A method for detecting particles on the surface of a mask glass area

Abstract

The present invention discloses a method for detecting surface particles in the glass area of ​​a mask. The method comprises the following steps: S01: initializing a defect result matrix C and obtaining an image T obtained by illuminating the mask with transmitted light; S02: identifying chromium areas in image T and assigning corresponding "ignore" marks to pixels representing the chromium areas in the defect result matrix C; S03: identifying edge areas in image T after removing the chromium areas and assigning corresponding "ignore" marks to pixels representing the edge areas in the defect result matrix C; S04: filtering out the chromium areas and edge areas marked in steps S2 and S3 from image T, leaving only the glass area; identifying defects in the glass area and assigning corresponding "defect" marks to pixels representing defects in the defect result matrix C; and S05: performing a closing operation on the defect result matrix C, then counting defect locations and filtering defects based on length and / or width parameters to obtain final defect data. The method improves the capture sensitivity of defects in the glass area and effectively avoids interference from edges in defect detection.

Description

Technical Field

[0001] The invention relates to a method for detecting particles on the surface of a mask glass region, belonging to the technical field of semiconductor detection. Background Art

[0002] Currently, once a defect occurs in a mask, it is repeatedly propagated to every chip or wafer, directly impacting the yield of the photolithography process. Semiconductor mask hard defects are typically detected using transmitted light. The glass layer is light-transmissive, while the chromium layer is opaque. During photolithography, particles in the glass area are more severe than those in the chromium layer, and can cause fatal defects in the chip. Therefore, effectively detecting these glass particle defects is crucial. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a method for detecting particles on the surface of the glass area of ​​a mask, which improves the capture sensitivity of defects in the glass area and can effectively avoid the interference of edges on defect judgment.

[0004] In order to solve the above technical problems, the technical solution of the present invention is: a method for detecting particles on the surface of a mask glass area, the method comprising the following steps:

[0005] S01: Initialize the defect result matrix C and obtain the image T obtained by irradiating the mask with transmitted light;

[0006] S02: Identify the chromium area in the image T and mark the pixels representing the chromium area as being ignored in the defect result matrix C;

[0007] S03: Identify edge areas in the image T from which the chrome area is removed, and assign corresponding ignore marks to pixel points representing the edge areas in the defect result matrix C;

[0008] S04: Filter out the chrome area and edge area marked in steps S2 and S3 from the image T, leaving the glass area; identify defects in the glass area, and assign corresponding defect marks to the pixels representing the defects in the defect result matrix C;

[0009] S05: Perform a closing operation on the defect result matrix C, then count the defect locations, and filter the defects according to the length and / or width parameters of the defects to obtain the final defect data.

[0010] Further, step S02 is specifically as follows:

[0011] A grayscale threshold Thrd is set, and each pixel point [x, y] in the image T is traversed; when the grayscale value of a pixel point [x, y] is less than the grayscale threshold Thrd, the pixel point [x, y] is considered to be a chromium area, and the value of the pixel point [x, y] in the defect result matrix C is set to an ignore flag value representing ignore.

[0012] Further, step S03 is specifically as follows:

[0013] An edge distance threshold range is set, and each pixel point [x, y] in the image T is traversed except the pixel point representing the chrome area in step S02; wherein, when the grayscale value of the neighboring pixel point [x1, y1] of a certain pixel point [x, y] is less than the grayscale threshold Thrd, the pixel point [x1, y1] is considered to be an edge area, and the value of the pixel point [x1, y1] in the defect result matrix C is set to an ignore mark value representing ignore; wherein, x-range≤x1≤x+range, y-range≤y1≤y+range.

[0014] Furthermore, defects are identified in the glass area, and corresponding defect identification is performed on the pixel points representing defects in the defect result matrix C. Specifically, a grayscale change threshold GrayThrd is set, and each pixel point in the glass area and the adjacent pixel points are used as a pixel set. When the difference between the maximum and minimum grayscale values ​​of each pixel point in the pixel set is less than the grayscale change threshold GrayThrd, the value of the pixel point in the defect result matrix C is set to the ignore identification value representing ignore; otherwise, the value of the pixel point in the defect result matrix C is set to the defect identification value representing the defect.

[0015] Furthermore, the ignore flag value is 0.

[0016] Furthermore, the defect identification value is 255.

[0017] Furthermore, in the pixel set, the adjacent pixel points are the pixel points adjacent to the right, adjacent to the bottom, and diagonally to the lower right of the corresponding pixel point.

[0018] Furthermore, the defect result matrix C is initialized to be an all-0 matrix.

[0019] Furthermore, in step S05 , the defect positions in the defect result matrix C are mapped to the original graph for marking.

[0020] After adopting the above technical solution, when detecting by the method of the present invention, it is not necessary to provide design documents, but only the imaging data of the transmitted light, that is, the image T obtained by irradiating the mask with the transmitted light. The image T can be divided into three parts, namely: the glass area, the chrome area, and the edge area. The edge area is the transition area between the glass area and the chrome area. The chrome area is a completely opaque area, and its grayscale value is lower than the grayscale values ​​of the glass area, the edge area, and the particle defect. The present invention separates the glass area, the chrome area, and the edge area through appropriate methods, and then identifies the particle defects in the glass area; during the exposure process of the photolithography process, the particle defects will change the transmission of light, resulting in insufficient energy at the position that needs to be exposed. The present invention utilizes the characteristics of insufficient light energy during exposure of the particle defects and the opaque characteristics of the chromium shading material to detect glass dust particles and detached chromium, which is very convenient and highly sensitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a transmitted light detection diagram of the present invention;

[0022] FIG2(A) is a diagram of a transmitted light detection area of ​​the present invention;

[0023] FIG2(B) is a diagram showing the local grayscale value of the chrome area detected by transmitted light according to the present invention;

[0024] FIG3(A) is an edge region of a transmitted light detection diagram of the present invention;

[0025] FIG3(B) is a diagram showing the local grayscale value at the corner of the transmitted light detection image of the present invention;

[0026] FIG4(A) is a glass area of ​​a transmitted light detection diagram of the present invention;

[0027] FIG4(B) is a transmitted light detection diagram of the present invention showing the local grayscale value of particles in the glass area;

[0028] Figure 5 Schematic diagram of the defect result matrix C of the present invention;

[0029] Figure 6 This is a defect location diagram of the present invention. DETAILED DESCRIPTION

[0030] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments in conjunction with the accompanying drawings.

[0031] like Figures 1 to 6 As shown, a method for detecting particles on the surface of a mask glass area includes the following steps:

[0032] S01: Initialize the defect result matrix C and obtain the image T obtained by irradiating the mask with transmitted light, such as Figure 1 As shown; wherein, the defect result matrix C can be initialized to an all-0 matrix;

[0033] S02: Identify the chromium area in the image T and assign a corresponding ignore mark to the pixel points representing the chromium area in the defect result matrix C. Specifically, set a grayscale threshold Thrd and traverse each pixel point [x, y] in the image T. When the grayscale value of a certain pixel point [x, y] is less than the grayscale threshold Thrd, the pixel point [x, y] is considered to be a chromium area, and the value of the pixel point [x, y] in the defect result matrix C is set to an ignore mark value representing ignore, and finally separate the black area shown in Figure 2(A). The ignore mark value can be 0.

[0034] S03: Identify the edge area in the image T where the chrome area is removed, and assign a corresponding ignore mark to the pixel points representing the edge area in the defect result matrix C; specifically, set an edge distance threshold range, and traverse each pixel point [x, y] in the image T except the pixel points representing the chrome area in step S02; wherein, when the grayscale value of the neighboring pixel point [x1, y1] of a certain pixel point [x, y] is less than the grayscale threshold Thrd, the pixel point [x1, y1] is considered to be an edge area, and the value of the pixel point [x1, y1] in the defect result matrix C is set to an ignore mark value representing ignore, and finally separate the non-white area shown in Figure 3(A); wherein, x-range≤x1≤x+range, y-range≤y1≤y+range; the ignore mark value can also be 0;

[0035] S04: Filter out the chrome area and edge area marked in steps S2 and S3 from the image T, leaving the glass area (the gray area in Figure 4(A)); identify defects in the glass area, and assign corresponding defect marks to the pixels representing the defects in the defect result matrix C; specifically, set a grayscale change threshold GrayThrd, and use each pixel in the glass area and its adjacent pixels as a pixel set. When the difference between the maximum and minimum grayscale values ​​of each pixel in the pixel set is less than the grayscale change threshold GrayThrd, the value of the pixel in the defect result matrix C is set to the ignore mark value representing the ignore mark; otherwise, the value of the pixel in the defect result matrix C is set to the defect mark value representing the defect. The ignore mark value can also be 0, and the defect mark value can be 255.

[0036] S05: Perform a closed operation on the defect result matrix C, then count the defect locations, filter the defects according to the length (preset parameter) and / or width (preset parameter) parameters of the defects, and obtain the final defect data, such as Figure 5 As shown; then the non-zero positions in the defect result matrix C are mapped to the original graph for marking, and the data finally presented to the user is Figure 6 .

[0037] In this embodiment, in the pixel set, the adjacent pixel points are the pixel points adjacent to the right, adjacent to the bottom, and diagonally to the lower right of the corresponding pixel point.

[0038] In this embodiment, the grayscale threshold Thrd can be specifically 60; the edge distance threshold range can be specifically 3; the grayscale change threshold GrayThrd can be set in the range of [25,35]. When the value is less than 25, false defects will be caused near the edge of the graphic. When the value is greater than 35, defects will be missed.

[0039] In summary, this method has a very high sensitivity for capturing particles in the glass area of ​​the mask, and can simultaneously capture hard defects such as chromium oxide shedding, which can effectively avoid the interference of edges on defect judgment.

[0040] The specific embodiments described above further illustrate the technical problems, technical solutions and beneficial effects solved by the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting particles on the surface of a mask glass area, characterized in that: The steps of the method include: S01: Initialize the defect result matrix C and obtain the image T obtained by irradiating the mask with transmitted light; S02: Identify the chromium area in the image T and mark the pixels representing the chromium area as being ignored in the defect result matrix C; S03: Identify edge areas in the image T from which the chrome area is removed, and assign corresponding ignore marks to pixel points representing the edge areas in the defect result matrix C; S04: Filter out the chrome area and edge area marked in steps S2 and S3 from the image T, leaving the glass area; identify defects in the glass area, and assign corresponding defect marks to the pixels representing the defects in the defect result matrix C; S05: Perform a closing operation on the defect result matrix C, then count the defect locations, filter the defects based on the length and / or width parameters of the defects, and obtain the final defect data; Step S02 is specifically as follows: Set a grayscale threshold Thrd and traverse each pixel [x, y] in the image T. When the grayscale value of a pixel [x, y] is less than the grayscale threshold Thrd, the pixel [x, y] is considered to be a chromium area, and the value of the pixel [x, y] in the defect result matrix C is set to an ignore flag value indicating that it is ignored. Step S03 is specifically as follows: Set an edge distance threshold range, and traverse each pixel [x, y] in the image T except the pixel representing the chrome area in step S02; when the grayscale value of the neighboring pixel [x1, y1] of a certain pixel [x, y] is less than the grayscale threshold Thrd, the pixel [x1, y1] is considered to be an edge area, and the value of the pixel [x1, y1] in the defect result matrix C is set to an ignore flag value representing ignore; wherein, ; Defects are identified in the glass area, and corresponding defect marks are assigned to pixels representing defects in the defect result matrix C. Specifically, a grayscale change threshold GrayThrd is set. Each pixel in the glass area and its adjacent pixels are considered a pixel set. When the difference between the maximum and minimum grayscale values ​​of each pixel in the pixel set is less than the grayscale change threshold GrayThrd, the value of the pixel in the defect result matrix C is set to the ignore mark value, indicating that it is ignored. Otherwise, the value of the pixel in the defect result matrix C is set to the defect mark value, indicating that it is a defect. The ignore flag value is 0; The defect identification value is 255; Initialize the defect result matrix C to an all-0 matrix.

2. The method according to claim 1, characterized in that In the pixel set, the neighboring pixels are the pixels to the right, below, and lower right corner of the corresponding pixel.

3. The method according to claim 1, characterized in that In step S05 , the defect positions in the defect result matrix C are mapped to the original graph for marking.

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