KR101310029B1 - Detecting method of alignment mark - Google Patents

Detecting method of alignment mark Download PDF

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KR101310029B1
KR101310029B1 KR1020120026231A KR20120026231A KR101310029B1 KR 101310029 B1 KR101310029 B1 KR 101310029B1 KR 1020120026231 A KR1020120026231 A KR 1020120026231A KR 20120026231 A KR20120026231 A KR 20120026231A KR 101310029 B1 KR101310029 B1 KR 101310029B1
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alignment mark
center
inspection
image
lines
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KR1020120026231A
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Korean (ko)
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김윤혁
김재천
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삼성모바일디스플레이주식회사
주식회사 에이치비테크놀러지
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
    • H01L22/20—Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L23/00—Details of semiconductor or other solid state devices
    • H01L23/544—Marks applied to semiconductor devices or parts, e.g. registration marks, alignment structures, wafer maps
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L2223/00—Details relating to semiconductor or other solid state devices covered by the group H01L23/00
    • H01L2223/544—Marks applied to semiconductor devices or parts
    • H01L2223/54426—Marks applied to semiconductor devices or parts for alignment

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  • Computer Hardware Design (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Power Engineering (AREA)
  • Manufacturing & Machinery (AREA)
  • Physics & Mathematics (AREA)
  • Condensed Matter Physics & Semiconductors (AREA)
  • General Physics & Mathematics (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Processing (AREA)

Abstract

The present invention relates to an alignment mark detection method, and more particularly, to obtain an alignment mark image of a substrate using a camera, extracting an inspection image including the center of the alignment mark from the image, and extracting the alignment mark from the inspection image. Setting a virtual inspection area to include a center part, setting two or more pairs of boundary lines parallel to each other based on the center of the alignment mark among the boundary lines of the inspection area passing through the alignment mark as inspection lines, and Checking the pixel value of the corresponding image, checking each section in which the pixel value changes among each pixel value corresponding to each inspection line, displaying the pixel value of each section as a graph, and curve fitting the graph. Extracting the three-dimensional curve equation, the three-dimensional curve according to the curve fitting The second derivative of the equation, the second derivative to check the coordinate value of the pixel value 0 in the corresponding inspection line, the center coordinate value of this straight line by connecting the two zero coordinate values of each inspection line in a straight line And forming a center connection line connecting the center coordinate values of each pair of inspection lines parallel to each other in a straight line, and checking the coordinate values at which the center connection lines cross each other. Check the actual center point of the alignment mark with the coordinate of the intersection point where the connecting lines intersect.

Description

Detecting method of alignment mark

The present invention relates to a detection method, and more particularly, to obtain an alignment mark image using a single camera, extract a graph and equation for a section in which a pixel value is continuously changed from the image, and extract the alignment mark boundary coordinates. The present invention relates to an alignment mark detection method capable of confirming and confirming the center coordinates of an alignment mark using each boundary coordinate.

In general, when a pattern is formed on a semiconductor substrate, each alignment mark position of the substrate and the mask for forming the pattern on the substrate is aligned in the vertical direction, and then the pattern is formed on the substrate.

To this end, it is necessary to confirm the exact position of each alignment mark formed on the substrate and the original substrate, and each alignment mark is detected by a camera having a lens.

Of course, the camera is naturally used as an alignment microscope.

As described in Patent Registration No. 10-0506937 (July 30, 2005), a method of detecting an alignment mark is performed by sequentially photographing an alignment mark using a plurality of alignment microscopes and detecting the position thereof.

In other words, any portion of the substrate is picked up through the low magnification lens of the alignment microscope, and the image is compared with the reference data, and if any alignment mark is detected at the same position as the reference data, the substrate is moved by a predetermined coordinate.

Then, any other portion of the substrate is imaged through the high magnification lens of the alignment microscope, and the alignment mark is detected by comparing the image data with the reference data.

If the alignment mark is detected at the same position as the reference data through this process, the substrate is recognized at the correct position and proceeds to the next process. If the alignment mark is not detected at the same position as the reference data, alignment fail Recognize).

However, even if the alignment mark is located at the correct position, it may be an alignment fail. This is because there is no problem in the image of the alignment mark captured by the alignment microscope, but due to the characteristics of the semiconductor, there is a slight difference from the reference data. It happens as it happens.

For example, if the thickness of any one of the patterns composed of several layers on the substrate is slightly different, there is a difference in luminance in the image but there is no problem in the process.

Therefore, as described above, there is no problem in the process, but the reference data and the captured data have a problem in that alignment failure is caused by an image difference, and thus the process is delayed or a defective rate is generated.

In addition, even when comparing the alignment mark and the reference data, there is a limit in matching the center of the actual alignment mark because an error of the region of the actual alignment mark and the region recognized by each pixel is generated.

Accordingly, the present invention has been made to solve the above problems, to set the inspection area in the image including the alignment mark center point obtained by using a camera and a lens, and parallel to form the boundary of the inspection area Two pairs of test lines are formed, and a graph is formed for a section in which pixel values are continuously changed on each test line. Then, an equation by curve fitting is extracted, and this equation is quadraticly differentiated to generate two test lines. After checking the alignment mark boundary coordinates, the intermediate coordinates of these two coordinates are identified, and the two intermediate connecting lines intersect by forming two intersecting intermediate lines that interconnect each intermediate coordinate of two parallel inspection lines. The method of detecting alignment marks, which can check the center coordinates of alignment marks, can be obtained by checking the coordinates. The purpose is to give.

The present invention for achieving the above object, the step of obtaining the alignment mark image of the substrate using a camera, extracting the inspection image including the center of the alignment mark in the image, so that the center of the alignment mark in the inspection image Setting an imaginary inspection area, setting two or more pairs of boundary lines parallel to each other based on a center of the alignment mark among the boundary lines of the inspection area passing through the alignment mark as inspection lines; Checking a pixel value of a corresponding image, checking each section in which a pixel value changes among each pixel value corresponding to each inspection line, displaying a pixel value of each section as a graph, and curve fitting the graph ( extracting a 3D curve equation by fitting the curve, fitting the curve Quadratic differentiation of the three-dimensional curve equation according to the step; identifying coordinate values having a pixel value of zero in the corresponding inspection line by the second derivative; connecting two zero coordinate values of each inspection line with a straight line Checking a center coordinate value of the straight line, and forming a center connection line connecting the center coordinate values of the pair of inspection lines parallel to each other in a straight line, and checking the coordinate values at which the center connection lines intersect each other. It comprises a step, to identify the actual center point of the alignment mark with the coordinates of the intersection point where each of the center connecting lines intersect.

The extracting of the inspection image may include sequentially ordering a normal image including a central portion of an alignment mark image of a mask for forming a pattern on the substrate from the alignment mark image of the substrate obtained in the acquiring of the alignment mark image. In comparison, the inspection image including the center of the alignment mark is extracted as the position where the difference between the corresponding pixel values is the smallest is identified.

The inspection line passes through the alignment mark, and both ends thereof are positioned on a background in which the alignment mark and the color are distinguished.

In addition, the virtual inspection area is square or rectangular, and includes a center portion of the alignment mark, and two pairs of inspection lines that are parallel to each other are set, and each inspection line has a pixel value through the second derivative. Two straight lines each having two coordinate values of 0 and connecting the two coordinate values are formed, and the center coordinate values of each pair of test lines parallel to each other are checked by checking the center coordinate value of each straight line. Coordinate values are formed to form two center connection lines, and as the coordinate values of the intersection points at which the two center connection lines intersect are identified, the actual center point of the alignment mark is identified using the intersection point coordinate values.

As described above, according to the alignment mark detection method according to the present invention, the boundary mark and the center coordinate value of the alignment mark can be confirmed by using the pixel value continuously changing in the image including one alignment mark. It is a very useful and effective invention that can be confirmed more precisely than before.

1 is a view showing an alignment mark detection method according to the present invention,
2 is a diagram illustrating a center point extraction step of an alignment mark according to the present invention;
3 is a diagram illustrating an inspection line setting step according to the present invention;
4 is a diagram illustrating steps of graphing pixel values according to the present invention;
5 is a view showing a three-dimensional curve equation extraction step according to the present invention,
6 is a diagram showing the second derivative step of the three-dimensional curve equation according to the present invention,
7 is a diagram illustrating a step of checking coordinate values intersecting a center connection line according to the present invention.

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings.

It should be noted that the present invention is not limited to the scope of the present invention but is only illustrative and various modifications are possible within the scope of the present invention.

1 is a diagram illustrating an alignment mark detection method according to the present invention, FIG. 2 is a diagram illustrating a center point extraction step of an alignment mark according to the present invention, and FIG. 3 is a diagram illustrating an inspection line setting step according to the present invention. 4 is a diagram illustrating a step of graphically representing pixel values according to the present invention, FIG. 5 is a diagram illustrating a three-dimensional curve equation extraction step according to the present invention, and FIG. FIG. 7 is a diagram illustrating a second derivative step of a dimensional curve equation, and FIG. 7 is a diagram illustrating a coordinate value checking step of a center connection line according to the present invention.

As shown in the figure, the alignment mark detection method includes an alignment mark image acquisition step S10, an inspection image extraction step S20, a virtual inspection area setting step S30, an inspection line setting step S40, and an inspection line image. Pixel value checking step (S50), the step of graphing the pixel value (S60), three-dimensional curve equation extraction step (S70), three-dimensional curve equation second derivative step (S80), check the coordinate value of the pixel value 0 Step S90, the step of checking the center coordinate value of the straight line connecting the two zero coordinate values (S100) and the step of checking the intersecting coordinate values of the center connecting line connecting the center coordinate values by the straight lines, respectively (S110).

First, in the alignment mark image acquisition step (S10), the alignment mark image 20 of the substrate 10 is obtained by using a camera.

In addition, the inspection image extraction step S20 extracts the inspection image 25 including the center of the alignment mark 30 from the alignment mark image 20, and the virtual inspection area setting step S30 is the alignment mark 30. The virtual inspection area 40 including the center of the set will be set.

The inspection line setting step S40 includes two or more pairs of boundary lines parallel to each other based on the center of the alignment mark 30 among the boundary lines of the inspection area 40 passing through the alignment mark 30, respectively. Will be set.

In addition, the pixel value check step (S50) of the inspection line image confirms the pixel value of the image corresponding to each inspection line 50, and the step (S60) of representing the pixel value as a graph corresponds to each inspection line 50. Each section in which the pixel value changes among each pixel value is checked, and the pixel value of each section is graphed.

Dimensional curve equation extraction step (S70) is curve fitting (curve fitting) the graph, it is to extract the three-dimensional curve equation using the graph.

The second-order differential step (S80) of the three-dimensional curve equation is the second-order differentiation of the three-dimensional curve equation according to the curve fitting, and the first-order differentiation of the three-dimensional curve equation, and the second derivative of the first-order differential equation.

In the coordinate value checking step (S90) in which the pixel value is zero, the coordinate value having the pixel value of zero is confirmed in the corresponding inspection line 50 by the second derivative.

In addition, the step of checking the center coordinate value of the straight line connecting two zero coordinate values (S100) confirms the center coordinate value of the straight line by connecting two zero coordinate values of each inspection line 50 with a straight line.

The intersecting coordinate value checking step (S110) of the center connection line connecting the center coordinate values with straight lines respectively connects the center connection line 60 connecting the center coordinate values of each pair of parallel inspection lines 50 with each other in a straight line. And the coordinate value P at which the center connection line 60 intersects.

Here, the actual center point of the alignment mark 30 is identified by the intersection point value P at which the center connection lines 60 intersect, and the intersection point value P is the actual center point of the alignment mark 30.

As such, after confirming the center point of each alignment mark 30 of the substrate 10 on which the pattern is to be formed, the pattern to be formed is precisely matched with each center point of the corresponding alignment mark of the original substrate 1 on which the pattern is formed. Can be formed.

Of course, each center point of each alignment mark of the mask 1 can also be confirmed by the said method.

Here, the inspection image extraction step (S20) is an alignment mark image of the mask (1) for forming a pattern on the substrate 10 from the alignment mark image of the substrate 10 obtained in the step (S10) to obtain an alignment mark image The normal image including the center of the image (2) is sequentially compared and confirmed.

In other words, as shown in FIG. 2, by filtering the alignment mark image of the substrate 10 by the normal image 2, the difference between the corresponding pixel values of the normal image 2 and the alignment mark image is confirmed. As the position having the smallest value is identified, the region including the center point in the alignment mark image of the substrate 10 may be identified.

Accordingly, the inspection image 25 including the center of the alignment mark can be extracted.

In the inspection line setting step S40, the inspection line 50 passes through the alignment mark 30, and both ends thereof are positioned on the background where the alignment mark 30 and the color are distinguished.

In other words, each inspection line 50 is formed to pass through a portion of the alignment mark 30 so that two portions of the continuous pixel values on the inspection line 50 are present in two sections so that the boundary of the alignment mark 30 is present. This is to check the coordinate corresponding to.

Here, as shown in FIG. 3, in one embodiment, the virtual inspection area 40 is set to a square or a rectangle to include a center point of the alignment mark 30.

Accordingly, the inspection line 50 has two pairs of inspection lines 50 parallel to each other, and each inspection line 50 has coordinate values of zero pixel values through the second derivative step S80. You will have two.

Four straight lines are formed to connect the two coordinate values, and the center coordinates of each straight line are checked to form two center connecting lines by connecting the center coordinates of the parallel lines. As the coordinate values of the intersection points where the two center connection lines intersect, the actual center point of the alignment mark is identified by the intersection point coordinate values.

Looking at the process of confirming the coordinate value of the pixel value is 0, the pixel value of the inspection line image is confirmed in step (S50) to check each pixel value of the image corresponding to each inspection line 50, and then shown in FIG. As described above, each pixel value corresponding to each inspection line 50 is graphed in the step S60 of displaying the pixel values in the graph.

Of course, the graph only shows a section in which the pixel value changes in the inspection line 50, and the graph is constructed by setting the coordinate value of the pixel to 0 before the change of the pixel value starts.

As an example, the graph illustrated in FIG. 4 illustrates pixel values for respective positions of a continuously changing section among pixel values of the inspection line 50. The lowest pixel value is 10 and the highest pixel value is Assume 60.

Accordingly, pixel values of each pixel of the inspection line 50 illustrated in the graphs are 10, 10, 20, 40, 50, 60, and 60, as shown in the drawing.

As shown in FIG. 5, the graph of FIG. 4 is shown by curve fitting, and a three-dimensional curve equation can be extracted.

This three-dimensional curve equation,

Figure 112012020716575-pat00001
Is,

By substituting the values of a, b, c, and d, the corresponding three-dimensional curve equation can be extracted.

In one embodiment, a = -0.8333, b = 9.7619, c = -22.262, d = 22.857, if you substitute,

Figure 112012020716575-pat00002
to be.

As shown in FIG. 6, the first-order derivative of the three-dimensional curve equation for the curved-fitted three-dimensional curve of FIG. 5 is followed by the second derivative.

The second derivative is

Figure 112012020716575-pat00003
Is,

The equations can be extracted by substituting the values of e and f.

If the second derivative of the three-dimensional curve equation of the above embodiment,

Figure 112012020716575-pat00004
to be.

In the step S90 of checking the coordinate value of the pixel value (S90), the value of x is substituted by inserting 0 into y so that the coordinate of the pixel value is 0.

Substituting 0 for y in the second derivative of the second equation,

Figure 112012020716575-pat00005
to be.

Here, the coordinate value at which the x value of each graph corresponds to 1.952 can be confirmed.

Of course, on the contrary, it is natural that the inspection line 50 has intervals of 60, 60, 50, 40, 20, 10, and 10 with pixel values of each pixel. Through the second derivative of the three-dimensional curve equation, the coordinate value of the pixel value is identified.

Accordingly, the two coordinate values having the pixel value of 0 are identified in each inspection line 50, and the two coordinate values having the pixel value of 0 are respectively identified at the four inspection lines 50 according to an exemplary embodiment. do.

Here, x in the graph is a coordinate value, and y represents a pixel value, and it is applicable even if four inspection lines 50 set in the inspection area 40 are formed horizontally and vertically, respectively.

As shown in FIG. 7, four inspection lines 50 are designated as A, B, C, and D, respectively, and zero coordinate values of the inspection line A are designated as (A1, A) and (A2, A), respectively. , The coordinate values of 0 of inspection line B are (B, B1) and (B, B2), respectively, and the coordinate values of 0 of inspection line C are (C1, C) and (C2, C), respectively. The coordinate values of 0 are denoted by (D, D1) and (D, D2), respectively.

After checking the center coordinate value of the straight line connecting the two zero coordinate values (S100), after confirming the center value of the straight line connecting the two zero coordinate values of each inspection line 50, the center coordinate value accordingly Will be confirmed.

In other words, the center value of the straight line connecting (A1, A) and (A2, A) is

Figure 112012020716575-pat00006
The coordinate value can be checked using the center value (A3, A).

In this way, straight lines (B) connecting (B, B1) and (B, B2), straight lines (C), (D, D1) and (D, connecting (C1, C) and (C2, C) The center coordinate values can be confirmed by checking the respective center values (B, B3), (C3, C), and (D, D3) with respect to the straight line D connecting D2).

The center connecting line K is formed by connecting the center coordinates (A3, A) and (C3, C) of the parallel lines A and C, and the center coordinates (B, B3) of the B and D, which are parallel to each other. Form a center connection line L connecting and (D, D3), respectively.

The coordinate values at which the center connection line K intersects with the center connection line L are checked at step S110 of checking the coordinate values intersecting with the center connection line, and the center connection line K and the center connection line L are two linear functions as a linear function. You can check the intersection.

To do this, look at the equation,

The equation for a straight line (K) connecting (A3, A) and (C3, C) is m1x + n1 = y,

m1 = (A-C) / (A3-C3),

n1 = A-m1 x A3.

Here, A and C correspond to y of the corresponding coordinate value, and A3 and C3 correspond to x of the corresponding coordinate value.

The equation for a straight line (L) connecting (B, B3) and (D, D3) is m2x + n2 = y,

m2 = (B3-D3) / (B-D)

n2 = B3-m2 * B.

Here, B and D correspond to y of the corresponding coordinate value, and B3 and D3 correspond to x of the corresponding coordinate value.

P (x, y) is the point where two straight lines (K and L) intersect.

x = (n1-n2) / (m2-m1)

y = [m1 × {(n1-n2) / (m2-m1)}] + n1

Accordingly, the point P (x, y) at which the two center connection lines intersect can be confirmed, and the coordinate value of the center point of the alignment mark can be confirmed by the intersection point P (x, y). The alignment marks can be aligned more precisely and easily than in the prior art, thereby improving the precision and quality of the work.

1: Mask 2: Normal image
10: substrate 20: alignment mark image
25: inspection image 30: alignment mark
40: inspection area 50: inspection line
60: center connection line P: intersection coordinate value

Claims (4)

Obtaining an alignment mark image of a substrate using a camera;
Extracting an inspection image including a center portion of an alignment mark from the image;
Setting a virtual inspection area to include a center portion of an alignment mark in the inspection image;
Setting at least two pairs of boundary lines parallel to each other based on a center of the alignment mark among the boundary lines of the inspection area passing through the alignment mark as respective inspection lines;
Checking a pixel value of an image corresponding to each inspection line;
Checking each section in which the pixel value changes among the pixel values corresponding to each of the inspection lines, and displaying the pixel values of each section in a graph;
Curve fitting of the graph to extract a three-dimensional curve equation;
Second derivative of the three-dimensional curve equation according to the curve fitting;
Confirming a coordinate value having a pixel value of 0 by the second derivative in a corresponding inspection line;
Confirming a center coordinate value of the straight line by connecting two zero coordinate values of each inspection line with a straight line; And
And forming a center connection line connecting the center coordinate values of the pair of inspection lines parallel to each other in a straight line, and checking the coordinate values at which the center connection lines cross each other.
Alignment mark detection method, characterized in that for confirming the actual center point of the alignment mark by the intersection coordinate value of each of the center connection line.
The method of claim 1, wherein the extracting the inspection image comprises:
From the alignment mark image of the substrate obtained in the step of acquiring the alignment mark image, the normal image including the center portion of the alignment mark image of the mask for forming the pattern is sequentially compared to have the smallest difference between the corresponding pixel values. Alignment mark detection method, characterized in that for extracting the inspection image including the center of the alignment mark in accordance with the position.
The method of claim 1, wherein the inspection line,
Alignment mark detection method, characterized in that both ends of the alignment mark and the alignment mark and the color is located on the background is distinguished.
The method of claim 1,
The virtual inspection area is square or rectangular, and includes a center of the alignment mark, and two pairs of inspection lines parallel to each other are set.
Each of the inspection lines has two coordinate values each having a pixel value of zero through the second differentiation step, and four straight lines connecting the two coordinate values are formed.
Check the center coordinates of each straight line to form two center connecting lines by connecting the center coordinates of each pair of parallel inspection lines among the center coordinates,
And identifying an actual center point of the alignment mark based on the intersection point coordinates as the coordinate values of the intersection points where the two center connection lines intersect.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111142343A (en) * 2020-01-02 2020-05-12 长江存储科技有限责任公司 Method for generating center coordinates of alignment mark
CN117080142A (en) * 2023-10-11 2023-11-17 迈为技术(珠海)有限公司 Positioning method for center point of alignment mark and wafer bonding method

Citations (4)

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Publication number Priority date Publication date Assignee Title
JPH0663740B2 (en) * 1987-09-28 1994-08-22 住友重機械工業株式会社 Alignment mark position detection method
JP2532926B2 (en) 1988-09-29 1996-09-11 住友重機械工業株式会社 Alignment mark position detection method
JP2004111860A (en) 2002-09-20 2004-04-08 Canon Inc Position detecting method and device
JP2005030963A (en) 2003-07-08 2005-02-03 Canon Inc Position detecting method

Patent Citations (4)

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Publication number Priority date Publication date Assignee Title
JPH0663740B2 (en) * 1987-09-28 1994-08-22 住友重機械工業株式会社 Alignment mark position detection method
JP2532926B2 (en) 1988-09-29 1996-09-11 住友重機械工業株式会社 Alignment mark position detection method
JP2004111860A (en) 2002-09-20 2004-04-08 Canon Inc Position detecting method and device
JP2005030963A (en) 2003-07-08 2005-02-03 Canon Inc Position detecting method

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111142343A (en) * 2020-01-02 2020-05-12 长江存储科技有限责任公司 Method for generating center coordinates of alignment mark
CN117080142A (en) * 2023-10-11 2023-11-17 迈为技术(珠海)有限公司 Positioning method for center point of alignment mark and wafer bonding method
CN117080142B (en) * 2023-10-11 2024-02-06 迈为技术(珠海)有限公司 Positioning method for center point of alignment mark and wafer bonding method

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