Wafer defect detection method and device

Abstract

The present application discloses a method and device for detecting wafer defects. The method includes: scanning the wafer surface to obtain a grayscale image of the wafer surface; searching for suspected defective pixels; calculating the grayscale average value of the neighboring pixels of the suspected defective pixel; the neighboring pixels include several pixels located on the first side of the suspected defective pixel and several pixels located on the second side of the suspected defective pixel; determining whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value to obtain a determination result; determining whether the suspected defective pixel is a defect according to the determination result and the preset grayscale difference absolute value threshold of the bright area and the dark area. The method provided by the present disclosure avoids the influence of the grayscale value of the suspected defective pixel on the grayscale value average value, and achieves the beneficial effect of improving the accuracy of defect detection and reducing misjudgment.

Description

[0001] Technical Area

[0002] The present disclosure relates to the field of semiconductor technology, and more particularly to a method and device for detecting wafer defects. Background Art

[0003] In the semiconductor product manufacturing industry, in order to improve product yield and improve defects, the defect detection process is very important. Redundancy, crystal defects, and scratch pattern omissions are all common wafer defects. Wafer surface redundancy, among the surface defects of the wafer, the redundancy on the wafer surface is a common type of defect on the wafer surface. Nano-scale tiny particles, micron-scale dust, and residues from related processes may all cause redundant defects on the wafer surface. During the defect detection process, the defect detection equipment obtains the detection data and uses the defect detection algorithm to determine whether it is a defect. In the prior art, there are many problems, such as the defect detection rate is not high enough, the false detection rate is high, and the proportion of false defects that are misjudged is high, which cannot meet the actual application needs in the semiconductor product manufacturing process.

[0004] The grayscale value of each pixel obtained by the inspection equipment is compared with the pixel next to it, and the grayscale difference is calculated. The grayscale curve is obtained by the grayscale difference. Figure 1 As shown. The threshold is a benchmark that uses grayscale difference to distinguish whether it is a defect. For example, if the threshold is 50, if the grayscale difference is greater than 50, it is a defect, and if the grayscale difference is less than 50, it is not a defect. The fixed threshold is a fixed value preset based on the actual application conditions. The problem with using a fixed threshold is that it is easy to make misjudgments when inspecting wafers for defects, and many false defects are detected. Depending on the grayscale curve of the wafer, many false defects will be generated in a specific wafer using a fixed threshold. Figure 1 In the example, if the curve of wafer B is compared with the threshold value, the right end of the curve is determined to be a defect even though it is not a defect.

[0005] like Figure 2 As shown, in order to improve the problems existing in the fixed threshold, a dynamic threshold is used. The dynamic threshold is not a fixed value, but the threshold used is different according to the different grayscale curves obtained on the wafer. Figure 2 It can be seen that the grayscale curves of wafer A and wafer B are different, and the threshold changes automatically according to the curves. Dynamic thresholds also have defects. There are various patterns and materials on the wafers used to make semiconductor chips. Therefore, the range of grayscale values ​​obtained on the wafer is also quite large. The image of the wafer is presented in a light and dark manner. The light and dark areas are different depending on the position of the wafer. Using dynamic thresholds, it is impossible to distinguish between light and dark areas. Summary of the invention

[0006] The purpose of the present disclosure is to provide a method and apparatus for detecting wafer defects. In order to have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important components or to describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0007] According to one aspect of an embodiment of the present disclosure, a method for detecting wafer defects is provided, comprising:

[0008] Scanning a wafer surface to obtain a grayscale image of the wafer surface; the wafer includes a plurality of identical bare chips; the grayscale image includes a plurality of pattern units; each of the pattern units corresponds to each of the bare chips one by one; each of the pattern units includes two grayscale regions, a bright region and a dark region; each of the pattern units includes a plurality of pixels; the bright region and the dark region each have their own preset grayscale value ranges;

[0009] Find suspected defective pixels;

[0010] Calculating the grayscale average of the neighboring pixels of the suspected defective pixel; the neighboring pixels include a number of pixels located on a first side of the suspected defective pixel and a number of pixels located on a second side of the suspected defective pixel; the second side is a side opposite to the first side;

[0011] Determine whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value, and obtain a determination result; the bright area and the dark area respectively have their own preset grayscale difference absolute value thresholds;

[0012] Whether the suspected defective pixel is defective is determined according to the determination result and the preset grayscale difference absolute value thresholds of the bright area and the dark area respectively.

[0013] According to another aspect of the embodiments of the present disclosure, there is provided a wafer defect detection device, comprising:

[0014] A scanning module is used to scan a wafer surface to obtain a grayscale image of the wafer surface; the wafer includes a plurality of identical bare chips; the grayscale image includes a plurality of pattern units; all the pattern units correspond to all the bare chips one by one; each of the pattern units includes two grayscale areas, a bright area and a dark area; each of the pattern units includes a plurality of pixels; the bright area and the dark area each have their own preset grayscale value range;

[0015] A search module, used to search for suspected defective pixels;

[0016] a calculation module, configured to calculate the grayscale average of the neighboring pixels of the suspected defective pixel; the neighboring pixels include a number of pixels located on a first side of the suspected defective pixel and a number of pixels located on a second side of the suspected defective pixel; the second side is a side opposite to the first side;

[0017] A first determination module is used to determine whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value, and obtain a determination result; the bright area and the dark area respectively have their own preset grayscale difference absolute value thresholds;

[0018] The second determination module is used to determine whether the suspected defective pixel is a defect according to the determination result and a preset grayscale difference absolute value threshold of each of the bright area and the dark area.

[0019] According to another aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned wafer defect detection method.

[0020] According to another aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. The program is executed by a processor to implement the above-mentioned wafer defect detection method.

[0021] The technical solution provided by one aspect of the embodiments of the present disclosure may have the following beneficial effects:

[0022] The wafer defect detection method provided by the embodiment of the present disclosure obtains a number of identical pattern units by scanning the wafer surface, finds out suspected defective pixels, calculates the grayscale average value of the neighboring pixels of the suspected defective pixels, determines whether the suspected defective pixels belong to a bright area or a dark area according to the grayscale average value, and determines whether the suspected defective pixels are defects according to the determination result and the preset grayscale difference absolute value thresholds of the bright area and the dark area respectively, thereby avoiding the influence of the grayscale value of the suspected defective pixels on the grayscale value average value, and achieving the beneficial effects of improving the accuracy of defect detection and reducing misjudgments.

[0023] Other features and advantages of the present disclosure will be described in the subsequent description, and part of them will become apparent from the description, or some of them can be inferred or determined without doubt from the description, or understood by practicing the embodiments of the present disclosure. The purposes and other advantages of the present disclosure can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present disclosure. For ordinary technicians in this area, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 A curve diagram showing the relationship between the number of defects and the grayscale difference of wafer A and wafer B in the method using a fixed threshold in the prior art is shown;

[0026] Figure 2 A curve diagram showing the relationship between the number of defects and the grayscale difference of wafer A and wafer B in the method using a dynamic threshold in the prior art is shown;

[0027] Figure 3 shows a grayscale image of the wafer surface;

[0028] Figure 4 An image of a pattern unit in a wafer grayscale image is shown;

[0029] Figure 5 A grayscale table of some pixels in a certain pattern unit in one embodiment of the present disclosure is shown;

[0030] Figure 6 Shows Figure 5 A table of the absolute value of the grayscale difference between two adjacent columns of pixels;

[0031] Figure 7 Shows Figure 5 Schematic diagram of a pixel with a grayscale value of 180 in the G-th column and its neighboring pixels;

[0032] Figure 8 A flow chart of a method for detecting wafer defects according to an embodiment of the present application is shown;

[0033] Fig. 9 A structural block diagram of a wafer defect detection device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0034] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0035] Various structural schematic diagrams according to embodiments of the present disclosure are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and technicians in this field may design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0036] In the context of the present disclosure, when a layer / element is referred to as being "on" another layer / element, the layer / element may be directly on the other layer / element or an intervening layer / element may exist between them. In addition, if a layer / element is "on" another layer / element in one orientation, the layer / element may be "below" the other layer / element when the orientation is reversed.

[0037] like Figure 3 As shown in FIG. 1 , it is a grayscale image of a wafer surface. The wafer includes a plurality of identical dies. The grayscale image has a plurality of pattern units. Each pattern unit corresponds to each die. The pattern units numbered 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12 are marked in the figure. Figure 4 As shown, each pattern unit has two grayscale areas, a bright area and a dark area, and each pattern unit includes a plurality of pixels.

[0038] like Figure 5 As shown, A, B, C, D, E, F, G, H, I, J, K, and L are used to represent the pixels at the same position in the 12 pattern units. The 8 pixels in the column A (here, each column takes 8 pixels as an example, and the actual number of pixels can be other numbers) are the pixels in Die1, the 8 pixels in the column B are the pixels in Die2, and so on. The upper four rows are the pixels in the bright area, and the lower four rows are the pixels in the dark area.

[0039] Calculate the absolute value of the grayscale difference between each column of pixels and the column of pixels to its right, such as Figure 6 shown.

[0040] from Figure 6 It can be seen that the grayscale difference in the bold box is too large (it can be compared with the preset threshold to determine the excessive grayscale difference), thereby determining the pixels corresponding to column G, rows 2, 3, 4, 6, 7 and 8 ( Figure 5 The pixels in the figure are suspected defective pixels.

[0041] like Figure 7As shown, taking the pixel corresponding to the grayscale value 180 as an example, the grayscale average values ​​of the four pixels 140, 150, 160, 140 on the left and the three pixels 155, 162 and 150 on the right are calculated. The calculation formula is

[0042] (140+150+160+140+155+162+150) / 7=151.

[0043] The four pixels on the left and the three pixels on the right are neighboring pixels of the pixel corresponding to the grayscale value 180. The range of the neighboring pixels can be adjusted according to actual needs. For example, the three pixels on the left and the four pixels on the right can be used as neighboring pixels, and so on.

[0044] For example, assuming that the preset grayscale value range of the dark area is [0,127) and the preset grayscale value range of the bright area is [128,255), the obtained grayscale average value 151 is compared with the preset grayscale value ranges of the bright area and the dark area respectively, and it can be determined that the grayscale average value 151 belongs to the bright area.

[0045] The bright region has a preset first grayscale difference absolute value threshold. For example, assuming that the first grayscale difference absolute value threshold of the bright region is 25, a pixel with a grayscale difference absolute value greater than 25 is determined to be a defect. Figure 7 As shown, the grayscale difference absolute value between the pixel in the Gth column and the pixel in the adjacent column in the bright area is in the bold box M. For example, assuming that the first grayscale difference absolute value threshold of the bright area is 40, the pixel with a grayscale difference absolute value greater than 40 is determined to be a defect.

[0046] The dark area has a preset second grayscale difference absolute value threshold, which may be different from the first grayscale difference absolute value threshold. For example, if the first grayscale difference absolute value threshold of the bright area is 30, the second grayscale difference absolute value threshold of the dark area may be set to 40. Figure 6 As shown, the absolute value of each grayscale difference in the bold box N is the absolute value of the grayscale difference between the pixel in the Gth column and the pixel in the adjacent column in the dark area.

[0047] The purpose of this is to determine whether each pixel belongs to a dark area or a bright area by the average grayscale value of neighboring pixels. After determining the grayscale area to which each pixel belongs, the corresponding grayscale difference absolute value threshold is applied.

[0048] In order to solve the defects of using dynamic thresholds, such as Figure 8 As shown, an embodiment of the present disclosure provides a method for detecting wafer defects, comprising the following steps:

[0049] S10, scanning the wafer surface to obtain a grayscale image of the wafer surface; the wafer includes a plurality of identical bare chips; the grayscale image has a plurality of pattern units. Each pattern unit corresponds to each bare chip one by one; each of the pattern units includes two grayscale regions, a bright region and a dark region; each of the pattern units includes a plurality of pixels; the bright region and the dark region each have their own preset grayscale value range.

[0050] Scanning the wafer surface using a scanning device includes: incident light or electrons on the wafer surface, collecting reflected or scattered light or electrons, and obtaining a grayscale image of the wafer surface.

[0051] like Figure 5 As shown, it is a grayscale image of the surface of a wafer, and the wafer includes a plurality of identical dies Die; the grayscale image has a plurality of pattern units. Each pattern unit corresponds to each die one by one. The pattern units numbered 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12 are marked in the figure. Each pattern unit has two grayscale areas, a bright area and a dark area, and each pattern unit includes a plurality of pixels.

[0052] S20, searching for suspected defective pixels.

[0053] In some embodiments, S20 includes:

[0054] S201, respectively calculating the absolute value of the grayscale difference between two pixels in each corresponding pixel pair of each pattern unit and an adjacent pattern unit located on a first side; the first side may be a left side or a right side, which is specifically set according to actual needs.

[0055] S202: Determine a suspected defective pixel according to the absolute value of the grayscale difference.

[0056] like Figure 6 As shown, A, B, C, D, E, F, G, H, I, J, K, and L are used to represent the pixels at the same position in the 12 pattern units. The 8 pixels in the column A (here, each column is taken as an example of 8 pixels, and the actual number of pixels can be greater than 8) are the pixels in the pattern unit 1, the 8 pixels in the column B are the pixels in the pattern unit 2, and so on. The upper four rows are the pixels in the bright area, and the lower four rows are the pixels in the dark area.

[0057] Calculate the absolute value of the grayscale difference between each column of pixels and the column of pixels to its right, such as Figure 7 shown.

[0058] from Figure 7 It can be seen from the figure that the grayscale difference in the bold box is too large, so the pixels corresponding to column G, rows 2, 3, 4, 6, 7 and 8 are determined ( Figure 6 The pixels in the figure are suspected defective pixels.

[0059] S30, calculating the grayscale average of the neighboring pixels of the suspected defective pixel; the neighboring pixels include a number of pixels located on a first side of the suspected defective pixel and a number of pixels located on a second side of the suspected defective pixel; the second side is a side opposite to the first side, if the first side is the left side, then the second side is the right side, if the first side is the right side, then the second side is the left side.

[0060] like Figure 7 As shown, taking the pixel corresponding to the grayscale value 180 as an example, the grayscale average values ​​of the four pixels 140, 150, 160, 140 on the left and the three pixels 155, 162 and 150 on the right are calculated. The calculation formula is

[0061] (140+150+160+140+155+162+150) / 7=151.

[0062] S40, determining whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value, and obtaining a determination result; the bright area and the dark area respectively have their own preset grayscale difference absolute value thresholds.

[0063] In some embodiments, S40 includes:

[0064] S401, comparing the grayscale average value with respective preset grayscale value ranges of the bright area and the dark area;

[0065] S402: If the grayscale average value belongs to the preset grayscale value range of the bright area, the suspected defective pixel belongs to the bright area;

[0066] S403: If the grayscale average value belongs to the preset grayscale value range of the dark area, the suspected defective pixel belongs to the dark area.

[0067] For example, assuming that the preset grayscale value range of the dark area is [0,127) and the preset grayscale value range of the bright area is [128,255), the obtained grayscale average value 151 is compared with the preset grayscale value ranges of the bright area and the dark area respectively, and it can be determined that the grayscale average value 151 belongs to the bright area.

[0068] S50: Determine whether the suspected defective pixel is defective according to the determination result and the preset grayscale difference absolute value thresholds of the bright area and the dark area respectively.

[0069] In some embodiments, S50 includes:

[0070] S501, if the determination result is that the suspected defective pixel belongs to the bright area, determining whether the absolute value of the grayscale difference of the other pixel in the corresponding pixel pair corresponding to the suspected defective pixel is greater than a preset grayscale difference absolute value threshold of the bright area; if so, determining that the suspected defective pixel is a defect; if not, determining that the suspected defective pixel is not a defect;

[0071] S502. If the determination result is that the suspected defective pixel belongs to the dark area, determine whether the absolute value of the grayscale difference of the other pixel in the corresponding pixel pair corresponding to the suspected defective pixel is greater than the preset grayscale difference absolute value threshold of the dark area; if so, determine that the suspected defective pixel is a defect; if not, determine that the suspected defective pixel is not a defect.

[0072] The bright area has a preset first grayscale difference absolute value threshold. For example, assuming that the first grayscale difference absolute value threshold of the bright area is 25, a pixel with a grayscale difference absolute value greater than 25 is determined to be a defect. For example, assuming that the first grayscale difference absolute value threshold of the bright area is 40, a pixel with a grayscale difference absolute value greater than 40 is determined to be a defect.

[0073] The dark area has a preset second grayscale difference absolute value threshold, which may be different from the first grayscale difference absolute value threshold. For example, if the first grayscale difference absolute value threshold of the bright area is 30, the second grayscale difference absolute value threshold of the dark area may be set to 40.

[0074] The purpose of this is to determine whether each pixel belongs to a dark area or a bright area by the average grayscale value of neighboring pixels. After determining the grayscale area to which each pixel belongs, the corresponding grayscale difference absolute value threshold is applied.

[0075] The wafer defect detection method provided in the embodiment of the present application obtains a number of identical pattern units by scanning the wafer surface, finds out suspected defective pixels, calculates the grayscale average value of the neighboring pixels of the suspected defective pixels, determines whether the suspected defective pixels belong to a bright area or a dark area according to the grayscale average value, and determines whether the suspected defective pixels are defects based on the determination result and the preset grayscale difference absolute value thresholds of the bright area and the dark area respectively, thereby avoiding the influence of the grayscale value of the suspected defective pixels on the grayscale value average value, and achieving the beneficial effects of improving the accuracy of defect detection and reducing misjudgments.

[0076] like Fig. 9 As shown, another embodiment of the present application provides a wafer defect detection device, comprising:

[0077] A scanning module is used to scan a wafer surface to obtain a grayscale image of the wafer surface; the wafer includes a plurality of identical bare chips; the grayscale image includes a plurality of pattern units; all the pattern units correspond to all the bare chips one by one; each of the pattern units includes two grayscale areas, a bright area and a dark area; each of the pattern units includes a plurality of pixels; the bright area and the dark area each have their own preset grayscale value range;

[0078] A search module, used to search for suspected defective pixels;

[0079] a calculation module, configured to calculate the grayscale average of the neighboring pixels of the suspected defective pixel; the neighboring pixels include a number of pixels located on a first side of the suspected defective pixel and a number of pixels located on a second side of the suspected defective pixel; the second side is a side opposite to the first side;

[0080] A first determination module is used to determine whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value, and obtain a determination result; the bright area and the dark area respectively have their own preset grayscale difference absolute value thresholds;

[0081] The second determination module is used to determine whether the suspected defective pixel is a defect according to the determination result and a preset grayscale difference absolute value threshold of each of the bright area and the dark area.

[0082] In some embodiments, the scanning module is specifically used to: incident light or electrons onto the wafer surface, and collect reflected or scattered light or electrons.

[0083] In some embodiments, the search module includes:

[0084] A first unit, configured to respectively calculate the absolute value of the grayscale difference between two pixels in each corresponding pixel pair of each pattern unit and an adjacent pattern unit located on the first side;

[0085] The second unit is used to determine the suspected defective pixel according to the absolute value of the grayscale difference.

[0086] Another embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the wafer defect detection method of any of the above-mentioned embodiments.

[0087] Another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the wafer defect detection method of any of the above-mentioned embodiments.

[0088] In the above description, the technical details of the patterning and etching of each layer are not described in detail. However, those skilled in the art should understand that various technical means can be used to form layers, regions, etc. of the desired shape. In addition, in order to form the same structure, those skilled in the art can also design methods that are not completely the same as the methods described above. In addition, although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in combination to advantage.

[0089] The embodiments of the present disclosure are described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, a person skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for detecting wafer defects, characterized in that: include: Scanning a wafer surface to obtain a grayscale image of the wafer surface; the wafer includes a plurality of identical bare chips; the grayscale image includes a plurality of pattern units; each of the pattern units corresponds to each of the bare chips one by one; each of the pattern units includes two grayscale regions, a bright region and a dark region; each of the pattern units includes a plurality of pixels; the bright region and the dark region each have their own preset grayscale value ranges; Find suspected defective pixels; Calculating the grayscale average of the neighboring pixels of the suspected defective pixel; the neighboring pixels include a number of pixels located on a first side of the suspected defective pixel and a number of pixels located on a second side of the suspected defective pixel; the second side is a side opposite to the first side; Determine whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value, and obtain a determination result; the bright area and the dark area respectively have their own preset grayscale difference absolute value thresholds; Determining whether the suspected defective pixel is a defect according to the determination result and the preset grayscale difference absolute value thresholds of the bright area and the dark area; The step of searching for suspected defective pixels comprises: respectively calculating the absolute value of the grayscale difference between two pixels in each corresponding pixel pair of each pattern unit and an adjacent pattern unit located on the first side; The suspected defective pixel is determined according to the absolute value of the grayscale difference.

2. The method according to claim 1, characterized in that Scanning the wafer surface includes: incident light or electrons onto the wafer surface, and collecting reflected or scattered light or electrons.

3. The method according to claim 1, characterized in that The determining, according to the grayscale average value, whether the suspected defective pixel belongs to the bright area or the dark area to obtain a determination result includes: Comparing the grayscale average with respective preset grayscale value ranges of the bright area and the dark area; If the grayscale average value belongs to the preset grayscale value range of the bright area, the suspected defective pixel belongs to the bright area; If the grayscale average value belongs to the preset grayscale value range of the dark area, the suspected defective pixel belongs to the dark area.

4. The method according to claim 3, characterized in that: The determining whether the suspected defective pixel is a defect according to the determination result and the preset grayscale difference absolute value thresholds of the bright area and the dark area respectively includes: If the determination result is that the suspected defective pixel belongs to the bright area, determining whether the absolute value of the grayscale difference of the other pixel in the corresponding pixel pair corresponding to the suspected defective pixel is greater than a preset grayscale difference absolute value threshold of the bright area; if so, determining that the suspected defective pixel is a defect; if not, determining that the suspected defective pixel is not a defect; If the determination result is that the suspected defective pixel belongs to the dark area, determine whether the absolute value of the grayscale difference of the other pixel in the corresponding pixel pair corresponding to the suspected defective pixel is greater than the preset grayscale difference absolute value threshold of the dark area; if so, determine that the suspected defective pixel is a defect; if not, determine that the suspected defective pixel is not a defect.

5. A wafer defect detection device, characterized in that: include: A scanning module is used to scan a wafer surface to obtain a grayscale image of the wafer surface; the wafer includes a plurality of identical bare chips; the grayscale image includes a plurality of pattern units; all the pattern units correspond to all the bare chips one by one; each of the pattern units includes two grayscale areas, a bright area and a dark area; each of the pattern units includes a plurality of pixels; the bright area and the dark area each have their own preset grayscale value range; A search module, used to search for suspected defective pixels; a calculation module, configured to calculate the grayscale average of the neighboring pixels of the suspected defective pixel; the neighboring pixels include a number of pixels located on a first side of the suspected defective pixel and a number of pixels located on a second side of the suspected defective pixel; the second side is a side opposite to the first side; A first determination module is used to determine whether the suspected defective pixel belongs to the bright area or the dark area according to the grayscale average value, and obtain a determination result; the bright area and the dark area respectively have their own preset grayscale difference absolute value thresholds; A second determination module, configured to determine whether the suspected defective pixel is a defect according to the determination result and a preset grayscale difference absolute value threshold of each of the bright area and the dark area; The search module includes: A first unit, configured to respectively calculate the absolute value of the grayscale difference between two pixels in each corresponding pixel pair of each pattern unit and an adjacent pattern unit located on the first side; The second unit is used to determine the suspected defective pixel according to the absolute value of the grayscale difference.

6. The device according to claim 5, characterized in that The scanning module is specifically used to: incident light or electrons onto the surface of the wafer, and collect reflected or scattered light or electrons.

7. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method according to any one of claims 1 to 4.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method according to any one of claims 1 to 4.

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