阅读说明：本技术 一种掩模表面颗粒缺陷检测方法 (Mask surface particle defect detection method ) 是由 刘建明 刘庄 于 2021-08-05 设计创作，主要内容包括：本发明公开了一种掩模表面颗粒缺陷检测方法,方法的步骤中包括：获取透射光照射掩模得到的透射灰度图像T和反射光照射掩模得到的反射灰度图像R,对反射灰度图像进行反色运算得到反射灰度反色图像；获取透射灰度图像和反射灰度反色图像中各像素的法向量的方向角角度数据,根据相应方向角角度数据构建透射图像角度矩阵A和反射图像角度矩阵B；对透射图像角度矩阵A和反射图像角度矩阵B进行数据分析,得到缺陷位置,根据缺陷位置构建缺陷结果矩阵C。本发明能够很好地识别颗粒缺陷,检测产能高。(The invention discloses a method for detecting particle defects on the surface of a mask, which comprises the following steps: acquiring a transmission gray image T obtained by irradiating the mask by the transmission light and a reflection gray image R obtained by irradiating the mask by the reflection light, and performing reverse color operation on the reflection gray image to obtain a reflection gray reverse color image; acquiring direction angle data of normal vectors of pixels in the transmission gray level image and the reflection gray level reverse color image, and constructing a transmission image angle matrix A and a reflection image angle matrix B according to the corresponding direction angle data; and performing data analysis on the transmission image angle matrix A and the reflection image angle matrix B to obtain defect positions, and constructing a defect result matrix C according to the defect positions. The invention can well identify the particle defects and has high detection productivity.)

1. A method for detecting particle defects on the surface of a mask is characterized by comprising the following steps:

acquiring a transmission gray image T obtained by irradiating the mask by the transmission light and a reflection gray image R obtained by irradiating the mask by the reflection light, and performing reverse color operation on the reflection gray image to obtain a reflection gray reverse color image;

acquiring direction angle data of normal vectors of pixels in the transmission gray level image and the reflection gray level reverse color image, and constructing a transmission image angle matrix A and a reflection image angle matrix B according to the corresponding direction angle data;

performing data analysis on the transmission image angle matrix A and the reflection image angle matrix B to obtain defect positions, and constructing a defect result matrix C according to the defect positions;

in the process of acquiring the direction angle data of the normal vector of each pixel: taking the pixel and the adjacent pixels of the pixel as a pixel cluster, and when the difference between the maximum value and the minimum value of the gray scale of each pixel in the pixel cluster is smaller than a first gray scale threshold value T1, identifying the direction angle value of the normal vector of the pixel as an angle contrast value; when the difference between the maximum value and the minimum value of the gray scale of each pixel in the pixel cluster is larger than or equal to a first gray scale threshold value T1, calculating the normal vector of the pixel according to the pixel cluster, and acquiring the direction angle value corresponding to the normal vector;

in the data analysis process: when both A (x, y) and B (x, y) are angle comparison values and T (x, y) + R (x, y) is smaller than a second gray level threshold value T2, the position of the corresponding pixel of the coordinate point (x, y) is a defect position;

when A (x, y) is not the angle comparison value and B (x +/-m, y +/-n) is the angle comparison value, the position of the pixel corresponding to A (x, y) is the defect position and is the defect of the glass area;

when A (x, y) is not the angle contrast value and B (x +/-m, y +/-n) has a non-angle contrast value and does not have a direction angle value of which the difference with A (x, y) is less than a preset angle threshold Te, the position of the pixel corresponding to A (x, y) is an edge defect;

when B (x, y) is not the angle comparison value and A (x +/-m, y +/-n) is the angle comparison value, the position of the corresponding pixel of B (x, y) is a defect position and is a defect of a Cr area;

when B (x, y) is not an angle comparison value and A (x +/-m, y +/-n) has a non-angle comparison value and does not have a direction angle value of which the difference with B (x, y) is less than a preset angle threshold Te, the position of the pixel corresponding to B (x, y) is an edge defect; wherein the content of the first and second substances,

a (x, y) is a direction angle value of a normal vector of a pixel under the coordinate point (x, y) in the transmission image angle matrix a;

b (x, y) is a direction angle value of a normal vector of a pixel under the coordinate point (x, y) in the reflection image angle matrix B;

t (x, y) is a gray value of a pixel under the coordinate point (x, y) in the transmission gray image T;

r (x, y) is a gray value of a pixel under the coordinate point (x, y) in the reflection gray image R;

m is a preset search deviation value of the coordinate point x, and n is a preset search deviation value of the coordinate point y.

2. The method of claim 1, further comprising the steps of:

and performing closed operation on the defect result matrix C, then counting the defect positions, and performing defect filtering according to the length and/or width parameters of the defect positions to obtain a final defect result matrix C.

3. The method of claim 2, wherein the step of detecting the particle defects on the surface of the mask comprises,

the defect positions in the final defect result matrix C are mapped onto the transmission gray image T and/or the reflection gray image R.

4. The method of claim 1, wherein the step of detecting the particle defects on the surface of the mask comprises,

for each of the pixels, neighborhood pixels of the pixel are pixels that are right-adjacent, down-adjacent, and down-right diagonal to the pixel.

5. The method of claim 1 or 4, wherein the step of detecting the particle defects on the surface of the mask comprises,

the normal vector of the pixel is calculated as follows:

constructing a coordinate system where the pixel cluster is located;

obtaining a quadrant of each pixel in the pixel group in a coordinate system, and adding a sign to the gray value of the corresponding pixel as a coordinate point value of the pixel according to the quadrant of each pixel;

acquiring a direction vector from a coordinate point of each pixel in the pixel cluster to a coordinate origin of a coordinate system;

the sum of the direction vectors of all pixels in the pixel cluster is calculated, and the reverse vector thereof is taken as the normal vector of the pixel.

Technical Field

The invention relates to a method for detecting particle defects on the surface of a mask, and belongs to the technical field of semiconductor detection.

Background

At present, a semiconductor mask is generally detected by transmitted light aiming at hard defects, a Cr layer is opaque, particles on the surface of the Cr layer cannot be captured, although the Cr layer does not influence photoetching, the particles can drift to a quartz layer or a mosi layer to cause photoetching fatal defects, meanwhile, haze which is also a photoetching fatal defect can be formed after long-time use in a wafer factory, and how to effectively detect the non-logic defects is particularly important.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provide a method for detecting the particle defects on the surface of a mask, which can well identify the particle defects and has high detection productivity.

In order to solve the technical problems, the technical scheme of the invention is as follows: a method for detecting particle defects on the surface of a mask comprises the following steps:

acquiring a transmission gray image T obtained by irradiating the mask by the transmission light and a reflection gray image R obtained by irradiating the mask by the reflection light, and performing reverse color operation on the reflection gray image to obtain a reflection gray reverse color image;

acquiring direction angle data of normal vectors of pixels in the transmission gray level image and the reflection gray level reverse color image, and constructing a transmission image angle matrix A and a reflection image angle matrix B according to the corresponding direction angle data;

performing data analysis on the transmission image angle matrix A and the reflection image angle matrix B to obtain defect positions, and constructing a defect result matrix C according to the defect positions;

in the process of acquiring the direction angle data of the normal vector of each pixel: taking the pixel and the adjacent pixels of the pixel as a pixel cluster, and when the difference between the maximum value and the minimum value of the gray scale of each pixel in the pixel cluster is smaller than a first gray scale threshold value T1, identifying the direction angle value of the normal vector of the pixel as an angle contrast value; when the difference between the maximum value and the minimum value of the gray scale of each pixel in the pixel cluster is larger than or equal to a first gray scale threshold value T1, calculating the normal vector of the pixel according to the pixel cluster, and acquiring the direction angle value corresponding to the normal vector;

in the data analysis process: when both A (x, y) and B (x, y) are angle comparison values and T (x, y) + R (x, y) is smaller than a second gray level threshold value T2, the position of the corresponding pixel of the coordinate point (x, y) is a defect position;

when A (x, y) is not the angle comparison value and B (x +/-m, y +/-n) is the angle comparison value, the position of the pixel corresponding to A (x, y) is the defect position and is the defect of the glass area;

when A (x, y) is not the angle contrast value and B (x +/-m, y +/-n) has a non-angle contrast value and does not have a direction angle value of which the difference with A (x, y) is less than a preset angle threshold Te, the position of the pixel corresponding to A (x, y) is an edge defect;

when B (x, y) is not the angle comparison value and A (x +/-m, y +/-n) is the angle comparison value, the position of the corresponding pixel of B (x, y) is a defect position and is a defect of a Cr area;

when B (x, y) is not an angle comparison value and A (x +/-m, y +/-n) has a non-angle comparison value and does not have a direction angle value of which the difference with B (x, y) is less than a preset angle threshold Te, the position of the pixel corresponding to B (x, y) is an edge defect; wherein the content of the first and second substances,

a (x, y) is a direction angle value of a normal vector of a pixel under the coordinate point (x, y) in the transmission image angle matrix a;

b (x, y) is a direction angle value of a normal vector of a pixel under the coordinate point (x, y) in the reflection image angle matrix B;

t (x, y) is a gray value of a pixel under the coordinate point (x, y) in the transmission gray image T;

r (x, y) is a gray value of a pixel under the coordinate point (x, y) in the reflection gray image R;

m is a preset search deviation value of the coordinate point x, and n is a preset search deviation value of the coordinate point y.

Further, the method comprises the following steps:

and performing closed operation on the defect result matrix C, then counting the defect positions, and performing defect filtering according to the length and/or width parameters of the defect positions to obtain a final defect result matrix C.

Further, the defect positions in the final defect result matrix C are mapped onto the transmission gray image T and/or the reflection gray image R.

For each of the pixels, neighborhood pixels of the pixel are pixels that are right-adjacent, down-adjacent, and down-right diagonal to the pixel.

Further, the method for calculating the normal vector of the pixel is as follows:

constructing a coordinate system where the pixel cluster is located;

obtaining a quadrant of each pixel in the pixel group in a coordinate system, and adding a sign to the gray value of the corresponding pixel as a coordinate point value of the pixel according to the quadrant of each pixel;

acquiring a direction vector from a coordinate point of each pixel in the pixel cluster to a coordinate origin of a coordinate system;

the sum of the direction vectors of all pixels in the pixel cluster is calculated, and the reverse vector thereof is taken as the normal vector of the pixel.

After the technical scheme is adopted, during detection, a design file is not required to be provided, only a transmission image obtained by irradiating the mask with transmission light and a reflection image obtained by irradiating the mask with reflection light are provided at the same time, then normal vector data of each pixel of each image are respectively calculated, and an edge area and a non-edge area can be separated by using angle data of the normal vectors, so that particle defects can be identified by using an angle threshold of the edge area and a gray threshold of the non-edge area, the detection productivity is high, particle detection is more comprehensive than conventional DB detection, DB data required during DB detection is not required, and the data confidentiality is strong.

Drawings

FIG. 1 is a transmission gray scale image of the present invention;

FIG. 2 is a reflected gray image of the present invention;

FIG. 3 is a transmitted light method vector diagram of the present invention;

FIG. 4 is a vector diagram of the reflection optic method of the present invention;

FIG. 5 is a diagram of the defect location of the present invention.

Detailed Description

In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.

A method for detecting particle defects on the surface of a mask comprises the following steps:

acquiring a transmission gray image T (shown in figure 1) obtained by irradiating the mask by the transmission light and a reflection gray image R (shown in figure 2) obtained by irradiating the mask by the reflection light, and performing reverse color operation on the reflection gray image to obtain a reflection gray reverse color image;

acquiring direction angle data of normal vectors of pixels in the transmission gray level image and the reflection gray level reverse color image, and constructing a transmission image angle matrix A (shown in figure 3) and a reflection image angle matrix B (shown in figure 4) according to the corresponding direction angle data;

performing data analysis on the transmission image angle matrix A and the reflection image angle matrix B to obtain defect positions, and constructing a defect result matrix C according to the defect positions;

in the process of acquiring the direction angle data of the normal vector of each pixel: taking the pixel and the adjacent pixels of the pixel as a pixel cluster, and when the difference between the maximum value and the minimum value of the gray scale of each pixel in the pixel cluster is smaller than a first gray scale threshold value T1, identifying the direction angle value of the normal vector of the pixel as an angle contrast value; when the difference between the maximum value and the minimum value of the gray scale of each pixel in the pixel cluster is larger than or equal to a first gray scale threshold value T1, calculating the normal vector of the pixel according to the pixel cluster, and obtaining a direction angle value corresponding to the normal vector, wherein the range of the direction angle value is 0-360 degrees;

in the data analysis process: when a (x, y) and B (x, y) are both angle comparison values and T (x, y) + R (x, y) is smaller than the second gray level threshold T2, the position where the corresponding pixel of the coordinate point (x, y) is located is a defect position, which may be set to 255 in the defect result matrix C;

when a (x, y) is not the angle comparison value and B (x ± m, y ± n) are both the angle comparison values, the position where a (x, y) corresponds to the pixel is the defect position, and is the defect of the glass region, and the defect position may be set to 200 in the defect result matrix C;

when A (x, y) is not the angle contrast value and B (x +/-m, y +/-n) has a non-angle contrast value, and there is no direction angle value whose difference with A (x, y) is less than the preset angle threshold Te, then the position of the pixel corresponding to A (x, y) is an edge defect, and the defect position can be set to 225 in the defect result matrix C;

when B (x, y) is not the angle comparison value and a (x ± m, y ± n) are both the angle comparison values, the position of the corresponding pixel of B (x, y) is the defect position, which may be set to 100 in the defect result matrix C, and is the defect of the Cr area;

when B (x, y) is not the angle contrast value and A (x +/-m, y +/-n) has a non-angle contrast value, and there is no direction angle value with the difference between B (x, y) and B (x, y) being less than the preset angle threshold Te, then the position of the pixel corresponding to B (x, y) is an edge defect, and the defect position can be set to 125 in the defect result matrix C; wherein the content of the first and second substances,

b (x + -m, y + -n) refers to the azimuth angle values within the range x in [ x-m, x + m ] and y in [ y-n, y + n ] in the reflection image angle matrix B;

a (x + -m, y + -n) refers to the azimuth angle values within the range x-m, x + m and y-n, y + n in the transmission image angle matrix A;

a (x, y) is a direction angle value of a normal vector of a pixel under the coordinate point (x, y) in the transmission image angle matrix a;

b (x, y) is a direction angle value of a normal vector of a pixel under the coordinate point (x, y) in the reflection image angle matrix B;

t (x, y) is a gray value of a pixel under the coordinate point (x, y) in the transmission gray image T;

r (x, y) is a gray value of a pixel under the coordinate point (x, y) in the reflection gray image R;

m is a preset search deviation value of the coordinate point x, and n is a preset search deviation value of the coordinate point y. In this embodiment, m is 2 and n is 2.

In the present embodiment, the angle comparison value may be identified as 65535, and the first gray threshold T1, the second gray threshold T2, and the preset angle threshold Te may be preset as required.

The method also comprises the following steps:

and performing closed operation on the defect result matrix C, then counting the defect positions, and performing defect filtering according to the length and/or width parameters of the defect positions to obtain a final defect result matrix C.

And mapping the defect position in the final defect result matrix C to the transmission gray image T and/or the reflection gray image R, wherein a corresponding defect position map on the transmission gray image T is shown in fig. 5.

For each of the pixels, neighborhood pixels of the pixel are pixels that are right-adjacent, down-adjacent, and down-right diagonal to the pixel.

The normal vector of the pixel is calculated as follows:

constructing a coordinate system where the pixel cluster is located;

obtaining a quadrant of each pixel in the pixel group in a coordinate system, and adding a sign to the gray value of the corresponding pixel as a coordinate point value of the pixel according to the quadrant of each pixel;

acquiring a direction vector from a coordinate point of each pixel in the pixel cluster to a coordinate origin of a coordinate system;

the sum of the direction vectors of all pixels in the pixel cluster is calculated, and the reverse vector thereof is taken as the normal vector of the pixel.

The above embodiments are described in further detail to solve the technical problems, technical solutions and advantages of the present invention, and it should be understood that the above embodiments are only examples of the present invention and are not intended to limit the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.