CN116912242B - Method for positioning defects of nanoimprint wafer - Google Patents
Method for positioning defects of nanoimprint wafer Download PDFInfo
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- 230000007547 defect Effects 0.000 title claims abstract description 56
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005507 spraying Methods 0.000 claims abstract description 149
- 238000012216 screening Methods 0.000 claims abstract description 10
- 235000012431 wafers Nutrition 0.000 claims description 167
- 230000002159 abnormal effect Effects 0.000 claims description 65
- 239000003292 glue Substances 0.000 claims description 31
- 238000005520 cutting process Methods 0.000 claims description 12
- 239000007921 spray Substances 0.000 claims description 11
- 230000009191 jumping Effects 0.000 claims description 3
- 239000013078 crystal Substances 0.000 claims 1
- 238000012545 processing Methods 0.000 abstract description 4
- 230000009286 beneficial effect Effects 0.000 description 7
- 238000013528 artificial neural network Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000001127 nanoimprint lithography Methods 0.000 description 2
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30148—Semiconductor; IC; Wafer
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses a method for positioning defects of a nanoimprint wafer, which belongs to the technical field of image processing, wherein a plurality of standard images are taken, a spraying region error threshold and a wafer region error threshold among the standard images are calculated, then a real-time image is compared with any standard image to obtain a real-time spraying region difference value and a real-time wafer region difference value, a spraying region of the real-time image with defects and a wafer region of the real-time image with defects are firstly screened out through the spraying region error threshold and the wafer region error threshold, namely the spraying region error threshold and the wafer region error threshold are used for primarily screening out the real-time image with defects, and then the spraying region, the wafer region and the wafer region of the standard image are cut to realize regional comparison, so that the positions of the defects are found, and the defects are detected and positioned in a wider range.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method for positioning defects of a nanoimprint wafer.
Background
Nanoimprint lithography uses nanoimprint techniques to spray a droplet of nanoimprint resist onto a wafer at a location where an electronic circuit pattern is to be imprinted. The position of the nano-imprinting glue is used for determining the shape of an electronic loop pattern and the performance of a chip. The defect cannot be positioned by human eyes in the nanoimprint process, so that the defect in the nanoimprint lithography process is often detected by means of machine vision. The existing defect detection method for the image usually adopts a neural network, but the neural network needs a large number of samples to train, and has defects of a certain type in the training process, so that the neural network can only identify the defects of a corresponding type, and the defect type identification is limited.
Disclosure of Invention
Aiming at the defects in the prior art, the method for positioning the defects of the nanoimprint wafer solves the problem that the defect type identification is limited in the existing image defect identification technology based on the neural network.
In order to achieve the aim of the invention, the invention adopts the following technical scheme: a method for positioning defects of a nanoimprint wafer comprises the following steps:
s1, collecting images of different wafers sprayed with nano-imprinting glue under normal conditions, and obtaining a plurality of standard images;
s2, calculating a spraying area error threshold value and a wafer area error threshold value according to a plurality of standard images;
s3, comparing the real-time image with the standard image to obtain a real-time spraying area difference value and a real-time wafer area difference value, wherein the real-time image is an image of a wafer sprayed with nano imprinting glue in the nano imprinting process;
s4, when the difference value of the real-time spraying area is larger than the error threshold value of the spraying area, respectively cutting the spraying area of the real-time image and the spraying area of the standard image to obtain a plurality of real-time spraying subareas and a plurality of standard spraying subareas;
s5, comparing the real-time spraying subarea of the same area with a standard spraying subarea, screening out an abnormal real-time spraying subarea, and finding out a defect position from the abnormal real-time spraying subarea;
s6, when the difference value of the real-time wafer area is larger than the error threshold value of the wafer area, respectively cutting the wafer area of the real-time image and the wafer area of the standard image to obtain a plurality of real-time wafer sub-areas and a plurality of standard wafer sub-areas;
s7, comparing the real-time wafer subarea and the standard wafer subarea in the same area, screening out an abnormal real-time wafer subarea, and finding out a defect position from the abnormal real-time wafer subarea.
The beneficial effects of the invention are as follows: according to the method, a plurality of standard images are taken, a spraying area error threshold value and a wafer area error threshold value among the standard images are calculated, then the real-time images are compared with any standard image to obtain a real-time spraying area difference value and a real-time wafer area difference value, a spraying area of the real-time image with defects and a wafer area of the real-time image with defects are firstly screened out through the spraying area error threshold value and the wafer area error threshold value, namely the spraying area error threshold value and the wafer area error threshold value are used for initially screening out the real-time image with defects, and then the spraying area, the wafer area and the spraying area and the wafer area of the standard images of the real-time images are cut to realize partition comparison, so that defect positions are found, and wider-range defect detection and positioning are realized.
Further, the step S2 includes the following sub-steps:
s21, taking pixel values of pixel points of the nano-imprinting glue on the standard image as nano-imprinting glue color values;
s22, calculating the similarity between pixel values of other pixel points on the standard image and the color value of the nano-imprinting glue;
s23, classifying the pixel points with the similarity larger than a first similarity threshold value on the standard image as a spraying area, and classifying the pixel points with the similarity smaller than or equal to the first similarity threshold value as a wafer area;
s24, taking a spraying area of a standard image as a reference spraying area, and taking a wafer area of the standard image as a reference wafer area;
s25, subtracting pixel values of the same positions of the spraying areas of other standard images and the reference spraying area to obtain a spraying area error threshold;
s26, subtracting the pixel values of the same positions of the wafer area of each other standard image and the reference wafer area to obtain a wafer area error threshold.
The beneficial effects of the above further scheme are: according to the method, pixel values of pixel points of the nano imprinting glue on the standard image are taken as the color values of the nano imprinting glue, so that the similarity between the pixel values of other pixel points and the color values of the nano imprinting glue is calculated, the standard image is partitioned according to the similarity, a spraying area and a wafer area are obtained, one of the spraying area and the wafer area is taken as a reference, error conditions between other spraying areas and the reference spraying area are calculated, and the error threshold of the spraying area and the same processing mode of the wafer area are obtained.
Further, the formula of the error threshold value of the spraying area obtained in S25 is as follows:
，/>wherein s is th F is the spray zone error threshold k,j For the pixel value at the j-th position point on the sprayed area of the k-th standard image, f o,j For referencing the pixel value of the jth position point on the spraying area, M is a positive integer, I is an absolute value operation, max is a maximum value, M 1 The number of pixel points on the spraying area of the standard image is M 2 For the number of pixel points on the reference spraying area, j is the number of the position points on the first type spraying area, K is the number of other standard images, and K is the number of the standard images.
Further, the formula for obtaining the wafer area error threshold in S26 is:
，/>wherein w is th For wafer area error threshold, p k,i Pixel value p at the ith position point on the wafer area of the kth standard image o , i For reference to the pixel value at the i-th position point on the wafer area, N is a positive integer, N 1 The number of pixel points on the wafer area of the standard image is N 2 For the number of pixel points on the reference wafer area, max is the maximum value, i is the absolute value operation, i is the number of the position points on the first type wafer area, K is the number of other standard images, and K is the number of the standard images.
The beneficial effects of the above further scheme are: when the error threshold value of the spraying area is calculated, the spraying areas of other standard images are subtracted from the reference spraying area at the same position point, and the average pixel value difference value of the spraying area of each standard image and the reference spraying area is determined according to the pixel value difference value at the same position point, namely the error threshold value of the spraying area, so that the error range of each image under normal conditions is estimated, and the processing mode of the wafer area is the same.
Further, the step S3 includes the following sub-steps:
s31, taking pixel values of pixel points of the nano-imprinting glue on the standard image as nano-imprinting glue color values;
s32, calculating the similarity between the pixel value of each pixel point on the real-time image and the color value of the nano imprinting glue;
s33, classifying the pixel points with the similarity larger than a second similarity threshold value on the real-time image as a spraying area, and classifying the pixel points with the similarity smaller than or equal to the second similarity threshold value as a wafer area;
s34, subtracting pixel values at the same positions of the spraying area of the real-time image and the spraying area of the standard image to obtain a real-time spraying area difference value;
and S35, subtracting the pixel values of the same positions of the wafer area on the real-time image and the wafer area of the standard image to obtain a real-time wafer area difference value.
The beneficial effects of the above further scheme are: according to the method, the real-time image is partitioned according to the color value of the nano imprinting glue on the standard image, the spraying area and the wafer area are obtained, and then the spraying area and the wafer area of the real-time image are compared with the spraying area and the wafer area of any standard image in position, so that the real-time spraying area difference value and the real-time wafer area difference value are determined.
Further, the formula for obtaining the real-time spraying area difference in S34 is as follows:
，/>wherein s is t Is sprayed in real timeDifference of coating area, f m The pixel value f of the mth position point on the spraying area of the real-time image o,m The pixel value of the m-th position point on the spraying area of the standard image is maximum, and max is the maximum value,/>E is the number of pixel points on the spraying area of the real-time image, M 1 The number of pixel points on the spraying area of the standard image is calculated, the absolute value of the pixel points is calculated, and the m is the number of the position points on the spraying area of the second type.
Further, the formula for obtaining the real-time wafer area difference in S35 is as follows:
，/>wherein w is t For real-time wafer area difference, p n Pixel value, p, for the nth location point on the wafer area of the real-time image o,n The pixel value of the nth position point on the wafer area of the standard image is the maximum value of max, < +.>Is a positive integer, Y is the number of pixel points on the wafer area of the real-time image, N 1 The number of pixel points on the wafer area of the standard image is calculated by absolute value, and n is the number of position points on the wafer area of the second type.
Further, the processes of the methods for finding the defect position in S5 and S7 are the same, the real-time spray sub-area and the real-time wafer sub-area are both named as real-time sub-areas, the standard spray sub-area and the standard wafer sub-area are both named as standard sub-areas, and the method for finding the defect position in S5 or S7 specifically includes:
a1, calculating an abnormal value of a real-time subarea according to a pixel point quantity difference value and a position coordinate difference value of the real-time subarea and a standard subarea in the same area;
a2, when the abnormal value is larger than an abnormal threshold value, marking the real-time subarea as an abnormal real-time subarea, wherein in S5, the abnormal real-time subarea is an abnormal real-time spraying subarea, and in S7, the abnormal real-time subarea is an abnormal real-time wafer subarea;
a3, finding the defect position from the abnormal real-time subarea.
The beneficial effects of the above further scheme are: the method comprises the steps of cutting a spraying area and a wafer area of a real-time image with defects to obtain real-time subareas, calculating an abnormal value of one real-time subarea according to the pixel point quantity difference value and the position coordinate difference value of the same area, evaluating the abnormal degree of the real-time subarea, and finding out the abnormal real-time subarea.
Further, the formula for calculating the abnormal value of the real-time subarea in the A1 is as follows:
wherein ab is an outlier of the real-time subregion, n tu N is the difference of the pixel number tu The number of pixels of the standard subarea, x 1,c Is the abscissa, y, of the c-th pixel point on the real-time subarea 1,c The ordinate of the c-th pixel point on the real-time subarea is the serial numbers of the pixels of the real-time subarea and the standard subarea, and x 2,c Is the abscissa, y of the c-th pixel point on the standard subarea 2,c Is the ordinate of the C pixel point on the standard subarea, C 1 C is the number of pixel points on the real-time subarea 2 The number of pixel points on the standard subarea is the absolute value operation.
The beneficial effects of the above further scheme are: the abnormal degree of the real-time subarea is represented to the greatest extent through the pixel point quantity difference value and the position coordinate difference value.
Further, the A3 includes the following sub-steps:
a31, setting an expansion window, wherein the size of the expansion window is as followsR is the number of traversals, and the initial value of r is 0;
a32, respectively placing the expansion window in the central areas of the abnormal real-time subarea and the standard subarea, and calculating the difference of the number of pixels between the abnormal real-time subarea and the standard subarea under the current expansion window;
a33, adding 1 to r, jumping to A32 until the expansion window is larger than the abnormal real-time subarea or the standard subarea, and ending the traversal;
a34, finding the corresponding traversal times h when the difference of the number of pixel points is larger than the difference threshold value, and newly increasing the range of the position of the defect on the abnormal real-time subarea on the expansion window corresponding to the h traversal timeH is an integer greater than 1.
The beneficial effects of the above further scheme are: according to the invention, the size of the set expansion window is continuously changed according to the different times of traversal, the difference between the areas where the expansion window is located on the abnormal real-time subarea and the standard subarea is represented by traversing the difference between the number of pixels between the abnormal real-time subarea and the standard subarea under the expansion window each time, as the image is partitioned into the spraying area and the wafer area, the pixel points with similar pixel values are arranged in the spraying area, the defect position can be found through the change of the pixel points on the spraying area, the wafer area is the same, the change threshold is set, and the found difference is the required defect position.
According to the invention, the real-time image with defects is screened out firstly through the spraying area error threshold value and the wafer area error threshold value, the data volume processed in the subsequent process is reduced, the abnormal real-time subarea is screened out again through the abnormal threshold value, and the data volume processed in the subsequent process is reduced again.
Drawings
FIG. 1 is a flow chart of a method for locating defects on a nanoimprint wafer.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
As shown in fig. 1, a method for positioning defects of a nanoimprint wafer includes the following steps:
s1, collecting standard images: acquiring images of different wafers sprayed with nano imprinting glue under normal conditions to obtain a plurality of standard images;
s2, calculating an error threshold value: according to the standard images, calculating a spraying area error threshold value and a wafer area error threshold value respectively;
s3, comparing the real-time image with the standard image: comparing the real-time image with the standard image to obtain a real-time spraying area difference value and a real-time wafer area difference value, wherein the real-time image is an image of a wafer sprayed with nano imprinting glue in the nano imprinting process;
s4, cutting the spraying area: when the difference value of the real-time spraying area is larger than the error threshold value of the spraying area, respectively cutting the spraying area of the real-time image and the spraying area of the standard image to obtain a plurality of real-time spraying subareas and a plurality of standard spraying subareas;
s5, screening abnormal real-time spraying subareas: comparing the real-time spraying subarea in the same area with a standard spraying subarea, screening out an abnormal real-time spraying subarea, and finding out a defect position from the abnormal real-time spraying subarea;
s6, cutting the wafer area: when the difference value of the real-time wafer area is larger than the error threshold value of the wafer area, respectively cutting the wafer area of the real-time image and the wafer area of the standard image to obtain a plurality of real-time wafer subareas and a plurality of standard wafer subareas;
s7, screening out abnormal real-time wafer sub-areas: comparing the real-time wafer subarea and the standard wafer subarea in the same area, screening out abnormal real-time wafer subareas, and finding out defect positions from the abnormal real-time wafer subareas.
In the invention, the cameras for shooting the standard image and the real-time image are the same camera, the shooting parameters are the same, and the position angles are the same.
In the invention, the area sprayed with the nano-imprinting glue belongs to the same area, a plurality of standard images and real-time images belong to images of different wafers sprayed with the nano-imprinting glue on a production line, the standard images are sample images without defects, and the real-time images are images collected on the production line in real time.
The step S2 comprises the following sub-steps:
s21, taking pixel values of pixel points of the nano-imprinting glue on the standard image as nano-imprinting glue color values;
s22, calculating the similarity between pixel values of other pixel points on the standard image and the color value of the nano-imprinting glue;
s23, classifying the pixel points with the similarity larger than a first similarity threshold value on the standard image as a spraying area, and classifying the pixel points with the similarity smaller than or equal to the first similarity threshold value as a wafer area;
s24, taking a spraying area of a standard image as a reference spraying area, and taking a wafer area of the standard image as a reference wafer area;
s25, subtracting pixel values of the same positions of the spraying areas of other standard images and the reference spraying area to obtain a spraying area error threshold;
s26, subtracting the pixel values of the same positions of the wafer area of each other standard image and the reference wafer area to obtain a wafer area error threshold.
The formula of the error threshold value of the spraying area obtained in the step S25 is as follows:
，/>wherein s is th F is the spray zone error threshold k,j For the pixel value at the j-th position point on the sprayed area of the k-th standard image, f o,j For referencing the pixel value of the jth position point on the spraying area, M is a positive integer, I is an absolute value operation, max is a maximum value, M 1 The number of pixel points on the spraying area of the standard image is M 2 The number of pixel points on the reference spraying area; on the same position point, if a pixel value exists in a spraying area of the standard image, setting the pixel value of a reference spraying area at which the pixel value does not exist as 0; and on the same position point, if the reference spraying area has a pixel value, setting the pixel value of the spraying area of the standard image at the position without the pixel value as 0, wherein j is the number of the position point on the first type of spraying area, K is the number of other standard images, and K is the number of the standard image.
Because the pixel point distribution of the spraying area of the standard image is different from that of the reference spraying area on the same position point, the pixel value of the position where the pixel point does not exist is set to be 0, so that the difference between the two areas is represented to the greatest extent.
The formula for obtaining the wafer area error threshold in S26 is as follows:
，/>wherein w is th For wafer area error threshold, p k,i Pixel value p at the ith position point on the wafer area of the kth standard image o , i For reference to the pixel value at the i-th position point on the wafer area, N is a positive integer, N 1 The number of pixel points on the wafer area of the standard image is N 2 For the number of pixel points on the reference wafer area, max is the maximum value, and I is the absolute value operation; on the same position point, if the pixel value exists in the wafer area of the standard image, setting the pixel value of the reference wafer area at the position without the pixel value to be 0; and on the same position point, if the pixel value exists in the reference wafer area, setting the pixel value of the position, without the pixel value, of the wafer area of the standard image to be 0, wherein i is the number of the position point on the first type wafer area, K is the number of other standard images, and K is the number of the standard image.
The step S3 comprises the following substeps:
s31, taking pixel values of pixel points of the nano-imprinting glue on the standard image as nano-imprinting glue color values;
s32, calculating the similarity between the pixel value of each pixel point on the real-time image and the color value of the nano imprinting glue;
s33, classifying the pixel points with the similarity larger than a second similarity threshold value on the real-time image as a spraying area, and classifying the pixel points with the similarity smaller than or equal to the second similarity threshold value as a wafer area;
s34, subtracting pixel values at the same positions of the spraying area of the real-time image and the spraying area of the standard image to obtain a real-time spraying area difference value;
and S35, subtracting the pixel values of the same positions of the wafer area on the real-time image and the wafer area of the standard image to obtain a real-time wafer area difference value.
The formula for obtaining the real-time spraying area difference value in the step S34 is as follows:
，/>wherein s is t For real-time spray area difference, f m The pixel value f of the mth position point on the spraying area of the real-time image o,m The pixel value of the m-th position point on the spraying area of the standard image is maximum, and max is the maximum value,/>E is the number of pixel points on the spraying area of the real-time image, M 1 The number of pixel points on a spraying area of the standard image is calculated, and the absolute value is calculated; on the same position point, if the pixel value exists in the spraying area of the real-time image, setting the pixel value of the spraying area of the standard image at the position without the pixel value to be 0; and on the same position point, if the pixel value exists in the spraying area of the standard image, setting the pixel value of the spraying area of the real-time image at the position without the pixel value to be 0, wherein m is the number of the position point on the second type of spraying area.
The formula for obtaining the real-time wafer area difference in S35 is as follows:
，/>wherein w is t For real-time wafer area difference, p n Pixel value, p, for the nth location point on the wafer area of the real-time image o,n The pixel value of the nth position point on the wafer area of the standard image is the maximum value of max, < +.>Is a positive integer, Y is the number of pixel points on the wafer area of the real-time image, N 1 The number of pixel points on a wafer area of a standard image is calculated, and the absolute value is calculated; on the same position point, if the pixel value exists in the wafer area of the real-time image, setting the pixel value of the position without the pixel value in the wafer area of the standard image to be 0; and on the same position point, if the pixel value exists in the wafer area of the standard image, setting the pixel value of the non-pixel value position of the wafer area of the real-time image to be 0, wherein n is the number of the position point on the second type wafer area.
When the cutting is carried out in the S4 and the S6, the spraying area of the real-time image and the spraying area of the standard image adopt the same cutting mode, and the wafer area of the real-time image and the wafer area of the standard image adopt the same cutting mode, so that the correspondence of each area is ensured.
In this embodiment, the region may be divided into a plurality of sub-regions having the same area in an equal division manner.
The process of the method for finding the defect position in S5 and S7 is the same, the real-time spraying subarea and the real-time wafer subarea are both named as real-time subarea, the standard spraying subarea and the standard wafer subarea are both named as standard subarea, and the method for finding the defect position in S5 or S7 specifically comprises the following steps:
a1, calculating an abnormal value of a real-time subarea according to a pixel point quantity difference value and a position coordinate difference value of the real-time subarea and a standard subarea in the same area;
a2, when the abnormal value is larger than an abnormal threshold value, marking the real-time subarea as an abnormal real-time subarea, wherein in S5, the abnormal real-time subarea is an abnormal real-time spraying subarea, and in S7, the abnormal real-time subarea is an abnormal real-time wafer subarea;
a3, finding the defect position from the abnormal real-time subarea.
The formula for calculating the abnormal value of the real-time subarea in the A1 is as follows:
wherein ab is an outlier of the real-time subregion, n tu N is the difference of the pixel number tu The number of pixels of the standard subarea, x 1,c Is the abscissa, y, of the c-th pixel point on the real-time subarea 1,c The ordinate of the c-th pixel point on the real-time subarea is the serial numbers of the pixels of the real-time subarea and the standard subarea, and x 2,c Is the abscissa, y of the c-th pixel point on the standard subarea 2,c Is the ordinate of the C pixel point on the standard subarea, C 1 C is the number of pixel points on the real-time subarea 2 The number of pixel points on the standard subarea is the absolute value operation.
The A3 comprises the following substeps:
a31, setting an expansion window, wherein the size of the expansion window is as followsR is the number of traversals, and the initial value of r is 0;
a32, respectively placing the expansion window in the central areas of the abnormal real-time subarea and the standard subarea, and calculating the difference of the number of pixels between the abnormal real-time subarea and the standard subarea under the current expansion window;
a33, adding 1 to r, jumping to A32 until the expansion window is larger than the abnormal real-time subarea or the standard subarea, and ending the traversal;
a34, finding the corresponding traversal times h when the difference of the number of pixel points is larger than the difference threshold value, and newly increasing the range of the position of the defect on the abnormal real-time subarea on the expansion window corresponding to the h traversal timeH is an integer greater than 1.
More specifically, when the difference between the number of pixels is smaller, the non-abnormal range can be marked first, and when the difference between the number of pixels is larger than the difference threshold, the newly increased range of the expansion window isThe abnormal region is the place.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The method for positioning the defects of the nanoimprint wafer is characterized by comprising the following steps of:
s1, collecting images of different wafers sprayed with nano-imprinting glue under normal conditions, and obtaining a plurality of standard images;
s2, calculating a spraying area error threshold value and a wafer area error threshold value according to a plurality of standard images;
s3, comparing the real-time image with the standard image to obtain a real-time spraying area difference value and a real-time wafer area difference value, wherein the real-time image is an image of a wafer sprayed with nano imprinting glue in the nano imprinting process;
s4, when the difference value of the real-time spraying area is larger than the error threshold value of the spraying area, respectively cutting the spraying area of the real-time image and the spraying area of the standard image to obtain a plurality of real-time spraying subareas and a plurality of standard spraying subareas;
s5, comparing the real-time spraying subarea of the same area with a standard spraying subarea, screening out an abnormal real-time spraying subarea, and finding out a defect position from the abnormal real-time spraying subarea;
s6, when the difference value of the real-time wafer area is larger than the error threshold value of the wafer area, respectively cutting the wafer area of the real-time image and the wafer area of the standard image to obtain a plurality of real-time wafer sub-areas and a plurality of standard wafer sub-areas;
s7, comparing the real-time wafer subarea and the standard wafer subarea in the same area, screening out an abnormal real-time wafer subarea, and finding out a defect position from the abnormal real-time wafer subarea;
the step S2 comprises the following sub-steps:
s21, taking pixel values of pixel points of the nano-imprinting glue on the standard image as nano-imprinting glue color values;
s22, calculating the similarity between pixel values of other pixel points on the standard image and the color value of the nano-imprinting glue;
s23, classifying the pixel points with the similarity larger than a first similarity threshold value on the standard image as a spraying area, and classifying the pixel points with the similarity smaller than or equal to the first similarity threshold value as a wafer area;
s24, taking a spraying area of a standard image as a reference spraying area, and taking a wafer area of the standard image as a reference wafer area;
s25, subtracting pixel values of the same positions of the spraying areas of other standard images and the reference spraying area to obtain a spraying area error threshold;
s26, subtracting pixel values of the same positions of the wafer area of each other standard image and the reference wafer area to obtain a wafer area error threshold;
the formula of the error threshold value of the spraying area obtained in the step S25 is as follows:
，
，
wherein s is th F is the spray zone error threshold k,j For the pixel value at the j-th position point on the sprayed area of the k-th standard image, f o,j For referencing the pixel value of the jth position point on the spraying area, M is a positive integer, I is an absolute value operation, max is a maximum value, M 1 For the purpose of markingThe number of pixel points on the spraying area of the quasi-image, M 2 J is the number of the position points on the first type spraying area, K is the number of other standard images, and K is the number of the standard images;
the formula for obtaining the wafer area error threshold in S26 is as follows:
，
，
wherein w is th For wafer area error threshold, p k,i Pixel value p at the ith position point on the wafer area of the kth standard image o , i For reference to the pixel value at the i-th position point on the wafer area, N is a positive integer, N 1 The number of pixel points on the wafer area of the standard image is N 2 For the number of pixel points on the reference wafer area, max is the maximum value, i is the absolute value operation, i is the number of the position points on the first type wafer area, K is the number of other standard images, and K is the number of the standard images.
2. The method for positioning defects on a nanoimprinted wafer according to claim 1, wherein S3 comprises the following sub-steps:
s31, taking pixel values of pixel points of the nano-imprinting glue on the standard image as nano-imprinting glue color values;
s32, calculating the similarity between the pixel value of each pixel point on the real-time image and the color value of the nano imprinting glue;
s33, classifying the pixel points with the similarity larger than a second similarity threshold value on the real-time image as a spraying area, and classifying the pixel points with the similarity smaller than or equal to the second similarity threshold value as a wafer area;
s34, subtracting pixel values at the same positions of the spraying area of the real-time image and the spraying area of the standard image to obtain a real-time spraying area difference value;
and S35, subtracting the pixel values of the same positions of the wafer area on the real-time image and the wafer area of the standard image to obtain a real-time wafer area difference value.
3. The method for positioning a nano-imprint wafer defect according to claim 2, wherein the formula for obtaining the real-time spray area difference in S34 is:
，
，
wherein s is t For real-time spray area difference, f m The pixel value f of the mth position point on the spraying area of the real-time image o,m The pixel value of the m-th position point on the spraying area of the standard image is represented by max, which is the maximum value,e is the number of pixel points on the spraying area of the real-time image, M 1 The number of pixel points on the spraying area of the standard image is calculated, the absolute value of the pixel points is calculated, and the m is the number of the position points on the spraying area of the second type.
4. The method for positioning a nano-imprint wafer defect according to claim 2, wherein the formula for obtaining the real-time wafer area difference in S35 is:
，
，
wherein w is t For real-time wafer area difference, p n Crystal for real-time imagePixel value, p, of nth position point on circular area o,n The pixel value of the nth position point on the wafer area of the standard image, max is the maximum value,is a positive integer, Y is the number of pixel points on the wafer area of the real-time image, N 1 The number of pixel points on the wafer area of the standard image is calculated by absolute value, and n is the number of position points on the wafer area of the second type.
5. The method for positioning a defect on a nanoimprint wafer according to claim 1, wherein the steps of the method for finding a defect position in S5 and S7 are the same, the real-time spray sub-region and the real-time wafer sub-region are both named as real-time sub-regions, the standard spray sub-region and the standard wafer sub-region are both named as standard sub-regions, and the method for finding a defect position in S5 or S7 specifically comprises:
a1, calculating an abnormal value of a real-time subarea according to a pixel point quantity difference value and a position coordinate difference value of the real-time subarea and a standard subarea in the same area;
a2, when the abnormal value is larger than an abnormal threshold value, marking the real-time subarea as an abnormal real-time subarea, wherein in S5, the abnormal real-time subarea is an abnormal real-time spraying subarea, and in S7, the abnormal real-time subarea is an abnormal real-time wafer subarea;
a3, finding the defect position from the abnormal real-time subarea.
6. The method for positioning a nanoimprint wafer defect of claim 5, wherein the formula for calculating the outlier of the real-time sub-region in A1 is:
，
wherein ab is an outlier of the real-time subarea, n tu N is the difference of the pixel number tu The number of pixels of the standard subarea, x 1,c Is the abscissa, y, of the c-th pixel point on the real-time subarea 1,c The ordinate of the c-th pixel point on the real-time subarea is the serial numbers of the pixels of the real-time subarea and the standard subarea, and x 2,c Is the abscissa, y of the c-th pixel point on the standard subarea 2,c Is the ordinate of the C pixel point on the standard subarea, C 1 C is the number of pixel points on the real-time subarea 2 The number of pixel points on the standard subarea is the absolute value operation.
7. The method of claim 5, wherein A3 comprises the sub-steps of:
a31, setting an expansion window, wherein the size of the expansion window is as followsR is the number of traversals, and the initial value of r is 0;
a32, respectively placing the expansion window in the central areas of the abnormal real-time subarea and the standard subarea, and calculating the difference of the number of pixels between the abnormal real-time subarea and the standard subarea under the current expansion window;
a33, adding 1 to r, jumping to A32 until the expansion window is larger than the abnormal real-time subarea or the standard subarea, and ending the traversal;
a34, finding the corresponding traversal times h when the difference of the number of pixel points is larger than the difference threshold value, and newly increasing the range of the position of the defect on the abnormal real-time subarea on the expansion window corresponding to the h traversal timeH is an integer greater than 1.
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