According to the maximum grayscale value of the pixel at each position, a preprocessing map of the wafer area can be generated. This preprocessing map reflects the maximum brightness or grayscale performance of the pixel at each position in the wafer area under the acquisition viewing angle. The embodiment of the present application synthesizes the preprocessing map of the wafer area by the maximum grayscale value of the pixel at the same position in multiple surface images that only include the wafer area, so that the preprocessing map of the wafer area includes "bright spots" under the illumination angles of each preset light source, so that the preprocessing map effectively includes all through-defect areas, that is, includes all potential areas where micropipe defects may exist. The embodiment of the present application identifies micropipe defects from a pre-processed image of a wafer area, which can effectively reduce the micropipe defect identification range, thereby improving the accuracy and efficiency of micropipe defect identification.

[0049] In the above embodiment, the first preset grayscale threshold and the second preset grayscale threshold may be determined empirically, and may be determined specifically by counting the grayscale values ​​of the pixels corresponding to the wafer region in the surface image of the wafer. That is, the first preset grayscale threshold and the second preset grayscale threshold are used to distinguish the background from the foreground in the surface image, that is, to extract the wafer region in the surface image.

[0050] In an embodiment of the present application, optionally, step 103 includes: performing mean filtering on the preprocessed image to obtain a mean filtered image; subtracting the grayscale value of the corresponding pixel in the preprocessed image from the grayscale value of each pixel in the mean filtered image to obtain the grayscale difference corresponding to each pixel, and obtaining a difference image based on the grayscale difference corresponding to each pixel; for each pixel in the difference image, determining the relationship between the grayscale value corresponding to the pixel in the difference image and a third preset grayscale threshold, and taking the pixel whose grayscale value is greater than the third preset grayscale threshold as the second target pixel, and taking the area composed of the second target pixel as the suspected microtubule defect area.

[0051] In this embodiment, after obtaining the pre-processed image corresponding to the wafer area, the pre-processed image can be subjected to mean filtering to obtain a mean filtered image. Mean filtering is a technique for smoothing an image, which reduces the noise in the image by replacing the value of each pixel in the image with the average value of the pixel values ​​around it, so that the image can be smoothed and the influence of random noise on subsequent steps can be reduced. Afterwards, the grayscale value of each pixel in the mean filtered image is subtracted from the grayscale value of the corresponding pixel in the pre-processed image, and then the grayscale difference of each pixel can be obtained. Through this operation, the difference between the smoothed image and the initial pre-processed image can be calculated. After obtaining the grayscale difference corresponding to each pixel, a difference image can be further generated based on these grayscale differences. The grayscale value of each pixel in the difference image represents the grayscale difference between the pre-processed image and the mean filtered image at the pixel. Then, for each pixel in the difference image, the size relationship between its grayscale value and the third preset grayscale threshold is compared. If the gray value of a certain pixel is greater than the third preset gray threshold, it is considered that this pixel may be caused by a microtube defect, because microtube defects usually cause large gray changes in local areas of the image. Afterwards, this pixel can be marked as a second target pixel. The area composed of all second target pixels is regarded as a suspected microtube defect area. It should be noted that the above-mentioned second target pixel may constitute a plurality of unconnected areas, so each area can be used as a suspected microtube defect area at this time, so that all suspected microtube defect areas included in the preprocessing image can be obtained. In addition, the third preset gray threshold can also be determined based on experience, or after a large number of surface images are processed according to the above steps to obtain a difference map, it is determined by counting the gray values ​​of the pixels running through the area in the difference map, which is used to determine the suspected microtube defect detection area from the difference map. The embodiment of the present application identifies possible microtube defect areas by judging the size relationship between the gray value of the pixel point in the difference map and the third preset gray threshold, which can greatly improve the detection accuracy of the suspected microtube defect area.

[0052] In an embodiment of the present application, optionally, when the surface image corresponding to any preset light source includes only one, the "for each surface image corresponding to the preset light source, determine the bright area and the dark area on the surface image" in step 104 includes: for each pixel point in the surface image corresponding to the any preset light source, determine the relationship between the grayscale value of the pixel point in the surface image corresponding to the any preset light source and a fourth preset grayscale threshold and a fifth preset grayscale threshold; if the grayscale value is greater than the fourth preset grayscale threshold and less than the fifth preset grayscale threshold, take the pixel point as the third target pixel point, determine the bright area of ​​the surface image corresponding to the any preset light source according to the third target pixel point, and take the remaining area as the dark area, wherein the fourth preset grayscale threshold is less than the fifth preset grayscale threshold.

[0053] In this embodiment, the surface image corresponding to a preset light source or some preset light sources may be one. For a preset light source that only includes one surface image, for each pixel in the surface image, the relationship between its grayscale value and two preset grayscale thresholds is determined, where the two preset grayscale thresholds may include a fourth preset grayscale threshold and a fifth preset grayscale threshold, and the fourth preset grayscale threshold is less than the fifth preset grayscale threshold. For each pixel in the surface image, if the grayscale value of a pixel in the surface image is greater than the fourth preset grayscale threshold and less than the fifth preset grayscale threshold, then the pixel is regarded as a third target pixel. It should be noted that the fourth preset grayscale threshold and the fifth preset grayscale threshold may be determined based on experience or based on historical surface images, and setting the fourth preset grayscale threshold and the fifth preset grayscale threshold is used to extract bright areas and dark areas from the surface image. By setting the fourth preset grayscale threshold and the fifth preset grayscale threshold, the grayscale value of the pixel in the micropipe defect area can be limited, so that the extracted bright area is closer to the "bright spot" corresponding to the micropipe defect. Afterwards, the bright area in the surface image is determined based on all third target pixels. The remaining area (i.e., the area composed of pixels whose grayscale values ​​are not between the fourth preset grayscale threshold and the fifth preset grayscale threshold) is regarded as a dark area. The embodiment of the present application compares the relationship between the grayscale value of each pixel in the surface image and the fourth preset grayscale threshold and the fifth preset grayscale threshold, classifies the pixels into third target pixels and other pixels, determines the bright area of ​​the surface image according to the third target pixel, and regards the remaining area as a dark area, so as to effectively extract the "bright spot" in the surface image caused by micropipe defects.

[0054] In an embodiment of the present application, optionally, when the surface images corresponding to any preset light source include multiple images, before the "for each pixel point in the surface image corresponding to any preset light source, determining the relationship between the grayscale value of the pixel point in the surface image corresponding to any preset light source and the fourth preset grayscale threshold and the fifth preset grayscale threshold", the method also includes: merging the multiple surface images corresponding to any preset light source according to the maximum grayscale value of the pixel points at the same position in the multiple surface images corresponding to any preset light source to replace the surface image.

[0055] In this embodiment, some surface images corresponding to the preset light sources may include multiple images. In this case, the multiple surface images may be merged first, and then the bright area and the dark area may be extracted from the merged surface image. Specifically, if the surface images corresponding to a preset light source include multiple images, then for each pixel at the same position in these surface images, the grayscale value of the pixel in the multiple surface images corresponding to the preset light source is determined, and the maximum value of these grayscale values ​​is found. Using the maximum grayscale value found above, the multiple surface images are merged to obtain a merged surface image, and then the merged surface image is used to extract the subsequent bright area and the dark area. Specifically, for the merged surface image, the relationship between the grayscale value of each pixel in the surface image and two preset grayscale thresholds is determined, where the two preset grayscale thresholds may include a fourth preset grayscale threshold and a fifth preset grayscale threshold, and the fourth preset grayscale threshold is less than the fifth preset grayscale threshold. For each pixel in the merged surface image, if the grayscale value of a pixel in the surface image is greater than the fourth preset grayscale threshold and less than the fifth preset grayscale threshold, then the pixel is regarded as a third target pixel. Subsequently, the bright area in the merged surface image is determined based on all the third target pixels, and the remaining area in the merged surface image is used as the dark area. In the embodiment of the present application, when there are multiple surface images corresponding to a preset light source, the multiple surface images are merged according to the maximum grayscale value of the pixels at the same position, which can improve the accuracy of bright area extraction of the surface image under the preset light source, and thus improve the detection accuracy of micropipe defects.

[0056] In an embodiment of the present application, optionally, the step 104 of "verifying each suspected microtube defect area according to the bright area and the dark area of ​​the surface image corresponding to each preset light source" includes: for each suspected microtube defect area included in the preprocessing image, determining a target light source from each preset light source, and registering the surface image corresponding to the target light source with the preprocessing image, finding the intersection between the bright area of ​​the registered surface image and the suspected microtube defect area to obtain a first intersection area, and finding the intersection between the dark area of ​​the registered surface image and the suspected microtube defect area to obtain a second intersection area; calculating the ratio between the first intersection area and the suspected microtube defect area to obtain a first ratio, and When the first ratio is greater than a preset threshold, the number of bright times corresponding to the target light source is counted up by one, and the ratio between the second intersection area and the suspected micropipe defect area is calculated to obtain a second ratio, and when the second ratio is greater than the preset threshold, the number of dark times corresponding to the target light source is counted up by one; the target light source is eliminated from the preset light sources, and the process returns to the step of determining the target light source from the preset light sources until all the preset light sources are eliminated, and the bright time count results corresponding to the preset light sources are summed, and the dark time count results are summed, and when the sum of the bright times is greater than 0, and the sum of the dark times is greater than 1, it is determined that the suspected micropipe defect area is a real micropipe defect area.

[0057] In this embodiment, each suspected micropipe defect area in the preprocessing image can be verified by using the bright area and dark area of ​​the surface image under each preset light source to determine whether the suspected micropipe defect area is a real micropipe defect area. First, any one of the preset light sources can be selected as the target light source, and then the surface image corresponding to the target light source is registered with the preprocessing image so that the surface image corresponding to the target light source and the wafer area in the preprocessing image overlap in space. Here, when the surface image of the target light source includes only one, the surface image can be directly used to register with the preprocessing image; when the surface image of the target light source includes multiple images, the surface image after the surface images are merged can be used to register with the preprocessing image.

[0058] After the registration process, for each suspected microtubule defect region in the preprocessing image, the intersection between the suspected microtubule defect region and the bright region of the surface image can be calculated, and then the first intersection region can be obtained. At the same time, the intersection between the suspected microtubule defect region and the dark region of the surface image can be calculated, and then the second intersection region can be obtained. After that, the ratio between the first intersection region and the suspected microtubule defect region is calculated to obtain a first ratio. If the first ratio is greater than a preset threshold, it means that the overlap between the suspected microtubule defect region and the bright region in the surface image corresponding to the target light source meets the requirement, that is, the suspected microtubule defect region is bright in the surface image corresponding to the target light source, and then the bright count corresponding to the target light source can be increased by 1, that is, the bright count is changed from 0 to 1. Similarly, the ratio between the second intersection area and the suspected micropipe defect area is calculated to obtain a second ratio. If the second ratio is greater than the above-mentioned preset threshold, it means that the part of the suspected micropipe defect area overlapping with the dark area in the surface image corresponding to the target light source meets the requirement, that is, the suspected micropipe defect area is dark in the surface image corresponding to the target light source, then the dark count corresponding to the target light source can be added by 1, that is, the dark count is changed from 0 to 1. At this time, the verification corresponding to the target light source is completed, and the target light source can be removed from the preset light sources. Afterwards, one is selected from the remaining preset light sources as the target light source again, and the above steps are repeated until all preset light sources have been processed, and the bright count and dark count corresponding to each preset light source are obtained. Then, the bright counts of all preset light sources are summed to obtain the bright count sum result; at the same time, the dark counts of all preset light sources are summed to obtain the dark count sum result. If the bright count sum result is greater than 0, and the dark count sum result is greater than 1, it is determined that the suspected micropipe defect area is a real micropipe defect area.

[0059] For example, for the suspected microtube defect region 1 in the preprocessing image, the first intersection area between the suspected microtube defect region 1 and the bright area of ​​the target light source can be calculated, and then the first ratio between the first intersection area and the suspected microtube defect region 1 is calculated. After judgment, it is found that the first ratio is greater than a preset threshold (assuming it is 0.7), then the bright number count corresponding to the target light source is increased by 1. At the same time, the second intersection area between the suspected microtube defect region 1 and the dark area of ​​the target light source is calculated, and then the second ratio between the second intersection area and the suspected microtube defect region 1 is calculated. After judgment, it is found that the second ratio is less than the preset threshold (the above 0.7), then the dark number corresponding to the target light source is still 0. Then use the same method to calculate the bright count and dark count of the suspected microtubule defect area 1 under the remaining preset light sources: assuming that there are 4 preset light sources, the dark count under the remaining two preset light sources is 1, and the bright count is 0; the bright count and dark count under the remaining one preset light source are both 0, then the total bright count of the suspected microtubule defect area under the four preset light sources is 1, and the total dark count is 2, which means that the suspected microtubule defect area 1 is a real microtubule defect area. For each suspected microtubule defect area, the above method can be used for verification. The embodiment of the present application is as follows Figure 2 When the preset light source is set in a certain manner, the physical property of the micropipe defect penetrating the wafer is utilized. When imaging under four preset light sources, the micropipe defect will inevitably appear bright under at least one preset light source and dark under two preset light sources. Based on this feature, the real micropipe defect area can be quickly identified from multiple suspected micropipe defect areas.

[0060] In an embodiment of the present application, optionally, after the "verifying each of the suspected microtubule defect regions" in step 104, the method further includes: when the suspected microtubule defect region is a real microtubule defect region, marking the suspected microtubule defect region with a first marker in the preprocessing image; otherwise, marking the suspected microtubule defect region with a second marker.

[0061] In this embodiment, once the suspected microtubule defect area is confirmed as a real microtubule defect area, the first mark can be used to mark it in the preprocessing diagram so that subsequent processing or analysis can quickly identify these real microtubule defect areas. Specifically, the first mark can be a color mark, a frame mark, etc. For those suspected microtubule defect areas that are not real microtubule defect areas, a second mark can be used for marking processing to prompt relevant staff to perform subsequent evaluation and analysis of the real defects corresponding to these suspected microtubule defect areas. The embodiment of the present application uses different marks to mark the real microtubule defect areas and the remaining suspected microtubule defect areas in the preprocessing diagram, which not only helps to quickly identify the real microtubule defect areas and the remaining suspected microtubule defect areas, but also helps to accurately and efficiently perform subsequent processing steps (such as defect analysis, repair suggestions, report generation, etc.).

[0062] In an embodiment of the present application, optionally, before step 101, the method further includes: for each of the preset light sources, controlling the preset light source to turn on, and controlling the image acquisition device to acquire the surface image of the wafer, inputting the surface image of the wafer into a control parameter calculation model, obtaining the image acquisition control parameters of the image acquisition device, and recording the image acquisition control parameters corresponding to the preset light source; accordingly, the method further includes: in response to a detection instruction for micropipe defects on a wafer, turning on one preset light source at a time in a preset order, adjusting the preset parameters of the image acquisition device based on the image acquisition control parameters corresponding to the turned-on preset light source, and controlling the image acquisition device to acquire the surface image corresponding to the wafer after the adjustment.

[0063] In this embodiment, for each preset light source, after a preset light source is turned on separately, the image acquisition device can be controlled to acquire the surface image of the wafer. The acquired wafer surface image is then input into a control parameter calculation model. The model can be obtained based on machine learning or deep learning training, and the optimal image acquisition control parameters are calculated by analyzing the information in the surface image (such as brightness, contrast, clarity, etc.). These image acquisition control parameters may include the exposure time, gain, white balance, etc. of the camera, and these parameters jointly determine the quality and characteristics of the acquired image. After calculating the optimal image acquisition control parameters, the image acquisition control parameters under the preset light source can be recorded. In this way, in the subsequent wafer micropipe defect detection process, the optimal image acquisition control parameters can be quickly selected according to the light source number, thereby improving the detection efficiency.

[0064] After recording the optimal image acquisition control parameters corresponding to each preset light source, when a detection instruction for wafer micropipe defects is received, one preset light source can be turned on each time in a preset order. For the currently turned-on preset light source, the preset parameters of the image acquisition device can be adjusted based on the previously recorded image acquisition control parameters, thereby ensuring that the image quality captured under the lighting conditions of the current preset light source is optimal. After adjusting the preset parameters of the image acquisition device, the image acquisition device is controlled to capture the surface image of the wafer. The embodiment of the present application automatically adjusts the image acquisition control parameters of the image acquisition device for different preset light source activation environments, thereby ensuring that the captured image quality is optimal, thereby improving the subsequent detection accuracy and efficiency of wafer micropipe defects.

[0065] Further, as Figure 1 The specific implementation of the method, the embodiment of the present application provides a device for detecting micro-pipe defects in a wafer, such as Fig. 9 As shown, the device comprises:

[0066] A surface image acquisition module, used to acquire multiple surface images corresponding to the wafer to be inspected for micropipe defects under the same acquisition angle of view, wherein the multiple surface images include surface images acquired after each preset light source is turned on separately, and the setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect;

[0067] A pre-processing image generating module, used to respectively determine the maximum grayscale value corresponding to each pixel point at the same position in the plurality of surface images, and determine the pre-processing image of the wafer area under the acquisition viewing angle according to the maximum grayscale value of the pixel point at each position;

[0068] A preliminary defect detection module is used to perform preliminary micropipe defect detection on the preprocessed image to obtain a suspected micropipe defect area included in the preprocessed image;

[0069] The defect verification module is used to determine the bright area and the dark area on the surface image corresponding to each preset light source, and verify each suspected microtube defect area according to the bright area and the dark area of ​​the surface image corresponding to each preset light source to determine whether the suspected microtube defect area is a real microtube defect area.

[0070] Optionally, the image acquisition device setting surface and the preset light source setting surface are distributed on both sides or the same side of the wafer, the preset light source is set on the preset light source setting surface, the distance between each preset light source and the projection point of the center of the wafer on the preset light source setting surface is the same, the angle between the line between each two adjacent preset light sources and the projection point is 90°, the irradiation direction of each preset light source is toward the wafer, and the angle formed between the irradiation direction of each preset light source and the wafer surface is equal.

[0071] Optionally, the preprocessing graph generating module is used to:

[0072] Determine the maximum grayscale value corresponding to each pixel at the same position in the plurality of surface images respectively, and obtain an initial preprocessing image according to the maximum grayscale value of the pixel at each position;

[0073] Selecting a target surface image from the plurality of surface images, determining for each pixel in the target surface image a relationship between a grayscale value corresponding to the pixel in the target surface image and a first preset grayscale threshold and a second preset grayscale threshold, if the grayscale value is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, taking the pixel as a first target pixel, and determining a wafer area corresponding to the target surface image according to the first target pixel, wherein the first preset grayscale threshold is less than the second preset grayscale threshold;

[0074] The initial preprocessed image is registered with the target surface image, and the initial preprocessed image is intercepted according to the wafer area in the target surface image to obtain a preprocessed image of the wafer area under the acquisition viewing angle.

[0075] Optionally, the preprocessing graph generating module is used to:

[0076] Selecting a target surface image from the plurality of surface images, determining for each pixel in the target surface image a relationship between a grayscale value corresponding to the pixel in the target surface image and a first preset grayscale threshold and a second preset grayscale threshold, if the grayscale value is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, taking the pixel as a first target pixel, and determining a wafer area corresponding to the target surface image according to the first target pixel, wherein the first preset grayscale threshold is less than the second preset grayscale threshold;

[0077] According to the wafer area corresponding to the target surface image, each surface image is intercepted and processed to obtain a surface image containing only the wafer area, and according to the maximum grayscale value corresponding to the pixel points at the same position in multiple surface images containing only the wafer area, a preprocessing image of the wafer area under the acquisition viewing angle is obtained.

[0078] Optionally, the defect preliminary detection module is used to:

[0079] Performing mean filtering on the preprocessed image to obtain a mean filtered image;

[0080] Subtract the grayscale value of the corresponding pixel in the preprocessing image from the grayscale value of each pixel in the mean filtering image to obtain the grayscale difference corresponding to each pixel, and obtain a difference image according to the grayscale difference corresponding to each pixel;

[0081] For each pixel point in the difference map, determine the relationship between the grayscale value corresponding to the pixel point in the difference map and the third preset grayscale threshold, and take the pixel points with grayscale values ​​greater than the third preset grayscale threshold as the second target pixel points, and take the area formed by the second target pixel points as the suspected microtube defect area.

[0082] Optionally, when there is only one surface image corresponding to any preset light source, the defect verification module is used to:

[0083] For each pixel point in the surface image corresponding to any one of the preset light sources, determine the relationship between the grayscale value of the pixel point in the surface image corresponding to any one of the preset light sources and the fourth preset grayscale threshold and the fifth preset grayscale threshold; if the grayscale value is greater than the fourth preset grayscale threshold and less than the fifth preset grayscale threshold, take the pixel point as the third target pixel point, determine the bright area of ​​the surface image corresponding to any one of the preset light sources based on the third target pixel point, and take the remaining area as the dark area, wherein the fourth preset grayscale threshold is less than the fifth preset grayscale threshold.

[0084] Optionally, when the surface images corresponding to any preset light source include multiple images, the device further includes:

[0085] An image merging module is used to, for each pixel point in the surface image corresponding to any preset light source, determine the relationship between the grayscale value of the pixel point in the surface image corresponding to any preset light source and the fourth preset grayscale threshold and the fifth preset grayscale threshold, and then merge the multiple surface images corresponding to any preset light source according to the maximum grayscale value of the pixel points at the same position in the multiple surface images corresponding to any preset light source to replace the surface image.

[0086] Optionally, the defect verification module is used to:

[0087] For each suspected micropipe defect region included in the preprocessing image, a target light source is determined from each preset light source, and a surface image corresponding to the target light source is registered with the preprocessing image, an intersection is calculated between a bright area of ​​the registered surface image and the suspected micropipe defect region to obtain a first intersection region, and an intersection is calculated between a dark area of ​​the registered surface image and the suspected micropipe defect region to obtain a second intersection region;

[0088] Calculating a ratio between the first intersection area and the suspected micropipe defect area to obtain a first ratio, and when the first ratio is greater than a preset threshold, increasing the number of bright times corresponding to the target light source by one count, and calculating a ratio between the second intersection area and the suspected micropipe defect area to obtain a second ratio, and when the second ratio is greater than the preset threshold, increasing the number of dark times corresponding to the target light source by one count;

[0089] The target light source is eliminated from the preset light sources, and the process returns to the step of determining the target light source from the preset light sources until all the preset light sources are eliminated. The bright number counting results corresponding to each preset light source are summed, and the dark number counting results are summed. When the sum of the bright number is greater than 0, and the sum of the dark number is greater than 1, it is determined that the suspected microtube defect area is a real microtube defect area.

[0090] Optionally, the device further comprises:

[0091] A marking module is used for marking each of the suspected microtubule defect regions with a first mark in the preprocessing image after verifying the suspected microtubule defect region, when the suspected microtubule defect region is a real microtubule defect region, and otherwise, marking the suspected microtubule defect region with a second mark.

[0092] Optionally, the device further comprises:

[0093] A control parameter calculation module is used for, before acquiring a plurality of surface images under the same acquisition angle corresponding to the wafer to be inspected for micropipe defects, for each of the preset light sources, controlling the preset light source to be turned on, and controlling the image acquisition device to acquire the surface image of the wafer, inputting the surface image of the wafer into the control parameter calculation model, obtaining the image acquisition control parameters of the image acquisition device, and recording the image acquisition control parameters corresponding to the preset light source;

[0094] Accordingly, the device further comprises:

[0095] A control parameter adjustment module is used to respond to a detection instruction for wafer micropipe defects, turn on a preset light source each time in a preset order, adjust the preset parameters of the image acquisition device based on the image acquisition control parameters corresponding to the turned-on preset light source, and control the image acquisition device to acquire the surface image corresponding to the wafer after the adjustment.

[0096] It should be noted that for other corresponding descriptions of the functional units involved in the wafer micropipe defect detection device provided in the embodiment of the present application, reference can be made to Figures 1 to 8 The corresponding description in the method will not be repeated here.

[0097] The present application also provides a computer device, which may be a personal computer, a server, a network device, etc. Fig.10 As shown, the computer device includes a bus, a processor, a memory and a communication interface, and may also include an input and output interface and a display device. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store location information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in each method embodiment are implemented.

[0098] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0099] In one embodiment, a computer-readable storage medium is provided. The computer-readable storage medium may be non-volatile or volatile, and stores a computer program thereon. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0100] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0101] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0102] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0103] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0104] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for detecting wafer micropipe defects, characterized in that: include: Acquire multiple surface images corresponding to the wafer to be inspected for micropipe defects under the same acquisition angle of view, wherein the multiple surface images include surface images acquired after each preset light source is turned on separately, and the setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect; Determine respectively the maximum grayscale values ​​corresponding to the pixels at the same positions in the plurality of surface images, and determine the preprocessing image of the wafer area under the acquisition viewing angle according to the maximum grayscale values ​​of the pixels at each position; Performing preliminary microtubule defect detection on the preprocessed image to obtain a suspected microtubule defect area included in the preprocessed image; For the surface image corresponding to each preset light source, the bright area and the dark area on the surface image are determined, and each of the suspected microtube defect areas is verified based on the bright area and the dark area of ​​the surface image corresponding to each preset light source to determine whether the suspected microtube defect area is a real microtube defect area.

2. The method according to claim 1, characterized in that The image acquisition device setting surface and the preset light source setting surface are distributed on both sides or the same side of the wafer, the preset light source is set on the preset light source setting surface, the distance between each preset light source and the projection point of the center of the wafer on the preset light source setting surface is the same, the angle between the line between each two adjacent preset light sources and the projection point is 90°, the irradiation direction of each preset light source is toward the wafer, and the angle formed between the irradiation direction of each preset light source and the wafer surface is equal.

3. The method according to claim 2, characterized in that The step of respectively determining the maximum grayscale values ​​corresponding to the pixels at the same positions in the plurality of surface images, and determining the preprocessing image of the wafer area under the acquisition viewing angle according to the maximum grayscale values ​​of the pixels at each position, comprises: Determine the maximum grayscale value corresponding to each pixel at the same position in the plurality of surface images respectively, and obtain an initial preprocessing image according to the maximum grayscale value of the pixel at each position; Selecting a target surface image from the plurality of surface images, determining for each pixel in the target surface image a relationship between a grayscale value corresponding to the pixel in the target surface image and a first preset grayscale threshold and a second preset grayscale threshold, if the grayscale value is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, taking the pixel as a first target pixel, and determining a wafer area corresponding to the target surface image according to the first target pixel, wherein the first preset grayscale threshold is less than the second preset grayscale threshold; The initial preprocessed image is registered with the target surface image, and the initial preprocessed image is intercepted according to the wafer area in the target surface image to obtain a preprocessed image of the wafer area under the acquisition viewing angle.

4. The method according to claim 2, characterized in that: The step of respectively determining the maximum grayscale values ​​corresponding to the pixels at the same positions in the plurality of surface images, and determining the preprocessing image of the wafer area under the acquisition viewing angle according to the maximum grayscale values ​​of the pixels at each position, comprises: Selecting a target surface image from the plurality of surface images, determining for each pixel in the target surface image a relationship between a grayscale value corresponding to the pixel in the target surface image and a first preset grayscale threshold and a second preset grayscale threshold, if the grayscale value is greater than the first preset grayscale threshold and less than the second preset grayscale threshold, taking the pixel as a first target pixel, and determining a wafer area corresponding to the target surface image according to the first target pixel, wherein the first preset grayscale threshold is less than the second preset grayscale threshold; According to the wafer area corresponding to the target surface image, each surface image is intercepted and processed to obtain a surface image containing only the wafer area, and according to the maximum grayscale value corresponding to the pixel points at the same position in multiple surface images containing only the wafer area, a preprocessing image of the wafer area under the acquisition viewing angle is obtained.

5. The method according to claim 3 or 4, characterized in that: The preliminary detection of micropipe defects on the preprocessed image to obtain a suspected micropipe defect area included in the preprocessed image includes: Performing mean filtering on the preprocessed image to obtain a mean filtered image; Subtract the grayscale value of the corresponding pixel in the preprocessing image from the grayscale value of each pixel in the mean filtering image to obtain the grayscale difference corresponding to each pixel, and obtain a difference image according to the grayscale difference corresponding to each pixel; For each pixel point in the difference map, determine the relationship between the grayscale value corresponding to the pixel point in the difference map and the third preset grayscale threshold, and take the pixel points with grayscale values ​​greater than the third preset grayscale threshold as the second target pixel points, and take the area formed by the second target pixel points as the suspected microtube defect area.

6. The method according to claim 2, characterized in that When there is only one surface image corresponding to any preset light source, determining the bright area and the dark area on the surface image for each surface image corresponding to the preset light source includes: For each pixel point in the surface image corresponding to any one of the preset light sources, determine the relationship between the grayscale value of the pixel point in the surface image corresponding to any one of the preset light sources and the fourth preset grayscale threshold and the fifth preset grayscale threshold; if the grayscale value is greater than the fourth preset grayscale threshold and less than the fifth preset grayscale threshold, take the pixel point as the third target pixel point, determine the bright area of ​​the surface image corresponding to any one of the preset light sources based on the third target pixel point, and take the remaining area as the dark area, wherein the fourth preset grayscale threshold is less than the fifth preset grayscale threshold.

7. The method according to claim 6, characterized in that When the surface images corresponding to any preset light source include multiple images, before determining, for each pixel point in the surface image corresponding to any preset light source, the relationship between the grayscale value of the pixel point in the surface image corresponding to any preset light source and the fourth preset grayscale threshold and the fifth preset grayscale threshold, the method further includes: According to the maximum grayscale value of the pixel point at the same position in the multiple surface images corresponding to the any preset light source, the multiple surface images corresponding to the any preset light source are merged to replace the surface image.

8. A wafer micropipe defect detection device, characterized in that: include: A surface image acquisition module, used to acquire multiple surface images corresponding to the wafer to be inspected for micropipe defects under the same acquisition angle of view, wherein the multiple surface images include surface images acquired after each preset light source is turned on separately, and the setting position of each preset light source relative to the wafer is determined based on the physical characteristics of the micropipe defect; A pre-processing image generating module, used to respectively determine the maximum grayscale value corresponding to each pixel point at the same position in the plurality of surface images, and determine the pre-processing image of the wafer area under the acquisition viewing angle according to the maximum grayscale value of the pixel point at each position; A preliminary defect detection module is used to perform preliminary micropipe defect detection on the preprocessed image to obtain a suspected micropipe defect area included in the preprocessed image; The defect verification module is used to determine the bright area and the dark area on the surface image corresponding to each preset light source, and verify each suspected microtube defect area according to the bright area and the dark area of ​​the surface image corresponding to each preset light source to determine whether the suspected microtube defect area is a real microtube defect area.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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