Defect detection method, device, detection equipment and storage medium for wafer

Abstract

Embodiments of the present application provide a defect detection method, apparatus, detection equipment, and storage medium for wafers. In some embodiments of the present application, the defect detection method for wafers includes: detecting pixels on the edge of the wafer in the image to be tested of the wafer; selecting multiple pixels from the pixels on the edge, and determining the pixel path between adjacent pixels in the selected multiple pixels; and determining whether the wafer has defects based on the pixel path. Through the above embodiments, the detection equipment can automatically detect defects on the edge of the wafer.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of semiconductor technology, and more specifically, to a defect detection method, apparatus, detection equipment, and storage medium for wafers. Background Art

[0002] Wafer refers to the silicon chip used to make silicon semiconductor integrated circuits. It is the carrier used to produce integrated circuits. Therefore, the quality of the wafer directly affects the yield rate and manufacturing cost of the chip. In the actual process of making wafers, it is inevitable that some wafers will have defects, such as gaps caused by cracks on the edge of the wafer. Therefore, it is necessary to test the wafers to obtain wafers that meet the standards.

[0003] Currently, most engineers usually use naked eye observation to find wafer defects when inspecting wafers. However, this manual inspection method greatly reduces the inspection efficiency and accuracy. Summary of the invention

[0004] In a first aspect, an embodiment of the present application provides a defect detection method for a wafer, comprising: detecting pixels on an edge of a wafer in an image of the wafer to be tested; selecting a plurality of pixels from the pixels on the edge, and determining a pixel path between adjacent pixels in the selected plurality of pixels; and determining whether the wafer has a defect based on the pixel path.

[0005] In some embodiments of the present application, determining whether a wafer has a defect based on a pixel path includes: determining that a wafer has a defect in response to a corner point existing on the pixel path.

[0006] In some embodiments of the present application, a corner point includes a pixel with a sudden gradient change on a pixel path.

[0007] In some embodiments of the present application, a corner point includes a pixel on a pixel path whose grayscale value suddenly changes.

[0008] In some embodiments of the present application, the method further includes: in response to a defect existing on the wafer, determining a defect length according to a distance between corner points.

[0009] In some embodiments of the present application, determining the defect length includes: determining image feature values ​​of connected pixels on a line between a first corner point and a second corner point among the corner points in the image to be tested; and in response to the presence of connected pixels whose image feature value difference with the first corner point or the second corner point is greater than a first threshold, determining that there is a defect between the first corner point and the second corner point, and determining the distance between the first corner point and the second corner point as the defect length of the wafer between the first corner point and the second corner point.

[0010] In some embodiments of the present application, the image feature value is a gradient value or a grayscale value.

[0011] In some embodiments of the present application, the second corner point and the first corner point are located on the same pixel path.

[0012] In some embodiments of the present application, the second corner point is a corner point adjacent to or close to the first corner point.

[0013] In some embodiments of the present application, a pixel path between adjacent pixels is a straight line path or an arc path.

[0014] In the second aspect, an embodiment of the present application provides a defect detection device for a wafer, comprising: an edge detection module for detecting pixels on the edge of a wafer in an image of the wafer to be tested; a path determination module for selecting a plurality of pixels from the pixels on the edge and determining a pixel path between adjacent pixels in the selected plurality of pixels; and a defect detection module for determining whether the wafer has defects based on the pixel path.

[0015] In some embodiments of the present application, the defect detection module is configured to: determine that a defect exists in the wafer in response to the existence of a corner point on the pixel path.

[0016] In some embodiments of the present application, the defect detection module is further configured to: in response to the presence of a defect in the wafer, determine the defect length according to the distance between the corner points of the pixel path.

[0017] In some embodiments of the present application, the defect detection module is configured to: determine image feature values ​​of connected pixels on a line between a first corner point and a second corner point among the corner points in the image to be tested; and in response to the presence of connected pixels whose image feature value difference with the first corner point or the second corner point is greater than a first threshold, determine that there is a defect between the first corner point and the second corner point, and determine the distance between the first corner point and the second corner point as the defect length of the wafer between the first corner point and the second corner point.

[0018] In some embodiments of the present application, the second corner point and the first corner point are located on the same pixel path.

[0019] In some embodiments of the present application, the second corner point is a corner point adjacent to or close to the first corner point.

[0020] In some embodiments of the present application, a corner point includes a pixel with a sudden gradient change on a pixel path.

[0021] In some embodiments of the present application, a corner point includes a pixel on a pixel path whose grayscale value suddenly changes.

[0022] In a third aspect, an embodiment of the present application provides a detection device, comprising: a memory for storing computer instructions; and a processor for communicating with the memory to execute the computer instructions, thereby implementing the defect detection method mentioned in the above embodiment.

[0023] In a fourth aspect, an embodiment of the present application provides a readable storage medium, in which computer instructions are stored. When the computer instructions are executed by a processor, the defect detection method mentioned in the above embodiment is implemented.

[0024] According to the implementation mode of the present application, defect detection is performed on the wafer by analyzing the pixel paths between adjacent pixels among multiple pixels selected from the edge of the wafer, so that the defect detection device can automatically detect wafer defects, thereby reducing the difficulty of building a wafer product line and the probability of false alarms in manual integration, thereby improving the efficiency of wafer online, reducing the cost of building a wafer product line, and improving the accuracy of the product line. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings, in which:

[0026] Figure 1 is a schematic flow chart of a defect detection method for a wafer according to some embodiments of the present application;

[0027] Figure 2 is a schematic diagram of an image to be tested of a wafer according to some embodiments of the present application;

[0028] Figure 3 is a schematic diagram of an edge of a wafer detected according to some embodiments of the present application;

[0029] Figure 4 is a schematic diagram of a pixel path according to some embodiments of the present application;

[0030] Figure 5 yes Figure 2 A local enlarged schematic diagram of area A;

[0031] Figure 6 is a schematic diagram of a wafer edge according to some embodiments of the present application;

[0032] Figure 7 yes Figure 6 A local enlarged schematic diagram of area B.

[0033] Figure 8 is a schematic structural diagram of a defect detection device according to some embodiments of the present application;

[0034] Fig. 9It is a schematic diagram of the structure of a detection device according to some embodiments of the present application. DETAILED DESCRIPTION

[0035] In order to better understand the present application, a more detailed description will be made of various aspects of the present application with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present application, and are not intended to limit the scope of the present application in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0036] It should be noted that in this specification, the expressions first, second, third, etc. are only used to distinguish one feature from another feature area, and do not represent any limitation on the features, especially do not represent any order of precedence. For example, without departing from the teaching of this application, the first corner point discussed in this application may also be referred to as the second corner point, and vice versa.

[0037] As used herein, the terms "substantially," "approximately," and similar terms are used as terms of approximation, not degree, and are intended to account for the inherent variations in measurements or calculations that would be recognized by those of ordinary skill in the art.

[0038] It should also be understood that expressions such as "include", "comprising", "having", "including" and / or "comprising" are open rather than closed expressions in this specification, which indicate the presence of the stated features, elements and / or components, but do not exclude the presence of one or more other features, elements, components and / or their combinations. In addition, when describing the embodiments of the present application, the use of "may" means "one or more embodiments of the present application". And, the term "exemplary" is intended to refer to an example or illustration.

[0039] Unless otherwise specified, all words (including engineering terms and scientific and technological terms) used in this article have the same meaning as those commonly understood by ordinary technicians in the field to which this application belongs. It should also be understood that, unless clearly stated in this application, words defined in common dictionaries should be interpreted as having the same meaning as their meaning in the context of the relevant technology, and should not be interpreted in an idealized or overly formal sense.

[0040] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. In addition, unless explicitly limited or contradictory to the context, the specific steps included in the method described in the present application are not necessarily limited to the order described, but can be performed in any order or in parallel. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0041] Figure 1 1 is a flow chart of a defect detection method 1000 for wafers according to an embodiment of the present application. The defect detection method 1000 for wafers mentioned in the embodiment of the present application can be executed by a device with processing functions such as a defect detection device for wafers (also referred to as a detection device), and the following is an exemplary description using a defect detection device as an example. Figure 1 As shown, the defect detection method 1000 for a wafer provided in an embodiment of the present application may include, for example:

[0042] S11, detecting pixels on the edge of the wafer in the image to be tested of the wafer.

[0043] S12, selecting a plurality of pixels from the pixels on the edge, and determining a pixel path between adjacent pixels in the selected plurality of pixels.

[0044] S13, determining whether the wafer has defects based on the pixel path.

[0045] According to the implementation mode of the present application, defect detection is performed on the wafer by analyzing the pixel paths between adjacent pixels among multiple pixels selected from the edge of the wafer, so that the defect detection device can automatically detect wafer defects, thereby reducing the difficulty of building a wafer product line and the probability of false alarms in manual integration, thereby improving the efficiency of wafer online, reducing the cost of building a wafer product line, and improving the accuracy of the product line.

[0046] Step S11

[0047] In some embodiments of the present application, the defect detection device may detect pixels on the edge of the wafer in the image to be tested of the wafer by an edge detection algorithm. For example, the image to be tested 20 of the wafer 21 may be, for example Figure 2 As shown, there are defects in area A and area B. The defect detection device may use an edge detection algorithm such as a canny edge detection operator to perform edge detection on the image 20 to be tested. The schematic image of the edge 22 of the wafer 21 to be tested is shown in FIG. Figure 3 shown.

[0048] It should be understood that other edge detection operators may be selected as needed without departing from the teaching of the present application, and the present application does not impose any limitation on this.

[0049] In some embodiments of the present application, the image to be tested may be, for example, a scanning electron microscope image of the top surface or the bottom surface of the wafer.

[0050] In some other embodiments of the present application, the image to be tested may be, for example, an image of the top surface or bottom surface of a wafer taken by a silicon wafer surface particle tester.

[0051] It should be understood that, without departing from the teaching of the present application, images capable of characterizing the top or bottom surface structure of the wafer may be taken by other equipment as images to be tested, and the present application does not impose any limitation on this.

[0052] It should be understood that, without departing from the teachings of the present application, image processing operations such as grayscale processing may be performed on the captured image in order to extract the edge of the wafer, and the present application does not impose any limitation on this.

[0053] Step S12

[0054] In some embodiments of the present application, determining a pixel path may include, for example: selecting a preset number of pixels from an edge; and determining a pixel path between adjacent pixels. The preset number may be at least 10, and at most 100 or 1000, etc., which is not limited in the present application.

[0055] It should be understood that, without departing from the teachings of this application, the specific value of the preset number can be determined based on data such as the size information of the wafer, the size information of the image to be measured, the size information of the detected edge, and the present application does not limit the specific value of the preset number.

[0056] In some embodiments of the present application, a pixel path between adjacent pixels is a straight line path.

[0057] It should be understood that without departing from the teachings of the present application, adjacent pixels may be connected by arcs based on the radius of the detected edge, and the pixel path between adjacent pixels may be an arc path. The defect detection device may also determine the pixel path by other means, and the present application does not limit the method of determining the pixel path.

[0058] For ease of understanding, the process of determining a pixel path is exemplarily described below.

[0059] Figure 3 is a schematic diagram of an edge of a wafer detected according to some embodiments of the present application, Figure 4 is a schematic diagram of a pixel path according to some embodiments of the present application.

[0060] For example, the defect detection device may select a preset number of pixels at equal intervals to construct a pixel path. Since the edge of the wafer is close to a circle, the defect detection device may be based on Figure 3The image shown in the figure detects the center and radius of the detected edge through the center and radius detection algorithm. The defect detection device calculates the center angle (α) between two pixels selected in sequence based on a preset number (x), for example, α=360 / x. The defect detection device can arbitrarily select a pixel from the detected edge as a pixel for constructing a pixel path. Based on the pixel, the defect detection device uses the line connecting the detected center of the circle and the pixel as the rotation line, and the detected center of the circle as the fixed point to rotate the rotation line. After the rotation line radius rotates 360 / x degrees, any pixel on the intersection of the rotation line and the detected edge (for example, the pixel closest to the center of the circle or the pixel farthest from the center of the circle, etc.) is selected as the pixel for subsequent determination of the pixel path, or the pixel that coincides with the end of the rotation line is selected as the pixel for subsequent determination of the pixel path until the rotation line returns to the starting position. In the above manner, x pixels can be selected. After selecting x pixels, each pixel can be connected in sequence to obtain a pixel path between each pixel. For example, in Figure 3 Based on the edge shown in FIG. 1 , if the pixel that coincides with the end of the rotation line is selected as the pixel for subsequently determining the pixel path, the pixel path formed by the 20 pixels (P1-P20) finally selected can be, for example: Figure 4 shown.

[0061] It should be understood that, without departing from the teachings of the present application, the defect detection device may also uniformly select a preset number of pixels on the detected edge in other ways, and the present application does not impose any limitation on this.

[0062] It should be understood that for ease of understanding, the implementation of the present application is illustratively described by taking the selection of pixels at equal intervals as an example. Without departing from the teachings of the present application, a preset number of pixels may also be selected at different intervals, and the present application does not impose any restrictions on this.

[0063] It should be understood that the defect detection device may also determine the pixel path in other ways without departing from the teachings of the present application, and the present application does not limit this.

[0064] Step S13

[0065] In some embodiments of the present application, the defect detection device determines whether a wafer has defects based on a pixel path, which may include, for example: determining that a wafer has defects in response to the presence of a corner point on the pixel path. Herein, a corner point may refer to a point whose attributes are particularly prominent in a certain aspect. In the process of detecting a corner point, a specific meaning may be given to the corner point detection according to the purpose of detection. By way of example, in an embodiment of the present application, a corner point may refer to a pixel where a sudden change occurs in parameters such as a gradient or a grayscale value. Herein, a sudden change refers to a large change in a specified parameter of a certain pixel. For example, along the direction of corner point detection, the change in a specified parameter of a certain pixel relative to a specified parameter of the previous pixel exceeds a preset value. Herein, the preset value may be set based on the parameter type specified based on the purpose of detection, the requirements for detection accuracy and detection speed, etc., and is not limited here.

[0066] For ease of understanding, the following Figure 5 , an exemplary description is given by taking the grayscale value as an example of the specified parameter.

[0067] Figure 5 yes Figure 2 A partial enlarged schematic diagram of area A. Figure 5 It can be seen that there is a defect in the pixel path P18-P19. For the defect detection device, in the process of performing corner point detection along pixel P18 to pixel P19, it can be found that before reaching pixel C1, the grayscale value of the pixels between pixel P18 and pixel C1 is close to 255 (white), however, at pixel C1, the grayscale value is close to 0 (black), and the grayscale value changes suddenly. The defect detection device can use pixel C1 as a corner point, and record information such as the coordinates of pixel C1 as the position information of a corner point in the image to be tested. Similarly, the defect detection device can detect that pixel C2 is also a corner point, and record information such as the coordinates of pixel C2 as the position information of another corner point in the image to be tested. Therefore, by detecting whether there are pixels with gradient mutations on the pixel path, it can be determined whether the wafer has defects. The defect detection device can detect defects of the wafer through corner points, realize automatic detection of defects of the wafer, without relying on manual detection, and improve detection efficiency and accuracy.

[0068] It should be understood that, without departing from the teaching of the present application, when the specified parameter is a grayscale value, the way to determine whether the grayscale value changes suddenly can be to determine whether the difference between the grayscale value of the current pixel and the grayscale value of the previous pixel is greater than a first threshold a1, and a1 can be set according to the situation of the image to be tested. For example, the image to be tested is a wafer image processed as a black and white image, and a1 can be any value in (50, 200), specifically, it can be any value between (100, 150). The specific value of a1 can be determined according to the accuracy of the defect detection device, the image quality of the image to be tested, etc.

[0069] It should be understood that for ease of understanding, Figure 5 The image shown may be an image after denoising and other processing. In other embodiments, since the pixels between pixel P18 and pixel C1 are close to the edge of the wafer, their actual color may be gray close to black instead of white, so that the grayscale value of pixel P18, the grayscale value of pixel C1, and the grayscale value of pixels from pixel P18 to pixel C1 are close to 0, instead of the grayscale value of pixel C1 and the grayscale value of pixels from pixel P18 to pixel C1 being equal to 255. Alternatively, in other embodiments, due to factors such as the large value of the preset number, the pixel path finally determined is more in line with the extracted wafer edge, so that the grayscale value of pixel P18, the grayscale value of pixel C1, and the grayscale value of pixels from pixel P18 to pixel C1 are close to 0, instead of the grayscale value of pixel C1 and the grayscale value of pixels from pixel P18 to pixel C1 being equal to 255. In the implementations similar to the above-mentioned grayscale values ​​of pixel P18, pixel C1, and the grayscale values ​​of pixels from pixel P18 to pixel C1 are close to 0, due to the defects in the wafer, the pixels of the detected edge are closer to the center of the circle, the pixels between pixel C1 and pixel C2 do not overlap with the edge of the wafer, and their grayscale values ​​are close to or equal to 255, and the grayscale value mutation still occurs. It can be seen that in various implementations, the defect detection device can detect the pixels with grayscale value mutations corresponding to the defects as corner points, and is not affected by changes in factors such as the processing process of the image to be tested or the selection of a preset number.

[0070] It should be understood that, in some embodiments, the pixels selected for determining the pixel path (for example, pixels P1 to P20) are located on the edge of the wafer, and the pixel path has a low degree of fit with the edge of the wafer, so that the grayscale value difference between the point in the middle of the pixel path and the pixels at both ends of the pixel path (i.e., the pixels selected for determining the pixel path) is relatively large. In this case, the defect detection device may eliminate the pixels at both ends of the pixel path, or eliminate the pixels at both ends of the pixel path and some pixel points close to the pixels at both ends and then perform corner point detection to reduce the situation where the pixels at both ends are mistakenly identified as corner points due to sudden changes at the two ends due to low fit.

[0071] It should be understood that for ease of observation, the drawings (such as Figures 3 to 7 ) takes white as the background color and black as the color of the edge pixels. In other implementations, the background color of the image to be tested may be black, and the color of the edge pixels may be white or other colors, and the present application does not impose any limitation on this.

[0072] It should be understood that, similar to the grayscale value, when there is a defect on the pixel path, the gradient of the pixel at the defect will also change suddenly. The process of detecting corner points on the pixel path based on the gradient of the image can refer to the process of detecting edges in image processing based on gradient detection, which will not be described in detail here.

[0073] After completing the exemplary description of corner point detection, the following is an exemplary description of the process of determining the defect length based on the detected corner points.

[0074] In some embodiments of the present application, after determining that a defect exists in a wafer, the defect detection device determines the defect length based on the distance between the corner points.

[0075] For example, after detecting the corner points on the edge of the wafer in the image to be tested, if the number of corner points on the edge of the wafer is equal to 2, the defect detection device may use the straight-line distance between the two corner points as the defect length of the wafer.

[0076] However, if the number of corner points on the edge of the wafer is greater than 2, the defect detection device cannot determine which two corner points correspond to the same defect. This problem is particularly prominent when the distances between multiple corner points are close.

[0077] Based on the above situation, the defect detection device determines the defect length, for example, including: determining the image feature value of the connected pixels on the line between the first corner point and the second corner point in the image to be tested; and in response to the existence of a connected pixel whose difference with the image feature value of the first corner point or the second corner point is greater than a first threshold, determining that there is a defect between the first corner point and the second corner point, and determining the distance between the first corner point and the second corner point as the defect length of the wafer between the first corner point and the second corner point. By way of example, the defect detection device selects a second corner point from other corner points of the plurality of corner points except the first corner point for the first corner point of the plurality of corner points of the pixel path; obtains the image feature value of the pixel located between the first corner point and the second corner point in the image to be tested; in response to the difference between the image feature value of the pixel and the image feature value of the first corner point, or the difference between the image feature value of the pixel and the image feature value of the second corner point, determines the defect length of the wafer between the first corner point and the second corner point according to the distance between the first corner point and the second corner point.

[0078] For ease of understanding, the method of selecting the second corner point is exemplarily described below.

[0079] Method 1

[0080] In some embodiments of the present application, the second corner point and the first corner point are located on the same pixel path. In response to the presence of a corner point on the same pixel path as the first corner point among other corner points, the defect detection device may use the corner point on the same pixel path as the second corner point. Figure 6 ,Will Figure 6 After the corner point J3 in the pixel path P18-P19 is used as the first corner point, since there is also a corner point J4 on the pixel path P18-P19, the corner point J4 can be preferentially used as the second corner point. For example, since the defect on the edge of the wafer is usually a notch defect, the distance between the two ends of the notch is small (that is, the distance between the corner points corresponding to the notch is small), and the corner points corresponding to the notch are usually located on the same pixel path. The defect detection device selects the corner point located on the same pixel path as the first corner point as the second corner point. The probability that the area between the first corner point and the second corner point is where the notch is located is higher, which can improve the efficiency of finding defects.

[0081] Optionally, in response to the absence of a corner point on the same pixel path as the first corner point among the other corner points, the defect detection device may use a corner point adjacent to or close to the first corner point among the other corner points as the second corner point. For example, the two corner points corresponding to the gap are usually adjacent. If the defect detection device fails to find the defect based on the corner point on the same pixel path as the first corner point, the defect detection device may find the defect through the adjacent or close corner points and determine the defect length. For example, see Figure 6 , after taking the corner point J1 on the pixel path P10-P11 as the first corner point, since there are no other corner points on the pixel path P10-P11, the corner point J2 close to the corner point J1 and located on the pixel paths P11 and P12 can be taken as the second corner point.

[0082] It should be understood that, without departing from the teachings of the present application, the defect detection device may also select the second corner point by other means when the second corner point does not exist in the same pixel path, and the present application does not impose any limitation on this.

[0083] Method 2

[0084] In some embodiments of the present application, the second corner point is a corner point adjacent to or close to the first corner point. The defect detection device may use a corner point adjacent to or close to the first corner point among other corner points except the first corner point as the second corner point. For example, since the defects on the wafer are usually notches and the distance between the notches is small, the defect detection device may use a corner point adjacent to or close to the first corner point as the second corner point to find the area where the notch is located.

[0085] It should be understood that, without departing from the teaching of the present application, the defect detection device may also select the second corner point based on other rules, and the present application does not limit this.

[0086] The above is an exemplary description of the method of selecting the second corner point. The following is an exemplary description of the method of determining the defect length of the wafer at the first corner point based on the selected second corner point.

[0087] For example, Figure 6Taking the edge of the wafer shown in the figure as an example, there are four corner points on the edge of the wafer, namely corner point 1 (J1), corner point 2 (J2), corner point 3 (J3) and corner point 4 (J4). The defect detection device selects any corner point from J1-J4 as the first corner point, and selects the closest corner point as the second corner point. For example, J1 is selected as the first corner point and J2 is selected as the second corner point. Figure 6 A local enlarged schematic diagram of area B is shown in Figure 7 The connected pixels between the first corner point and the second corner point in the image to be tested may be, for example, pixels on the straight line or arc where the first corner point and the second corner point are located. For example, Figure 7 The pixels on the dotted line between J1 and J2 in FIG. The arc line may be, for example, an arc line drawn with the center of the wafer as the center and the radius of the wafer as the radius and passing through J1 and J2. The defect detection device obtains the image feature values ​​(for example, gradient values ​​or grayscale values) of the connecting pixels between J1 and J2, and compares the image feature values ​​of the connecting pixels between J1 and J2 with the image feature values ​​of J1. It can be found that the image feature values ​​thereof will mutate. Therefore, the defect detection device can determine that there is a defect (also called a notch defect) between J1 and J2, and uses the distance between J1 and J2 as the defect length of the wafer at J1.

[0088] It should be understood that, without departing from the teaching of the present application, the first threshold value can be set based on experience, for example, the first threshold value can be 0, or other values ​​greater than 0, for example, 0 < first threshold value < the difference between the maximum and minimum values ​​of the image characteristic values ​​of the pixels in the image. When the first threshold value is greater than 0, the situation in which the defect detection device incorrectly determines the defect position due to the difference between the image characteristic values ​​(such as grayscale values) of the pixels on the edge of the wafer or the pixels near the edge of the wafer being uneven can be reduced, and the present application does not limit this.

[0089] As an example, when it is determined that there is no difference or there is a difference but the difference is less than the first threshold value (that is, the second corner point is not another corner point of the notch at the first corner point), the defect detection device selects the second corner point again, and re-executes the steps of obtaining the image feature values ​​of the pixels located between the first corner point and the second corner point in the image to be tested, and determining the defect length of the wafer at the first corner point, so as to re-find the defect at the first corner point.

[0090] For example, the defect detection device first selects a corner point located on the same pixel path as the second corner point. If it is determined that the second corner point is not another corner point of the gap at the first corner point, a corner point adjacent to or close to the first corner point can be selected as the second corner point, and subsequent operations can be performed again.

[0091] It should be understood that without departing from the teachings of the present application, when it is determined that the second corner point is another corner point of the gap that is not at the first corner point, the defect detection device can also find the defect and determine the defect length in other ways, and the present application does not impose any restrictions on this.

[0092] In some embodiments of the present application, when it is determined that the second corner point is another corner point of the notch at the first corner point, the defect detection device can also select a second corner point again for the first corner point. For example, after determining that J2 is another corner point of the defect at J1 and determining the defect length between J1 and J2, J3 is used as the second corner point, and the above judgment operation is performed for J1 and J4. By selecting multiple second corner points for the first corner point, it is possible to reduce the situation where defects are missed when there are continuous defects on the wafer.

[0093] In some embodiments of the present application, since the probability of a corner point being the corner point of multiple defects at the same time is small, the defect detection device can remove the first corner point and the other corner point of the defect at the first corner point from the multiple corner points of the pixel path after determining the defect length between the first corner point and the second corner point, so as to reduce the loss of computing resources caused by searching for the other corner point of the defect at the first corner point and determining the defect length, thereby improving the defect detection efficiency of the wafer.

[0094] It should be understood that, without departing from the teachings of the present application, the first corner point and another corner point of the defect at the first corner point may not be removed from the multiple corner points of the pixel path to reduce the possibility of missed defects when continuous defects occur at the edge of the wafer.

[0095] The step division of the above methods is only for the purpose of clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs without changing the core design of the algorithm and process are all within the scope of protection of this patent.

[0096] Figure 8 is a schematic block diagram of a defect detection apparatus 2000 for a wafer according to an exemplary embodiment of the present application.

[0097] like Figure 8As shown, the defect detection device 2000 may include, for example: an edge detection module 2100, a path determination module 2200, and a defect detection module 2300. The edge detection module 2100 may be used to detect pixels on the edge of the wafer in the image to be tested of the wafer. The path determination module 2200 may be used to select a plurality of pixels from the pixels on the edge, and determine a pixel path between adjacent pixels in the selected plurality of pixels. The defect detection module 2300 may be used to determine whether the wafer has a defect based on the pixel path.

[0098] According to the implementation mode of the present application, defect detection is performed on the wafer by analyzing the pixel paths between adjacent pixels among multiple pixels selected from the edge of the wafer, so that the defect detection device can automatically detect wafer defects, thereby reducing the difficulty of building a wafer product line and the probability of false alarms in manual integration, thereby improving the efficiency of wafer online, reducing the cost of building a wafer product line, and improving the accuracy of the product line.

[0099] In some embodiments of the present application, the edge detection module 2100 can detect the wafer 21 ( Figure 2 ) on the edge of the wafer. For example, the image 20 to be tested of the wafer 21 may be, for example Figure 2 As shown, there are defects in area A and area B. The edge detection module 2100 can select an edge detection algorithm based on a canny edge detection operator to perform edge detection on the image 20 to be tested. The schematic image of the edge 22 of the wafer 21 to be tested is shown in FIG. Figure 3 shown.

[0100] It should be understood that other edge detection operators may be selected as needed without departing from the teaching of the present application, and the present application does not impose any limitation on this.

[0101] In some embodiments of the present application, the image to be tested may be, for example, a scanning electron microscope image of the top or bottom surface of the wafer. The image to be tested may also be, for example, an image of the top or bottom surface of the wafer taken by a silicon wafer surface particle tester.

[0102] It should be understood that, without departing from the teaching of the present application, images capable of characterizing the top or bottom surface structure of the wafer may be taken by other equipment as images to be tested, and the present application does not impose any limitation on this.

[0103] In some embodiments of the present application, the path determination module 2200 determines the pixel path, which may include, for example: selecting a preset number of pixels from the edge; determining the pixel path between adjacent pixels. The preset number may be at least 10, and may be, for example, 100 or 1000 at most, etc., which is not limited by the present application. It should be understood that, without departing from the teachings of the present application, the specific value of the preset number may be determined based on data such as the size information of the wafer, the size information of the image to be measured, and the size information of the detected edge, and the present application does not limit the specific value of the preset number.

[0104] In some embodiments of the present application, the pixel path between adjacent pixels is a straight path. It should be understood that, without departing from the teaching of the present application, the adjacent pixels can also be connected by an arc according to the radius of the detected edge, and the pixel path between adjacent pixels is an arc path. The path determination module 2200 can also determine the pixel path in other ways, and the present application does not limit the way to determine the pixel path.

[0105] The above reference Figure 3 and Figure 4 The content described above can be applied to the process of determining the pixel path by the path determination module 2200. For example, the path determination module 2200 can select a preset number of pixels at equal intervals to construct the pixel path. Since the edge of the wafer is close to a circle, the path determination module 2200 can be based on Figure 3 The image shown in the figure is detected by the center and radius detection algorithm to detect the center and radius of the detected edge. The path determination module 2200 calculates the center angle (α) between two pixels selected in sequence based on the preset number (x), for example, α=360 / x. The path determination module 2200 can arbitrarily select a pixel from the detected edge as a pixel for constructing a pixel path. Based on the pixel, the path determination module 2200 uses the line connecting the detected center and the pixel as the rotation line, and the detected center as the fixed point to rotate the rotation line, and after the rotation line radius rotates 360 / x degrees, selects any pixel on the intersection of the rotation line and the detected edge (for example, the pixel closest to the center or the pixel farthest from the center, etc.) as the pixel for subsequent determination of the pixel path, or selects the pixel that coincides with the end of the rotation line as the pixel for subsequent determination of the pixel path, until the rotation line returns to the starting position. In the above manner, x pixels can be selected. After selecting x pixels, each pixel can be connected in sequence to obtain a pixel path between each pixel. For example, in Figure 3 Based on the edge shown in FIG. 1 , if the pixel that coincides with the end of the rotation line is selected as the pixel for subsequently determining the pixel path, the pixel path formed by the 20 pixels (P1-P20) finally selected can be, for example: Figure 4 shown.

[0106] It should be understood that, without departing from the teachings of the present application, the path determination module 2200 may also uniformly select a preset number of pixels on the detected edge in other ways, and the present application does not impose any limitation on this.

[0107] It should be understood that, for ease of understanding, the embodiments of the present application are illustrative in that the pixels are selected at equal intervals. Without departing from the teaching of the present application, a preset number of pixels may be selected at different intervals, and the present application does not limit this. In addition, without departing from the teaching of the present application, the path determination module 2200 may also determine the pixel path in other ways, and the present application does not limit this.

[0108] In some embodiments of the present application, the defect detection module 2300 determines whether the wafer has defects based on the pixel path, which may include, for example: determining that the wafer has defects in response to the existence of corner points on the pixel path. Among them, corner points may refer to points with particularly prominent properties in a certain aspect. In the process of detecting corner points, specific meanings may be given to corner point detection according to the purpose of detection. For example, in the embodiments of the present application, corner points may refer to pixels where parameters such as gradients and grayscale values ​​​​have undergone sudden changes.

[0109] Back to Figure 5 And take the pixel whose gray value suddenly changes on the corner point pixel path as an example. Figure 5 It can be seen that there is a defect in the pixel path P18-P19. For the defect detection device, in the process of performing corner point detection along pixel P18 to pixel P19, it can be found that before reaching pixel C1, the grayscale value of the pixels between pixel P18 and pixel C1 is close to 255 (white), however, at pixel C1, the grayscale value is close to 0 (black), and the grayscale value changes suddenly. The defect detection device can use pixel C1 as a corner point, and record information such as the coordinates of pixel C1 as the position information of a corner point in the image to be tested. Similarly, the defect detection device can detect that pixel C2 is also a corner point, and record information such as the coordinates of pixel C2 as the position information of another corner point in the image to be tested. Therefore, by detecting whether there are pixels with gradient mutations on the pixel path, it can be determined whether the wafer has defects. The defect detection module 2300 can detect defects of the wafer through corner points, realize automatic detection of defects of the wafer, without relying on manual detection, and improve detection efficiency and accuracy.

[0110] It should be understood that, without departing from the teaching of the present application, when the specified parameter is a grayscale value, the way to determine whether the grayscale value changes suddenly can be to determine whether the difference between the grayscale value of the current pixel and the grayscale value of the previous pixel is greater than a first threshold a1, and a1 can be set according to the situation of the image to be tested. For example, the image to be tested is a wafer image processed as a black and white image, and a1 can be any value in (50, 200), specifically, it can be any value between (100, 150). The specific value of a1 can be determined according to the accuracy of the defect detection device, the image quality of the image to be tested, etc.

[0111] It should be understood that for ease of understanding, Figure 5 The image shown may be an image after denoising and other processing. In other embodiments, since the pixels between pixel P18 and pixel C1 are close to the edge of the wafer, their actual color may be gray close to black instead of white, so that the grayscale value of pixel P18, the grayscale value of pixel C1, and the grayscale value of pixels from pixel P18 to pixel C1 are close to 0, instead of the grayscale value of pixel C1 and the grayscale value of pixels from pixel P18 to pixel C1 being equal to 255. Alternatively, in other embodiments, due to factors such as the large value of the preset number, the pixel path finally determined is more in line with the extracted wafer edge, so that the grayscale value of pixel P18, the grayscale value of pixel C1, and the grayscale value of pixels from pixel P18 to pixel C1 are close to 0, instead of the grayscale value of pixel C1 and the grayscale value of pixels from pixel P18 to pixel C1 being equal to 255. In the implementations similar to the above-mentioned grayscale values ​​of pixel P18, pixel C1, and the grayscale values ​​of pixels from pixel P18 to pixel C1 are close to 0, due to the defects in the wafer, the pixels of the detected edge are closer to the center of the circle, the pixels between pixel C1 and pixel C2 do not overlap with the edge of the wafer, and their grayscale values ​​are close to or equal to 255, and the grayscale value mutation still occurs. It can be seen that in various implementations, the defect detection device can detect the pixels with grayscale value mutations corresponding to the defects as corner points, and is not affected by changes in factors such as the processing process of the image to be tested or the selection of a preset number.

[0112] It should be understood that, in some embodiments, the pixels selected for determining the pixel path (for example, pixels P1 to P20) are located on the edge of the wafer, and the pixel path has a low degree of fit with the edge of the wafer, so that the grayscale value difference between the point in the middle of the pixel path and the pixels at both ends of the pixel path (i.e., the pixels selected for determining the pixel path) is relatively large. In this case, the defect detection device may eliminate the pixels at both ends of the pixel path, or eliminate the pixels at both ends of the pixel path and some pixel points close to the pixels at both ends and then perform corner point detection to reduce the situation where the pixels at both ends are mistakenly identified as corner points due to sudden changes at the two ends due to low fit.

[0113] It should be understood that for ease of observation, the drawings (such as Figures 3 to 7 ) takes white as the background color and black as the color of the edge pixels. In other implementations, the background color of the image to be tested may be black, and the color of the edge pixels may be white or other colors, and the present application does not impose any limitation on this.

[0114] It should be understood that, similar to the grayscale value, when there is a defect on the pixel path, the gradient of the pixel at the defect will also change suddenly. The process of detecting corner points on the pixel path based on the gradient of the image can refer to the process of detecting edges in image processing based on gradient detection, which will not be described in detail here.

[0115] After completing the exemplary description of corner point detection, the following is an exemplary description of the process of determining the defect length based on the detected corner points.

[0116] In some embodiments of the present application, after determining that a defect exists in the wafer, the defect detection module 2300 determines the defect length according to the distance between the corner points of the pixel path.

[0117] For example, after detecting the corner points on the edge of the wafer in the image to be tested, if the number of corner points on the edge of the wafer is equal to 2, the defect detection device may use the straight-line distance between the two corner points as the defect length of the wafer.

[0118] However, if the number of corner points on the edge of the wafer is greater than 2, the defect detection device cannot determine which two corner points correspond to the same defect. This problem is particularly prominent when the distances between multiple corner points are close.

[0119] Based on the above situation, determining the defect length may, for example, include: determining the image feature value of the connected pixels on the line between the first corner point and the second corner point in the corner points in the image to be tested; and in response to the existence of the connected pixels whose difference with the image feature value of the first corner point or the second corner point is greater than the first threshold, determining that there is a defect between the first corner point and the second corner point, and determining the distance between the first corner point and the second corner point as the defect length of the wafer between the first corner point and the second corner point. The second corner point may be selected by the above-mentioned "method one" and "method two".

[0120] It should be understood that, without departing from the teaching of the present application, the first threshold value can be set based on experience, for example, the first threshold value can be 0, or other values ​​greater than 0, for example, 0 < first threshold value < the difference between the maximum and minimum values ​​of the image characteristic values ​​of the pixels in the image. When the first threshold value is greater than 0, the situation in which the defect detection device incorrectly determines the defect position due to the difference between the image characteristic values ​​(such as grayscale values) of the pixels on the edge of the wafer or the pixels near the edge of the wafer being uneven can be reduced, and the present application does not limit this.

[0121] As an example, when it is determined that there is no difference or there is a difference but the difference is less than the first threshold (i.e., the second corner point is not another corner point of the gap at the first corner point), the defect detection module 2300 selects the second corner point again and re-executes the steps of obtaining the image feature values ​​of the pixels between the first corner point and the second corner point in the image to be tested, and determining the defect length of the wafer at the first corner point, so as to re-find the defect at the first corner point.

[0122] For example, the defect detection module 2300 first selects a corner point located on the same pixel path as the second corner point. If it is determined that the second corner point is not another corner point of the gap at the first corner point, a corner point adjacent to or close to the first corner point can be selected as the second corner point, and subsequent operations can be performed again.

[0123] It should be understood that without departing from the teachings of this application, when it is determined that the second corner point is another corner point of the gap that is not at the first corner point, the defect detection module 2300 can also find the defect and determine the defect length in other ways, and this application does not impose any restrictions on this.

[0124] In some embodiments of the present application, when it is determined that the second corner point is another corner point of the notch at the first corner point, the defect detection module 2300 can also select a second corner point again for the first corner point. For example, after determining that J2 is another corner point of the defect at J1 and determining the defect length between J1 and J2, J3 is used as the second corner point, and the above judgment operation is performed for J1 and J3. By selecting multiple second corner points for the first corner point, it is possible to reduce the situation where defects are missed when there are continuous defects on the wafer.

[0125] In some embodiments of the present application, since the probability of a corner point being the corner point of multiple defects at the same time is small, the defect detection module 2300 can remove the first corner point and the other corner point of the defect at the first corner point from the multiple corner points of the pixel path after determining the defect length between the first corner point and the second corner point, so as to reduce the loss of computing resources caused by searching for the other corner point of the defect at the first corner point and determining the defect length, thereby improving the defect detection efficiency of the wafer.

[0126] It should be understood that, without departing from the teachings of the present application, the first corner point and another corner point of the defect at the first corner point may not be removed from the multiple corner points of the pixel path to reduce the possibility of missed defects when continuous defects occur at the edge of the wafer.

[0127] It is worth mentioning that all modules involved in this embodiment are logic modules. In practical applications, a logic unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, this embodiment does not introduce units that are not closely related to solving the technical problem proposed by the present invention, but this does not mean that there are no other units in this embodiment.

[0128] The embodiments of the present application also provide a detection device and a readable storage medium.

[0129] Fig. 9 It is a block diagram of a detection device 3000 according to an embodiment of the present application. The device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0130] like Fig. 9As shown, the detection device 3000 includes: one or more processors 3100, a memory 3200, and an interface (not shown) for connecting various components, including a high-speed interface and a low-speed interface. The memory 3200 can be used to store computer instructions. The processor 3100 can be used to communicate with the memory to execute computer instructions, thereby realizing the defect detection method mentioned in the above embodiment. The various components are connected to each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor 3100 can process the instructions executed in the detection device 3000, including instructions stored in or on the memory 3200 to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In other embodiments, if necessary, multiple processors 3100 and / or multiple buses can be used together with multiple memories 3200 and multiple memories 3200. Similarly, multiple detection devices 3000 can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig. 9 A processor 3100 is taken as an example.

[0131] The memory 3200 is a readable storage medium provided in the present application, for example, a non-transitory computer readable storage medium. The memory 3200 stores instructions executable by at least one processor 3100, so that at least one processor 3100 executes the defect detection method provided in the present application. The readable storage medium of the present application stores computer instructions, which are used to cause a computer to execute the defect detection method for a wafer provided in the present application.

[0132] The memory 3200 is a non-transient computer-readable storage medium that can be used to store non-transient software programs, non-transient computer executable programs and modules. The processor 3100 executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory 3200, that is, implements the defect detection method for wafers in the above method embodiment.

[0133] The memory 3200 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the detection device for quality control, etc. In addition, the memory 3200 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage devices. In some embodiments, the memory 3200 may include a memory remotely arranged relative to the processor 3100, and these remote memories may be connected to the detection device 3000 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0134] The detection device 3000 may further include: an input device 3300 and an output device 3400. The processor 3100, the memory 3200, the input device 3300 and the output device 3400 may be connected via a bus or other means. Fig. 9 The example of connecting through bus is taken in the following.

[0135] The input device 3300 can receive input digital or character information, and generate key signal input related to user settings and function control of the detection device for quality control, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator rod, one or more mouse buttons, a trackball, a joystick and other input devices. The output device 3400 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display and a plasma display. In some embodiments, the display device may be a touch screen.

[0136] Various implementations of the systems and techniques described herein can be realized in digital electronic circuit systems, integrated circuit systems, dedicated ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0137] These computer programs (also referred to as programs, software, software applications, or code) include machine instructions for programmable processors and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or means (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0138] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0139] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area networks, wide area networks, and the Internet.

[0140] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a server of a distributed system, or a server combined with a blockchain. The server may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. The server may be a server of a distributed system, or a server combined with a blockchain. The server may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology.

[0141] According to the implementation mode of the present application, defect detection is performed on the wafer by analyzing the pixel path between pixels at the edge of the wafer, so that the detection equipment can automatically detect wafer defects, thereby reducing the difficulty of setting up the wafer product line and the probability of false alarms in manual integration, thereby improving the efficiency of wafer online, reducing the cost of setting up the wafer product line, and improving the accuracy of the product line.

[0142] The above description is only an implementation method of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of protection involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the technical concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A defect detection method for a wafer, characterized in that: include: Detecting pixels on an edge of the wafer in the image to be tested of the wafer; Selecting a plurality of pixels from the pixels on the edge, and determining a pixel path between adjacent pixels in the selected plurality of pixels; as well as determining whether the wafer has a defect based on the pixel path; The step of selecting a plurality of pixels from the pixels on the edge and determining a pixel path between adjacent pixels in the selected plurality of pixels comprises: Detecting the center and radius of the edge; Taking the line connecting the center of the circle and a pixel selected arbitrarily on the edge as the rotation line, taking the center of the circle as the vertex, rotating the rotation line, and selecting the pixel coincident with the end of the rotation line as the pixel for determining the pixel path, until the rotation line returns to the starting position; and The pixels are connected in sequence to obtain the pixel paths between the pixels.

2. The method according to claim 1, wherein: Determining whether the wafer has a defect based on the pixel path includes: In response to the presence of a corner point on the pixel path, it is determined that the wafer has a defect.

3. The method according to claim 2, wherein: The corner points include pixels on the pixel path where the gradient suddenly changes; or, The corner points include pixels on the pixel path whose grayscale values ​​suddenly change.

4. The method according to claim 2, wherein: The method further comprises: In response to the wafer having a defect, a defect length is determined according to the distance between the corner points.

5. The method according to claim 4, wherein: Determining the defect length includes: Determine image feature values ​​of connected pixels in the image to be tested that are located on a line connecting a first corner point and a second corner point among the corner points; and In response to the existence of connected pixels whose image feature value difference with the first corner point or the second corner point is greater than a first threshold, it is determined that the defect exists between the first corner point and the second corner point, and the distance between the first corner point and the second corner point is determined as the defect length of the wafer between the first corner point and the second corner point.

6. The method according to claim 5, wherein: The second corner point and the first corner point are located on the same pixel path.

7. The method according to claim 5, wherein: The second corner point is a corner point adjacent to or close to the first corner point.

8. The method according to any one of claims 5 to 7, wherein: The image characteristic value is a gradient value or a grayscale value.

9. A defect detection device for a wafer, characterized in that: include: An edge detection module, used to detect pixels on the edge of the wafer in the image to be tested of the wafer; A path determination module, used for selecting a plurality of pixels from the pixels on the edge, and determining a pixel path between adjacent pixels in the selected plurality of pixels; as well as A defect detection module, used for determining whether the wafer has a defect based on the pixel path; Wherein, the path determination module is further configured to: Detecting the center and radius of the edge; Taking the line connecting the center of the circle and a pixel selected arbitrarily on the edge as the rotation line, taking the center of the circle as the vertex, rotating the rotation line, and selecting the pixel coincident with the end of the rotation line as the pixel for determining the pixel path, until the rotation line returns to the starting position; as well as The pixels are connected in sequence to obtain the pixel paths between the pixels.

10. The device according to claim 9, wherein: The defect detection module is configured to: In response to the presence of a corner point on the pixel path, it is determined that the wafer has a defect.

11. The device according to claim 10, wherein: The defect detection module is further configured to: In response to the wafer having a defect, a defect length is determined according to the distance between the corner points.

12. The device according to claim 11, wherein The defect detection module is configured to: Determine image feature values ​​of connected pixels located on a line connecting a first corner point and a second corner point among the corner points in the image to be tested; as well as In response to the existence of connected pixels whose image feature value difference with the first corner point or the second corner point is greater than a first threshold, it is determined that the defect exists between the first corner point and the second corner point, and the distance between the first corner point and the second corner point is determined as the defect length of the wafer between the first corner point and the second corner point.

13. The device according to claim 12, wherein: The second corner point and the first corner point are located on the same pixel path.

14. The device according to claim 12, wherein: The second corner point is a corner point adjacent to or close to the first corner point.

15. The device according to claim 12, wherein: The image characteristic value is a gradient value or a grayscale value.

16. A detection device, characterized in that: include: Memory, for storing computer instructions; as well as A processor, configured to communicate with the memory to execute the computer instructions, thereby implementing the defect detection method according to any one of claims 1 to 8.

17. A readable storage medium, characterized in that: The readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the defect detection method according to any one of claims 1 to 8 is implemented.

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