Defect detection method, storage medium and terminal

Abstract

The invention discloses a defect detection method, a storage medium and a terminal, and the method comprises the steps: providing a to-be-detected wafer which comprises a plurality of rows of to-be-detected chips arranged in a first direction; obtaining the number of chips to be detected in each row and judging whether the number reaches a detection number threshold value or not; when it is judged that the number of the to-be-detected chips in any row A is smaller than a detection number threshold value, a compensation difference value between the detection number threshold value and the number of the to-be-detected chips in the row A is obtained; acquiring to-be-detected image data of each to-be-detected chip; copying the to-be-detected image data of any compensation difference number of to-be-detected chips not located in the row A to the row A, and generating compensation difference number of virtual to-be-detected image data; and according to the virtual to-be-detected image data and the to-be-detected image data in the row A and the to-be-detected image data of each row not located in the row A, judging whether the to-be-detected chip corresponding to the to-be-detected image data has defects or not, thereby effectively preventing detection blind spots from being swept in a detection missing area of the to-be-detected wafer.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor manufacturing technology, and in particular to a defect detection method, a storage medium, and a terminal. Background Art

[0002] Semiconductor integrated circuit chips are mass-produced, forming a large number of various types of semiconductor devices on the same substrate and interconnecting them to provide complete electronic functions. Defects generated in any step can lead to circuit failure. Therefore, during the manufacturing process, it is often necessary to perform defect detection and analysis on the manufacturing structure of each step to identify the cause of the defects and eliminate them. However, with the rapid development of ultra-large-scale integrated circuits (ULSI), the integration of chips is getting higher and higher, and the size of devices is getting smaller and smaller. Correspondingly, the size of defects generated during the manufacturing process that are sufficient to affect the device yield is also getting smaller and smaller, placing higher demands on defect detection of semiconductor devices.

[0003] However, there are still many problems in the defect detection process in the existing technology. Summary of the Invention

[0004] The technical problem solved by the present invention is to provide a defect detection method, a storage medium and a terminal to prevent missed detection in the edge area of the wafer and eliminate detection blind spots.

[0005] To solve the above problems, the present invention provides a defect detection method, comprising: providing a wafer to be inspected, the wafer to be inspected comprising several rows of chips to be inspected arranged along a first direction, the chips to be inspected in each row arranged along a second direction, the first direction being perpendicular to the second direction; obtaining the number of chips to be inspected in each row, and judging whether the number of chips to be inspected in each row reaches a detection number threshold; when it is judged that the number of chips to be inspected in any row A is less than the detection number threshold, obtaining a compensation difference between the detection number threshold and the number of chips to be inspected in row A; obtaining image data to be inspected of each chip to be inspected; copying the image data to be inspected of any chip to be inspected that is not located in row A by the compensation difference to row A, generating virtual image data to be inspected by the compensation difference in row A; judging whether the chip to be inspected corresponding to the image data to be inspected has a defect based on the virtual image data to be inspected and the image data to be inspected in row A, as well as the image data to be inspected in each row that is not located in row A.

[0006] Optionally, each of the image data to be detected has the same arrangement and number of pixels, and each pixel has a pixel value to be detected.

[0007] Optionally, the detection quantity threshold is 3, and the compensation difference value is 1 or 2.

[0008] Optionally, when the number of the chips to be detected in row A is 2 and the compensation difference value is 1, the method for determining whether the chip to be detected corresponding to the image data to be detected is defective according to the virtual image data to be detected and the image data to be detected in row A includes: obtaining an absolute value of a first pixel deviation between the pixel values to be detected at corresponding same-position pixel points of the image data to be detected of the chip a to be detected and the image data to be detected of the chip b to be detected in row A; obtaining an absolute value of a second pixel deviation between the pixel values to be detected at corresponding same-position pixel points of the image data to be detected of the chip b to be detected and the virtual image data to be detected in row A; providing a pixel detection threshold; comparing each of the absolute values of the first pixel deviation and each of the absolute values of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip to be detected corresponding to the image data to be detected is defective.

[0009] Optionally, when both the first pixel deviation value and the second pixel deviation value corresponding to the same-position pixel points are greater than the pixel detection threshold, it is determined that the chip b to be detected is defective; when the first pixel deviation value corresponding to the same-position pixel points is greater than the pixel detection threshold and the second pixel deviation value is less than the pixel detection threshold, it is determined that the chip a to be detected is defective.

[0010] Optionally, when the number of the chips to be detected in row A is 1 and the compensation difference value is 2, the method for determining whether the chip to be detected corresponding to the image data to be detected is defective according to the virtual image data to be detected and the image data to be detected in row A includes: obtaining an absolute value of a first pixel deviation between the pixel values to be detected at corresponding same-position pixel points of the image data to be detected of the chip to be detected and the virtual image data c to be detected in row A; obtaining an absolute value of a second pixel deviation between the pixel values to be detected at corresponding same-position pixel points of the image data to be detected of the chip to be detected and the virtual image data d to be detected in row A; providing a pixel detection threshold; comparing each of the absolute values of the first pixel deviation and each of the absolute values of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip to be detected corresponding to the image data to be detected is defective.

[0011] Optionally, when both the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position are greater than the pixel detection threshold, it is determined that the chip a to be detected has a defect; when at least one of the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position is less than the pixel detection threshold, it is determined that the chip to be detected has no defect.

[0012] Optionally, a method for determining whether the chip to be detected corresponding to the image data to be detected is defective according to each row of the image data to be detected that is not in row A includes: obtaining the absolute value of the first pixel deviation between the pixel values to be detected at the corresponding same-position pixel points of the image data to be detected of the chip a to be detected and the image data to be detected of the chip b to be detected among any continuously arranged chips a to be detected, chips b to be detected, and chips c to be detected in each row; the absolute value of the second pixel deviation between the pixel values to be detected at the corresponding same-position pixel points of the image data to be detected of the chip c to be detected and the image data to be detected of the chip b to be detected; providing a pixel detection threshold; comparing each absolute value of the first pixel deviation and each absolute value of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip to be detected corresponding to the image data to be detected is defective.

[0013] Optionally, when both the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position are greater than the pixel detection threshold, it is determined that the chip b to be detected has a defect; when the first pixel deviation value corresponding to the pixel points at the same position is greater than the pixel detection threshold and the second pixel deviation value is less than the pixel detection threshold, it is determined that the chip a to be detected has a defect; when the first pixel deviation value corresponding to the pixel points at the same position is less than the pixel detection threshold and the second pixel deviation value is greater than the pixel detection threshold, it is determined that the chip c to be detected has a defect.

[0014] Optionally, a method for obtaining the number of chips to be detected in each row includes: obtaining the number of chips to be detected in each row through a first scanning process.

[0015] Optionally, a method for obtaining the image data to be detected of each chip to be detected includes: obtaining the image data to be detected of each chip to be detected through a second scanning process.

[0016] Optionally, when it is determined that the number of chips to be detected in each row is greater than or equal to the detection quantity threshold, it is determined whether the chip to be detected corresponding to the image data to be detected is defective according to the image data to be detected in each row.

[0017] Optionally, after determining whether the to-be-detected chip corresponding to the to-be-detected image data has a defect, the method further includes: deleting the virtual to-be-detected image data in row A; forming a scanned image based on the to-be-detected image data of each row, and marking the defect positions of the to-be-detected chips in the scanned image.

[0018] Correspondingly, the technical solution of the present invention also provides a storage medium, on which computer instructions are stored, and characterized in that when the computer instructions run, they execute the steps of the method in any one of the above technical solutions.

[0019] Correspondingly, the technical solution of the present invention also provides a terminal, including a memory and a processor, and a computer instruction capable of running on the processor is stored on the memory, and characterized in that when the processor runs the computer instruction, it executes the steps of the method in any one of the above technical solutions.

[0020] Compared with the prior art, the technical solution of the present invention has the following advantages:

[0021] In the defect detection method of the technical solution of the present invention, when the number of the to-be-detected chips in any row A is detected to be less than the detection quantity threshold, by copying the to-be-detected image data of any of the compensation difference number of the to-be-detected chips that are not in row A into row A, virtual to-be-detected image data of the compensation difference number is generated in row A, thereby effectively preventing detection omission areas in the to-be-detected wafer and eliminating detection blind spots.

[0022] Further, after determining whether the to-be-detected chip corresponding to the to-be-detected image data has a defect, the method further includes: deleting the virtual to-be-detected image data in row A; forming a scanned image based on the to-be-detected image data of each row, and marking the defect positions of the to-be-detected chips in the scanned image. By printing out the physical scanned image, the detected defect positions are presented more intuitively. Description of the Drawings

[0023] Figures 1 to 3 is a schematic structural diagram of each step of a defect detection method;

[0024] Figure 4 is a flowchart of a defect detection method in an embodiment of the present invention;

[0025] Figures 5 to 10 is a schematic structural diagram of each step of a defect detection method in an embodiment of the present invention. Detailed Embodiment

[0026] As described in the background art, there are still many problems in the defect detection process of the prior art. The following will be specifically described with reference to the drawings.

[0027] Figures 1 to 3 It is a schematic structural diagram of each step of a defect detection method.

[0028] Please refer to Figure 1 , provide a wafer 100 to be detected, the wafer 100 to be detected includes a plurality of chips to be detected arranged in a first direction X, each row of the chips to be detected is arranged in a second direction Y, the first direction X is perpendicular to the second direction Y, and the plurality of chips to be detected include: a first chip to be detected 101, a second chip to be detected 102, and a third chip to be detected 103 that are arranged adjacent to each other along the first direction X.

[0029] Please refer to Figure 2 , respectively obtain first image data 101a of the first chip to be detected 101, second image data 102a of the second chip to be detected 102, and third image data 103a of the third chip to be detected 103. The first image data 101a, the second image data 102a, and the third image data 103a have the same arrangement and number of pixel points. Among them, each pixel point of the first image data 101a has a first pixel value to be detected, each pixel point of the second image data 102a has a second pixel value to be detected, and each pixel point of the third image data 103a has a third pixel value to be detected.

[0030] Please refer to Figure 3 , compare the first image data 101a with the second image data 102a, and obtain the absolute value of the first pixel deviation between the first pixel value to be detected of each pixel point in the first image data 101a and the second pixel value to be detected of the pixel point at the corresponding same position in the second image data 102a; compare the second image data 102a with the third image data 103a, and obtain the absolute value of the second pixel deviation between the second pixel value to be detected of each pixel point in the second image data 102a and the third pixel value to be detected of the pixel point at the corresponding same position in the third image data 103a; provide a pixel detection threshold; compare each absolute value of the first pixel deviation and each absolute value of the second pixel deviation with the pixel detection threshold respectively, and determine whether there are defects in the first chip to be detected 101, the second chip to be detected 102, and the third chip to be detected 103.

[0031] Please continue to refer to Figure 3, in one embodiment, when both the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position are greater than the pixel detection threshold, it is determined that the second chip to be detected 102 is defective.

[0032] In one embodiment, when the first pixel deviation value corresponding to the pixel points at the same position is greater than the pixel detection threshold and the second pixel deviation value is less than the pixel detection threshold, it is determined that the first chip to be detected 101 is defective (not shown).

[0033] In one embodiment, when the first pixel deviation value corresponding to the pixel points at the same position is less than the pixel detection threshold and the second pixel deviation value is greater than the pixel detection threshold, it is determined that the third chip to be detected 103 is defective (not shown).

[0034] For the defect scanning of the wafer to be detected 100, the principle of the current industry scanner is to capture defects by comparing the chip to be detected with the chips to be detected arranged along the first direction X on its adjacent two sides. To meet the current wafer defect capture method, it is necessary to require that the number of chips to be detected in each row is greater than or equal to 3.

[0035] However, when approaching the edge region of the wafer to be detected, there are often less than 3 chips to be detected in a row, making it impossible to perform scanning and comparison, resulting in no defect information for the chips to be detected in that row, and further increasing the risk of low yield of the wafer to be detected.

[0036] On this basis, the present invention provides a defect detection method, a storage medium, and a terminal. When it is detected that the number of chips to be detected in any row A is less than the detection quantity threshold, by copying the to-be-detected image data of any of the compensation difference number of chips to be detected that are not in row A into row A, the compensation difference number of virtual to-be-detected image data are generated in row A, thereby effectively preventing detection omission areas in the wafer to be detected and eliminating detection blind spots.

[0037] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention will be given with reference to the accompanying drawings.

[0038] Figure 4 is a flowchart of a defect detection method according to an embodiment of the present invention.

[0039] Please refer to Figure 4 , the defect detection method includes:

[0040] Step S101: Provide a wafer to be detected, where the wafer to be detected includes a plurality of rows of chips to be detected arranged in a first direction, and each row of the chips to be detected is arranged in a second direction, and the first direction is perpendicular to the second direction.

[0041] Step S102: Obtain the number of chips to be detected in each row, and determine whether the number of chips to be detected in each row reaches a detection quantity threshold.

[0042] Step S103: When it is determined that the number of chips to be detected in any row A is less than the detection quantity threshold, obtain a compensation difference value between the detection quantity threshold and the number of chips to be detected in row A.

[0043] Step S104: Obtain the image data to be detected of each chip to be detected.

[0044] Step S105: Copy the image data to be detected of any compensation difference value of the chips to be detected that are not in row A to row A, and generate virtual image data to be detected with the compensation difference value in row A.

[0045] Step S106: Determine whether the chip to be detected corresponding to the image data to be detected has a defect according to the virtual image data to be detected and the image data to be detected in row A, and the image data to be detected of each row that is not in row A.

[0046] The following will describe each step of the defect detection method in detail with reference to the accompanying drawings.

[0047] Figures 5 to 10 It is a schematic structural diagram of each step of a defect detection method in an embodiment of the present invention.

[0048] Please refer to Figure 5 , provide a wafer 200 to be detected, where the wafer 200 to be detected includes a plurality of rows of chips 201 to be detected arranged in a first direction X, and each row of the chips 201 to be detected is arranged in a second direction Y, and the first direction X is perpendicular to the second direction Y.

[0049] It should be noted that in this embodiment, a plurality of the chips 201 to be detected are divided by scribe lanes. After defect detection of the chips 201 to be detected, subsequent cutting processing is performed on the scribe lanes, so that the wafer 200 to be detected is divided into a plurality of the chips 201 to be detected.

[0050] Please refer to Figure 6 , obtain the number of chips 201 to be detected in each row, and determine whether the number of chips 201 to be detected in each row reaches a detection quantity threshold.

[0051] In this embodiment, the method for obtaining the number of the chips 201 to be detected in each row includes: obtaining the number of the chips 201 to be detected in each row through the first scanning process 202.

[0052] In this embodiment, the path of the first scanning process 202 is scanned in an "S" shape as shown in the figure. The first scanning process 202 is only used to detect the number of the chips 201 to be detected in each row, and is not used to obtain the image data of each chip 201 to be detected.

[0053] Please continue to refer to Figure 6 , when it is determined that the number of the chips 201 to be detected in any row A is less than the detection quantity threshold, obtain the compensation difference between the detection quantity threshold and the number of the chips 201 to be detected in row A.

[0054] It should be noted that since the wafer 200 to be detected has a circular structure and the width of the wafer 200 to be detected gradually decreases from the center to the edge, the situation where the number of the chips 201 to be detected is less than the detection quantity threshold often occurs in the edge region of the wafer 200 to be detected.

[0055] In this embodiment, it is shown that the situation where the number of the chips 201 to be detected is less than the detection quantity threshold appears in the edge regions on the opposite sides of the wafer 200 to be detected. Specifically, it is shown that the number of the chips 201 to be detected in row A is 1.

[0056] In other embodiments, the number of the chips 201 to be detected in row A may also be 2.

[0057] In other embodiments, the number of the chips 201 to be detected in each row may also be greater than or equal to 3.

[0058] In this embodiment, the detection quantity threshold is 3. This is because when the subsequent scanning machine performs defect detection, it adopts a row detection principle. Defects are captured by comparing the chips 201 in the middle of each row with the chips 201 on both sides of it, that is, by comparing with two adjacent chips 201 along the first direction X. Therefore, the number of the chips 201 to be detected in each row must be greater than or equal to 3, otherwise the comparison detection cannot be performed.

[0059] In this embodiment, since the number of the chips 201 to be detected in row A is 1 and the detection quantity threshold is 3, the compensation difference is 2.

[0060] In other embodiments, when the number of the chips 201 to be detected in row A is 2, the compensation difference is 1.

[0061] In other embodiments, when the number of the chips 201 to be detected in each row is greater than or equal to 3, the compensation difference does not need to be obtained.

[0062] Please refer to Figure 7 to obtain the image data to be detected of each of the chips 201 to be detected.

[0063] In this embodiment, the method for obtaining the image data to be detected of each of the chips 201 to be detected includes: obtaining the image data to be detected of each of the chips 201 to be detected through a second scanning process 203.

[0064] In this embodiment, the path of the second scanning process 203 also performs scanning according to the "S"-shaped path shown above. The second scanning process 203 is used to obtain the image data of each of the chips 201 to be detected, and stores them in sequence after obtaining the image data of each of the chips 201 to be detected.

[0065] It should be noted that in this embodiment, each of the image data to be detected has the same arrangement and number of pixel points, and each pixel point has a pixel value to be detected, so that it can be used for comparison between different subsequent image data to be detected.

[0066] Please refer to Figure 8 to copy the image data to be detected of any of the compensation difference number of the chips 201 not located in row A into row A, and generate the compensation difference number of virtual image data to be detected in row A.

[0067] In this embodiment, any two corresponding image data to be detected of the chips 201 not located in row A are selected and copied into row A to generate two virtual image data to be detected in row A.

[0068] In other embodiments, when the number of the chips 201 to be detected in row A is 2, any one corresponding image data to be detected of the chips 201 not located in row A is selected and copied into row A to generate one virtual image data to be detected in row A.

[0069] In other embodiments, when the number of the chips 201 to be detected in each row is greater than or equal to 3, no compensation processing for virtual image data to be detected needs to be performed on any row.

[0070] Please refer to Figure 9, based on the virtual image data to be detected and the image data to be detected in row A, as well as the image data to be detected in each row that is not in row A, determine whether there are defects in the chip 201 to be detected corresponding to the image data to be detected.

[0071] In this embodiment, when the number of chips 201 to be detected in any row A is less than the detection quantity threshold, by copying the image data to be detected of any of the compensation difference number of chips 201 that are not in row A into row A, generate the compensation difference number of virtual image data to be detected in row A, thereby effectively preventing detection omissions in the wafer 200 to be detected and eliminating detection blind spots.

[0072] Please continue to refer to Figure 9 , in this embodiment, the number of chips 201 to be detected in row A is 1, and the compensation difference is 2. The method for determining whether there are defects in the chip 201 to be detected corresponding to the image data to be detected based on the virtual image data to be detected and the image data to be detected in row A includes: obtaining the absolute value of the first pixel deviation between the pixel values to be detected at the corresponding same position pixels of the image data to be detected of the chip 201 to be detected in row A and the virtual image data to be detected c; obtaining the absolute value of the second pixel deviation between the pixel values to be detected at the corresponding same position pixels of the image data to be detected of the chip 201 to be detected in row A and the virtual image data to be detected d; providing a pixel detection threshold; comparing each absolute value of the first pixel deviation and each absolute value of the second pixel deviation with the pixel detection threshold respectively to determine whether there are defects in the chip 201 to be detected corresponding to the image data to be detected.

[0073] Please continue to refer to Figure 9 , correspondingly, when both the first pixel deviation value and the second pixel deviation value corresponding to the same position pixel points are greater than the pixel detection threshold, it is determined that the chip 201a to be detected has defects.

[0074] When at least one of the first pixel deviation value and the second pixel deviation value corresponding to the same position pixel points is less than the pixel detection threshold, it is determined that the chip to be detected has no defects (not shown).

[0075] In other embodiments, when the number of the chips to be detected in row A is 2 and the compensation difference value is 1, the method for determining whether the chip to be detected corresponding to the image data to be detected is defective according to the virtual image data to be detected and the image data to be detected in row A includes: obtaining the absolute value of the first pixel deviation between the pixel values to be detected at the corresponding same-position pixels of the image data to be detected of the chip a to be detected and the image data to be detected of the chip b to be detected in row A; obtaining the absolute value of the second pixel deviation between the pixel values to be detected at the corresponding same-position pixels of the image data to be detected of the chip b to be detected and the virtual image data to be detected in row A; providing a pixel detection threshold; comparing each absolute value of the first pixel deviation and each absolute value of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip to be detected corresponding to the image data to be detected is defective. Correspondingly, when both the first pixel deviation value and the second pixel deviation value corresponding to the same-position pixels are greater than the pixel detection threshold, it is determined that the chip b to be detected is defective; when the first pixel deviation value corresponding to the same-position pixels is greater than the pixel detection threshold and the second pixel deviation value is less than the pixel detection threshold, it is determined that the chip a to be detected is defective (not shown).

[0076] In this embodiment, the method for determining whether the chip 201 to be detected corresponding to the image data to be detected in each row not located in row A is defective includes: obtaining the absolute value of the first pixel deviation between the pixel values to be detected at the corresponding same-position pixels of the image data to be detected of the chip a201 to be detected and the image data to be detected of the chip b201 to be detected among any continuously arranged chips a201 to be detected, chips b201 to be detected, and chips c201 to be detected in each row; the absolute value of the second pixel deviation between the pixel values to be detected at the corresponding same-position pixels of the image data to be detected of the chip c201 to be detected and the image data to be detected of the chip b201 to be detected; providing a pixel detection threshold; comparing each absolute value of the first pixel deviation and each absolute value of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip 201 to be detected corresponding to the image data to be detected is defective.

[0077] Please continue to refer to Figure 9 , correspondingly, when both the first pixel deviation value and the second pixel deviation value corresponding to the same-position pixels are greater than the pixel detection threshold, it is determined that the chip b201 to be detected is defective.

[0078] When the first pixel deviation value corresponding to the pixel points at the same position is greater than the pixel detection threshold, and the second pixel deviation value is less than the pixel detection threshold, it is determined that the chip a201 to be detected has a defect (not shown).

[0079] When the first pixel deviation value corresponding to the pixel points at the same position is less than the pixel detection threshold, and the second pixel deviation value is greater than the pixel detection threshold, it is determined that the chip c201 to be detected has a defect (not shown).

[0080] In other embodiments, when it is determined that the number of chips to be detected in each row is greater than or equal to 3, according to the image data to be detected in each row, it is determined whether the chips to be detected corresponding to the image data to be detected have defects. The specific comparison process is the same as the method of determining whether the chips to be detected corresponding to the image data to be detected in each row not located in row A have defects as described above, and will not be elaborated here.

[0081] Please refer to Figure 10 , after determining whether the chip 201 to be detected corresponding to the image data to be detected has a defect, delete the virtual image data to be detected in row A; form a scanned image 300 according to the image data to be detected in each row, and mark the defect position 301 of the chip 201 to be detected in the scanned image 300.

[0082] In this embodiment, by printing out the physical scanned image 300, the detected defect positions are presented more intuitively.

[0083] Correspondingly, an embodiment of the present invention also provides a storage medium, on which computer instructions are stored, and characterized in that when the computer instructions run, they execute the steps of the method in any one of the above embodiments.

[0084] Correspondingly, an embodiment of the present invention also provides a terminal, including a memory and a processor, and computer instructions capable of running on the processor are stored on the memory, and characterized in that when the processor runs the computer instructions, it executes the steps of the method in any one of the above embodiments.

[0085] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention should be subject to the scope defined by the claims.

Claims

1. A defect detection method, characterized in that, Including: Providing a wafer to be detected, the wafer to be detected including a plurality of rows of chips to be detected arranged in a first direction, each row of the chips to be detected being arranged in a second direction, the first direction being perpendicular to the second direction; Obtaining the number of chips to be detected in each row and determining whether the number of chips to be detected in each row reaches a detection quantity threshold; When it is determined that the number of chips to be detected in any row A is less than the detection quantity threshold, obtaining a compensation difference value between the detection quantity threshold and the number of chips to be detected in row A; Obtaining the image data to be detected of each chip to be detected; Copying the image data to be detected of any of the compensation difference value of the chips to be detected that are not in row A to row A, and generating the image data of the compensation difference value of virtual chips to be detected in row A; Judging whether the chip to be detected corresponding to the image data to be detected has a defect according to the virtual image data to be detected and the image data to be detected in row A, and the image data to be detected of each row that is not in row A.

2. The defect detection method according to claim 1, characterized in that, Each of the image data to be detected has pixel points with the same arrangement and quantity, and each pixel point has a pixel value to be detected.

3. The defect detection method according to claim 2, characterized in that The detection quantity threshold is 3, and the compensation difference value is 1 or 2.

4. The defect detection method according to claim 3, wherein When the number of chips to be detected in row A is 2 and the compensation difference value is 1, the method for judging whether the chip to be detected corresponding to the image data to be detected has a defect according to the virtual image data to be detected and the image data to be detected in row A includes: obtaining an absolute value of a first pixel deviation between the pixel values to be detected at corresponding same-position pixel points of the image data to be detected of the chip to be detected a and the image data to be detected of the chip to be detected b in row A; obtaining an absolute value of a second pixel deviation between the pixel values to be detected at corresponding same-position pixel points of the image data to be detected of the chip to be detected b and the virtual image data to be detected in row A; providing a pixel detection threshold; comparing each absolute value of the first pixel deviation and each absolute value of the second pixel deviation with the pixel detection threshold respectively to judge whether the chip to be detected corresponding to the image data to be detected has a defect.

5. The defect detection method according to claim 4, wherein When both the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position are greater than the pixel detection threshold, it is judged that the chip to be detected b has a defect; when the first pixel deviation value corresponding to the pixel points at the same position is greater than the pixel detection threshold and the second pixel deviation value is less than the pixel detection threshold, it is judged that the chip to be detected a has a defect.

6. The defect detection method according to claim 3, wherein When the number of the chips to be detected in row A is 1 and the compensation difference value is 2, the method for determining whether the chip to be detected corresponding to the image data to be detected is defective according to the virtual image data to be detected and the image data to be detected in row A includes: obtaining the absolute value of the first pixel deviation between the pixel values to be detected at the corresponding same-position pixel points of the image data to be detected and the virtual image data to be detected c of the chip to be detected in row A; obtaining the absolute value of the second pixel deviation between the pixel values to be detected at the corresponding same-position pixel points of the image data to be detected and the virtual image data to be detected d of the chip to be detected in row A; providing a pixel detection threshold; comparing each of the absolute values of the first pixel deviation and each of the absolute values of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip to be detected corresponding to the image data to be detected is defective.

7. The defect detection method according to claim 6, wherein When both the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position are greater than the pixel detection threshold, it is determined that the chip to be detected a is defective; when at least one of the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position is less than the pixel detection threshold, it is determined that the chip to be detected is not defective.

8. The defect detection method according to claim 2, wherein The method for determining whether the chip to be detected corresponding to the image data to be detected in each row not located in row A is defective includes: obtaining the absolute value of the first pixel deviation between the pixel values to be detected at the corresponding same-position pixel points of the image data to be detected of the chip to be detected a and the image data to be detected of the chip to be detected b among any continuously arranged chips to be detected a, chips to be detected b, and chips to be detected c in each row; the absolute value of the second pixel deviation between the pixel values to be detected at the corresponding same-position pixel points of the image data to be detected of the chip to be detected c and the image data to be detected of the chip to be detected b; providing a pixel detection threshold; comparing each of the absolute values of the first pixel deviation and each of the absolute values of the second pixel deviation with the pixel detection threshold respectively to determine whether the chip to be detected corresponding to the image data to be detected is defective.

9. The defect detection method according to claim 8, wherein When both the first pixel deviation value and the second pixel deviation value corresponding to the pixel points at the same position are greater than the pixel detection threshold, it is determined that the chip to be detected b is defective; when the first pixel deviation value corresponding to the pixel points at the same position is greater than the pixel detection threshold and the second pixel deviation value is less than the pixel detection threshold, it is determined that the chip to be detected a is defective; When the first pixel deviation value corresponding to the pixel points at the same position is less than the pixel detection threshold and the second pixel deviation value is greater than the pixel detection threshold, it is determined that the chip to be detected c is defective.

10. The defect detection method according to claim 1, characterized in that, [[ID=?]]The method for obtaining the number of the chips to be detected in each row includes: obtaining the number of the chips to be detected in each row by a first scanning process. It should be noted that there seems to be a mistake in the original text where the ID in the last paragraph is written as [[ID=?]] instead of . It has been translated as [[ID=?]] as per the instruction to preserve the original tags. If this is an error in the original, it should be corrected for a more accurate translation.

11. The defect detection method according to claim 1, wherein, The method for obtaining the image data to be detected of each of the chips to be detected includes: obtaining the image data to be detected of each of the chips to be detected through a second scanning process.

12. The defect detection method according to claim 1, wherein When it is determined that the number of the chips to be detected in each row is greater than or equal to the detection quantity threshold, based on the image data to be detected in each row, it is determined whether there are defects in the chips to be detected corresponding to the image data to be detected.

13. The defect detection method according to claim 1, characterized in that After determining whether there are defects in the chips to be detected corresponding to the image data to be detected, it further includes: deleting the virtual image data to be detected in row A; forming a scanned image based on the image data to be detected in each row, and the defect positions of the chips to be detected are marked in the scanned image.

14. A storage medium having computer instructions stored thereon, characterized in that, When the computer instructions run, the steps of the method according to any one of claims 1 to 13 are executed.

15. A terminal, comprising a memory and a processor, wherein computer instructions capable of running on the processor are stored on the memory, characterized in that When the processor runs the computer instructions, the steps of the method according to any one of claims 1 to 13 are executed.

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