A method for determining a seed light circle area in a seed process

Abstract

The application discloses a method for determining a crystal bar aperture area in a seeding process, which comprises the following steps: establishing a coordinate system, establishing the coordinate system by using a gray scale diagram of the aperture, taking the number of rows as the X axis and the number of columns as the Y axis, and taking each point (x, y) on the image as a pixel value; determining the number of rows where the interface M is located according to the average value of the row pixel points; processing the area below the row where the interface M is located as black, and processing the area above the row where the interface M is located as the aperture area. The method can greatly reduce the threshold value of the aperture, even if the brightness of the aperture changes greatly, the method will not cause false detection, greatly improves the stability of the aperture detection, and improves the anti-interference of the system. The method is used for image pre-processing before the calculation of the diameter and liquid level measurement, and is used for the stability of the diameter and liquid level measurement in the crystal bar growth process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, in particular to a method for determining a crystal bar light circle area in a crystal pulling process. BACKGROUND

[0002] Single crystal furnace: a single crystal furnace is a kind of device for growing dislocation-free single crystal by using a graphite heater to melt polycrystalline materials such as polycrystalline silicon in an inert gas (mainly argon and helium) environment.

[0003] In the crystal pulling process, the light circle forms a bright reflection under the liquid surface, as shown in Figure 1 When the camera determines the threshold boundary of the bright crescent-shaped light circle Figure 1 , the threshold value of the light circle is difficult to determine due to the over-brightness of the reflection, and the actual light circle boundary is misdetected, that is, the reflection is detected as the actual light circle, thereby causing measurement errors. SUMMARY

[0004] In view of the above technical deficiencies, the purpose of the present application is to provide a method for determining a crystal bar light circle area in a crystal pulling process to solve the problems raised in the background art.

[0005] To solve the above technical problems, the present application adopts the following technical scheme:

[0006] The present application provides a method for determining a crystal bar light circle area in a crystal pulling process, comprising the following steps:

[0007] (1) Establishing a coordinate system

[0008] A coordinate system is established based on the gray scale of the light circle, the X axis is the row number, the Y axis is the column number, each point (x, y) on the image corresponds to a pixel value, the row number R, the column number C and the pixel value are automatically stored in the camera, and they are known data;

[0009] (2) Determining the row number of the interface M according to the average value of the row pixel points;

[0010] (3) Treating the area below the row of the interface M as black, and the area above the row of the interface M as the light circle area.

[0011] Preferably, in step (2), the row number is taken as the horizontal coordinate, and the average value of the row pixels is taken as the vertical coordinate, a curve AVG graph is drawn, and the row number range of the interface M is determined by the row number of the trough M in the graph.

[0012] Preferably, in step (2), the derivative of the curve AVG graph is calculated to obtain the change rate DEV=AVG', and the derivative is also plotted, the point N with the maximum change rate in the graph is found, and the row number of the interface M is the row number of the point closest to the point N, greater than the point N, and with the minimum average value of the row pixels.

[0013] Preferably, in step (2), the specific method of taking the row pixel average value is as follows:

[0014] There are Ctotal points in each row of the image, and the average value Ax of all the points in the xth row is calculated,

[0015] Ax=(A1+A2+A3...+A C总 ) / C 总 (1).

[0016] Preferably, in step (1), the total number of rows is 533, the total number of columns is 280, and the pixel value of the point in the picture is between 0 and 255, the pixel value of black is 0, and the pixel value of white is 255.

[0017] Preferably, in step (2),

[0018] M1=N1+X (2)

[0019] M1 is the number of rows where the interface M is located; N1 is the number of rows where the maximum value N of the row pixel average value change rate is located, and X is the offset, X is a positive value.

[0020] Preferably, in step (3), the method of processing the area below the M interface as black is to change all the pixel values below the M interface to 0.

[0021] The beneficial effects of the present application are as follows:

[0022] (1) The present application uses the principle of mirror symmetry, calculates the row pixel average value, makes a curve of the row pixel average value, determines the range of the M row number through the wave trough M, then takes the derivative of the curve, finds the point N with the minimum derivative, and in the gray scale image, the M point is below the N point, so the M row number is greater than the N row number. In combination with the row pixel average value and the derivative table, the M position can be determined, that is, the position of the interface M of the aperture and its reflection. Then the area below the interface M is processed as black, which can ensure the integrity of the aperture, greatly reduce the threshold of the aperture, even if the brightness of the aperture changes greatly, it will not cause false detection, greatly improve the stability of the aperture detection, and at the same time, the anti-interference of the system can be improved.

[0023] (2) The present method is used in the initial stage of crystal drawing, that is, the image is preprocessed to remove the reflection before the calculation of the diameter and the liquid level measurement, which can improve the stability of the diameter and the liquid level measurement in the crystal rod growth process.

[0024] (3) The present application is simple to operate and convenient to use, and provides a basis for the controllable growth of crystal rods.

[0025] (4) The present application can avoid the interference of the inverted image in image processing by processing the inverted image as black, which is verified in theory and practice. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0027] Figure 1 The gray scale diagram of the crystal bar aperture and its inverted image;

[0028] Figure 2 The coordinate system diagram of the middle aperture and its inverted image; Figure 1 The coordinate system diagram of the middle aperture and its inverted image;

[0029] Figure 3 The curve AVG diagram of the relationship between the average value of row pixels and the row number;

[0030] Figure 4 The curve diagram of the change rate of the average value of row pixels after derivation and the row number; Figure 3 The curve diagram of the change rate of the average value of row pixels after derivation and the row number;

[0031] Figure 5 The local enlarged view of the aperture and its inverted image; Figure 1 The local enlarged view of the aperture and its inverted image, wherein the No. 1 position is the N point. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort belong to the scope of protection of the present application.

[0033] Embodiment:

[0034] The present application provides a method for determining the crystal bar aperture area in the seeding process, comprising the following steps:

[0035] (1) Establishing a coordinate system

[0036] According to the principle of mirror imaging, the aperture and its inverted image are mirror symmetric about the liquid mirror, and there is a relatively dark region between the aperture and its inverted image. The region is located at the interface M, and the aperture gray scale diagram is established as Figure 1 The coordinate system of the aperture gray scale diagram is established as Figure 2As shown, the X-axis represents the number of rows, and the Y-axis represents the number of columns. Each point (x, y) on the image corresponds to a pixel value. The number of rows, columns, and pixel values ​​are automatically stored in the camera and are known data. In this embodiment, there are 533 rows and 280 columns. The pixel values ​​of the points in the image are between 0 and 255. The value of a black pixel is 0, and the value of a white pixel is 255.

[0037] (2) Take the average value of row pixels

[0038] Each row of the image has 280 pixels. Calculate the average pixel value of all pixels in each row. A x ,

[0039] A x =(A1+A2+A3...+A 280 ) / 280(1)

[0040] The average pixel value per row is shown in Table 1. A graph is plotted with the row number on the x-axis and the average pixel value per row on the y-axis. The results are as follows: Figure 3 As shown in the curve AVG, Figure 3 The location of the mid-wave trough M is the location of the interface M; from Figure 2 Analysis shows that from top to bottom, as the number of rows increases, the pixel value increases, reaching its maximum at the aperture. In the area between the aperture and the reflection, the pixel value decreases, becoming darker. When reaching the aperture and reflection again, the pixel value increases. This analysis is consistent with... Figure 3 Correspondingly, Figure 3 The trough M position in the middle is Figure 2 The location of the middle boundary mirror M.

[0041] (3) Determine the location of point M

[0042] because Figure 3 There may be multiple points with the same value as point M; for example, the reflection may also show trough positions. Figure 3 The derivative of the curve AVG is taken to obtain the rate of change DEV = AVG'. The specific values ​​of the derivative are shown in Table 1. A graph of the derivative is also plotted, and the results are as follows: Figure 4 As shown in the figure, the point with the largest rate of change is point N, which is the point where the brightness decreases the fastest from bright to dark.

[0043] In this embodiment, the comparison Figure 3 The trough M is around line 240, see comparison. Figure 4The row number of the point with the maximum change rate of the row pixel average value is N, and the row number of the point with the minimum derivative is found near the row 235 in combination with Table 1, and N1=236 is quickly obtained, and then the row number of the point closest to the N point and greater than the N point in the row pixel average value is found, and M1=242 is quickly obtained. It can be seen that the row number of the point with the minimum row pixel average value is not the same as the row number of the point with the maximum change rate of the row pixel average value, and the difference between the two is 6 rows.

[0044] In combination with Table 1 and Figure 5 The row number of the interface M is the row number of the point with the minimum row pixel average value, the point with the maximum change rate of the row pixel average value is the first position, and the position of the bottom end of the aperture, that is, the position of the pixel from yes to no, and the first position and the interface M have a certain distance, that is, the offset. The following formula is derived:

[0045] M1=N1+X (2)

[0046] M1 is the row number of the interface M, N1 is the row number of the point with the maximum change rate N of the row pixel average value, and X is the offset, which can be adjusted according to the actual situation.

[0047] In this embodiment, X=6.

[0048] (4) Removing the inverted image

[0049] In the camera setting, all pixel values below the M interface are changed to 0, that is, the region below the M interface is processed as black.

[0050] In this embodiment, all pixel values below the row 242 are changed to 0, that is, the region below the M interface is processed as black, so that the interference of the inverted image is eliminated in the crystal pulling process.

[0051] Table 1: Row pixel average value and derivative table

[0052]

[0053] In the crystal pulling process, the camera takes a picture every few hundred milliseconds, and the inverted image processing of the present method is performed every time a picture is taken, so the inverted image processing is a continuous process.

[0054] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method of determining a seed light circle area in a seed process, characterized by, It comprises the following steps: (1) Establishing coordinate system Establishing coordinate system with gray scale of aperture, X axis is row number, Y axis is column number, every point (x, y) on the image corresponds to a pixel value, row number R, column number C and pixel value are stored in camera automatically, which are known data; (2) Determining row number of interface M according to average value of row pixel points; (3) Treating the area below interface M as black, and the area above interface M as aperture area, in step (2), taking row number as horizontal coordinate, and taking average value of row pixel as vertical coordinate, making curve AVG, determining row number range of interface M through wave trough M, and making derivation of curve AVG, getting change rate DEV=AVG', at the same time, making graph of derivative, the point with maximum change rate in the graph is N point, referring to average value of row pixel and derivative table, the row number of interface M is the row number of the point nearest to N point, and the row number is greater than N point, and the average value of row pixel is minimum.

2. The method of claim 1, wherein the step of determining the area of the boule aperture is performed by: In step (2), the specific method of taking average value of row pixel is as follows: ​ There are C points in each row of the image 总 The average value of all points pixels in the xth row is calculated , = (A1+A2+A3...+A C总 ) / C 总 (1).

3. The method of claim 2, wherein the step of determining the area of the boule aperture comprises the steps of: determining the center of the boule aperture; and determining the area of the boule aperture based on the center of the boule aperture. In step (1), the row number is 533 in total, the column number is 280 in total, the pixel value of the point in the picture is between 0 and 255, the pixel value of black is 0, and the pixel value of white is 255.

4. The method of claim 1, wherein the step of determining the area of the boule aperture is performed by a computer program. In step (2), M1=N1+X (2) M1 is the row number of interface M; N1 is the row number of the point with maximum change rate of average value of row pixel N, and X is offset, and X is positive value.

5. The method of claim 1, wherein the step of determining the area of the boule aperture comprises the step of: In step (3), the method of treating the area below M interface as black is that all pixel values below M interface are changed to 0. ​

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