CN112213314A - Detection method and detection system for wafer side surface defects - Google Patents

Detection method and detection system for wafer side surface defects Download PDF

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CN112213314A
CN112213314A CN201910628971.3A CN201910628971A CN112213314A CN 112213314 A CN112213314 A CN 112213314A CN 201910628971 A CN201910628971 A CN 201910628971A CN 112213314 A CN112213314 A CN 112213314A
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CN112213314B (en
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刘明宗
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Changxin Memory Technologies Inc
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9501—Semiconductor wafers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9501—Semiconductor wafers
    • G01N21/9505—Wafer internal defects, e.g. microcracks
    • G—PHYSICS
    • G01—MEASURING; TESTING
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    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G01N2021/8861—Determining coordinates of flaws
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques

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Abstract

A detection method and a detection system for a wafer side surface defect are disclosed, wherein the detection method for the wafer side surface defect comprises the steps of carrying out gray level processing on an annular side surface image corresponding to an annular side surface of a wafer to be detected after obtaining the annular side surface image to obtain a gray level image; and detecting the gray level image based on a characteristic point detection method to obtain angular points, wherein the positions corresponding to the angular points are the positions of the defects. By adopting the method, the side surface defects of the wafer are detected, whether the process technology or the corresponding structural design has defects can be judged by detecting whether the side surface of the wafer ring has defects, and the technology and designer can optimize the corresponding technology and structural design according to the detected defects, so that the yield of products is improved, and the wafer is prevented from being scrapped.

Description

Detection method and detection system for wafer side surface defects
Technical Field
The invention relates to the field of semiconductor manufacturing, in particular to a method and a system for detecting defects on the side surface of a wafer.
Background
Semiconductor integrated circuit fabrication is mainly through the process steps of exposure, etching, ion implantation, thin film deposition, and chemical mechanical polishing, etc., a large number of various types of semiconductor devices and interconnection lines connecting the semiconductor devices are formed on a silicon substrate. Wherein, defects generated in any one step of the process may cause the fabrication of the circuit to fail or fail. Therefore, in the process manufacturing, it is often necessary to perform defect detection and analysis on the multi-step process, to find out the cause of the defect, and to eliminate the defect.
The existing defect detection method completely depends on manual work, and when a process problem occurs, a possible reason is found and improvement measures are taken by reviewing a wafer edge image shot after an exposure process; however, such a process modification period is too long and consumes a lot of labor.
Disclosure of Invention
The invention aims to solve the technical problem of how to automatically detect the defects of the wafer, so that the process problems can be found as soon as possible, the process yield is improved, and the production cost is reduced.
The invention provides a method for detecting defects on the side surface of a wafer, which comprises the following steps:
providing a wafer to be detected, wherein the wafer to be detected comprises a top surface, an opposite bottom surface and an annular side surface positioned between the top surface and the bottom surface;
obtaining an annular side surface image corresponding to the annular side surface of the wafer to be detected;
carrying out gray processing on the surface image of the annular side surface to obtain a gray image;
and detecting the gray level image based on a characteristic point detection method to obtain angular points, wherein the positions corresponding to the angular points are the positions of the defects.
Optionally, the process of separating the annular side surface image from the initial detection image includes: finding a boundary of the annular side surface image with an upper background image and a lower background image; and taking the image between the two boundary lines as an annular side surface image corresponding to the annular side surface of the wafer to be detected.
Optionally, the process of finding the boundary line is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
Optionally, a global threshold method or a local threshold method is used to binarize the gray-processed initial detection image.
Optionally, the global threshold method includes a large law method, a maximum entropy method, or an iteration method; the local threshold value method comprises a binarization method based on a Bernsen algorithm, a binarization method based on a Sauvola algorithm, a binarization method based on a Niblack algorithm or a binarization method based on a Wolf algorithm.
Optionally, the process of performing gray processing on the annular side surface image to obtain a gray image includes: and after the annular side surface image is obtained, directly carrying out gray level processing on the obtained annular side surface image to obtain a gray level image.
Optionally, the process of performing gray processing on the annular side surface image to obtain a gray image includes: the annular side surface image comprises a substrate image and a plurality of film layer images which are sequentially stacked on the substrate image; separating the film layer image from the annular side surface image after obtaining the annular side surface image; and carrying out gray level processing on the film layer image to obtain a gray level image.
Optionally, the process of separating the film layer image from the annular side surface image includes: finding a boundary between the film layer image and the upper background image and the substrate image; the image between the two boundaries is taken as the film layer image.
Optionally, the process of finding the boundary line is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
Optionally, an edge detection method is used to binarize the gray-processed initial detection image.
Optionally, the edge detection method uses a Sobel edge detection operator, a Laplacian edge detection operator, a Canny edge detection operator, a Prewitt edge detection operator, or a Roberts edge detection operator.
Optionally, the initial detection image is acquired by acquiring a circle of the side surface of the wafer to be detected through an image acquisition device.
Optionally, the feature point detection method includes a Harris-based corner detection method, an SUSAN-based corner detection method, a FAST-based corner detection method, a FASTER-based corner detection method, a SIFT-based corner detection method, and an SURF-based corner detection method.
Optionally, when a notch for positioning is formed in the edge of the wafer to be detected, a notch image corresponding to the notch is formed in the surface image of the annular side surface; excluding notch images in the annular side surface image.
The invention also provides a system for detecting the defects on the side surface of the wafer, which comprises:
the wafer providing unit is used for providing a wafer to be detected, and the wafer to be detected comprises a top surface, an opposite bottom surface and an annular side surface positioned between the top surface and the bottom surface;
the annular side surface image obtaining unit is used for obtaining an annular side surface image corresponding to the annular side surface of the wafer to be detected;
the gray processing unit is used for carrying out gray processing on the surface image of the annular side surface to obtain a gray image;
and the characteristic point detection unit is used for detecting the gray level image based on a characteristic point detection method to obtain an angular point, wherein the position corresponding to the angular point is the position of the defect.
Optionally, the annular side surface image obtaining unit includes an initial detection image obtaining unit and a separating unit, the initial detection image obtaining unit is configured to obtain an initial detection image, the initial detection image includes an annular side surface image, an upper background image located on the annular side surface image, and a lower background image located under the annular side surface image, and the separating unit is configured to separate the annular side surface image from the initial detection image.
Optionally, the process of separating the annular side surface image from the initial detection image by the separation unit includes: finding a boundary of the annular side surface image with an upper background image and a lower background image; and taking the image between the two boundary lines as an annular side surface image corresponding to the annular side surface of the wafer to be detected.
Optionally, the process of finding the boundary line is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
Optionally, a global threshold method or a local threshold method is used to binarize the gray-processed initial detection image.
Optionally, the global threshold method includes a large law method, a maximum entropy method, or an iteration method; the local threshold value method comprises a binarization method based on a Bernsen algorithm, a binarization method based on a Sauvola algorithm, a binarization method based on a Niblack algorithm or a binarization method based on a Wolf algorithm.
Optionally, after the annular side surface image obtaining unit obtains the annular side surface image, the gray processing unit directly performs gray processing on the obtained annular side surface image to obtain a gray image.
Optionally, the annular side surface image includes a substrate image and a plurality of sequentially stacked film layer images located on the substrate image, and the separation unit is further configured to separate the film layer images from the annular side surface image; the gray processing unit is also used for carrying out gray processing on the film layer image to obtain a gray image.
Optionally, the process of separating the film layer image from the annular side surface image by the separation unit includes: finding a boundary between the film layer image and the upper background image and the substrate image; the image between the two boundaries is taken as the film layer image.
Optionally, the process of finding the boundary line is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
Optionally, an edge detection method is used to binarize the gray-processed initial detection image.
Optionally, the edge detection method uses a Sobel edge detection operator, a Laplacian edge detection operator, a Canny edge detection operator, a Prewitt edge detection operator, or a Roberts edge detection operator.
Optionally, the initial detection image is acquired by acquiring a circle of the side surface of the wafer to be detected through an image acquisition device.
Optionally, the feature point detection method includes a Harris-based corner detection method, an SUSAN-based corner detection method, a FAST-based corner detection method, a FASTER-based corner detection method, a SIFT-based corner detection method, and an SURF-based corner detection method.
Optionally, the apparatus further includes a notch image removing unit, configured to, when a notch for positioning exists at an edge of the wafer to be detected, have a corresponding notch image in the annular side surface image; excluding notch images in the annular side surface image.
Compared with the prior art, the technical scheme of the invention has the following advantages:
according to the method for detecting the side surface defect of the wafer, after the annular side surface image corresponding to the annular side surface of the wafer to be detected is obtained, the annular side surface image is subjected to gray processing to obtain a gray image; and detecting the gray level image based on a characteristic point detection method to obtain angular points, wherein the positions corresponding to the angular points are the positions of the defects. By adopting the method, the automatic detection of the side surface defects of the wafer is realized, whether the process technology or the corresponding structural design has defects can be judged by automatically detecting whether the side surface of the wafer ring has defects, and the process and designer can optimize the corresponding process and structural design according to the detected defects, so that the correction period is shortened, the yield of products is improved, and the wafer is prevented from being scrapped.
Further, after the initial detection image is obtained, the annular side surface image is separated from the initial detection image so as to prevent the upper background image and the lower background image from influencing the accuracy of subsequent detection of the defect.
Further, the process of finding the boundary is as follows: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary. The boundary can be found quickly and accurately through the process, the efficiency and the accuracy of the detection method are improved, and the performance and the efficiency of the detection system are improved.
Further, separating the film layer image from the annular side surface image; carrying out gray level processing on the film layer image to obtain a gray level image; and detecting the gray level image based on a characteristic point detection method to obtain the defect, wherein the gray level image corresponding to the substrate image does not need to be subjected to the characteristic point detection method, so that the defect detection efficiency is improved.
Further, the method for binarizing the gray-scale processed initial detection image may also adopt an edge detection method to improve the precision of boundary acquisition.
Drawings
FIGS. 1-3 are schematic flow charts illustrating a method for detecting defects on a side surface of a wafer according to an embodiment of the present invention;
FIGS. 4-21 are schematic structural diagrams illustrating a wafer side defect inspection process according to an embodiment of the present invention;
FIG. 22 is a schematic structural diagram of a system for detecting defects on a wafer side according to an embodiment of the present invention.
Detailed Description
As background art, the existing defect detection method cannot realize automatic detection of defects generated in the process.
The invention provides a method and a system for detecting the side surface defect of a wafer, wherein the method for detecting the side surface defect of the wafer comprises the steps of carrying out gray level processing on an annular side surface image corresponding to the annular side surface of the wafer to be detected after obtaining the annular side surface image to obtain a gray level image; and detecting the gray level image based on a characteristic point detection method to obtain angular points, wherein the positions corresponding to the angular points are the positions of the defects. By adopting the method, the side surface defects of the wafer are detected, whether the process technology or the corresponding structural design has defects can be judged by detecting whether the side surface of the wafer ring has defects, and the technology and designer can optimize the corresponding technology and structural design according to the detected defects, so that the correction period is shortened, the yield of products is improved, and the wafer is prevented from being scrapped.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In describing the embodiments of the present invention in detail, the drawings are not to be considered as being enlarged partially in accordance with the general scale, and the drawings are only examples, which should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Referring to fig. 1, an embodiment of the invention provides a method for detecting a defect on a side surface of a wafer, including the steps of:
step S201, providing a wafer to be detected, wherein the wafer to be detected comprises a top surface, an opposite bottom surface and an annular side surface positioned between the top surface and the bottom surface;
step S202, obtaining an annular side surface image corresponding to the annular side surface of the wafer to be detected;
step S203, carrying out gray processing on the surface image of the annular side surface to obtain a gray image;
and S204, detecting the gray level image based on a characteristic point detection method to obtain angular points, wherein the positions corresponding to the angular points are the positions of the defects.
The foregoing process will be described in detail with reference to the accompanying drawings.
Step S201 is performed to provide a wafer to be detected, where the wafer to be detected includes a top surface, an opposite bottom surface, and an annular side surface located between the top surface and the bottom surface.
In this embodiment, the wafer to be detected is a wafer after any one of exposure, etching, ion implantation, thin film deposition, and chemical mechanical polishing.
The fabrication process of integrated circuits is the fabrication of semiconductor devices (transistors, memories) on a substrate and interconnect structures connecting the semiconductor substrates. The interconnect structure is fabricated on a substrate by a layer-by-layer process. For example, after a plurality of semiconductor devices (e.g., a plurality of transistors including a gate on a surface of a substrate and source and drain regions in the semiconductor substrate on both sides of the gate) are formed on a substrate, when a first layer of interconnection structure connected to the semiconductor devices is fabricated, a dielectric layer is formed on the substrate, a metal plug connected to the semiconductor devices is formed in the dielectric layer, and then a metal line connected to the metal plug is formed on the dielectric layer; and then forming a second-layer interconnection structure on the first-layer interconnection structure, wherein the formation process of the second-layer interconnection structure is similar to that of the first-layer interconnection structure until the last-layer interconnection structure is formed. In this embodiment, referring to fig. 4, the wafer 100 to be tested at least includes a substrate 101 and a plurality of stacked film layers 102 located on the substrate 101, and an interconnection structure is formed in the film layer 102. The wafer 100 to be inspected comprises a top surface 11 and an opposite bottom surface 10 and an annular side surface 12 between the top surface 11 and the bottom surface 10.
In an embodiment, the substrate 101 may be specifically a silicon (Si) substrate, a germanium (Ge) substrate, or a silicon germanium (GeSi) substrate, a silicon carbide (SiC) substrate; or a silicon-on-insulator (SOI) substrate, a germanium-on-insulator (GOI) substrate. In this embodiment, the substrate is a silicon substrate.
It has been found that during the fabrication of an integrated circuit, semiconductor devices and interconnect structures are formed on the surface (top surface) of the substrate 101, and no semiconductor devices and interconnect structures are formed on the edge of the wafer 100 to be detected, so that the side surface of the wafer 100 to be detected is still a complete layer-by-layer laminated film layer 102, and the film layer 102 may include several sequentially laminated dielectric layers, where the material of the dielectric layer is silicon oxide, silicon nitride, a low-k dielectric material (a dielectric material with a relative dielectric constant lower than 3.9), or an ultra-low-k dielectric material (a dielectric material with a relative dielectric constant lower than 2.8), or other suitable dielectric materials. In this embodiment, referring to fig. 5, fig. 5 is a schematic structural diagram of a partial side surface of the wafer to be detected, where the side surface of the wafer to be detected includes a substrate 101 and a film layer 102 located on the substrate 101, and the film layer 102 includes a first dielectric layer 21 located on the substrate 101, a second dielectric layer 22 located on the first dielectric layer 21, and a third dielectric layer 23 located on the second dielectric layer 22. In this embodiment, the number of the film layers 102 is three for example only, and in other embodiments, the number of the film layers may be other numbers.
And S202, obtaining an annular side surface image corresponding to the annular side surface of the wafer to be detected.
As shown in the foregoing, through research, during the manufacturing process of the integrated circuit, the edge of the wafer 100 to be detected does not form a semiconductor device and an interconnection structure, so that the side surface of the wafer 100 to be detected is still a complete layer-by-layer laminated film layer 102, and further research finds that, when there is no problem in the process or the corresponding structure design, there is no defect in the film layer 102 (refer to fig. 5), and when there is a problem in the process or the corresponding structure design, there is a corresponding defect (such as a crack, or peeling off (peeling) of the film layer) that is also embodied in the film layer 102 on the side surface of the wafer to be detected, so that by detecting whether there is a defect in the wafer ring-shaped side surface, it can be determined whether there is a defect in the process or the corresponding structure design, and a process and a designer can optimize the corresponding process and structure design according to the detected defect, therefore, the correction period is shortened, the yield of products is improved, and the scrapping of wafers is avoided.
In an embodiment, referring to fig. 2, the obtaining process (S203) of the annular side surface image includes: step S261, obtaining an initial detection image, where the initial detection image includes an annular side surface image, an upper background image located on the annular side surface image, and a lower background image located under the annular side surface image; step S262, separating the annular side surface image from the initial inspection image.
And acquiring the initial detection image by acquiring a circle of the side surface of the wafer to be detected through image acquisition equipment. In an embodiment, referring to fig. 6, the image capturing apparatus includes two cameras 31, the two cameras 31 are aligned with the side surface 12 of the wafer 100 to be detected and fixed, the wafer 100 to be detected rotates at least one circle when being photographed, and the image capturing apparatus synthesizes images of the two cameras 31 obtained from the side surface of the wafer 100 to be detected, so as to obtain an initial detection image. In other embodiments, the wafer 100 to be detected is fixed, and the camera 31 rotates around the wafer 100 to be detected for one circle to obtain an initial detection image.
Because the camera has a certain field angle when shooting, not only the surface of the side surface of the wafer to be detected can be imaged, but also the top surface of the wafer to be detected (or the top surface of the wafer to be detected also comprises a background above the wafer to be detected) and the bottom surface of the wafer to be detected (or the bottom surface of the wafer to be detected also comprises a background below the wafer to be detected) (in an embodiment, the background of the wafer to be detected can be made of a low-reflectivity material when detecting), so that the obtained initial detection image not only comprises the image of the side surface of the wafer to be detected, but also comprises images (corresponding to an upper background image and a lower background image) corresponding to the top surface of the wafer to be detected (or the top surface of the wafer to be detected also comprises the background above the wafer.
In a specific embodiment, the upper one of the cameras obtains images of the side surface 12 and the top surface 11 of the wafer 100 to be inspected, and the lower one of the cameras obtains images of the side surface 12 and the bottom surface 10 of the wafer 100 to be inspected.
In an embodiment, the edge of the wafer 100 to be detected has a notch (notch) for positioning, before the image acquisition device performs shooting, the position of the notch (notch) on the edge of the wafer 100 to be detected is obtained, then shooting is performed from the position of the notch (notch), and after the image acquisition device rotates for one circle, shooting is completed from the position of the notch (notch), so that the initial detection image has a corresponding notch image, and the annular side surface image obtained from the initial detection image subsequently also has a corresponding notch image, and the notch image has a position mark; and subsequently excluding notch images in the annular side surface image according to the position marks. Specifically, the notch image in the annular side surface image may be excluded before or after the annular side surface image is subjected to the gray scale processing (before the gray scale image is detected based on the feature point detection method).
In this embodiment, referring to fig. 7, fig. 7 is a schematic structural diagram of an initial inspection image 1001 obtained when the side surface of the wafer 100 to be inspected shown in fig. 5 and 6 is photographed, where the initial inspection image 1001 includes: a substrate image 1011 corresponding to a substrate 101 (refer to fig. 6), a film image 1021 corresponding to a film 102 (fig. 5 and 6) and located on the substrate image 1011, wherein the film image 1021 includes a first medium layer 211 image (corresponding to a first medium layer 21 in fig. 5), a second medium layer 221 image (corresponding to a second medium layer 22 in fig. 5), and a third medium layer image 231 (corresponding to a third medium layer 23 in fig. 5) stacked in sequence, and the initial detection image 1001 further includes an upper background image 1041 located on the film image 1021 and a lower background image 1031 located below the substrate image.
After the initial inspection image is obtained, the ring-shaped side surface image or the film layer image 1021 needs to be separated from the initial inspection image to prevent the upper background image 1041 and the lower background image 1031 from affecting the accuracy of the subsequent inspection of the defect.
In one embodiment, referring to fig. 3, the process of separating the annular side surface image from the initial inspection image (S262) includes: performing step S271 to find a boundary between the annular side surface image and the upper background image and the lower background image; step S272 is performed to use the image between the two dividing lines as the annular side surface image corresponding to the annular side surface of the wafer to be detected.
The integral gray values of the upper background image and the lower background image corresponding to the background of the wafer to be detected during shooting are smaller than the integral gray value of the annular side surface image, so that the boundary between the annular side surface image and the upper background image and the lower background image can be found according to the change of the gray values.
The obtained dividing line includes an upper dividing line and a lower dividing line.
In one embodiment, the process of finding the boundary is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary. The boundary can be found quickly and accurately through the process, and the efficiency and the accuracy of the detection method are improved.
The pixels may be divided according to the resolution of the camera, for example, when the resolution of the camera is a × B, the initial image is correspondingly divided into a × B pixels, for example, 5200 × 2040 pixels. In other embodiments, the pixels may be divided in other manners. The more pixels are divided, the greater the accuracy in subsequent detection.
When dividing the pixels, corresponding position coordinates P are established.
Referring to fig. 8, fig. 8 is a schematic diagram of a binarized initial detected image 1002 obtained after the initial detected image 1001 in fig. 7 is subjected to gray scale processing and binarization, and the binarized initial detected image 1002 includes: a binarized substrate image 1012 corresponding to the substrate image 1011 in fig. 7, a binarized film layer image 1022 corresponding to the film layer image 1021 in fig. 7, and a binarized upper background image 1042 and a binarized lower background image 1032 corresponding to the upper background image 1041 and the lower background image 1031, respectively, in fig. 7. Fig. 9 is an enlarged schematic structural diagram of a part of the image 41 in the binarized initial detected image 1002 in fig. 8 in an embodiment, the binarized initial detected image 1002 in fig. 8 is obtained by a global threshold method or a local threshold method, each square in fig. 9 represents a pixel, the number "0" or "1" in the square is a mark value corresponding to each pixel, "1" represents black, and "0" represents white.
The global threshold method or the local threshold method is a process of setting the gray value of each pixel point of the initial detection image to be 0 or 255 according to different thresholds and algorithms, namely, the whole initial detection image presents an obvious black-and-white effect, and each pixel point can be correspondingly marked as '1' or '0' or '1' after binarization.
The global threshold value method comprises a large law method, a maximum entropy method or an iteration method; the local threshold value method comprises a binarization method based on a Bernsen algorithm, a binarization method based on a Sauvola algorithm, a binarization method based on a Niblack algorithm or a binarization method based on a Wolf algorithm.
In other embodiments, the method for binarizing the gray-scale processed initial detection image may also adopt an edge detection method, and the edge detection method will be described in detail later.
After binarization, adding the mark values corresponding to all or part of pixels in each row to obtain a row mark value, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels. In this embodiment, the mark values corresponding to some pixels in each row are added to obtain a row mark value, which reduces the calculation amount when obtaining the boundary, and thus can improve the operation efficiency, specifically referring to fig. 10, in fig. 10, some pixels in each row are added to obtain a row mark value (for example, in fig. 10, the mark value of the first row is added to obtain a row mark value "1" corresponding to the first row, and the mark value of the third row is added to obtain a row mark value "7" corresponding to the third row), and the obtained row mark values may be stored in a list 51, and each stored row mark value is associated with a corresponding position of each row in the binarized initial detection image. In another embodiment, the marking values corresponding to all pixels in each row may be added to obtain a row marking value, and several rows of pixels correspond to obtain several row marking values.
And after obtaining a plurality of row mark values, obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of a boundary. The position where the row mark value changes suddenly is two positions where the row mark value changes most severely, specifically, a difference value may be obtained by subtracting the row marks corresponding to two adjacent rows, and it is determined whether the difference value is greater than a set threshold value, if the difference value is greater than the set threshold value, a boundary line between adjacent rows is a boundary line, and if the difference value is less than the set threshold value, the boundary line between adjacent rows is not a boundary line, and in a specific embodiment, the size of the threshold value may be 40% -70% of the maximum row mark value. In other embodiments, the two positions with the largest mutation amplitude are taken as the positions of the boundary line according to the mutation amplitude. Referring to fig. 10, the line marker value is abruptly changed at a boundary (P1 position) between pixels in the second line and pixels in the third line and at a boundary (P2 position) between pixels in the tenth line and pixels in the eleventh line, and two abrupt change positions (P1 position and P1 position) are associated with positions where a boundary (lower boundary) 61 and a boundary (upper boundary) 62 (refer to fig. 11 or fig. 12) can be obtained in the binarized initial detected image 1002 and the initial detected image 1001.
With reference to fig. 12 and 13, an image between two boundary lines (the boundary line 61 and the boundary line 62) in the initial inspection image 1001 is taken as an annular side surface image 1003 corresponding to the annular side surface of the wafer to be inspected.
The upper background image 1041 (refer to fig. 12) on the boundary line 62 and the lower background image 1031 under the boundary line 61 may be clipped or eliminated by a corresponding picture processing process to obtain the ring-shaped side surface image 1003.
In an embodiment, since the initial detection image is subjected to the gray scale processing before the binarization, the obtained two abrupt change positions may be directly corresponding to positions of two boundaries (an upper boundary and a lower boundary) obtained from the initial detection image after the gray scale processing, an upper background image on the upper boundary and a lower background image under the lower boundary in the initial detection image after the gray scale processing are cut off or eliminated by a corresponding picture processing process to obtain a ring-shaped side surface image after the gray scale processing, and then the ring-shaped side surface image after the gray scale processing may be directly detected based on a feature point detection method to obtain corner points, where the positions corresponding to the corner points are positions of defects, so as to simplify the detection process and improve the detection efficiency.
And S203, performing gray processing on the annular side surface image to obtain a gray image.
In this embodiment, after the annular side surface image is obtained, the obtained annular side surface image is directly subjected to gray scale processing to obtain a gray scale image.
In other embodiments, the annular side surface image comprises a substrate image and a plurality of sequentially stacked film layer images on the substrate image; separating the film layer image from the annular side surface image after obtaining the annular side surface image; and carrying out gray level processing on the film layer image to obtain a gray level image. The separation of the film layer images will be described in detail later.
Specifically referring to fig. 14, the annular side surface image 1003 is subjected to grayscale processing to obtain a grayscale image.
The purpose of performing gray processing is to represent each pixel point on the annular side surface image 1003 by using a gray value of 0-255, so as to detect the defect in the following process.
And S204 is executed, the gray level image is detected based on a characteristic point detection method, an angular point is obtained, and the position corresponding to the angular point is the position of the defect.
The feature point detection method comprises a Harris-based corner detection method, a SUSAN-based corner detection method, a FAST-based corner detection method, a FASTER-based corner detection method, a SIFT-based corner detection method and an SURF-based corner detection method.
Specifically, the Harris-based corner point detection method is a first-order derivative matrix detection method based on image gray scale, and the main idea of the detection method is local self-similarity/autocorrelation, namely the similarity between an image block in a certain local window and an image block in a window after slight movement in each direction.
In other embodiments, the defect detection method may also use edge detection, and then a contour detection (contour detection) and a contour matching (contour matching) method.
In an embodiment, referring to fig. 15, the grayscale image is detected based on a feature point detection method to obtain corner points, where a position corresponding to the corner points is a position of the defect 240.
The defect 240 includes a crack, or a peeling defect of the film, or other defects, for example, the defect 240 is a crack defect formed in the second dielectric layer 22 (corresponding to the second dielectric layer image 221). When the defect 240 is detected, it can be determined whether a defect exists in a previous process (a process for forming the second dielectric layer 22) or a corresponding structural design (a structure in the second dielectric layer and in a film layer placed on the second dielectric layer or in a film layer below the second dielectric layer), and a process and a designer can optimize the corresponding process and structural design according to the detected defect, so that the yield of products is improved, and the wafer is prevented from being scrapped.
In another embodiment, the method for binarizing the gray-scale processed initial detection image may further adopt an edge detection method to improve the accuracy of boundary line acquisition. The edge of the image represents the position with the maximum gray scale change, and the edge detection method is to determine the edge of the image according to the intensity of the gray scale change on the image.
The edge detection method adopts a Sobel edge detection operator, a Laplacian edge detection operator, a Canny edge detection operator, a Prewitt edge detection operator or a Roberts edge detection operator.
Referring to fig. 16, fig. 16 is an enlarged schematic diagram of a partial image 41 in the binarized initial detected image 1002 in fig. 8 according to an embodiment, the binarized initial detected image 1002 in fig. 8 is obtained by an edge detection method, each pixel in fig. 16 is represented by "0" or "1", "1" indicates an edge pixel, and "0" indicates a non-edge pixel, and it can be seen from fig. 16 that the number of marks "1" is larger at the boundary between the binarized upper background image 1042 (corresponding to the upper background image) and the binarized film-layer image 1022 (corresponding to the film-layer image), at the boundary between the binarized film-layer image 1022 (corresponding to the film-layer image) and the binarized substrate image 1012 (corresponding to the substrate image), and at the boundary between the binarized substrate image 1012 (corresponding to the substrate image) and the binarized lower background image 1032.
Referring to fig. 17, the mark values corresponding to all or part of the pixels in each row in fig. 16 are added to obtain a row mark value, the pixels in several rows correspondingly obtain several row mark values (for example, the mark value of the first row in fig. 16 or fig. 17 is added to obtain a row mark value "1" corresponding to the first row, the mark value of the third row is added to obtain a row mark value "5" corresponding to the third row, the upper background image 1042 corresponds to the first row of pixels, and the row number is gradually increased along the y-axis square), and the obtained several row mark values may be stored in a list 51, and each stored row mark value is associated with the corresponding position of each row in the binarized initial detection image. In another embodiment, the marking values corresponding to all pixels in each row may be added to obtain a row marking value, and several rows of pixels correspond to obtain several row marking values.
After obtaining a plurality of line mark values, obtaining positions of abrupt changes of the line mark values, where the positions of abrupt changes of the line mark values in fig. 17 include three, including a first abrupt change position, a second abrupt change position, and a third abrupt change position, where the first abrupt change position is on the 3 rd line (or the P1 position, the edge or boundary between the upper background image and the film layer image), the second abrupt change position is on the 10 th line (or the P1M position, the edge or boundary between the film layer image and the substrate image), and the third abrupt change position is on the 13 th line (or the P2 position, the edge or boundary between the substrate image and the lower background image).
In an embodiment, when it is necessary to obtain the annular side surface image 1003, the first abrupt position (or the P1 position) and the third abrupt position (or the P2 position) are corresponded to positions where the boundary line (lower boundary line) 61 and the boundary line (upper boundary line) 62 (refer to fig. 11 or fig. 12) can be obtained in the binarized initial detected image 1002 (refer to fig. 11) and the initial detected image 1001 (refer to fig. 12).
In another embodiment, referring to fig. 18, when a film layer image needs to be obtained (or needs to be separated from the circular side surface image), the first abrupt position (or P1 position) and the second abrupt position (or P1M position) are mapped to positions where a boundary (lower boundary) 61 and a boundary (upper boundary) 62 can be obtained in the binarized initial detected image 1002 and the initial detected image 1001 (refer to fig. 18), and a space between the boundary (lower boundary) 61 and the boundary (upper boundary) 62 is the film layer image. Separating the film layer image from the annular side surface image, and performing gray level processing on the film layer image to obtain a gray level image; and detecting the gray level image based on a characteristic point detection method to obtain the defect, wherein the gray level image corresponding to the substrate image does not need to be subjected to the characteristic point detection method, so that the defect detection efficiency is improved.
In other embodiments, the boundary may be obtained by other methods, specifically, after the edge detection method is used to perform binarization, a straight line detection (Hough transform) method is used to find the boundary.
Referring to fig. 19, after the boundary line is obtained, the upper background image 1041 (refer to fig. 18) on the boundary line 62 and the substrate image 1011 and the lower background image 1031 under the boundary line 61 may be clipped or eliminated by a corresponding photo process to obtain a film-layer image 1021.
Referring to fig. 20, the film layer image 1021 is subjected to a gray scale process to obtain a gray scale image.
Referring to fig. 21, the grayscale image is detected based on a feature point detection method to obtain corner points, where the positions corresponding to the corner points are the positions of the defects 240.
In one embodiment, when a notch for positioning is formed in the edge of the wafer to be detected, a notch image corresponding to the notch is formed in the surface image of the annular side surface; excluding notch images in the annular side surface image. Specifically, the notch image in the annular side surface image may be excluded before or after the annular side surface image is subjected to the grayscale processing (before the grayscale image is detected based on the feature point detection method).
An embodiment of the present invention further provides a system for detecting defects on a side surface of a wafer, referring to fig. 22, including:
the wafer providing unit 300 is used for providing a wafer to be detected, wherein the wafer to be detected comprises a top surface, an opposite bottom surface and an annular side surface positioned between the top surface and the bottom surface;
an annular side surface image obtaining unit 301, configured to obtain an annular side surface image corresponding to an annular side surface of the wafer to be detected;
a gray processing unit 304, configured to perform gray processing on the annular side surface image to obtain a gray image;
a feature point detection unit 305, configured to detect the grayscale image based on a feature point detection method, to obtain an angular point, where a position corresponding to the angular point is a position of the defect.
In an embodiment, the annular side surface image obtaining unit 301 includes an initial detection image obtaining unit 303 and a separating unit 302, the initial detection image obtaining unit 303 is configured to obtain an initial detection image, the initial detection image includes an annular side surface image, an upper background image located on the annular side surface image, and a lower background image located under the annular side surface image, and the separating unit 302 is configured to separate the annular side surface image from the initial detection image.
In an embodiment, the process of separating the annular side surface image from the initial detection image by the separation unit 302 includes: finding a boundary of the annular side surface image with an upper background image and a lower background image; and taking the image between the two boundary lines as an annular side surface image corresponding to the annular side surface of the wafer to be detected.
In one embodiment, the process of finding the boundary is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
The gray processing unit 304 binarizes the gray-processed initial detection image by using a global threshold method or a local threshold method.
In an embodiment, the global thresholding method comprises a large law method, a maximum entropy method, or an iterative method. The local threshold value method comprises a binarization method based on a Bernsen algorithm, a binarization method based on a Sauvola algorithm, a binarization method based on a Niblack algorithm or a binarization method based on a Wolf algorithm.
In an embodiment, after the annular side surface image obtaining unit 301 obtains the annular side surface image, the gray processing unit 304 directly performs gray processing on the obtained annular side surface image to obtain a gray image.
And acquiring the initial detection image by acquiring a circle of the side surface of the wafer to be detected through image acquisition equipment.
The annular side surface image comprises a substrate image and a plurality of sequentially stacked film layer images positioned on the substrate image, and the separation unit 302 is further configured to separate the film layer images from the annular side surface image; the gray processing unit 304 is further configured to perform gray processing on the film layer image to obtain a gray image; the feature point detection unit 305 detects the grayscale image based on a feature point detection method, and obtains a defect.
The process of separating the film layer image from the annular side surface image by the separation unit 302 includes: finding a boundary between the film layer image and the upper background image and the substrate image; the image between the two boundaries is taken as the film layer image.
In one embodiment, the process of finding the boundary is: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary. And carrying out binarization on the initial detection image after the gray processing by adopting an edge detection method.
In one embodiment, the edge detection method employs a Sobel edge detector, a Laplacian edge detector, a Canny edge detector, a Prewitt edge detector, or a Roberts edge detector.
In one embodiment, the feature point detection method includes Harris-based corner detection method, SUSAN-based corner detection method, FAST-based corner detection method, FASTER-based corner detection method, SIFT-based corner detection method, SURF-based corner detection method.
In an embodiment, the feature point detecting unit 305 includes a notch image excluding unit, configured to, when a notch for positioning exists at an edge of the wafer to be detected, have a corresponding notch image in the annular side surface image; excluding notch images in the annular side surface image. Specifically, the notch image in the annular side surface image may be excluded before or after the annular side surface image is subjected to the grayscale processing (before the grayscale image is detected based on the feature point detection method).
It should be noted that, the definition or description of the same or similar parts in this embodiment (the system for detecting a wafer side defect) and the foregoing embodiment (the process or method for detecting a wafer side defect) is not repeated in this embodiment, and specific reference is made to the description or definition of the corresponding parts in the foregoing embodiment.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.

Claims (30)

1. A method for detecting defects on a side surface of a wafer is characterized by comprising the following steps:
providing a wafer to be detected, wherein the wafer to be detected comprises a top surface, an opposite bottom surface and an annular side surface positioned between the top surface and the bottom surface;
obtaining an annular side surface image corresponding to the annular side surface of the wafer to be detected;
carrying out gray processing on the surface image of the annular side surface to obtain a gray image;
and detecting the gray level image based on a characteristic point detection method to obtain angular points, wherein the positions corresponding to the angular points are the positions of the defects.
2. The method of claim 1, wherein the obtaining of the annular side surface image comprises: obtaining an initial detection image, wherein the initial detection image comprises an annular side surface image, an upper background image positioned on the annular side surface image and a lower background image positioned under the annular side surface image; separating the annular side surface image from the initial inspection image.
3. The method of detecting wafer side defects according to claim 2, wherein said separating said annular side surface image from an initial inspection image comprises: finding a boundary of the annular side surface image with an upper background image and a lower background image; and taking the image between the two boundary lines as an annular side surface image corresponding to the annular side surface of the wafer to be detected.
4. The method of claim 3, wherein the step of finding the boundary line comprises: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
5. The method for detecting the side defect of the wafer as claimed in claim 4, wherein a global threshold method or a local threshold method is adopted to binarize the gray-processed initial detection image.
6. The method for detecting the side defect of the wafer as claimed in claim 5, wherein the global threshold method comprises a large law method, a maximum entropy method or an iterative method; the local threshold value method comprises a binarization method based on a Bernsen algorithm, a binarization method based on a Sauvola algorithm, a binarization method based on a Niblack algorithm or a binarization method based on a Wolf algorithm.
7. The method for detecting the side defect of the wafer as claimed in claim 2, wherein the step of performing gray processing on the surface image of the annular side surface to obtain a gray image comprises: and after the annular side surface image is obtained, directly carrying out gray level processing on the obtained annular side surface image to obtain a gray level image.
8. The method for detecting the side defect of the wafer as claimed in claim 2, wherein the step of performing gray processing on the surface image of the annular side surface to obtain a gray image comprises: the annular side surface image comprises a substrate image and a plurality of film layer images which are sequentially stacked on the substrate image; separating the film layer image from the annular side surface image after obtaining the annular side surface image; and carrying out gray level processing on the film layer image to obtain a gray level image.
9. The method of detecting wafer side defects according to claim 8, wherein the separating the film layer image from the annular side surface image comprises: finding a boundary between the film layer image and the upper background image and the substrate image; the image between the two boundaries is taken as the film layer image.
10. The method of claim 9, wherein the step of finding the boundary line comprises: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
11. The method for detecting the side defect of the wafer as claimed in claim 4 or 10, wherein an edge detection method is adopted to binarize the gray processed initial detection image.
12. The method of claim 11, wherein the edge detection method employs a Sobel edge detector, a Laplacian edge detector, a Canny edge detector, a Prewitt edge detector, or a Roberts edge detector.
13. The method for detecting the side defect of the wafer as claimed in claim 2, wherein the initial detection image is obtained by collecting a circle of the side of the wafer to be detected through an image collecting device.
14. The method of claim 1, wherein the feature point inspection method comprises Harris-based corner inspection, SUSAN-based corner inspection, FAST-based corner inspection, FASTER-based corner inspection, SIFT-based corner inspection, and SURF-based corner inspection.
15. The method for detecting the side defect of the wafer as claimed in claim 1, wherein when the edge of the wafer to be detected has a notch for positioning, the annular side surface image has a notch image corresponding to the notch; excluding notch images in the annular side surface image.
16. A system for detecting defects in a side surface of a wafer, comprising:
the wafer providing unit is used for providing a wafer to be detected, and the wafer to be detected comprises a top surface, an opposite bottom surface and an annular side surface positioned between the top surface and the bottom surface;
the annular side surface image obtaining unit is used for obtaining an annular side surface image corresponding to the annular side surface of the wafer to be detected;
the gray processing unit is used for carrying out gray processing on the surface image of the annular side surface to obtain a gray image;
and the characteristic point detection unit is used for detecting the gray level image based on a characteristic point detection method to obtain an angular point, wherein the position corresponding to the angular point is the position of the defect.
17. The wafer side defect detection system of claim 16, wherein the annular side surface image obtaining unit comprises an initial inspection image obtaining unit for obtaining an initial inspection image including an annular side surface image, an upper background image on the annular side surface image, and a lower background image under the annular side surface image, and a separating unit for separating the annular side surface image from the initial inspection image.
18. The wafer side defect detection system of claim 17, wherein the separating unit separating the annular side surface image from the initial inspection image comprises: finding a boundary of the annular side surface image with an upper background image and a lower background image; and taking the image between the two boundary lines as an annular side surface image corresponding to the annular side surface of the wafer to be detected.
19. The system of claim 18, wherein the finding of the dividing line comprises: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
20. The system for detecting the side defect of the wafer as claimed in claim 19, wherein the gray-processed initial detection image is binarized by using a global threshold method or a local threshold method.
21. The wafer side defect detection system of claim 20, wherein said global thresholding comprises a law maximization, entropy maximization, or an iterative; the local threshold value method comprises a binarization method based on a Bernsen algorithm, a binarization method based on a Sauvola algorithm, a binarization method based on a Niblack algorithm or a binarization method based on a Wolf algorithm.
22. The system of claim 17, wherein after the ring-shaped side surface image obtaining unit obtains the ring-shaped side surface image, the gray processing unit directly performs gray processing on the obtained ring-shaped side surface image to obtain a gray image.
23. The wafer side defect detection system of claim 17, wherein the annular side surface image comprises a substrate image and a plurality of sequentially stacked film layer images on the substrate image, and the separation unit is further configured to separate the film layer images from the annular side surface image; the gray processing unit is also used for carrying out gray processing on the film layer image to obtain a gray image.
24. The wafer side defect detection system of claim 23, wherein the process of separating the film layer image from the annular side surface image by the separation unit comprises: finding a boundary between the film layer image and the upper background image and the substrate image; the image between the two boundaries is taken as the film layer image.
25. The system of claim 24, wherein the finding of the dividing line comprises: dividing the initial detection image into a plurality of pixels; carrying out gray level processing on the initial detection image; binarizing the initial detection image after the gray processing, and correspondingly marking each pixel as a value of '0' or '1'; adding the mark values corresponding to all or part of pixels in each row to obtain row mark values, and obtaining a plurality of row mark values corresponding to a plurality of rows of pixels; and obtaining the position of the row mark value mutation, wherein the position of the row mark mutation is the position of the boundary.
26. The system for detecting the side defect of the wafer as claimed in claim 19 or 25, wherein the gray-processed initial detection image is binarized by using an edge detection method.
27. The system of claim 26, wherein the edge detection method employs a Sobel edge detector, a Laplacian edge detector, a Canny edge detector, a Prewitt edge detector, or a Roberts edge detector.
28. The system for detecting the lateral defect of the wafer as claimed in claim 17, wherein the initial detection image is obtained by collecting a circle of the lateral surface of the wafer to be detected through an image collecting device.
29. The system of claim 16, wherein the feature point inspection method comprises Harris-based corner inspection, SUSAN-based corner inspection, FAST-based corner inspection, FASTER-based corner inspection, SIFT-based corner inspection, SURF-based corner inspection.
30. The system for detecting the lateral defect of the wafer as claimed in claim 16, further comprising a notch image removing unit, configured to have a corresponding notch image in the annular lateral surface image when the edge of the wafer to be detected has a notch for positioning; excluding notch images in the annular side surface image.
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