Single-view-field defect detection method, device and equipment for wafer and medium

Abstract

The invention discloses a wafer single-view-field defect detection method, device and equipment and a medium. The wafer comprises a plurality of view field areas, the plurality of view field areas comprise at least one single view field area, the single view field area comprises at least three sub single view field areas, the single view field defect detection method comprises the following steps: obtaining a single view field image and a single view field reference image of the single view field area, the single view field image comprises at least three sub single view field images, and the single view field reference image comprises at least three sub single view field images; the sub-single-field-of-view images correspond to the sub-single-field-of-view areas, the single-field-of-view reference images comprise at least three sub-single-field-of-view reference images, and the sub-single-field-of-view reference images correspond to the sub-single-field-of-view images; determining the pixel distortion amount of the sub-single-field-of-view image according to the sub-single-field-of-view image and the sub-single-field-of-view reference image; and determining a defect detection result of the to-be-detected sub-single-field-of-view area according to the pixel distortion amount of the sub-single-field-of-view image. By adopting the single-view-field defect detection method, defect detection of the single-view-field area on the wafer can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of wafer defect detection, and in particular to a single-field-of-view defect detection method, device, equipment and medium for wafers. Background Art

[0002] The economic situation of manufacturing very large scale integrated circuits has led to a progressive reduction in the critical dimensions of integrated circuits. As device dimensions decrease, the size of tolerable defects also decreases, which in turn requires defect inspection equipment with higher sensitivity.

[0003] The fabrication of semiconductor devices, such as logic and memory devices, typically involves processing semiconductor wafers using a number of fabrication processes to form the various features and multiple layers of the semiconductor devices. For example, photolithography is a semiconductor fabrication process that involves transferring a pattern from a mask to a photoresist disposed on a semiconductor wafer. Additional examples of semiconductor fabrication processes include, but are not limited to, chemical mechanical polishing (CMP), etching, deposition, and ion implantation. Defects can form during any of these processes. Therefore, wafers are inspected for defects after more than one process step.

[0004] Die-to-die differential image methods are widely used in defect detection. In classic die-to-die inspection algorithms, to prevent color differences between chips in different rows from affecting the inspection results, three or more fields of view are required within a specific area (e.g., the same row). The difference results of these three or more fields of view are then used to determine whether defects exist in each field of view.

[0005] When using the die-to-die differential imaging method, it is required that a specific area of ​​the wafer contain at least three or more field of view areas. This method cannot be used in scenarios with less than three chip fields of view.

[0006] Therefore, there is an urgent need for an inspection method for a field of view region in which the number of field of view regions in a specific area of ​​a wafer is less than three (ie, a single field of view region). Summary of the Invention

[0007] The present invention provides a method, device, equipment and medium for single-field-of-view defect detection of wafers, so as to solve the problem that existing wafer detection methods cannot perform defect detection on a single-field-of-view area in a wafer.

[0008] In a first aspect, an embodiment of the present invention provides a single field of view defect detection method for a wafer, wherein the wafer includes multiple field of view areas, the multiple field of view areas include at least one single field of view area, the single field of view area includes at least three sub-single field of view areas, and the single field of view defect detection method includes:

[0009] Acquiring a monoscopic image and a monoscopic reference image of the monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images corresponding to the sub-monoscopic area, and the monoscopic reference image includes at least three sub-monoscopic reference images corresponding to the sub-monoscopic image;

[0010] determining a pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image;

[0011] The defect detection result of the sub-monoscopic area to be detected is determined according to the pixel distortion amount of the sub-monoscopic image.

[0012] Optionally, determining a defect detection result of a sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image includes:

[0013] determining at least two reference sub-monoscopic images based on the pixel distortion amount of the sub-monoscopic image, wherein the at least two reference sub-monoscopic images include at least two sub-monoscopic images having the smallest difference in pixel distortion amount from the sub-monoscopic image to be detected;

[0014] Determine a defect detection result of the sub-monoscopic area to be detected according to the sub-monoscopic image to be detected and at least two reference sub-monoscopic images.

[0015] Optionally, determining a defect detection result of the sub-monoscopic area to be detected according to the sub-monoscopic image to be detected and at least two reference sub-monoscopic images includes:

[0016] generating a differential image according to the to-be-detected sub-monoscopic image and at least two reference sub-monoscopic images;

[0017] Determine a defect detection result of the sub-monoscopic area to be detected according to the differential image.

[0018] Optionally, before acquiring the field of view image and the reference image of the monoscopic area, the monoscopic defect detection method further includes:

[0019] Controlling the camera to collect field images of the plurality of field areas according to a preset collection path;

[0020] Acquiring a monoscopic image of the monoscopic area includes:

[0021] A monoscopic image of the monoscopic area is obtained from the field of view images of the plurality of field of view areas, wherein the monoscopic area includes the area in which the number of the field of view areas in a specific area is less than three, and the specific area includes an area in the wafer extending along a first direction and arranged along a second direction or an area in the wafer extending along a second direction and arranged along the first direction, and the first direction intersects with the second direction.

[0022] Optionally, determining the pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image includes:

[0023] The pixel distortion amount of the sub-monoscopic image is determined according to the following corresponding relationship:

[0024] DieDiff (m，n) =|DiePre(r (m，n) )-DiePost(r (m,n) )|+|DiePre(c (m，n) )-DiePost(c (m，n) )|;

[0025] Among them, DieDiff (m,n) represents the pixel distortion of the sub-monoscopic reference image located at the mth row and the nth column in the monoscopic image, DiePre(r (m,n) ,c (m,n) ) represents the pixel coordinates of the sub-monoscopic reference image at the mth row and the nth column in the monoscopic reference image, DiePost(r (m,n) ,c (m,n )) represents the pixel coordinates of the sub-monoscopic image located at the mth row and nth column in the monoscopic image, m is an integer and m≥1, and n is an integer and n≥1.

[0026] Optionally, determining at least two reference sub-monoscopic images according to the pixel distortion amount of the sub-monoscopic image includes:

[0027] Determine a preselected monoscopic image according to the sub-monoscopic image to be detected, wherein the preselected monoscopic image includes the sub-monoscopic image to be detected and the sub-monoscopic image adjacent to the sub-monoscopic image to be detected;

[0028] At least two reference sub-monoscopic images are determined from the pre-selected monoscopic images.

[0029] In a second aspect, an embodiment of the present invention provides a single-chip field-of-view defect detection device for performing the single-field-of-view defect detection method as described in the first aspect, the defect detection device comprising:

[0030] an image acquisition unit, configured to acquire a monoscopic image and a monoscopic reference image of the monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images corresponding to the sub-monoscopic area, and the monoscopic reference image includes at least three sub-monoscopic reference images corresponding to the sub-monoscopic image;

[0031] a pixel distortion amount determining unit, configured to determine the pixel distortion amount of the sub-monoscopic image based on the sub-monoscopic image and the sub-monoscopic reference image;

[0032] The defect detection result determining unit is used to determine the defect detection result of the sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image.

[0033] In a third aspect, an embodiment of the present invention provides a single-field-of-view defect detection device, characterized in that the single-field-of-view defect detection device includes:

[0034] one or more processors;

[0035] a storage device for storing one or more programs;

[0036] When the one or more programs are executed by the one or more processors, the one or more processors implement the single-field defect detection method as described in the first aspect.

[0037] In a fourth aspect, an embodiment of the present invention provides a storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the single-field defect detection method as described in the first aspect is implemented.

[0038] The technical solution of the embodiment of the present invention first determines the pixel distortion amount of the sub-monoscopic field of view image based on the acquired sub-monoscopic field of view image and the sub-monoscopic field of view reference image, and then determines the defect detection result of the sub-monoscopic field of view area to be detected based on the pixel distortion amount of the sub-monoscopic field of view image. This can realize defect detection in the monoscopic field of view area on the wafer, and solves the problem that the existing wafer inspection method cannot perform defect detection on the monoscopic field of view area in the wafer.

[0039] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 A schematic structural diagram of a wafer provided by an embodiment of the present invention;

[0042] Figure 2 A schematic structural diagram of a monoscopic field of view area provided by an embodiment of the present invention;

[0043] Figure 3 Flowchart of a single field of view defect detection method for wafers provided by an embodiment of the present invention

[0044] Figure 4 A single-field image provided by an embodiment of the present invention;

[0045] Figure 5 A reference monoscopic image provided by an embodiment of the present invention;

[0046] Figure 6 A flowchart of another single-field-of-view defect detection method for wafers provided by an embodiment of the present invention;

[0047] Figure 7 A flowchart of another single-field-of-view defect detection method for wafers provided in an embodiment of the present invention;

[0048] Figure 8 A schematic structural diagram of a single-field-of-view defect detection device for wafers provided by an embodiment of the present invention;

[0049] Figure 9 A schematic structural diagram of a single-field-of-view defect detection device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0051] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices. The directions or positional relationships indicated by the terms "upper", "lower", "left", "right", etc. are based on the directions or positional relationships shown in the drawings and are only used to illustrate the relative positional relationships between the various components or components, and do not particularly limit the specific installation directions of the various components or components.

[0052] Figure 1 A schematic structural diagram of a wafer provided by an embodiment of the present invention is shown. Figure 2 A schematic diagram of a monoscopic field of view provided in an embodiment of the present invention, referring to Figure 1 and Figure 2 The wafer in the embodiment of the present invention includes multiple field of view areas 11, the multiple field of view areas 11 include at least one single field of view area 111, and the single field of view area 111 includes at least three sub-single field of view areas 1111. Figure 2 In the illustrated embodiment, the monoscopic area 111 includes 16 sub-monoscopic areas 1111 arranged in a 4×4 array. It should be noted that the embodiment of the present invention does not limit the number and arrangement of the sub-monoscopic areas 1111 in the monoscopic area 111.

[0053] Figure 3 A flowchart of a single field of view defect detection method for a wafer according to an embodiment of the present invention is provided. Figure 3 The single-field-of-view defect detection method for wafers in the embodiment of the present invention is applicable to situations where defect detection is required in a single-field-of-view area of ​​a wafer. The single-field-of-view defect detection method can be performed by a single-field-of-view defect detection device for wafers. The device can be implemented using software and / or hardware and specifically configured in a single-field-of-view defect detection device. The single-field-of-view defect detection method in the embodiment of the present invention includes:

[0054] S110. Acquire a monoscopic image and a monoscopic reference image of a monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images, each corresponding to the sub-monoscopic area; and the monoscopic reference image includes at least three sub-monoscopic reference images, each corresponding to the sub-monoscopic image.

[0055] For example, the monoscopic defect detection device in the embodiment of the present invention is connected to the camera for communication, and the monoscopic image of the monoscopic area can be obtained by the camera. The obtained monoscopic image is as follows: Figure 4 As shown in the figure, due to the distortion of the camera itself, the types of distortion include barrel distortion, pincushion distortion, tangential distortion, etc., so the single-field image obtained by the camera will inevitably have the following distortions: Figure 4 The monoscopic reference image refers to a monoscopic image without distortion, such as Figure 5 As shown, the image is determined when the wafer is designed and can be pre-stored in a storage device. The single-field defect detection device in the embodiment of the present invention can be communicated with the storage device and obtained from the storage device when the single-field reference image is needed for defect detection.

[0056] exist Figure 4 In the illustrated embodiment, the monoscopic image 111A includes 16 sub-monoscopic images 1111A arranged in a 4×4 array. Figure 2 and Figure 3 , the sub-monoscopic image 1111A and the sub-monoscopic area 1111 may correspond one to one, and the relative position of the corresponding sub-monoscopic area 1111 in the monoscopic area 111 is the same as the relative position of the corresponding sub-monoscopic image 1111A in the monoscopic image 111A. For example, the sub-monoscopic area 1111 arranged in the first row and second column in the monoscopic area 111 corresponds to the sub-monoscopic image 1111A arranged in the first row and second column in the monoscopic image 111A. Figure 5 In the illustrated embodiment, the monoscopic reference image 111B includes 16 sub-monoscopic reference images 1111B arranged in a 4×4 array. Figure 4 and Figure 5 , sub-monoscopic reference image 1111B and sub-monoscopic reference image 1111A may correspond one-to-one, and the relative position of the corresponding sub-monoscopic reference image 1111A in monoscopic image 111A is the same as the relative position of the corresponding sub-monoscopic reference image 1111B in monoscopic reference image 111B. For example, sub-monoscopic image 1111A arranged in the first row and second column of monoscopic image 111A corresponds to sub-monoscopic reference image 1111B arranged in the first row and second column of monoscopic reference image 111B.

[0057] S120 : Determine a pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image.

[0058] refer to Figure 2 、 Figure 4 and Figure 5The monoscopic area 111 further includes at least three chips 1112 , and the chips 1112 correspond to the sub-monoscopic area 1111 .

[0059] For example, in Figure 2 In the illustrated embodiment, the monoscopic area 111 includes 16 chips 1112 arranged in a 4×4 array. The chips 1112 may correspond one to one with the sub-monoscopic areas 1111 , and each sub-monoscopic area 1111 includes one chip 1112 .

[0060] It is understandable that pixel distortion generally refers to the distortion or deformation of the image caused by non-ideal changes in the geometry of pixels in a digital image due to some reason. The pixel distortion amount of the sub-monoscopic image 1111A in the embodiment of the present invention can be used to express the degree of distortion or deformation of the sub-monoscopic image 1111A.

[0061] Illustratively, the pixel distortion amount of the sub-monoscopic image 1111A may be determined based on the corresponding sub-monoscopic image 1111A and the sub-monoscopic reference image 1111B.

[0062] Specifically, determining the pixel distortion amount of the sub-monoscopic image 1111A according to the sub-monoscopic image 1111A and the sub-monoscopic reference image 1111B includes: determining the pixel distortion amount of the sub-monoscopic image 1111A according to the following corresponding relationship:

[0063] DieDiff (m,n) =|DiePre(r (m,n) )-DiePost(r (m，n) )|+|DiePre(c (m,n) )-DiePost(c (m,n) )|.

[0064] Among them, DieDiff (m,n) represents the pixel distortion of the sub-monoscopic reference image 1111A located at the mth row and the nth column in the monoscopic image 111A, DiePre(r (m,n) ,c (m,n) ) represents the pixel coordinates of the sub-monoscopic reference image 1111B at the mth row and nth column in the monoscopic reference image 111B, DiePost(r (m,n) ,c (m,n) ) represents the pixel coordinates of the sub-monoscopic image 1111A located at the m-th row and the n-th column in the monoscopic image 111A, where m is an integer and m≥1, and n is an integer and n≥1.

[0065] It should be noted that the pixel coordinate DiePre(r (m,n) ,c (m,n)) on the monoscopic reference image 111B and the relative position of the coordinate system corresponding to DiePost(r (m,n) ,c (m,n) ) have the same relative position on the monoscopic image 111A. For example, the pixel coordinates DiePre(r (m,n) ,c (m,n) ) corresponds to the origin of the coordinate system at the center of the single-view reference image 111B, DiePost(r (m,n) ,c (m,n) ) is also at the center of the monoscopic image 111A, and the directions of the two corresponding coordinate axes are also the same.

[0066] S130 , determining a defect detection result of the sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image.

[0067] For example, it can be understood that the pixel distortion amount will affect the defect detection result of the sub-monoscopic area 1111A. In the embodiment of the present invention, one monoscopic area 111A includes at least three sub-monoscopic areas 1111A, corresponding to at least three sub-monoscopic images 1111B. With reference to the existing Die-To-Die detection algorithm and taking into account the impact of the pixel distortion amount on the defect detection result, the embodiment of the present invention can determine the defect detection result of the sub-monoscopic area to be detected based on the sub-monoscopic image to be detected and its pixel distortion amount, as well as other sub-monoscopic images other than the detection sub-monoscopic image and their pixel distortion amounts.

[0068] The embodiment of the present invention first determines the pixel distortion amount of the sub-monoscopic image 1111A based on the acquired sub-monoscopic image 1111A and the sub-monoscopic reference image 1111B, and then determines the defect detection result of the sub-monoscopic area to be detected based on the pixel distortion amount of the sub-monoscopic image 1111A, thereby realizing defect detection of the monoscopic area 111 on the wafer, solving the problem that the existing wafer detection method cannot perform defect detection on the monoscopic area in the wafer.

[0069] Figure 6 A flowchart of another single-field-of-view defect detection method for wafers provided by an embodiment of the present invention is provided. Figure 6 The embodiment shown in the figure describes in detail how to determine the defect detection result of the sub-monoscopic area to be detected based on the pixel distortion amount of the sub-monoscopic image. Figure 6 The single-field defect detection method in the embodiment of the present invention includes:

[0070] S210. Acquire a monoscopic image and a monoscopic reference image of a monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images, each corresponding to the sub-monoscopic area; and the monoscopic reference image includes at least three sub-monoscopic reference images, each corresponding to the sub-monoscopic image.

[0071] S220 : Determine a pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image.

[0072] S230. Determine at least two reference sub-monoscopic images based on the pixel distortion amount of the sub-monoscopic image, wherein the at least two reference sub-monoscopic images include at least two sub-monoscopic images having the smallest difference in pixel distortion amount from the sub-monoscopic image to be detected.

[0073] Exemplary, reference Figure 4 and Figure 5 After determining the sub-monoscopic image to be detected from the 16 sub-monoscopic images 1111A, at least two sub-monoscopic images 1111A with the smallest difference in pixel distortion from the sub-monoscopic image to be detected can be selected from the remaining 15 sub-monoscopic images 1111A as reference sub-monoscopic images based on the pixel distortion of the sub-monoscopic image to be detected.

[0074] In another feasible embodiment, at least two reference sub-monoscopic images are determined based on the pixel distortion amount of the sub-monoscopic image 1111A, including: determining a preselected monoscopic image based on the sub-monoscopic image to be detected, the preselected monoscopic image including the sub-monoscopic image to be detected and a sub-monoscopic image adjacent to the sub-monoscopic image to be detected; and determining at least two reference sub-monoscopic images from the preselected monoscopic image.

[0075] Exemplarily, if the sub-monoscopic image to be detected is a sub-monoscopic image 1111A located at the four corners of the monoscopic image 111A, then there are three sub-monoscopic images 1111A adjacent to the sub-monoscopic image to be detected, and two sub-monoscopic images 1111A with the smallest difference in pixel distortion from the sub-monoscopic image to be detected can be selected from the three sub-monoscopic images 1111A as reference sub-monoscopic images.

[0076] If the sub-monoscopic image to be detected is a sub-monoscopic image 1111A located on the four sides of the monoscopic image 111A but not at the four corners, then there are five sub-monoscopic images 1111A adjacent to the sub-monoscopic image to be detected. Two sub-monoscopic images with the smallest difference in pixel distortion from the sub-monoscopic image to be detected can be selected from the five sub-monoscopic images 1111A as reference sub-monoscopic images.

[0077] If the sub-monoscopic image to be detected is the sub-monoscopic image 1111A located in the middle area of ​​the monoscopic image 111A, there are 8 sub-monoscopic images 1111A adjacent to the sub-monoscopic image to be detected. From the 8 sub-monoscopic images 1111A, the two sub-monoscopic images with the smallest difference in pixel distortion from the sub-monoscopic image to be detected can be selected as reference sub-monoscopic images.

[0078] It is understood that the greater the number of reference sub-monoscopic images, the more accurate the defect detection results for the sub-monoscopic area to be inspected. It should be noted that embodiments of the present invention do not limit the number of reference sub-monoscopic images; an appropriate number of reference sub-monoscopic images can be selected based on the number of sub-monoscopic images 1111A included in the pre-selected monoscopic image that are not the sub-monoscopic image to be inspected, as well as the accuracy requirements for the defect detection results.

[0079] Compared with selecting a reference sub-monoscopic image from sub-monoscopic images 1111A other than the sub-monoscopic image to be detected, the embodiment of the present invention reduces the amount of indexes for selecting reference sub-monoscopic images by first determining a pre-selected monoscopic image based on the sub-monoscopic image to be detected, and then determining at least two reference sub-monoscopic images from the pre-selected monoscopic image, which is beneficial to improving the effect of defect detection.

[0080] S240 , determining a defect detection result of the sub-monoscopic area to be detected according to the sub-monoscopic image to be detected and at least two reference sub-monoscopic images.

[0081] As a feasible implementation method, the defect detection result of the sub-single field of view area to be detected is determined based on the sub-single field of view image to be detected and at least two reference sub-single field of view images, including: generating a differential image based on the sub-single field of view image to be detected and at least two reference sub-single field of view images; and determining the defect detection result of the sub-single field of view area to be detected based on the differential image.

[0082] For example, a differential image can be generated between the sub-monoscopic image to be inspected and each reference sub-monoscopic image. If each differential image shows a significant difference between the sub-monoscopic area to be inspected and the reference sub-monoscopic area, it can be determined that a defect exists in the sub-monoscopic area to be inspected, and furthermore, the presence and location of the defect in monoscopic area 111 can be determined. It should be noted that the sub-monoscopic area to be inspected corresponds to the sub-monoscopic image to be inspected, and the reference sub-monoscopic area corresponds to the reference sub-monoscopic image in a one-to-one manner.

[0083] Figure 7 A flowchart of another single-field-of-view defect detection method for wafers provided in an embodiment of the present invention is provided. Figure 7 The embodiment shown enriches the process of the single field of view defect detection method and provides a detailed description of how to obtain a single field of view image of a single field of view area. Figure 7The single-field defect detection method in the embodiment of the present invention includes:

[0084] S310: Control the camera to collect field images of multiple field areas according to a preset collection path.

[0085] For example, the preset acquisition path can be pre-set and stored in a memory. When the single-field defect detection device in the embodiment of the present invention needs to execute step S310, the preset acquisition path can be retrieved from the memory, and then the camera can be controlled to acquire a field of view image of each field of view area in the wafer according to the preset acquisition path. It should be noted that the preset acquisition path can be used for row-by-row acquisition or column-by-column acquisition, and this is not limited in the embodiment of the present invention.

[0086] S320. Acquire a field of view reference image, and acquire a monoscopic image of a monoscopic area from field of view images of multiple field of view areas, wherein the monoscopic image includes at least three sub-monoscopic images, each sub-monoscopic image corresponds to a sub-monoscopic area, and the monoscopic reference image includes at least three sub-monoscopic reference images, each sub-monoscopic reference image corresponds to a sub-monoscopic image.

[0087] It should be noted that the reference Figure 1 The single field of view area 111 in the embodiment of the present invention includes a field of view area 11 in which the number of field of view areas 11 in the specific area 10 is less than three, and the specific area 10 includes an area extending along the first direction X and arranged along the second direction Y in the wafer, or an area extending along the second direction Y and arranged along the first direction X in the wafer, and the first direction X intersects the second direction Y.

[0088] For example, in Figure 1 In the illustrated embodiment, the single viewing area 111 is a viewing area 11 located in two specific areas 10 at both ends of the second direction Y.

[0089] S330 : Determine a pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image.

[0090] S340 , determining a defect detection result of the sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image.

[0091] Based on the same inventive concept, an embodiment of the present invention provides a single-chip field-of-view defect detection device. Figure 8 A schematic diagram of a single field of view defect detection device for a wafer according to an embodiment of the present invention is provided. Figure 8 , the single field of view defect detection device in the embodiment of the present invention includes:

[0092] An image acquisition unit 410 is configured to acquire a monoscopic image and a monoscopic reference image of a monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images corresponding to the sub-monoscopic area, and the monoscopic reference image includes at least three sub-monoscopic reference images corresponding to the sub-monoscopic image.

[0093] The pixel distortion amount determining unit 420 is configured to determine the pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image.

[0094] The defect detection result determining unit 430 is configured to determine a defect detection result of the sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image.

[0095] Optionally, the image acquisition unit 410 in the embodiment of the present invention is further configured to control the camera to acquire field images of multiple field areas according to a preset acquisition path.

[0096] The single-field-of-view defect detection device provided in the embodiment of the present invention can execute the single-field-of-view defect detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0097] Figure 9 A schematic diagram of a monoscopic defect detection device 500 that can be used to implement an embodiment of the present invention is shown. The monoscopic defect detection device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The monoscopic defect detection device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0098] like Figure 9As shown, the monoscopic defect detection device 500 includes at least one processor 510 and a memory, such as a read-only memory (ROM) 520 and a random access memory (RAM) 530, communicatively connected to the at least one processor 510. The memory stores a computer program executable by the at least one processor. The processor 510 can perform various appropriate actions and processes based on the computer program stored in the read-only memory (ROM) 520 or loaded from the storage unit 580 into the random access memory (RAM) 530. The RAM 530 can also store various programs and data required for the operation of the monoscopic defect detection device 500. The processor 510, ROM 520, and RAM 530 are interconnected via a bus 540. An input / output (I / O) interface 550 is also connected to the bus 540.

[0099] Multiple components in the monoscopic defect inspection device 500 are connected to the I / O interface 550, including an input unit 560, such as a keyboard and mouse; an output unit 570, such as various types of displays and speakers; a storage unit 580, such as a magnetic disk and optical disk; and a communication unit 590, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 590 allows the monoscopic defect inspection device 500 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0100] Processor 510 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 510 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 510 executes the various methods and processes described above, such as the single-field defect detection method.

[0101] In some embodiments, the monoscopic defect detection method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 580. In some embodiments, part or all of the computer program can be loaded and / or installed on the monoscopic defect detection device 500 via the ROM 520 and / or the communication unit 590. When the computer program is loaded into the RAM 530 and executed by the processor 510, one or more steps of the monoscopic defect detection method described above can be performed. Alternatively, in other embodiments, the processor 510 can be configured to perform the monoscopic defect detection method in any other suitable manner (e.g., via firmware).

[0102] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes 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.

[0103] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0104] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0105] To provide user interaction, the systems and techniques described herein can be implemented on a monoscopic defect detection device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the monoscopic defect detection device. Other types of devices can also be used to provide user interaction. For example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback). Input from the user can also be received in any form, including acoustic input, voice input, or tactile input.

[0106] The systems and techniques described herein can 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 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 can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0107] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0108] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0109] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for detecting defects in a single field of view of a wafer, wherein the wafer includes a plurality of field of view areas, the plurality of field of view areas includes at least one single field of view area, the single field of view area includes at least three sub-monoscopic field of view areas, and the method comprises: Acquiring a monoscopic image and a monoscopic reference image of the monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images corresponding to the sub-monoscopic area, and the monoscopic reference image includes at least three sub-monoscopic reference images corresponding to the sub-monoscopic image; determining a pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image; The defect detection result of the sub-monoscopic area to be detected is determined according to the pixel distortion amount of the sub-monoscopic image.

2. The single field of view defect detection method according to claim 1, characterized in that: Determining a defect detection result of a sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image includes: determining at least two reference sub-monoscopic images based on the pixel distortion amount of the sub-monoscopic image, wherein the at least two reference sub-monoscopic images include at least two sub-monoscopic images having the smallest difference in pixel distortion amount from the sub-monoscopic image to be detected; Determine a defect detection result of the sub-monoscopic area to be detected according to the sub-monoscopic image to be detected and at least two reference sub-monoscopic images.

3. The single field of view defect detection method according to claim 2, characterized in that: Determining a defect detection result of the sub-monoscopic area to be detected according to the sub-monoscopic image to be detected and at least two reference sub-monoscopic images includes: generating a differential image according to the to-be-detected sub-monoscopic image and at least two reference sub-monoscopic images; Determine a defect detection result of the sub-monoscopic area to be detected according to the differential image.

4. The single field of view defect detection method according to claim 1, characterized in that: Before acquiring the field of view image and the reference image of the monoscopic field of view area, the monoscopic field of view defect detection method further includes: Controlling the camera to collect field images of the plurality of field areas according to a preset collection path; Acquiring a monoscopic image of the monoscopic area includes: A monoscopic image of the monoscopic area is obtained from the field of view images of the plurality of field of view areas, wherein the monoscopic area includes the area in which the number of the field of view areas in a specific area is less than three, and the specific area includes an area in the wafer extending along a first direction and arranged along a second direction or an area in the wafer extending along a second direction and arranged along the first direction, and the first direction intersects with the second direction.

5. The single field of view defect detection method according to claim 1, characterized in that: Determining a pixel distortion amount of the sub-monoscopic image according to the sub-monoscopic image and the sub-monoscopic reference image includes: The pixel distortion amount of the sub-monoscopic image is determined according to the following corresponding relationship: TheDiff (m，n) =|ThePre(r (m，n) )-ThePost(r (m，n) )|+|ThePre(c (m，n) )-ThePost(c (m，n) )|; Among them, DieDiff (m,n) represents the pixel distortion of the sub-monoscopic reference image located at the mth row and the nth column in the monoscopic image, DiePre(r (m,n) ,c (m,n) ) represents the pixel coordinates of the sub-monoscopic reference image at the mth row and the nth column in the monoscopic reference image, DiePost(r (m,n) ,c (m,n) ) represents the pixel coordinates of the sub-monoscopic image located at the mth row and the nth column in the monoscopic image, m is an integer and m≥1, and n is an integer and n≥1.

6. The single field of view defect detection method according to claim 2, characterized in that: Determining at least two reference sub-monoscopic images according to the pixel distortion amount of the sub-monoscopic image includes: Determine a preselected monoscopic image according to the sub-monoscopic image to be detected, wherein the preselected monoscopic image includes the sub-monoscopic image to be detected and the sub-monoscopic image adjacent to the sub-monoscopic image to be detected; At least two reference sub-monoscopic images are determined from the pre-selected monoscopic images.

7. A single-chip field-of-view defect detection device, used to perform the single-field-of-view defect detection method according to any one of claims 1 to 6, characterized in that: The defect detection device comprises: an image acquisition unit, configured to acquire a monoscopic image and a monoscopic reference image of the monoscopic area, wherein the monoscopic image includes at least three sub-monoscopic images corresponding to the sub-monoscopic area, and the monoscopic reference image includes at least three sub-monoscopic reference images corresponding to the sub-monoscopic image; a pixel distortion amount determining unit, configured to determine the pixel distortion amount of the sub-monoscopic image based on the sub-monoscopic image and the sub-monoscopic reference image; The defect detection result determining unit is used to determine the defect detection result of the sub-monoscopic area to be detected according to the pixel distortion amount of the sub-monoscopic image.

8. A single field of view defect detection device, characterized in that: The single field of view defect detection device comprises: one or more processors; a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the single-field defect detection method according to any one of claims 1 to 6.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the single-field defect detection method according to any one of claims 1 to 6 is implemented.

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