Die image grayscale correction method, computer equipment and computer storage medium

Abstract

The embodiment of the present application discloses a die image grayscale correction method, a computer device and a computer storage medium. The embodiment of the present application includes: determining a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, obtaining m first scaling factors, determining a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, obtaining n second scaling factors, determining a scaling ratio of the target die according to the m first scaling factors and the n second scaling factors, correcting the grayscale value of the image of the target die according to the scaling ratio, obtaining a grayscale corrected image of the target die, eliminating the influence of chromatic aberration on the grayscale value of the die image, avoiding the deviation of the grayscale value of the die image due to chromatic aberration, and thus affecting the accuracy of the die defect detection result.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of chip die detection, and specifically to a die image grayscale correction method, a computer device, and a computer storage medium. Background Art

[0002] There is color difference between dies in the wafer, especially when the die size is large, for example, the die size is 43mm*37mm, then the number of dies in a row of 12-inch wafer is only 3-10. At this time, the span between dies is very large, and it is easy for the imaging of the die to produce color difference due to the unevenness of light. The color difference will interfere with the subsequent defect detection process of the die based on the grayscale value of the image, affecting the detection results of the die. Summary of the invention

[0003] The embodiments of the present application provide a die image grayscale correction method, a computer device, and a computer storage medium for correcting the grayscale value of an image to eliminate the influence of chromatic aberration on the grayscale value of the die image.

[0004] A first aspect of an embodiment of the present application provides a die image grayscale correction method, the method comprising:

[0005] Acquire an image of a target die to be corrected, and acquire an image of a reference die; the image of the target die and the image of the reference die both include an m×n pixel matrix, where m and n are both positive integers greater than 1;

[0006] Determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and obtain m first scaling factors;

[0007] Determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, and obtain n second scaling factors;

[0008] Determining a scaling ratio of the target die according to the m first scaling factors and the n second scaling factors;

[0009] The grayscale value of the image of the target die is corrected according to the scaling ratio to obtain a grayscale-corrected image of the target die.

[0010] A second aspect of an embodiment of the present application provides a computer device, the computer device comprising:

[0011] An acquisition unit, used to acquire an image of a target die to be corrected and an image of a reference die; the image of the target die and the image of the reference die both include an m×n pixel matrix, where m and n are both positive integers greater than 1;

[0012] A first determining unit, configured to determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, to obtain m first scaling factors;

[0013] A second determining unit, configured to determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, to obtain n second scaling factors;

[0014] a third determining unit, configured to determine a scaling ratio of the target die according to the m first scaling coefficients and the n second scaling coefficients;

[0015] A correction unit is used to correct the grayscale value of the image of the target die according to the scaling ratio to obtain a grayscale corrected image of the target die.

[0016] A third aspect of an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the method of the first aspect when executing the computer program.

[0017] A fourth aspect of an embodiment of the present application provides a computer storage medium, in which instructions are stored. When the instructions are executed on a computer, the computer executes the method of the first aspect.

[0018] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0019] A first scaling factor is determined according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and m first scaling factors are obtained. A second scaling factor is determined according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, and n second scaling factors are obtained. The scaling ratio of the target die is determined according to the m first scaling factors and the n second scaling factors. The grayscale value of the image of the target die is corrected according to the scaling ratio to obtain a grayscale corrected image of the target die, thereby eliminating the influence of chromatic aberration on the grayscale value of the die image, and avoiding the deviation of the grayscale value of the die image due to chromatic aberration, thereby affecting the accuracy of the die defect detection result. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a process of a die image grayscale correction method in an embodiment of the present application;

[0021] Figure 2 This is another flow chart of the die image grayscale correction method in the embodiment of the present application;

[0022] Figure 3 An exemplary schematic diagram of an arrangement of pixels in a target die image and a reference die image in an embodiment of the present application;

[0023] Figure 4 An exemplary schematic diagram of an arrangement of multiple dies in a wafer in an embodiment of the present application;

[0024] Figure 5 A schematic diagram of a process for obtaining a matrix composed of first scaling coefficients according to a portion of pixel rows of a target die and a reference die in an embodiment of the present application;

[0025] Figure 6 A schematic diagram of a process for obtaining a matrix composed of second scaling coefficients according to partial pixel columns of a target die and a reference die in an embodiment of the present application;

[0026] Figure 7 An exemplary schematic diagram of the display effects of the target die image before and after correction in the embodiment of the present application;

[0027] Figure 8-1 An exemplary schematic diagram of n portions of m first scaling coefficients constituting an m×n first matrix in an embodiment of the present application;

[0028] Figure 8-2 An exemplary schematic diagram of m×n second matrices formed by m portions of n second scaling coefficients in an embodiment of the present application;

[0029] Figure 8-3 Based on Figure 8-1 The first matrix shown is Figure 8-2 An exemplary schematic diagram of the scaling ratio calculated by the second matrix shown;

[0030] Figure 8-4 An exemplary schematic diagram of each pixel of the image of the target die and its grayscale value in an embodiment of the present application;

[0031] Figure 8-5 Based on Figure 8-3 The scale shown is similar to Figure 8-4 The grayscale corrected image of the target die is obtained by calculating each pixel and grayscale value of the image of the target die shown;

[0032] Fig. 9 This is a schematic diagram of the structure of a computer device in an embodiment of the present application;

[0033] Fig.10This is another structural diagram of a computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The embodiments of the present application provide a die image grayscale correction method, a computer device, and a computer storage medium for correcting the grayscale value of an image to eliminate the influence of chromatic aberration on the grayscale value of the die image.

[0035] The die image grayscale correction method in the embodiment of the present application is described below:

[0036] See also Figure 1 In the embodiment of the present application, one embodiment of the die image grayscale correction method includes:

[0037] 101. Acquire an image of a target die to be corrected, and acquire an image of a reference die;

[0038] The method of this embodiment can be applied to a computer device, which can be a device with data processing and computing capabilities such as a terminal and a server. The image of the target die whose grayscale is to be corrected in the wafer can be acquired using a camera device, and the computer device obtains the acquired image of the target die. Similarly, the image of the reference die in the wafer can also be acquired in the above manner.

[0039] The image of the target die and the image of the reference die are both composed of multiple pixels, which are arranged in an m×n pixel matrix, where m and n are both positive integers greater than 1, and each pixel has a corresponding grayscale value. However, the target die has chromatic aberration in its imaging due to the unevenness of light, which in turn causes the grayscale value of its imaged pixels to deviate too much from the grayscale value of the image pixels of nearby dies, affecting the defect detection process of the target die. Therefore, the grayscale value of its pixels needs to be corrected so that when the target die is subjected to defect detection based on the image of the target die, the grayscale value of the image will not affect the accuracy of the detection result.

[0040] 102. Determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and obtain m first scaling factors;

[0041] 103. Determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, to obtain n second scaling factors;

[0042] After obtaining the image of the target die and the image of the reference die, the grayscale value of the image of the target die can be adjusted and corrected according to the grayscale value of the image of the reference die. Since the pixels in the die image are distributed in an m×n pixel matrix, that is, corresponding to m rows of pixels and n columns of pixels, the first scaling factor can be determined according to the grayscale value of each pair of pixels in the same row between the target die and the reference die, and m first scaling factors can be obtained; and the second scaling factor can be determined according to the grayscale value of each pair of pixels in the same column between the target die and the reference die, and n second scaling factors can be obtained.

[0043] The same row means that the row of pixels in the target die image and the row of pixels in the reference die image are located at the same position in their respective images, for example, the first row in the target die image and the first row in the reference die image are the same row, the second row in the target die image and the second row in the reference die image are the same row, and so on. Similarly, the same column means that the column of pixels in the target die image and the column of pixels in the reference die image are located at the same position in their respective images, for example, the first column in the target die image and the first column in the reference die image are the same column, the second column in the target die image and the second column in the reference die image are the same column, and so on.

[0044] 104. Determine a scaling ratio of the target die according to the m first scaling coefficients and the n second scaling coefficients;

[0045] Since the m first scaling factors and the n second scaling factors are a group of arrays, that is, they are all distributed in one dimension, and the image of the target die is composed of a pixel matrix and is distributed in two dimensions, it is necessary to determine the scaling ratio of the two-dimensional distribution based on the m first scaling factors and the n second scaling factors. This scaling ratio is the same as the image dimension of the target die, so that the pixel grayscale value of the image of the target die can be corrected and adjusted according to this scaling ratio.

[0046] 105. Correcting the grayscale value of the image of the target die according to the scaling ratio to obtain a grayscale-corrected image of the target die;

[0047] After determining the scaling ratio, the grayscale value of the target die image can be corrected and adjusted according to the scaling ratio to eliminate the influence of chromatic aberration on the grayscale value of the die image, avoid the deviation of the grayscale value of the die image due to chromatic aberration and thus affect the accuracy of the die defect detection result, thereby obtaining a grayscale corrected image of the target die.

[0048] In this embodiment, a first scaling factor is determined according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and m first scaling factors are obtained. A second scaling factor is determined according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, and n second scaling factors are obtained. The scaling ratio of the target die is determined according to the m first scaling factors and the n second scaling factors. The grayscale value of the image of the target die is corrected according to the scaling ratio to obtain a grayscale corrected image of the target die, thereby eliminating the influence of chromatic aberration on the grayscale value of the die image, and avoiding the deviation of the grayscale value of the die image due to chromatic aberration, thereby affecting the accuracy of the die defect detection result.

[0049] In the following, Figure 1 Based on the embodiment shown, the embodiment of the present application is further described in detail. Figure 2 Another embodiment of the die image grayscale correction method in the embodiment of the present application includes:

[0050] 201. Acquire an image of a target die to be corrected, and acquire an image of a reference die;

[0051] In this embodiment, the target die and the reference die in the same wafer may be imaged to obtain an image of the target die and an image of the reference die.

[0052] like Figure 3 As shown, the image of the target die and the image of the reference die both include an m×n pixel matrix, that is, m rows of pixels and n columns of pixels, and each pixel has a corresponding grayscale value.

[0053] It should be noted that the image of the target die may include more than m rows of pixels and n columns of pixels, for example, the number of rows of pixels may be greater than m, or the number of columns of pixels may be greater than n. Similarly, the number of rows of pixels in the image of the reference die may be greater than m, or the number of columns of pixels may be greater than n.

[0054] The positional relationship between the target die and the reference die in the wafer may be that the reference die and the target die are located in the same row in the wafer, and the reference die and the target die are adjacent to each other, or there are x dies between the reference die and the target die, where x≥1 and is a positive integer.

[0055] like Figure 4 As shown, die1 to die5 in the wafer are dies in the same row in the wafer. If die3 is the target die, and die2, die4 and die3 are adjacent and die1, die5 and die3 are separated by 1 die, then die1, die2, die4 and die5 can all be used as reference dies to correct the grayscale value of die3.

[0056] The fewer the number of dies between the target die and the reference die, the shorter the distance the camera moves, and the more convenient it is to obtain images (i.e., image acquisition) for the reference die. Therefore, it is most convenient to obtain images for the reference die when the target die is adjacent to the reference die.

[0057] After obtaining the target die image and the reference die image, the two can be aligned according to the arrangement positions of rows and columns, such as aligning the pixels in the first row of the target die image with the pixels in the first row of the reference die image, or aligning the pixels in the first column of the target die image with the pixels in the first column of the reference die image, and so on, so that the pixels in the same row or the same column between the target die image and the reference die image are aligned with each other to facilitate processing in subsequent steps.

[0058] 202. Determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and obtain m first scaling factors;

[0059] In this embodiment, there are multiple ways to determine the first scaling factor. One way may be to respectively determine the first statistical characteristic value corresponding to the grayscale value of each row of pixels in the image of the target die to obtain m first statistical characteristic values, and respectively determine the second statistical characteristic value corresponding to the grayscale value of each row of pixels in the image of the reference die to obtain m second statistical characteristic values, calculate the quotient of the second statistical characteristic value corresponding to each pair of pixels in the same row between the target die and the reference die, use the quotient as the first scaling factor, and obtain m first scaling factors.

[0060] Among them, the first statistical characteristic value or the second statistical characteristic value can be any statistical characteristic value that can represent the average level of the grayscale value of the pixels in the row, for example, it can be a statistical characteristic value such as the mean, median, mode, etc. For example, the mean of the grayscale value of each row of pixels in the image of the target die can be calculated to obtain m first means, the mean of the grayscale value of each row of pixels in the image of the reference die can be calculated to obtain m second means, and then the quotient of the second mean and the first mean corresponding to each pair of pixels in the same row between the target die and the reference die is calculated, such as calculating the quotient between the second mean corresponding to the first row of pixels of the reference die image and the first mean corresponding to the first row of pixels of the target die image to obtain a first scaling factor; calculating the quotient between the second mean corresponding to the second row of pixels of the reference die image and the first mean corresponding to the second row of pixels of the target die image to obtain another first scaling factor... and so on, the m first scaling factors can be calculated in sequence. This method compares the overall average grayscale value of the entire row of pixels between the target die image and the reference die image, so the calculated first scaling factor can reflect the overall grayscale value difference between the two, thereby facilitating the subsequent grayscale value adjustment and correction of the target die image.

[0061] In addition, the first scaling factor can also be determined by calculating the quotient of the grayscale values ​​of each pair of pixels at the same position between the target die and the reference die, and then calculating n quotients corresponding to each row of pixels, averaging these n quotients, and using this average as the first scaling factor. This method can sequentially compare the grayscale value differences of each pixel at the same position between the target die image and the reference die image, and achieve a more fine-grained grayscale value comparison, thereby more accurately reflecting the difference in each detail between the target die image and the reference die image, and achieving detailed adjustment and correction of the grayscale value of the target die image. This embodiment does not limit the method for determining the first scaling factor, as long as the method for calculating the first scaling factor can reflect the grayscale value difference comparison between the target die image and the reference die image.

[0062] 203. Determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, to obtain n second scaling factors;

[0063] In this embodiment, there are multiple ways to determine the second scaling factor. One way may be to respectively determine the third statistical eigenvalue corresponding to the grayscale value of each column of pixels in the image of the target die to obtain n third statistical eigenvalues, and respectively determine the fourth statistical eigenvalue corresponding to the grayscale value of each column of pixels in the image of the reference die to obtain n fourth statistical eigenvalues, calculate the quotient of the fourth statistical eigenvalue corresponding to each pair of pixels in the same column between the target die and the reference die, use the quotient as the second scaling factor, and obtain n second scaling factors.

[0064] Among them, the third statistical characteristic value or the fourth statistical characteristic value can be any statistical characteristic value that can represent the average level of the grayscale value of the pixels in the column, for example, it can be a statistical characteristic value such as the mean, median, mode, etc. For example, the mean of the grayscale value of each column of the image of the target die can be calculated to obtain n third means, the mean of the grayscale value of each column of the image of the reference die can be calculated to obtain n fourth means, and then the quotient of the fourth mean and the third mean corresponding to each pair of pixels in the same column between the target die and the reference die is calculated, such as calculating the quotient between the fourth mean corresponding to the pixels in the first column of the reference die image and the third mean corresponding to the pixels in the first column of the target die image to obtain a second scaling factor; calculating the quotient between the fourth mean corresponding to the pixels in the second column of the reference die image and the third mean corresponding to the pixels in the second column of the target die image to obtain another second scaling factor... and so on, n second scaling factors can be calculated in sequence. This method compares the overall average grayscale values ​​of the entire column of pixels between the target die image and the reference die image, so that the calculated first scaling factor can reflect the overall grayscale value difference between the two, thereby facilitating the subsequent grayscale value adjustment and correction of the target die image.

[0065] In addition, the second scaling factor can also be determined by calculating the quotient of the grayscale values ​​of each pair of pixels at the same position between the target die and the reference die, and m quotients corresponding to each column of pixels can be calculated, and the average of these m quotients is used as the second scaling factor. This method can sequentially compare the grayscale value difference of each pixel at the same position between the target die image and the reference die image, and achieve a more fine-grained grayscale value comparison, thereby more accurately reflecting the difference in each detail between the target die image and the reference die image, and can achieve detailed adjustment and correction of the grayscale value of the target die image. This embodiment does not limit the method for determining the second scaling factor, as long as the method for calculating the second scaling factor can reflect the grayscale value difference comparison between the target die image and the reference die image.

[0066] 204. Determine a scaling ratio of the target die according to the m first scaling coefficients and the n second scaling coefficients;

[0067] Since noise may be introduced into the image due to various factors during die imaging acquisition, in order to eliminate noise data, before determining the scaling ratio of the target die, Gaussian filtering may be performed on the m first scaling factors and the n second scaling factors respectively to eliminate the noise therein. After Gaussian filtering is completed, the scaling ratio of the target die may be determined according to the m first scaling factors that have undergone Gaussian filtering and the n second scaling factors that have undergone Gaussian filtering.

[0068] In this embodiment, one way to determine the scaling ratio may be to copy the m first scaling coefficients arranged in columns (n-1) times, and then the n copies of the m first scaling coefficients constitute an m×n first matrix; copy the n second scaling coefficients arranged in rows (m-1) times, and then the m copies of the n second scaling coefficients constitute an m×n second matrix; calculate the mean of each pair of elements in the same position between the first matrix and the second matrix to obtain m×n means, and arrange the m×n means according to their respective corresponding same positions to form an m×n matrix, and the m×n matrix formed by the arrangement of the m×n means constitutes the scaling ratio.

[0069] For example, Figure 5 As shown, the values ​​in the first column are multiple second means corresponding to some pixel rows in the reference die image (i.e., the grayscale values ​​of all pixels in the pixel row are accumulated and then the average is calculated), the values ​​in the second column are multiple first means corresponding to some pixel rows in the target die image, the values ​​in the third column are the quotient of the second mean and the first mean corresponding to the same row between the values ​​in the first column and the values ​​in the second column, the values ​​in the fourth column are the values ​​obtained by Gaussian filtering the quotient of the third column, and the numerical matrix after the values ​​in the fourth column is a matrix formed by copying the values ​​in the fourth column to obtain multiple copies.

[0070] For example, Figure 6 As shown, the values ​​in the first row are multiple fourth means corresponding to some pixel columns in the reference die image (i.e., the grayscale values ​​of all pixels in the pixel column are accumulated and then the average is calculated), the values ​​in the second row are multiple third means corresponding to some pixel columns in the target die image, the values ​​in the third row are the quotient of the fourth mean and the third mean corresponding to the same column between the values ​​in the first row and the values ​​in the second row, the values ​​in the fourth row are the values ​​obtained by Gaussian filtering the quotient of the third row, and the numerical matrix after the values ​​in the fourth row is the matrix formed by copying the values ​​in the fourth row to obtain multiple copies.

[0071] After obtaining the first matrix and the second matrix, the mean of the elements at the same position of the two can be calculated. For example, take the element at the i-th row and j-th column of the first matrix and the element at the i-th row and j-th column of the second matrix (1≤i≤m, 1≤j≤n), calculate the mean of the two elements, and so on, until all the elements at the same position are calculated to obtain m×n means. Each of the m×n means is also arranged according to the position of the element to which it corresponds, forming an m×n matrix.

[0072] 205. Correcting the grayscale value of the image of the target die according to the scaling ratio to obtain a grayscale-corrected image of the target die;

[0073] After obtaining the scaling ratio, the grayscale value of the target die image can be corrected according to the scaling ratio. One correction method can be that since the scaling ratio and the target die image both constitute an m×n matrix, the grayscale value of each pixel in the m×n pixel matrix of the target die can be multiplied by the element corresponding to the same position as the pixel in the m×n matrix of the scaling ratio to obtain the grayscale corrected image of the target die. For example, for the (1, 1) pixel in the m×n pixel matrix of the target die image, its grayscale value can be multiplied by the value of the (1, 1) element in the m×n matrix of the scaling ratio, and the product is the new grayscale value of the (1, 1) pixel in the m×n pixel matrix of the target die image. By analogy, the grayscale value of the pixel at each position in the target die image can be adjusted to obtain a grayscale corrected image.

[0074] like Figure 7 As shown, the image above the arrow is the display effect of the target die image before correction, and there is obvious color difference compared with the image of the nearby die. The image below the arrow is the display effect of the target die image after correction. It can be seen that the grayscale of the image has changed significantly. After correction, the color difference has been eliminated, and the original display effect of the target die image is restored to meet the requirements of die defect detection for the grayscale value of the die image.

[0075] An application example of this embodiment is as follows Figure 8-1 to Figure 8-5 As shown, the m first scaling factors arranged in a column are copied (n-1) times, and then n copies of the m first scaling factors constitute the following Figure 8-1 The first m×n matrix shown in FIG. The n second scaling coefficients arranged in rows are copied (m-1) times, and then m copies of the n second scaling coefficients constitute the following Figure 8-2 The m×n second matrix shown in FIG. The mean of each pair of elements in the same position between the first matrix and the second matrix is ​​calculated to obtain m×n means, and these m×n means are arranged according to the corresponding same positions to form an m×n matrix. The m×n matrix formed by the arrangement of these m×n means is as follows: Figure 8-3Scaling ratio shown.

[0076] After obtaining the scaling factor, Figure 8-4 The gray value of each pixel in the m×n pixel matrix of the target die shown is multiplied by Figure 8-3 The element corresponding to the same position as the pixel in the m×n matrix with the scaling ratio shown is obtained as follows Figure 8-5 Grayscale corrected image of the target die shown.

[0077] The above describes the die image grayscale correction method in the embodiment of the present application. The following describes the computer device in the embodiment of the present application. Fig. 9 In the embodiment of the present application, one embodiment of the computer device includes:

[0078] An acquisition unit 901 is used to acquire an image of a target die to be corrected and an image of a reference die; the image of the target die and the image of the reference die both include an m×n pixel matrix, where m and n are both positive integers greater than 1;

[0079] A first determining unit 902 is configured to determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, to obtain m first scaling factors;

[0080] A second determining unit 903 is used to determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, to obtain n second scaling factors;

[0081] A third determining unit 904 is configured to determine a scaling ratio of the target die according to the m first scaling coefficients and the n second scaling coefficients;

[0082] The correction unit 905 is used to correct the grayscale value of the image of the target die according to the scaling ratio to obtain a grayscale corrected image of the target die.

[0083] In a preferred implementation of the present embodiment, the first determination unit 902 is specifically used to respectively determine the first statistical characteristic values ​​corresponding to the grayscale values ​​of each row of pixels in the image of the target die, and obtain m of the first statistical characteristic values; respectively determine the second statistical characteristic values ​​corresponding to the grayscale values ​​of each row of pixels in the image of the reference die, and obtain m of the second statistical characteristic values; calculate the quotient of the second statistical characteristic value corresponding to each pair of pixels in the same row between the target die and the reference die and use the quotient as the first scaling factor to obtain m of the first scaling factors.

[0084] In a preferred implementation of the present embodiment, the second determination unit 903 is specifically used to respectively determine the third statistical eigenvalues ​​corresponding to the grayscale values ​​of each column of pixels in the image of the target die, and obtain n of the third statistical eigenvalues; respectively determine the fourth statistical eigenvalues ​​corresponding to the grayscale values ​​of each column of pixels in the image of the reference die, and obtain n of the fourth statistical eigenvalues; calculate the quotient of the fourth statistical eigenvalue corresponding to each pair of pixels in the same column between the target die and the reference die and use the quotient as the second scaling factor to obtain n of the second scaling factors.

[0085] In a preferred implementation of the present embodiment, the third determination unit 904 is specifically used to copy the m first scaling coefficients arranged in columns (n-1) times, and n copies of the m first scaling coefficients constitute an m×n first matrix; copy the n second scaling coefficients arranged in rows (m-1) times, and m copies of the n second scaling coefficients constitute an m×n second matrix; calculate the mean of each pair of elements in the same position between the first matrix and the second matrix to obtain m×n means, and the m×n means are arranged according to their respective corresponding same positions to form an m×n matrix, and the m×n matrix formed by the arrangement of the m×n means constitutes the scaling ratio.

[0086] In a preferred implementation of this embodiment, the correction unit 905 is specifically used to multiply the grayscale value of each pixel in the m×n pixel matrix of the target die by the element corresponding to the same position as the pixel in the m×n matrix of the scaling ratio to obtain a grayscale corrected image of the target die.

[0087] In a preferred implementation of this embodiment, the third determination unit 904 is specifically used to perform Gaussian filtering on the m first scaling coefficients and the n second scaling coefficients respectively; and determine the scaling ratio of the target die based on the m first scaling coefficients that have completed Gaussian filtering and the n second scaling coefficients that have completed Gaussian filtering.

[0088] In a preferred implementation of this embodiment, the reference die and the target die are located in the same row in the wafer, and the reference die and the target die are adjacent to each other or there are x dies between the reference die and the target die, where x≥1 and is a positive integer.

[0089] In this embodiment, the operations performed by each unit in the computer device are the same as those described above. Figure 1 to Figure 2 The description in the illustrated embodiment is similar and will not be repeated here.

[0090] In this embodiment, a first scaling factor is determined according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and m first scaling factors are obtained. A second scaling factor is determined according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, and n second scaling factors are obtained. The scaling ratio of the target die is determined according to the m first scaling factors and the n second scaling factors. The grayscale value of the image of the target die is corrected according to the scaling ratio to obtain a grayscale corrected image of the target die, thereby eliminating the influence of chromatic aberration on the grayscale value of the die image, and avoiding the deviation of the grayscale value of the die image due to chromatic aberration, thereby affecting the accuracy of the die defect detection result.

[0091] The computer device in the embodiment of the present application is described below. Fig.10 In the embodiment of the present application, one embodiment of the computer device includes:

[0092] The computer device 1000 may include one or more central processing units (CPU) 1001 and a memory 1005 , wherein the memory 1005 stores one or more application programs or data.

[0093] The memory 1005 may be a volatile storage or a persistent storage. The program stored in the memory 1005 may include one or more modules, each of which may include a series of instruction operations in the computer device. Furthermore, the central processing unit 1001 may be configured to communicate with the memory 1005 and execute a series of instruction operations in the memory 1005 on the computer device 1000.

[0094] The computer device 1000 may also include one or more power supplies 1002, one or more wired or wireless network interfaces 1003, one or more input and output interfaces 1004, and / or one or more operating systems, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0095] The CPU 1001 can execute the aforementioned Figure 1 to Figure 2 The operations performed by the computer device in the illustrated embodiment will not be described in detail here.

[0096] The present application also provides a computer storage medium, wherein one embodiment includes: the computer storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the aforementioned Figure 1 to Figure 2 The operations performed by the computer device in the illustrated embodiment.

[0097] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0098] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0099] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0100] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0101] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.

Claims

1. A die image grayscale correction method, characterized in that: The method comprises: Acquire an image of a target die to be corrected, and acquire an image of a reference die; the image of the target die and the image of the reference die both include an m×n pixel matrix, where m and n are both positive integers greater than 1; Determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, and obtain m first scaling factors; Determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, and obtain n second scaling factors; Determining a scaling ratio of the target die according to the m first scaling factors and the n second scaling factors; The grayscale value of the image of the target die is corrected according to the scaling ratio to obtain a grayscale-corrected image of the target die.

2. The method according to claim 1, characterized in that The determining the first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die to obtain m first scaling factors includes: Respectively determine the first statistical characteristic values ​​corresponding to the grayscale values ​​of each row of pixels in the image of the target die, and obtain m first statistical characteristic values; Respectively determine the second statistical characteristic values ​​corresponding to the grayscale values ​​of each row of pixels in the image of the reference die to obtain m second statistical characteristic values; The quotient of the second statistical characteristic value and the first statistical characteristic value corresponding to each pair of pixels in the same row between the target die and the reference die is calculated, and the quotient is used as the first scaling factor to obtain m first scaling factors.

3. The method according to claim 1, characterized in that The step of determining the second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die to obtain n second scaling factors includes: Respectively determine the third statistical characteristic values ​​corresponding to the grayscale values ​​of each column of pixels in the image of the target die, and obtain n third statistical characteristic values; Respectively determine the fourth statistical eigenvalues ​​corresponding to the grayscale values ​​of each column of pixels in the image of the reference die to obtain n fourth statistical eigenvalues; The quotient of the fourth statistical eigenvalue and the third statistical eigenvalue corresponding to each pair of pixels in the same column between the target die and the reference die is calculated, and the quotient is used as the second scaling factor to obtain n second scaling factors.

4. The method according to any one of claims 1 to 3, characterized in that: The determining a scaling ratio of the target die according to the m first scaling factors and the n second scaling factors includes: Copying the m first scaling coefficients arranged in a column (n-1) times, and the n copies of the m first scaling coefficients form a first matrix of m×n; Copying the n second scaling coefficients arranged in a row (m-1) times, and forming an m×n second matrix with m copies of the n second scaling coefficients; The mean of each pair of elements in the same position between the first matrix and the second matrix is ​​calculated to obtain m×n means, and the m×n means are arranged according to the corresponding same positions to form an m×n matrix, and the m×n matrix formed by the arrangement of the m×n means constitutes the scaling ratio.

5. The method according to claim 4, characterized in that The step of correcting the grayscale value of the image of the target die according to the scaling ratio to obtain a grayscale-corrected image of the target die includes: The grayscale value of each pixel in the m×n pixel matrix of the target die is multiplied by the element corresponding to the same position as the pixel in the m×n matrix of the scaling ratio to obtain a grayscale corrected image of the target die.

6. The method according to claim 1, characterized in that The determining a scaling ratio of the target die according to the m first scaling factors and the n second scaling factors includes: Performing Gaussian filtering on the m first scaling coefficients and the n second scaling coefficients respectively; The scaling ratio of the target die is determined according to the m first scaling coefficients that complete the Gaussian filtering and the n second scaling coefficients that complete the Gaussian filtering.

7. The method according to any one of claims 1 to 6, characterized in that: The reference die and the target die are located in the same row in a wafer, and the reference die is adjacent to the target die or there are x dies between the reference die and the target die, where x is a positive integer.

8. A computer device, characterized in that: The computer device comprises: An acquisition unit, used to acquire an image of a target die to be corrected and an image of a reference die; the image of the target die and the image of the reference die both include an m×n pixel matrix, where m and n are both positive integers greater than 1; A first determining unit, configured to determine a first scaling factor according to the grayscale values ​​of each pair of pixels in the same row between the target die and the reference die, to obtain m first scaling factors; A second determining unit, configured to determine a second scaling factor according to the grayscale values ​​of each pair of pixels in the same column between the target die and the reference die, to obtain n second scaling factors; a third determining unit, configured to determine a scaling ratio of the target die according to the m first scaling coefficients and the n second scaling coefficients; A correction unit is used to correct the grayscale value of the image of the target die according to the scaling ratio to obtain a grayscale corrected image of the target die.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer storage medium, characterized in that: The computer storage medium stores instructions, and when the instructions are executed on a computer, the computer is caused to perform the method according to any one of claims 1 to 7.

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