CN114897853A

CN114897853A - Detection method and detection device for wafer and storage medium

Info

Publication number: CN114897853A
Application number: CN202210562259.XA
Authority: CN
Inventors: 赵哲; 谢真良; 陈金星; 王庆; 汪严莉
Original assignee: Yangtze Memory Technologies Co Ltd
Current assignee: Yangtze Memory Technologies Co Ltd
Priority date: 2022-05-23
Filing date: 2022-05-23
Publication date: 2022-08-12

Abstract

The embodiment of the application provides a wafer detection method, a wafer detection device and a storage medium. In some embodiments of the present application, a method for inspecting a wafer includes: determining an image characteristic value of a pixel of a side image of a wafer; counting image characteristic values of pixels of the side image; and determining whether the profile of the wafer is abnormal according to the statistical result. The wafer detection method, the wafer detection device and the storage medium can be used for carrying out abnormity detection on the wafer.

Description

Detection method and detection device for wafer and storage medium

Technical Field

Embodiments of the present disclosure relate to the field of semiconductor technology, and more particularly, to a wafer inspection method, an inspection apparatus, and a storage medium.

Background

Wafers refer to silicon chips used in the fabrication of silicon semiconductor integrated circuits and are carriers used in the production of integrated circuits, and therefore, the quality of wafers directly affects the yield and manufacturing cost of chips. In the actual process of manufacturing the wafer, defects such as a notch generated by a crack at the edge of the wafer are inevitably generated on a part of the wafer. Therefore, the wafer needs to be inspected to obtain a wafer meeting the standard.

Most engineers currently inspect wafers to find defects with their eyes. However, this manual detection greatly reduces the detection efficiency and the detection accuracy.

Disclosure of Invention

Embodiments of the present application provide an inspection method, an inspection apparatus, and a storage medium for a wafer, which can at least partially solve the above-mentioned problems in the prior art.

In one aspect, an embodiment of the present application provides a wafer inspection method, including: determining an image characteristic value of a pixel of a side image of a wafer; counting image characteristic values of pixels of the side image; and determining whether the profile of the wafer is abnormal according to the statistical result.

In some embodiments of the present application, the counting the image feature values of the side images includes: and respectively calculating the sum or the average value of the image characteristic values of the pixels of each row and/or column of the pixel array of the side image to obtain the image characteristic value of each row and/or column of the pixel array.

In some embodiments of the present application, determining whether the profile of the wafer is abnormal according to the statistical result includes: and determining that the profile of the wafer has an abnormality in response to the statistical result indicating that there are abnormal values in the image characteristic values of the rows and/or columns.

In some embodiments of the present application, after determining that there is an abnormality in the profile of the wafer in response to the statistics indicating that there is an abnormal value in the image feature values of the columns, the method further comprises: and determining the position of the profile abnormality of the wafer according to the row corresponding to the abnormal value.

In some embodiments of the present application, the method further comprises: determining the longitudinal length of the profile abnormal region according to the pixels with abnormal image characteristic values in the column corresponding to the abnormal values; determining the defect depth of the wafer according to the determined longitudinal length; and determining that the wafer has the notch defect in response to the defect depth being in the preset abnormal depth range.

In some embodiments of the present application, before determining whether the profile of the wafer is abnormal according to the statistical result, the method further includes: the image feature values of the rows and/or columns are smoothed.

In some embodiments of the present application, prior to determining the image feature values of the pixels of the side image of the wafer, the method further comprises: acquiring an original side image of a wafer; carrying out gray level processing on the original side image; and obtaining a side image according to the original side image after the gray processing.

In some embodiments of the present application, deriving the side image from the gray-scale processed original side image comprises: and carrying out binarization processing on the original side image subjected to the gray processing to obtain a side image.

In some embodiments of the present application, the wafer is provided with a notch for positioning, and the method further includes: and removing an image area corresponding to the notch of the wafer for positioning in the original side image by cutting the original side image.

In some embodiments of the present application, the image feature values comprise color values or luminance values.

Another aspect of the present disclosure provides an inspection apparatus for a wafer, including: the determining module is used for determining the image characteristic value of the pixel of the side image of the wafer; the statistical module is used for carrying out statistics on the image characteristic values of the pixels of the side image; and the detection module is used for determining whether the outline of the wafer is abnormal or not according to the statistical result.

In some embodiments of the present application, the statistics module is configured to: and respectively calculating the sum or the average value of the image characteristic values of the pixels of each row and/or column of the pixel array of the side image to obtain the image characteristic value of each row and/or column of the pixel array.

In some embodiments of the present application, the detection module is configured to: and determining that the profile of the wafer has an abnormality in response to the statistical result indicating that there are abnormal values in the image characteristic values of the rows and/or columns.

In some embodiments of the present application, the detection module is further configured to: and after determining that the profile of the wafer has an abnormality in response to the statistical result indicating that an abnormal value exists in the image characteristic values of the columns, determining the position of the profile abnormality of the wafer according to the column corresponding to the abnormal value.

In some embodiments of the present application, the detection module is further configured to: determining the longitudinal length of the profile abnormal region according to the pixels with abnormal image characteristic values in the column corresponding to the abnormal values; determining the defect depth of the wafer according to the determined longitudinal length; and determining that the wafer has the notch defect in response to the defect depth being in the preset abnormal depth range.

In some embodiments of the present application, the detection device further comprises: and the alarm module is used for feeding back alarm information in response to the fact that the outline of the wafer is abnormal or the wafer has a gap defect.

An embodiment of the present application further provides a detection apparatus, including: a memory for storing computer instructions; and a processor for communicating with the memory to execute the computer instructions to implement the detection method as mentioned in the above embodiments.

Embodiments of the present application also provide a readable storage medium, in which computer instructions are stored, and when executed by a processor, the computer instructions implement the detection method mentioned in the above embodiments.

According to the embodiment of the application, because the image characteristic values of the pixels in the abnormal area of the wafer profile in the side image of the wafer are different from the image characteristic values of the pixels in the normal position, the detection device can analyze whether the wafer profile is abnormal or not by counting the image characteristic values of the pixels in the side image of the wafer, so that the automatic detection of the abnormal wafer profile can be realized, and the detection efficiency and accuracy are improved compared with manual detection.

Drawings

Other features, objects, and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings. Wherein:

FIG. 1 is a flow chart of an inspection method for wafers according to some embodiments of the present application;

fig. 2 is a schematic top view of a wafer according to some embodiments of the present application;

FIG. 3 is an enlarged partial schematic view of region A of FIG. 2;

FIG. 4 is a schematic side view of a wafer according to some embodiments of the present application;

FIG. 5 is a schematic side view of a wafer according to another embodiment of the present application;

FIG. 6 is a schematic view of an original side image according to some embodiments of the present application;

FIG. 7 is a schematic side view image according to some embodiments of the present application;

FIG. 8 is a graphical illustration of a trend of a change in an image feature value for each column of a pixel array of a side image according to some embodiments of the present application;

FIG. 9 is a schematic block diagram of an inspection apparatus for wafers according to an exemplary embodiment of the present application;

FIG. 10 is a schematic block diagram of a detection apparatus according to an exemplary embodiment of the present application.

Detailed Description

For a better understanding of the present application, various aspects of the present application will be described in more detail with reference to the accompanying drawings. It should be understood that the detailed description is merely illustrative of exemplary embodiments of the present application and does not limit the scope of the present application in any way. Like reference numerals refer to like elements throughout the specification. The expression "and/or" includes any and all combinations of one or more of the associated listed items.

It should be noted that in this specification the expressions first, second, third etc. are only used to distinguish one feature from another, and do not indicate any limitation of features, in particular any order of precedence.

In the drawings, the thickness, size and shape of the components have been slightly adjusted for convenience of explanation. The figures are purely diagrammatic and not drawn to scale. As used herein, the terms "approximately", "about" and the like are used as table-approximating terms and not as table-degree terms, and are intended to account for inherent deviations in measured or calculated values that would be recognized by one of ordinary skill in the art.

It will be further understood that terms such as "comprising," "including," "having," "including," and/or "containing," when used in this specification, are open-ended and not closed-ended, and specify the presence of stated features, elements, and/or components, but do not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof. Furthermore, when describing embodiments of the present application, the use of "may" mean "one or more embodiments of the present application. Also, the term "exemplary" is intended to refer to an example or illustration.

Unless otherwise defined, all terms (including engineering and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. In addition, unless explicitly defined or contradicted by context, the specific steps included in the methods described herein are not necessarily limited to the order described, but can be performed in any order or in parallel. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

Fig. 1 is a flow chart of an inspection method 1000 for a wafer, which may be performed, for example, by an inspection apparatus, according to some embodiments of the present application. As shown in fig. 1, the present application provides an inspection method 1000 for a wafer, including:

and S11, determining the image characteristic value of the pixel of the side image of the wafer.

S12, image feature values of the pixels of the side image are counted.

And S13, determining whether the contour of the wafer is abnormal according to the statistical result.

For ease of understanding, the various steps of the inspection method 1000 for wafers are illustrated below.

Step S11

Fig. 2 is a schematic top view of a wafer 20 according to some embodiments of the present disclosure, fig. 3 is a partially enlarged schematic view of a region a in fig. 2, and fig. 4 is a schematic side view of the wafer 20 according to some embodiments of the present disclosure.

In some embodiments of the present application, the side image of the wafer may be a peripheral image of the wafer. Illustratively, the raw side image of the wafer is taken from the side surface rotating one revolution around the wafer 20. The shooting area is focused to the edge of the wafer, so that the side image of the wafer can further highlight the shape of the edge of the wafer, and the detection device can be used for detecting the abnormal outline of the wafer.

In some embodiments of the present application, the side image of the wafer may also be a side image of a top bevel angle or a bottom bevel angle of the wafer. Here, the top oblique view may refer to a view inclined from a top view to a side, and the bottom oblique view may refer to a view inclined from a bottom view to a side. For example, if the viewing angle is 0 degrees, the viewing angle is substantially perpendicular to the top surface of the wafer, the top oblique viewing angle may be (0 °, 90 °), and the bottom oblique viewing angle may be (90 °, 180 °). The side image of the top oblique view angle of the wafer is shot, so that the shot side image comprises the image of the wafer top, the difference between the image of the defect position and the image of the normal area of the wafer can be highlighted, and the detection device can be used for detecting the profile abnormality of the wafer.

In some embodiments of the present application, the image characteristic value of the pixel may be, for example, a color value (e.g., an RGB value or a gray value) of the pixel or a luminance value of the pixel. For example, as the profile of the wafer is abnormal due to the existence of the notch defect in the wafer, as can be seen from fig. 2 to 4, the color or brightness of the image area (e.g., the area B and the area C of fig. 4) corresponding to the notch of the wafer is different from the color or brightness of the other areas, the color of the image area corresponding to the notch is black, the color around the notch may be, for example, the color of the wafer body, and the brightness of the image area corresponding to the notch is lower than the brightness around the notch. The detection device can detect whether the wafer has defects by counting the color or brightness of each pixel in the side image.

In some embodiments of the present application, a notch for positioning is provided on the wafer, and the detection device may obtain the original side image, and remove an image area corresponding to the notch for positioning of the wafer in the original side image by cutting the original side image. In order to facilitate the calibration of the position of the wafer by the inspection device and/or other devices for wafers, a notch for positioning is usually provided at a fixed position of the wafer, so that the wafer is positioned by the inspection device and/or other devices for wafers. The detection device cuts the original side face image to remove the image area corresponding to the notch for positioning, so that the influence of the notch for positioning on the abnormal outline detection of the wafer can be reduced.

For ease of understanding, the manner in which the image area corresponding to the notch for positioning is removed is exemplarily described below.

Illustratively, the manner of acquiring the original side image includes: detecting the position of a notch for positioning of the wafer through a predefined notch detection algorithm for positioning; starting from the notch position of the wafer for positioning, images are shot around the wafer to obtain an original side image.

Fig. 5 is a schematic side view of a wafer according to another embodiment of the present application. The left area (area D) and the right area (area E) of the original side image of the wafer contain images of the notch for positioning.

As an example, the inspection apparatus may determine the x-direction size (i.e., the lateral length) of the notch for positioning in the original side image according to the approximate range of the actual width of the notch for positioning in the wafer circumferential direction given by the inspector and the actual length represented by each pixel in the image captured by the device capturing the original side image. Since the original side image is photographed from the position of the notch for positioning, and the image areas corresponding to the notch for positioning are located in the left area (also referred to as the start photographing area) and the right area (also referred to as the end photographing area) of the original side image, the detecting device may cut the image areas having a width at least the lateral length of the determined notch for positioning from the left area and the right area, respectively.

As another example, the inspection apparatus may determine the x-direction dimension (i.e., the lateral length) of the notch for positioning in the original side image according to the approximate range of the actual width of the notch for positioning in the wafer circumferential direction given by the inspector and the actual length represented by each pixel in the image captured by the device capturing the original side image. The detection device can determine the size (namely the longitudinal length) of the notch for positioning in the y direction in the original side image according to the approximate range of the length of the notch for positioning on the wafer along the radial direction of the wafer, the shooting angle and the actual length represented by each pixel in the image shot by the equipment for shooting the original side image, which are given by a detector. The detection device may determine an image area corresponding to the notch for positioning in the original side image according to the determined transverse length and longitudinal length of the notch for positioning in the original side image, and cut off the partial image area.

It should be understood that the predefined notch detection algorithm for positioning may be set according to the morphological feature of the notch for positioning, the image feature around the notch for positioning, etc. without departing from the teachings of the present application, and the present application is not limited thereto.

It should be understood that the detection device may also lock the image area of the notch for positioning in other ways without departing from the teachings of the present application, which is not limited by the present application.

In some embodiments of the present application, the process of acquiring the side image of the wafer by the detection device may include: acquiring an original side image of a wafer; carrying out gray level processing on the original side image; and obtaining a side image of the wafer according to the original side image after the gray processing. The original side image of the wafer may be the original side image after trimming or the original side image without trimming, which is not limited in this application.

As an example, fig. 6 is a schematic diagram of an original side image according to some embodiments of the present application. The detection device may perform gray scale processing on the original side image by a component method, a maximum value method, an average value method, a weighted average method, or the like. If the detection device adopts a component method, the brightness of RGB three components of the pixel in the original side image can be respectively used as the gray value of the pixel to obtain 3 candidate images, and one candidate image is selected as the original side image after gray processing according to the requirement. If the detection device adopts a maximum value method, the maximum value of RGB three-component brightness of the pixel in the original side image can be used as the gray value of the pixel, so that the original side image after gray processing is obtained. If the detection device adopts an average value method, the average value of the RGB three-component brightness of the pixels in the original side image can be used as the gray value of the pixels, so that the original side image after gray processing is obtained. If the detection device adopts a weighted average method, the three components can be weighted and averaged by different weights according to the importance or other indexes of each component in the RGB three components of the pixel, so that the original side image after the gray processing is obtained. For example, after the detection device cuts out the area image of the notch for positioning of the original side image shown in fig. 5, the cut original side image is subjected to the grayscale processing, and the obtained grayscale-processed original side image is shown in fig. 6. As can be seen from fig. 6, the area (area F) where the other notch is located in the original side image after the gradation processing is different from the image characteristics of the other area, and the detection device can perform the defect detection based on fig. 6.

It should be understood that the raw side image may also be grayscale processed in other ways without departing from the teachings of the present application, and the present application is not limited thereto.

Alternatively, the obtaining of the side image by the detection device according to the original side image after the gray processing may include: and carrying out binarization processing on the original side image subjected to the gray processing to obtain a side image of the wafer. For example, the detection device obtains a side image by binarizing the original side image after the gradation processing shown in fig. 6, and the side image has a defect region G as shown in fig. 7.

As an example, the process of the detection means performing the binarization process may include, for example: acquiring a preset threshold (for example, a median 127 of 0-255), and for each pixel in the original side image after the gray processing, changing the gray value of the pixel to 0 (namely black) in response to the gray value of the pixel being less than or equal to the threshold; in response to the gray scale value of a pixel being greater than the threshold, the gray scale value of the pixel is changed to 255 (i.e., white).

As another example, the process of the detection means performing the binarization process may include, for example: determining the gray level average value of each pixel in the pixel array; for each pixel in the original side image after the gray level processing, changing the gray level value of the pixel to 0 (namely black) in response to the fact that the gray level value of the pixel is smaller than or equal to the average gray level value; in response to the gray value of a pixel being greater than the gray average value, the gray value of the pixel is changed to 255 (i.e., white).

It should be understood that the detection device may select other ways to perform binarization processing on the grayscale-processed image without departing from the teachings of the present application, and the present application does not limit this.

Step S12 and step S13

In some embodiments of the present application, the manner in which the detection device performs statistics on the image features of the pixels of the side image may include: and respectively calculating the sum or the average value of the image characteristic values of the pixels of each row and/or column of the pixel array of the side image to obtain the image characteristic value of each row and/or column of the pixel array.

Optionally, the determining, by the detecting device, whether the profile of the wafer is abnormal according to the statistical result may include: and determining that the profile of the wafer has an abnormality in response to the statistical result indicating that there are abnormal values in the image characteristic values of the rows and/or columns. Wherein an outlier means that the value deviates significantly from the remaining values. Whether or not an abnormal value exists in the image feature values of the rows and/or columns can be detected by an abnormal value detection algorithm.

The following is an exemplary explanation taking the following image feature values as an example.

Illustratively, the image feature values of the columns of the pixel array are calculated in left-to-right or right-to-left order. Starting from j to 1, comparing whether the range of the image characteristic values of the j to j + U columns is larger than a preset value or not for the image characteristic value of the j to j + U columns, and if yes, determining that an abnormal value exists in the image characteristic values of the j to j + U columns. If not, determining that no abnormal value exists in the image characteristic values of the jth to jth + U columns, making j equal to j +1, and returning to the step of comparing whether the range between the image characteristic values of the jth to jth + U columns is larger than a preset value or not until j + U is equal to the number of columns of the pixel array. The specific values of the preset value and U may be determined according to information such as the size of the side image, for example, the preset value may be a value greater than or equal to 20, and U may be a value greater than or equal to 10. After determining that there is an abnormal value in the image feature values of the j-th to j + U-th columns, the most value among the image feature values of the j-th to j + U-th columns may be taken as the abnormal value. The most value may be a maximum value or a minimum value, and the details thereof are determined according to the processing procedure of the side image by the detection device.

Optionally, after detecting the abnormal value, the detection apparatus may further determine whether there is an abnormality in the profile of the wafer according to the distribution of the abnormal value. For example, for the trimmed original side surface image, since the image area of the notch for positioning has been trimmed in advance, the detection device determines that there is an abnormality in the outline of the wafer if an abnormal value is detected. For the original side image that is not cropped, the detection means may determine the abnormal value distribution area when the abnormal value is detected, since the side image includes an image area including a notch for positioning. For example, the detection device determines that the profile of the wafer is normal in response to the number of the abnormal value distribution areas being less than or equal to N; and determining that the profile of the wafer is abnormal in response to the number of the abnormal value distribution areas being larger than N. The value of N may be set according to the capturing mode of the original side image, for example, if the same portion of the image in the initial capturing region and the same portion of the image in the end capturing region of the original side image are removed, N is equal to 1, if the same portion of the image in the initial capturing region and the same portion of the image in the end capturing region of the original side image are not removed, the value of N is determined according to the initial capturing position, for example, if the original side image is captured from a notch for positioning, N is equal to 2, and if the original side image is captured from a position other than the notch for positioning, N is equal to 1.

As an example, the detection device obtains the image feature value (for example, the gray value of the pixel after the binarization processing) of each pixel in the pixel array of the side image, and calculates the sum or the average of the image feature values of the pixels of each row in the pixel array as the image feature value of the row. If the wafer has a defect, the image characteristic value of the pixel corresponding to the defect in the pixel array is different from the image characteristic values of the pixels around the pixel, and through counting the characteristic values of the pixels in each row, if the image characteristic value of a certain row is different from the image characteristic value of the rows around the certain row, whether the pixels corresponding to the defect are included in the pixels in the row can be judged according to the difference between the image characteristic value of the row and the image characteristic value of the rows around the certain row. For example, after counting the image feature values of each row, if the detection device determines that the difference between the image features of the ith row and the (i + 1) th row is very large, for example, greater than a first threshold, it may determine that the boundary (e.g., the intersection between the top surface and the side surface of the wafer) of the ith row and the (i + 1) th row is a boundary of the wafer, rather than a defect; if the image characteristic difference between the ith row and the (i + 1) th row is smaller than the first threshold value, the outline of the wafer can be judged to be abnormal.

It should be understood that the first threshold value may be determined according to the processing manner of the original side image, the number of columns of the pixel array of the side image, and the like in the process of obtaining the side image from the original side image by the detection device without departing from the teachings of the present application. For example, if the detection device performs the gray-scale processing and the binarization processing on the original side image to obtain the side image, and the number of rows of the pixel array is a, the first threshold may be, for example, 255 a T, and T may be, for example, any value between (70% and 100%), for example, 75%, 80%, 85%, 90%, 95%, and the like. The first threshold is not limited by the present application.

As another example, the detection device obtains the image feature value (for example, the gray value of the pixel after the binarization processing) of each pixel in the pixel array of the side image, and calculates the sum or the average of the image feature values of each column of pixels in the pixel array as the image feature value of the column. Taking the notch defect as an example, if the wafer does not have a notch, the image feature values of each row in the pixel array of the side image are substantially the same. If the wafer has a notch, the notch of the wafer usually extends from the edge of the wafer to the inside of the wafer, so that the difference between the image feature values of other pixel points in the row of the individual pixel points in the side image of the wafer is larger. The image characteristic values of each column of pixels of the pixel array are counted to obtain the image characteristic values of the columns, and the image characteristic values of the columns are compared to determine the area where the gap is located, so that the situation that the area where the gap is located is identified by mistake due to the fact that the image characteristic values of the pixels of different columns in the same row are different due to noise and the like can be reduced. For example, the detection device sums the image characteristic values of the pixels in each column of the pixel array of the side image, and the variation trend of the image characteristic values of the columns is shown in fig. 8, where in fig. 8, the abscissa is the number (j) of the columns of the pixel array and the ordinate is the image characteristic value (F) of the column. As can be seen from fig. 8, if an abnormal value exists at j — K, the detection device can determine that the wafer corresponding to the side image has a notch and the wafer profile is abnormal.

It should be understood that the detection apparatus may be configured with different methods for determining whether an abnormal value exists without departing from the teachings of the present application, for example, whether an abnormal value exists in the image feature values of each column is detected by an abnormal value detection algorithm, which is not limited by the present application.

Optionally, in the process of detecting the profile abnormality of the wafer based on the image feature values of the rows of the pixel array, the detection device may further determine the position of the profile abnormality of the wafer according to the row corresponding to the abnormal value after determining that the profile of the wafer is abnormal. As described above, since the image feature values of the rows in the pixel array of the side image are substantially the same, the detection apparatus can set the position of the profile abnormality of the wafer according to the row corresponding to the detected abnormal value.

Alternatively. After determining a column corresponding to an abnormal value, the detection device determines the longitudinal length of the profile abnormal region according to the pixels with abnormal image characteristic values in the column corresponding to the abnormal value; determining the defect depth of the wafer according to the determined longitudinal length; and determining that the wafer has the notch defect in response to the defect depth being within a preset abnormal depth range. The defect depth of the wafer may refer to a length along a radial direction of the wafer, and the longitudinal length may refer to a length along a Y-direction of the acquired side image.

Illustratively, the detecting means determines the j-th order of the side image ₁ Column to j ₂ Abnormal image characteristic value of the column, and determining j-th image of the side image ₁ Column to j ₂ Pixels with abnormal image characteristic values in pixels of columnsAnd from this the longitudinal length of the abnormal region (i.e. the length in the y-direction) is determined. For example, if the pixels with abnormal image feature values are continuously distributed in the side image, the longitudinal length is equal to the difference between the line numbers of the first pixel with abnormal image feature value and the last pixel with abnormal image feature value from the upper side of the side image to the lower side of the side image. For example, if the pixel with abnormal image feature value is ith ₁ Go to the ith ₂ If the image characteristic value of the pixel of the line is abnormal, the longitudinal length is determined to be i ₂ -i ₁ (e.g., the straight-line distance between point P to point Q in fig. 7). And if the pixels with abnormal image characteristic values are distributed in the side images in a segmented manner, integrating a plurality of segments, determining the segments corresponding to the defects in each integrated segment according to a preset search rule after integration is finished, and taking the number of the pixels of the segments corresponding to the defects as the longitudinal length. The integration method may be, for example: for each segment, if the number of pixels between adjacent segments is less than a predetermined threshold number of pixels (i) _pre ) Then the neighboring segments are integrated into one segment. The preset search rule is determined according to parameters of the photographing device of the side image, for example, the search rule indicates: the ith of the image _max Row and ith _min The segments between the rows serve as the segments corresponding to the defects. Wherein i _max And i _min According to the parameters of the shooting equipment. For example, if j ₁ The pixel with abnormal image characteristic value of the column is the ith pixel ₁ Line of pixels to ith ₂ Pixels of a row, and an ith ₃ Line of pixels to ith ₄ Abnormal image feature value of pixels of a line in response to i ₃ -i ₂ ＜i _pre Determining a longitudinal length of i ₄ -i ₁ In response to i ₃ -i ₂ ≥i _pre ，i ₂ And i ₁ At [ i ] _min ，i _max ]Has a longitudinal length equal to i ₂ -i ₁ (e.g., the straight-line distance between point P to point Q in fig. 7). And after the detection device determines the longitudinal length, taking the product of the longitudinal length and the actual length represented by each pixel in the side image as the defect depth of the wafer in the row. The detection device acquires the defect depth of the wafer in each rowAnd judging whether the obtained maximum value is in the abnormal depth range or not, if so, determining that the wafer has a notch defect, and if not, determining that the wafer has other defects. The distinguishing method of other defects can be defined according to the morphological characteristics of other defects, which is not listed here.

It should be understood that the anomaly depth range may be determined based on wafer structural characteristics, process requirements, etc., without departing from the teachings of the present application, e.g., the anomaly depth range may be, for example, (0, 0.1mm), which is not limited by the present application.

As another example, the detection device obtains the image feature values of each pixel in the pixel array of the side image (for example, the gray values of the pixels after binarization processing), and calculates the sum or average of the image feature values of the pixels in each row of the pixel array as the image feature value of the row; and calculating the sum or the average value of the image characteristic values of the pixels in each column in the pixel array as the image characteristic value of the column. The detection device can be used for comprehensively judging whether the outline of the wafer is abnormal or not by combining the pixel characteristics of the rows and the pixel characteristics of the columns of the pixel array of the side image. For example, the detection device determines that the wafer has an abnormality if the wafer is determined to have a defect based on the pixel features of the rows of the pixel array of the side image or if the wafer is determined to have a defect based on the pixel features of the columns of the pixel array of the side image. The abnormal wafer profile is detected through the characteristics, so that the condition that the wafer with the abnormal profile is judged as the wafer with the normal profile by mistake can be reduced, and the probability of missed judgment is reduced.

Alternatively, the detection device smoothes the image feature values of the rows and/or columns before determining whether the profile of the wafer is abnormal according to the statistical result. For example, noise may be present in the side image of the wafer, and the statistical row and/or column image feature values may be smoothed to reduce the effect of the noise on the statistical row and/or column image feature values.

It should be appreciated that the smoothing algorithm for the image feature values of the rows and/or columns may be selected as desired without departing from the teachings of the present application, which is not limited in this respect.

It should be understood that the detection device may also count the image feature values of the pixels based on other rules and adjust the manner of determining whether the profile of the wafer is abnormal based on the statistical rules, for example, count the rows and/or columns of the pixel array of the partial area of the side image and determine whether the profile is abnormal according to the statistical result, which is not limited in the present application.

In some embodiments of the present application, the detection apparatus may further feed back alarm information to the detector after determining that the profile of the wafer is abnormal or after determining that the wafer has a notch defect. For example, the detection device may feed back the alarm information to the detector by sending the alarm information, turning on an alarm ring, generating a detection result, and sending an email to the detector, which is not limited in this application.

The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.

Fig. 9 is a schematic block diagram of an inspection apparatus 2000 for wafers according to an exemplary embodiment of the present application.

As shown in fig. 9, the detection device 2000 may, for example, include: a determination module 2100, a statistics module 2200, and a detection module 2300. The determination module 2100 may be used to determine image feature values for pixels of a side image of a wafer. The statistic module 2200 may be configured to perform statistics on image feature values of pixels of the side image. The detection module 2300 may be configured to determine whether the profile of the wafer is abnormal according to the statistical result.

In some embodiments of the present application, referring to fig. 2-4, the side image of the wafer 20 may be a peripheral image of the wafer 20. For example, the side image obtained by photographing the wafer from the side surface rotating around the wafer 20 once can focus the photographing area to the edge of the wafer, so that the side image of the wafer can further highlight the shape of the edge of the wafer, which is beneficial for the detection device 2000 to detect the profile abnormality of the wafer.

In some embodiments of the present application, the side image of the wafer may also be a side image of a top bevel angle or a bottom bevel angle of the wafer. Here, the top oblique view may refer to a view inclined from a top view to a side, and the bottom oblique view may refer to a view inclined from a bottom view to a side. For example, if the viewing angle is 0 degrees, the viewing angle is substantially perpendicular to the top surface of the wafer, the top oblique viewing angle may be (0 °, 90 °), and the bottom oblique viewing angle may be (90 °, 180 °). By shooting the side image of the wafer at the top oblique viewing angle, the shot side image includes the image of the wafer dome, so that the difference between the image of the defect and the image of the normal region of the wafer can be highlighted, and the detection module 2300 is favorable for detecting the profile abnormality of the wafer based on the statistical result obtained by the statistics of the statistical module 2200.

In some embodiments of the present application, the image characteristic value of the pixel may be, for example, a color value (e.g., an RGB value or a gray value) of the pixel or a luminance value of the pixel. For example, as the profile of the wafer is abnormal due to the existence of the notch defect in the wafer, as can be seen from fig. 2 to 4, the color or brightness of the image area (e.g., the area B and the area C of fig. 4) corresponding to the notch of the wafer is different from the color or brightness of the other areas, the color of the image area corresponding to the notch is black, the color around the notch may be, for example, the color of the wafer body, and the brightness of the image area corresponding to the notch is lower than the brightness around the notch. The detecting module 2300 can detect whether there is a defect on the wafer based on the color value or the brightness value of each pixel in the side image counted by the counting module 2200.

In some embodiments of the present application, a notch is provided on the wafer for positioning, and the inspection apparatus 2000 further includes an image acquisition module (not shown) configured to: and acquiring an original side image, and cutting the original side image to remove an image area corresponding to the notch of the wafer for positioning in the original side image. In order to facilitate the wafer position calibration by the inspection apparatus 2000 and/or other apparatuses for wafers, a notch for positioning is usually formed at a fixed position of the wafer, so that the wafer is positioned by the inspection apparatus 2000 and/or other apparatuses for wafers. The image acquisition module cuts the original side face image to remove the image area corresponding to the notch for positioning, so that the influence of the notch for positioning on the abnormal outline detection of the wafer can be reduced.

Illustratively, the manner in which the image acquisition module acquires the raw side image includes: detecting the position of a notch for positioning of the wafer through a predefined notch detection algorithm for positioning; starting from the notch position of the wafer for positioning, images are shot around the wafer to obtain an original side image.

Illustratively, fig. 5 is a schematic side view of a wafer according to another embodiment of the present application. The left area (area D) and the right area (area E) of the original side image of the wafer contain images of the notch for positioning.

As an example, the image acquisition module may determine the lateral length of the notch for positioning in the original side image based on an approximate range of the x-direction dimension (i.e., lateral length) actual width of the notch for positioning given by the examiner and the actual length represented by each pixel in the image captured by the device capturing the original side image. Since the original side image is captured from the position of the notch for positioning, and the image areas corresponding to the notch for positioning are located in the left area (also referred to as the start capturing area) and the right area (also referred to as the end capturing area) of the original side image, the image acquisition module may respectively cut from the left area and the right area to image areas having a width at least equal to the lateral length of the determined notch for positioning.

As another example, the inspection apparatus may determine the x-direction dimension (i.e., the lateral length) of the notch for positioning in the original side image according to the approximate range of the actual width of the notch for positioning in the wafer circumferential direction given by the inspector and the actual length represented by each pixel in the image captured by the device capturing the original side image. The detection device can determine the size (namely the longitudinal length) of the notch for positioning in the y direction in the original side image according to the approximate range of the length of the notch for positioning on the wafer along the radial direction of the wafer, the shooting angle and the actual length represented by each pixel in the image shot by the equipment for shooting the original side image, which are given by the detector. The detection device may determine an image area corresponding to the notch for positioning in the original side image according to the determined transverse length and longitudinal length of the notch for positioning in the original side image, and cut off the partial image area.

It should be understood that the image acquisition module may also lock the image area of the notch for positioning in other ways without departing from the teachings of the present application, which is not limited by the present application.

In some embodiments of the present application, the image acquisition module is further configured to perform a grayscale process on the original side image; and obtaining a side image according to the original side image after the gray processing. The original side image of the wafer may be a trimmed image or an image that is not trimmed, which is not limited in this application.

As an example, the image obtaining module may perform gray processing on the original side image by a component method, a maximum value method, an average value method, a weighted average method, or the like. If the image acquisition module adopts a component method, the brightness of RGB three components of the pixel in the original side image can be respectively used as the gray value of the pixel to obtain 3 candidate images, and one candidate image is selected as the original side image after gray processing according to the requirement. If the image acquisition module adopts a maximum value method, the maximum value of RGB three-component brightness of the pixel in the original side image can be used as the gray value of the pixel, so that the original side image after gray processing is obtained. If the image acquisition module adopts an average value method, the average value of the RGB three-component brightness of the pixels in the original side image can be used as the gray value of the pixels, so that the original side image after gray processing is obtained. If the image acquisition module adopts a weighted average method, the three components can be weighted and averaged by different weights according to the importance or other indexes of each component in the RGB three components of the pixel, so that the original side image after the gray processing is obtained. For example, after the image acquisition module cuts out the area image of the notch for positioning of the original side image shown in fig. 5, the cut original side image is subjected to grayscale processing, and the obtained grayscale-processed original side image is shown in fig. 6. As can be seen from fig. 6, the area (area F) where the other gaps except the gap for positioning are located in the original side image after the gray processing is different from the image characteristics of the other areas, and the statistical module 2200 and the detection module 2300 are coupled to perform defect detection based on fig. 6.

It should be understood that the raw side image may also be grayscale processed in other ways without departing from the teachings of the present application, which is not limited by the present application.

Alternatively, the obtaining of the side image by the image obtaining module according to the original side image after the gray processing may include: and carrying out binarization processing on the original side image subjected to the gray processing to obtain a side image of the wafer. For example, the image acquisition module performs binarization processing on the original side image after the grayscale processing shown in fig. 6 to obtain a side image, where the side image is shown in fig. 7, and an area where the gap is located is an area G.

As an example, the process of the image acquisition module performing the binarization process may include, for example: acquiring a preset threshold (for example, a median 127 of 0-255), and for each pixel in the original side image after the gray processing, changing the gray value of the pixel to 0 (namely black) in response to the gray value of the pixel being less than or equal to the threshold; in response to the gray scale value of a pixel being greater than the threshold, the gray scale value of the pixel is changed to 255 (i.e., white).

As another example, the process of the image acquisition module performing the binarization process may include, for example: determining the gray level average value of each pixel in the pixel array; for each pixel in the original side image after the gray level processing, changing the gray level value of the pixel to 0 (namely black) in response to the fact that the gray level value of the pixel is smaller than or equal to the average gray level value; in response to the gray value of a pixel being greater than the gray average value, the gray value of the pixel is changed to 255 (i.e., white).

It should be understood that the image acquisition module may select other ways to perform binarization processing on the grayscale-processed image without departing from the teachings of the present application, and the present application does not limit this.

In some embodiments of the present application, the statistics module 2200 is configured to: and respectively calculating the sum or the average value of the image characteristic values of the pixels of each row and/or column of the pixel array of the side image to obtain the image characteristic value of each row and/or column of the pixel array.

Optionally, the detection module is configured to: and determining that the profile of the wafer has an abnormality in response to the statistical result indicating that there are abnormal values in the image characteristic values of the rows and/or columns.

Optionally, the detection module 2300 may be further configured to: and after the abnormal value is detected, determining whether the profile of the wafer has an abnormality or not by combining the distribution condition of the abnormal value. For example, for the trimmed original side image, since the image area of the notch for positioning has been trimmed in advance, the detection module 2300 determines that there is an abnormality in the outline of the wafer if an abnormal value is detected. For an original side image that is not cropped, the detection module 2300 may determine an abnormal value distribution area when an abnormal value is detected due to an image area including a notch for positioning in the side image. For example, the detection module 2300 determines that the profile of the wafer is normal in response to the number of the abnormal value distribution areas being less than or equal to N; and determining that the profile of the wafer is abnormal in response to the number of the abnormal value distribution areas being larger than N. The value of N may be set according to the capturing mode of the original side image, for example, if the same portion of the image in the initial capturing region and the same portion of the image in the end capturing region of the original side image are removed, N is equal to 1, if the same portion of the image in the initial capturing region and the same portion of the image in the end capturing region of the original side image are not removed, the value of N is determined according to the initial capturing position, for example, if the original side image is captured from a notch for positioning, N is equal to 2, and if the original side image is captured from a position other than the notch for positioning, N is equal to 1.

As an example, the statistical module 2200 obtains the image feature values (e.g., the gray values of the pixels after the binarization processing) of the pixels in the pixel array of the side image, and calculates, for each row of pixels in the pixel array, the sum or the average of the image feature values of the row of pixels as the image feature value of the row. If the wafer has a defect, the image characteristic value of the pixel corresponding to the defect in the pixel array is different from the image characteristic values of the pixels around the pixel, and through counting the characteristic values of the pixels in each row, if the image characteristic value of a certain row is different from the image characteristic value of the rows around the certain row, whether the pixels corresponding to the defect are included in the pixels in the row can be judged according to the difference between the image characteristic value of the row and the image characteristic value of the rows around the certain row. For example, after counting the image feature values of each row, if the detection module 2300 determines that the difference between the image features of the ith row and the (i + 1) th row is very large, for example, greater than a first threshold, it may determine that the boundary between the ith row and the (i + 1) th row is a wafer boundary, rather than a defect; if the image characteristic difference between the ith row and the (i + 1) th row is smaller than the first threshold value, the outline of the wafer can be judged to be abnormal.

It should be appreciated that the first threshold may be determined according to the way the original side image is processed by the image acquisition module in obtaining the side image from the original side image, the number of columns of the pixel array of the side image, and the like, without departing from the teachings of the present application. For example, if the image obtaining module performs the gray processing and the binarization processing on the original side image to obtain the side image, and the number of rows of the pixel array is a, the first threshold may be, for example, 255 a T, and T may be, for example, any value between (70%, 100%), e.g., 75%, 80%, 85%, 90%, 95%, and the like. The first threshold is not limited by the present application.

As another example, the statistical module 2200 obtains the image feature value (e.g., the gray value of the pixel after the binarization processing) of each pixel in the pixel array of the side image, and calculates, for each column of pixels in the pixel array, the sum or the average of the image feature values of the column of pixels as the image feature value of the column. Taking the notch defect as an example, if the wafer does not have a notch, the image feature values of each row in the pixel array of the side image are substantially the same. If the wafer has a notch, the notch of the wafer usually extends from the edge of the wafer to the inside of the wafer, so that the difference between the image feature values of other pixel points in the row of the individual pixel points in the side image of the wafer is larger. The image characteristic values of each column of pixels of the pixel array are counted to obtain the image characteristic values of the columns, and the image characteristic values of the columns are compared to determine the area where the gap is located, so that the situation that the area where the gap is located is identified by mistake due to the fact that the image characteristic values of the pixels of different columns in the same row are different due to noise and the like can be reduced. For example, the detection module 2300 sums up the image feature values of the pixels in each column of the pixel array of the side image, and the variation trend of the image feature values of each column is shown in fig. 8, where in fig. 8, the abscissa is the number (j) of columns of the pixel array and the ordinate is the image feature value (F) of the column. As can be seen from fig. 8, if an abnormal value exists at j — K, the detection module 2300 may determine that the wafer corresponding to the side image has a notch and the wafer profile is abnormal.

It should be appreciated that the detection module 2300 may be configured with different methods for determining whether an outlier exists without departing from the teachings of the present application, for example, the detection of whether an outlier exists in the image feature values of each column by an outlier detection algorithm, which is not limited by the present application.

Optionally, in the process of detecting the profile abnormality of the wafer based on the image feature values of the rows of the pixel array, the detection module 2300 is further configured to: and after the abnormal outline of the wafer is determined, determining the position of the abnormal outline of the wafer according to the row corresponding to the abnormal value. As described above, since the image feature values of each row in the pixel array of the side image are substantially the same, the detection module 2300 can set the position of the profile abnormality of the wafer according to the row corresponding to the detected abnormal value.

Alternatively. After determining the column corresponding to the abnormal value, the detection module 2300 determines the longitudinal length of the profile abnormal region according to the pixels with abnormal image characteristic values in the column corresponding to the abnormal value; determining the defect depth of the wafer according to the determined longitudinal length; and determining that the wafer has a notch defect in response to the defect depth being within a preset abnormal depth range.

For example, the detection module 2300 determines the jth of the side image ₁ Column to j ₂ Abnormal image characteristic value of the column, and determining j-th image of the side image ₁ Column to j ₂ The pixels with abnormal image characteristic values in the pixels of the row are used for determining the longitudinal length (namely the length in the y direction) of the abnormal road condition area. For example, if the pixels with abnormal image feature values are continuously distributed in the side image, the longitudinal length is equal to the difference between the line numbers of the first pixel with abnormal image feature value and the last pixel with abnormal image feature value from the upper side of the side image to the lower side of the side image. For example, if the pixel with abnormal image feature value is ith ₁ Go to the ith ₂ If the image characteristic value of the pixel of the line is abnormal, the longitudinal length is determined to be i ₂ -i ₁ . And if the pixels with abnormal image characteristic values are distributed in the side images in a segmented manner, integrating a plurality of segments, determining the segments corresponding to the defects in each integrated segment according to a preset search rule after integration is finished, and taking the number of the pixels of the segments corresponding to the defects as the longitudinal length. It is composed ofThe integration method may be, for example: for each segment, if the number of pixels between adjacent segments is less than a predetermined threshold number of pixels (i) _pre ) Then the neighboring segments are integrated into one segment. The preset search rule is determined according to parameters of the photographing device of the side image, for example, the search rule indicates: the ith of the image _max Row and ith _min The segments between the rows serve as the segments corresponding to the defects. Wherein i _max And i _min According to the parameters of the shooting equipment. For example, if j ₁ The pixel with abnormal image characteristic value of the column is the ith pixel ₁ Line of pixels to ith ₂ Pixels of a row, and an ith ₃ Line of pixels to ith ₄ Abnormal image feature value of pixels of a line in response to i ₃ -i ₂ ＜i _pre Determining a longitudinal length of i ₄ -i ₁ In response to i ₃ -i ₂ ≥i _pre ，i ₂ And i ₁ At [ i ] _min ，i _max ]Has a longitudinal length equal to i ₂ -i ₁ . After determining the longitudinal length, the detection module 2300 takes the product of the longitudinal length and the actual length represented by each pixel in the side image as the defect depth of the wafer in the row. The detection module 2300 acquires the maximum value of the defect depth of the wafer in each row, and determines whether the acquired maximum value is in the abnormal depth range, if so, it is determined that the wafer has a notch defect, and if not, it is determined that the wafer has other defects. The distinguishing method of other defects can be defined according to the morphological characteristics of other defects, which is not listed here.

As another example, the detection module 2300 obtains the image feature values (e.g., the gray values of the pixels after binarization processing) of the pixels in the pixel array of the side image, and calculates the sum or the average of the image feature values of the pixels in each row of the pixel array as the image feature value of the row; and calculating the sum or the average value of the image characteristic values of the pixels in each column in the pixel array as the image characteristic value of the column. The detection module 2300 can comprehensively determine whether the profile of the wafer is abnormal by combining the pixel characteristics of the rows and the pixel characteristics of the columns of the pixel array of the side image. For example, the detecting module 2300 determines that the wafer has a defect based on the pixel characteristics of the rows of the pixel array of the side image, or determines that the wafer has a defect based on the pixel characteristics of the columns of the pixel array of the side image, and determines that the wafer profile has an abnormality. The abnormal wafer profile is detected through the characteristics, so that the condition that the wafer with the abnormal profile is judged as the wafer with the normal profile by mistake can be reduced, and the probability of missed judgment is reduced.

Alternatively, the detection module 2300 is further configured to: and performing smoothing processing on the image characteristic values of the rows and/or the columns before determining whether the outline of the wafer is abnormal according to the statistical result. For example, noise points may be present in the side image of the wafer, and the statistical row and/or column image feature values may be smoothed to reduce the effect of the noise points on the statistical row and/or column image feature values.

It should be appreciated that the smoothing algorithm for the image feature values of the rows and/or columns may be selected as desired without departing from the teachings of the present application, which is not limited in this application.

It should be understood that, without departing from the teachings of the present application, the statistic module 2200 may also perform statistics on the image feature values of the pixels based on other rules, and adjust the manner in which the detecting module 2300 determines whether the profile of the wafer is abnormal based on the statistical rules, for example, the statistic module 2200 performs statistics on rows and/or columns of the pixel array of the partial area of the side image, and the detecting module 2300 determines whether the profile is abnormal according to the statistical result, which is not limited in the present application.

In some embodiments of the present disclosure, the inspection apparatus 2000 may further include an alarm module (not shown) for feeding back an alarm message to the inspector after determining that the profile of the wafer is abnormal or after determining that the wafer has a notch defect. For example, the alarm module may feed back the alarm information to the inspector by sending the alarm information, turning on an alarm ring, generating a detection result, sending an email to the inspector, and the like, which is not limited in the present application.

It will be appreciated that this embodiment is an apparatus embodiment corresponding to the method embodiment described above, and that this embodiment can be implemented in conjunction with the method embodiment described above. The related technical details mentioned in the above method embodiments are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related art details mentioned in the present embodiment can also be applied to the above-described method embodiment.

It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.

The embodiment of the application also provides a detection device and a readable storage medium.

Fig. 10 is a block diagram of a detection apparatus 3000 according to an embodiment of the present application. The apparatus is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.

As shown in fig. 10, the detection device 3000 includes: one or more processors 3100, memory 3200, and interfaces (not shown) for connecting the various components, including a high-speed interface and a low-speed interface. Memory 3200 may be used to store computer instructions. The processor 3100 may be configured to communicate with the memory to execute computer instructions to implement the defect detection methods as mentioned in the embodiments above. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. Processor 3100 can process instructions for execution within detection device 3000, including instructions stored in or on memory 3200 to display graphical information of a GUI on an external input/output device (such as a display device coupled to an interface). In other embodiments, multiple processors 3100 and/or multiple buses may be used, along with multiple memories 3200 and multiple memories 3200, if desired. Also, multiple detection devices 3000 may be connected, with each device providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 10 illustrates an example of a processor 3100.

Memory 3200 is a readable storage medium provided herein, e.g., a non-transitory computer readable storage medium. The memory 3200 has stored therein instructions executable by the at least one processor 3100 to cause the at least one processor 3100 to perform the defect detection methods provided herein. The readable storage medium of the present application stores computer instructions for causing a computer to execute the defect detection method for a wafer provided by the above-described embodiments of the present application.

Memory 3200, as a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor 3100 implements the defect detection method for a wafer in the above method embodiment by executing non-transitory software programs, instructions, and modules stored in the memory 3200 to execute various functional applications of the server and data processing.

The memory 3200 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of a detection device for controlling quality, and the like. Additionally, memory 3200 may comprise high speed random access memory and may further comprise non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 3200 may include memory remotely located from processor 3100, which may be connected to detection apparatus 3000 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The detection device 3000 may further include: an input device 3300 and an output device 3400. The processor 3100, the memory 3200, the input device 3300, and the output device 3400 may be connected by a bus or other means, and the bus connection is exemplified in fig. 10.

The input device 3300 may receive input numeric or character information and generate key signal inputs related to user settings and function control of a detection device for controlling quality, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointer stick, one or more mouse buttons, a track ball, a joystick, or other input device. The output device 3400 may include a display apparatus, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.

Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.

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

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, 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: local area networks, wide area networks, and the internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a server of a distributed system or a server incorporating a blockchain. The server can also be a cloud server, or an intelligent cloud computing server or an intelligent cloud host with artificial intelligence technology. The server may be a server of a distributed system or a server incorporating a blockchain. The server can also be a cloud server, or an intelligent cloud computing server or an intelligent cloud host with artificial intelligence technology.

The above description is only an embodiment of the present application and an illustration of the technical principles applied. It will be appreciated by a person skilled in the art that the scope of protection covered by the present application is not limited to the embodiments with a specific combination of the features described above, but also covers other embodiments with any combination of the features described above or their equivalents without departing from the technical idea. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims

1. An inspection method for a wafer, comprising:

determining an image characteristic value of a pixel of the side image of the wafer;

counting image characteristic values of pixels of the side images; and

and determining whether the outline of the wafer is abnormal or not according to the statistical result.

2. The method of claim 1, wherein the counting image feature values of the side images comprises:

and respectively calculating the sum or the average value of the image characteristic values of the pixels of each row and/or column of the pixel array of the side image to obtain the image characteristic value of each row and/or column of the pixel array.

3. The method of claim 2, wherein the determining whether the profile of the wafer is abnormal according to the statistical result comprises:

and determining that the profile of the wafer has an abnormality in response to the statistical result indicating that an abnormal value exists in the image characteristic values of the rows and/or columns.

4. The method of claim 3, wherein upon determining that the profile of the wafer is anomalous in response to the statistics indicating that an outlier is present in the image feature values of the column, the method further comprises:

and determining the position of the abnormal outline of the wafer according to the column corresponding to the abnormal value.

5. The method of claim 4, wherein the method further comprises:

determining the longitudinal length of the profile abnormal region according to the pixels with abnormal image characteristic values in the column corresponding to the abnormal values;

determining the defect depth of the wafer according to the determined longitudinal length; and

and determining that the wafer has a notch defect in response to the defect depth being in a preset abnormal depth range.

6. The method of claim 2, wherein prior to said determining whether the profile of the wafer is abnormal from the statistical result, the method further comprises:

and carrying out smoothing processing on the image characteristic values of the rows and/or the columns.

7. The method of any of claims 1 to 6, wherein prior to the determining image feature values for pixels of the side image of the wafer, the method further comprises:

acquiring an original side image of the wafer;

carrying out gray level processing on the original side face image; and

and obtaining the side image according to the original side image after the gray processing.

8. The method of claim 7, wherein said deriving the side image from the grayscale processed raw side image comprises:

and carrying out binarization processing on the original side image subjected to the gray processing to obtain the side image.

9. The method of claim 7, wherein a notch is provided on the wafer for positioning, the method further comprising:

and removing an image area corresponding to the notch for positioning in the original side image by cutting the original side image.

10. The method of any of claims 1 to 5, wherein the image feature values comprise color values or luminance values.

11. An inspection apparatus for a wafer, comprising:

the determining module is used for determining the image characteristic value of the pixel of the side image of the wafer;

the statistical module is used for carrying out statistics on the image characteristic values of the pixels of the side images; and

and the detection module is used for determining whether the outline of the wafer is abnormal or not according to the statistical result.

12. The apparatus of claim 11, wherein the statistics module is configured to:

13. The apparatus of claim 12, wherein the detection module is configured to:

14. The apparatus of claim 13, wherein the detection module is further configured to:

and after determining that the profile of the wafer is abnormal in response to the statistical result indicating that abnormal values exist in the image characteristic values of the rows, determining the position of the profile abnormality of the wafer according to the rows corresponding to the abnormal values.

15. The apparatus of claim 14, wherein the detection module is further configured to:

16. The apparatus of claim 15, wherein the detection apparatus further comprises:

and the alarm module is used for responding to the abnormal contour of the wafer or the gap defect of the wafer and feeding back alarm information.

17. A detection device, comprising:

a memory for storing computer instructions; and

a processor in communication with the memory to execute the computer instructions to implement the detection method of any one of claims 1 to 10.

18. A readable storage medium, having stored therein computer instructions, which when executed by a processor, implement the detection method of any one of claims 1 to 10.