CN114419045A - Method, device and equipment for detecting defects of photoetching mask plate and readable storage medium - Google Patents
Method, device and equipment for detecting defects of photoetching mask plate and readable storage medium Download PDFInfo
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Abstract
The invention provides a method, a device and equipment for detecting defects of a photoetching mask plate and a readable storage medium. The method comprises the following steps: acquiring a detection image and a reference image; respectively calculating according to the structural element direction operator, the detection image and the reference image to obtain the direction morphological gradient of each pixel point of the detection image and the direction morphological gradient of each pixel point of the reference image; calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value; and detecting defects of the photoetching mask plate according to the difference image. According to the invention, the defect detection is carried out on the photoetching mask plate by adopting a directional morphological gradient method instead of an adjacent unit gray contrast method, so that the problem that the detection result of the photoetching mask plate by the adjacent unit gray contrast method is not accurate enough is solved.
Description
Technical Field
The invention relates to the technical field of automatic optical detection, in particular to a method, a device and equipment for detecting defects of a photoetching mask plate and a readable storage medium.
Background
The photoetching mask plate is a high-quality glass plate coated with photosensitive materials, a manufacturer transmits standard plate making data to a pattern generator, the pattern generator generates and repeats patterns according to the standard plate making data to obtain layout data, and then the layout data are transferred to each layer of photoetching mask plate in a layering mode to obtain photoetching patterns. Therefore, the quality of the photolithographic mask plate directly affects the quality of the photolithographic pattern.
In the prior art, a photoetching mask plate is detected by adopting a neighboring unit gray scale comparison method, but the texture edge inside the photoetching mask plate is not sharp enough, so that imaging is easy to be focused virtually, and the film color difference exists between the minimum repeating units of the photoetching mask plate, so that the detection result of the photoetching mask plate by the neighboring unit gray scale comparison method is not accurate enough.
Disclosure of Invention
In order to solve the technical problem, the invention provides a method, a device and equipment for detecting defects of a photolithographic mask plate and a readable storage medium.
In a first aspect, the present invention provides a method for detecting defects of a photolithographic mask, the method comprising:
taking any minimum repeating unit image in the image of the photoetching mask plate as a detection image, and acquiring a reference image from the image of the photoetching mask plate product according to the texture period of the detection image;
calculating according to the structural element direction operator and the pixel value of each pixel point in the detection image to obtain the direction morphological gradient of each pixel point in the detection image;
calculating according to the structural element direction operator and the pixel value of each pixel point in the reference image to obtain the direction morphological gradient of each pixel point in the reference image;
calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value;
and detecting defects of the photoetching mask plate according to the difference image.
Optionally, the step of obtaining the directional morphological gradient of each pixel point in the detection image by calculating according to the structural element direction operator and the pixel value of each pixel point in the detection image includes:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the detection image into a first preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the detection image, wherein the first preset formula is as follows:
wherein,
representing the direction morphological gradient of each pixel point of the detection image,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and expressing the pixel value of each pixel point in the detection image.
Optionally, the step of calculating a directional morphological gradient of each pixel point in the reference image according to the structural element directional operator and the pixel value of each pixel point in the reference image includes:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the reference image into a second preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the reference image, wherein the second preset formula is as follows:
wherein,
the directional morphological gradient of each pixel point of the reference image is represented,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and the pixel values of all pixel points in the reference image are represented.
Optionally, the step of performing defect detection on the photolithographic mask plate according to the difference image comprises:
carrying out binarization segmentation on the difference image to obtain a binary image;
and extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photoetching mask plate has defects or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters.
Optionally, the step of performing binarization segmentation on the difference image to obtain a binary image includes:
judging whether the pixel value of each pixel point in the differential image is larger than a threshold value or not;
assigning the pixel value of the pixel point of which the pixel value is greater than the threshold value in the differential image map to be a first preset value;
and assigning the pixel value of the pixel point of which the pixel value is less than or equal to the threshold value in the differential image as a second preset value.
Optionally, the step of extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photolithographic mask plate is defective by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters includes:
extracting geometric shape characteristic parameters of a region of which the pixel value is a first preset value in the binary image, and extracting gray characteristic parameters of a region corresponding to the region of which the pixel value is the first preset value in the binary image in the detection image;
judging whether the geometric shape characteristic parameters and/or the gray characteristic parameters meet preset defect conditions or not;
if so, determining that the photoetching mask plate has defects;
if not, determining that the photoetching mask plate is not defective.
In a second aspect, the present invention further provides a device for detecting defects of a photolithographic mask, including:
the acquisition module is used for taking any minimum repeating unit image in the image of the photoetching mask plate as a detection image and acquiring a reference image from the image of the photoetching mask plate product according to the texture period of the detection image;
the first calculation module is used for calculating to obtain the directional morphological gradient of each pixel point of the detection image according to the structural element direction operator and the pixel value of each pixel point in the detection image;
the second calculation module is used for calculating the directional morphological gradient of each pixel point of the reference image according to the structural element directional operator and the pixel value of each pixel point in the reference image;
the third calculation module is used for calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value;
and the detection module is used for detecting defects of the photoetching mask plate according to the differential image.
Optionally, the detection module is specifically configured to:
carrying out binarization segmentation on the difference image to obtain a binary image;
and extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photoetching mask plate has defects or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters.
In a third aspect, the present invention further provides a device for detecting defects of a reticle, which includes a processor, a memory, and a reticle defect detection program stored on the memory and executable by the processor, wherein when the reticle defect detection program is executed by the processor, the method for detecting defects of a reticle is implemented.
In a fourth aspect, the present invention further provides a readable storage medium, on which a reticle defect detecting program is stored, wherein when the reticle defect detecting program is executed by a processor, the steps of the reticle defect detecting method described above are implemented.
In the invention, any minimum repetitive unit image in the image of the photoetching mask plate is taken as a detection image, and a reference image is obtained from the image of the photoetching mask plate product according to the texture period of the detection image; calculating according to the structural element direction operator and the pixel value of each pixel point in the detection image to obtain the direction morphological gradient of each pixel point in the detection image; calculating according to the structural element direction operator and the pixel value of each pixel point in the reference image to obtain the direction morphological gradient of each pixel point in the reference image; calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value; and detecting defects of the photoetching mask plate according to the difference image. According to the invention, the detection image and the reference image are obtained from the image of the photoetching mask plate, the direction morphological gradient of each pixel point of the detection image and the reference image is obtained through calculation, the difference image of the detection image and the reference image is obtained through the direction morphological gradient difference, the photoetching mask plate is subjected to defect detection according to the difference image, whether the photoetching mask plate has defects or not can be rapidly and accurately detected, the defect detection is carried out on the photoetching mask plate by adopting a direction morphological gradient method rather than an adjacent unit gray contrast method, and the problems that the imaging is easy to be in virtual focus due to the fact that the texture edge inside the photoetching mask plate is not sharp enough, and the detection result of the photoetching mask plate is not accurate enough through an adjacent unit gray comparison method are solved.
Drawings
Fig. 1 is a schematic hardware structure diagram of a photolithographic mask defect detection apparatus according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for detecting defects of a photolithographic mask blank according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a pixel point according to an embodiment of the method for detecting defects of a mask blank according to the present invention;
FIG. 4 is a schematic diagram of a detection area of a method for detecting defects of a photolithographic mask blank according to an embodiment of the present invention;
FIG. 5 is a functional block diagram of an embodiment of the apparatus for detecting defects of a photolithographic mask blank according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In a first aspect, an embodiment of the present invention provides a defect detecting apparatus for a reticle, which may be an apparatus with a data processing function, such as a Personal Computer (PC), a laptop computer, or a server.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of a lithography mask defect detecting apparatus according to an embodiment of the present invention. In this embodiment of the present invention, the apparatus for detecting defects of a reticle mask may include a processor 1001 (e.g., a Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used for realizing connection communication among the components; the user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard); the network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WI-FI interface, WI-FI interface); the memory 1005 may be a Random Access Memory (RAM) or a non-volatile memory (non-volatile memory), such as a magnetic disk memory, and the memory 1005 may optionally be a storage device independent of the processor 1001. Those skilled in the art will appreciate that the hardware configuration depicted in FIG. 1 is not intended to be limiting of the present invention, and may include more or less components than those shown, or some components in combination, or a different arrangement of components.
With continued reference to FIG. 1, a memory 1005, which is one type of computer storage medium in FIG. 1, may include an operating system, a network communication module, a user interface module, and a reticle defect detection program. The processor 1001 may call a mask blank defect detection program stored in the memory 1005, and execute the mask blank defect detection method according to the embodiment of the present invention.
In a second aspect, an embodiment of the present invention provides a method for detecting defects of a photolithographic mask blank.
In an embodiment, referring to fig. 2, fig. 2 is a schematic flow chart of an embodiment of a method for detecting defects of a photolithographic mask blank according to the present invention. As shown in fig. 2, the method for detecting defects of a photolithographic mask blank comprises:
step S10, taking any minimum repeated unit image in the image of the photoetching mask plate as a detection image, and acquiring a reference image from the image of the photoetching mask plate product according to the texture period of the detection image;
in this embodiment, the photolithographic mask plate is composed of a plurality of minimum repetition units, images of the photolithographic mask plate are collected through an imaging system, any minimum repetition unit image in the images of the photolithographic mask plate is used as a detection image, the minimum repetition unit image adjacent to the detection image is obtained from the images of the photolithographic mask plate product according to the texture period of the detection image, and the minimum repetition unit images adjacent to the detection image are fused to obtain a reference image.
Step S20, calculating according to the structural element direction operator and the pixel value of each pixel point in the detection image to obtain the direction morphological gradient of each pixel point in the detection image;
in this embodiment, the image gradient refers to a change rate of a certain pixel point of an image in both x and y directions, and is a two-dimensional vector, and the conventional image morphological gradient performs expansion operation and corrosion operation on a detected image respectively through structural elements to obtain an expanded image and a corrosion image, and then calculates a difference value between the expanded image and the corrosion image. And obtaining the image morphological gradient. According to the method, the structural element direction operator corresponding to the internal texture of the photoetching mask plate is obtained through deep learning and training, and the direction morphological gradient of each pixel point of the detection image can be obtained through calculation according to the structural element direction operator and the pixel value of each pixel point in the detection image. The lateral and/or vertical and/or oblique texture features of the image of the photoetching mask plate can be processed simultaneously through the directional morphological gradient, and compared with the traditional image morphological gradient application scene which can only process the lateral and/or vertical texture features of the image of the photoetching mask plate, the method is richer and can better detect the oblique texture defect of the photoetching mask plate.
Further, in one embodiment, the step S20 includes:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the detection image into a first preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the detection image, wherein the first preset formula is as follows:
wherein,
representing the direction morphological gradient of each pixel point of the detection image,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and expressing the pixel value of each pixel point in the detection image.
In this embodiment, a corresponding structural element direction operator is obtained according to the internal texture direction of the lithographic mask plate, the structural element direction operator and the pixel value of each pixel point in the detection image are substituted into a first preset formula, and a direction morphological gradient of each pixel point in the detection image is obtained through calculation, where the first preset formula is as follows:
wherein,
representing the direction morphological gradient of each pixel point of the detection image,
the coordinates of each pixel point are represented by,
a horizontal direction edge detection operator which is a structuring element direction operator,
a vertical direction edge detection operator that is a structuring element direction operator,
and expressing the pixel value of each pixel point in the detection image.
Specifically, if the texture direction in the photoetching mask plate is the horizontal direction, a structural element direction operator in the horizontal direction and a structural element direction operator in any other direction are selected to be calculated with the detection image, and if the structural element direction operator in the horizontal direction is the horizontal direction, the structural element direction operator in the horizontal direction is selected to be calculated with the detection image
The structural element direction operator in any other direction is in the vertical direction
And is and
detecting the image
Detecting the horizontal direction edge of the structural element direction operator
Vertical direction edge detection operator of structural element direction operator
And detecting the image
Substituting the direction morphological gradient into a first preset formula to calculate and obtain the direction morphological gradient of each pixel point of the detection image
The first preset formula is as follows:
further, if the texture direction in the photoetching mask plate is the vertical direction, a structural element direction operator in the vertical direction and a structural element direction operator in any other direction are selected to perform calculation with the detection image. And if the texture direction in the photoetching mask plate is a direction inclined by 45 degrees, selecting a structural element direction operator inclined by 45 degrees and a structural element direction operator in any other direction to calculate with the detection image.
Step S30, calculating the direction morphological gradient of each pixel point of the reference image according to the structural element direction operator and the pixel value of each pixel point in the reference image;
in this embodiment, according to the structural element direction operator and the pixel value of each pixel point in the reference image, the direction morphological gradient of each pixel point in the reference image can be obtained through calculation.
Further, in one embodiment, the step S30 includes:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the reference image into a second preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the reference image, wherein the second preset formula is as follows:
wherein,
the directional morphological gradient of each pixel point of the reference image is represented,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and the pixel values of all pixel points in the reference image are represented.
In this embodiment, a corresponding structural element direction operator is obtained according to the internal texture direction of the photolithographic mask plate, the structural element direction operator and the pixel value of each pixel point in the reference image are substituted into a second preset formula, and the directional morphological gradient of each pixel point in the reference image is obtained through calculation, where the second preset formula is as follows:
wherein,
direction morphology ladder for representing each pixel point of reference imageThe degree of the magnetic field is measured,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and the pixel values of all pixel points in the reference image are represented.
Specifically, if the texture direction in the photoetching mask plate is the horizontal direction, a structural element direction operator in the horizontal direction and a structural element direction operator in any other direction are selected to be calculated with a reference image, and if the structural element direction operator in the horizontal direction is the horizontal direction, the structural element direction operator in the horizontal direction is selected to be calculated with the reference image
The structural element direction operator in any other direction is in the vertical direction
And is and
reference picture
Detecting the horizontal direction edge of the structural element direction operator
Vertical direction edge detection operator of structural element direction operator
And a reference image
Substituting the direction morphological gradient into a second preset formula to calculate and obtain the direction morphological gradient of each pixel point of the reference image
The second predetermined formula is as follows:
further, if the texture direction in the photoetching mask plate is the vertical direction, a structural element direction operator in the vertical direction and a structural element direction operator in any other direction are selected to perform calculation with the reference image. And if the texture direction in the photoetching mask plate is a direction inclined by 45 degrees, selecting a structural element direction operator inclined by 45 degrees and a structural element direction operator in any other direction to calculate with the reference image.
Step S40, calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value;
in this embodiment, the directional morphological gradient of each pixel point of the detected image is calculated
Subtracting the directional morphological gradient of each pixel point at the corresponding position of the reference image
To obtain a detected image anda difference map of the reference image. The direction morphological gradient algorithm can eliminate errors within 2 pixels of alignment and the problem edge of a gentle image, and the defect that the alignment precision cannot be achieved at the pixel level by adopting a neighboring unit gray scale comparison method in the prior art is overcome.
Specifically, referring to fig. 3, fig. 3 is a schematic pixel point diagram of a method for detecting defects of a photolithographic mask plate according to an embodiment of the present invention. As shown in fig. 3, if the detected image is a regular hexagon, the reference image is also a regular hexagon, and the directional morphological gradient of the pixel point a of the detected image is subtracted by the pixel point at the position corresponding to the reference image
The difference of the directional morphological gradients of (a) and (b) is detected, the directional morphological gradient of the image pixel point (b) subtracts the pixel point at the position corresponding to the reference image
The difference of the direction morphological gradients is analogized, and the difference of the direction morphological gradients of the pixel points at the corresponding positions of the reference image is subtracted from the direction morphological gradients of the pixel points of the detection image to obtain a difference image of the detection image and the reference image.
And step S50, detecting defects of the photoetching mask plate according to the differential image.
In this embodiment, the defect detection is performed on the mask blank according to the difference image obtained in step S40, and it is determined whether the mask blank has a defect.
Further, in one embodiment, the step S50 includes:
step S501, performing binarization segmentation on the difference image to obtain a binary image;
step S502, extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photoetching mask plate is defective or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters.
In this embodiment, the difference image is binarized and segmented according to the pixel value of each pixel point in the difference image to obtain a binary image, and the geometric shape feature parameter and the grayscale feature parameter extraction region are determined according to the binary image. And extracting geometric shape characteristic parameters of the binary image, and extracting gray characteristic parameters of the detected image. Furthermore, whether the photoetching mask plate has defects is determined by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters, so that the problem that the detection result is not accurate enough by the extraction result of the single characteristic is avoided.
Further, in an embodiment, the step S501 includes:
judging whether the pixel value of each pixel point in the differential image is larger than a threshold value or not;
assigning the pixel value of the pixel point of which the pixel value is greater than the threshold value in the differential image map to be a first preset value;
and assigning the pixel value of the pixel point of which the pixel value is less than or equal to the threshold value in the differential image as a second preset value.
In this embodiment, if the threshold is 15 pixels, the first preset value is 255, and the second preset value is 0, it is determined whether the pixel value of each pixel in the difference image map is 15 pixels, the pixel value of the pixel larger than 15 pixels is assigned to 255, and the pixel value of the pixel smaller than or equal to 15 pixels is assigned to 0, so as to obtain a binary image. It is to be understood that the parameters in the present embodiment are only for reference and are not limited thereto.
Further, in an embodiment, step S502 includes:
extracting geometric shape characteristic parameters of a region of which the pixel value is a first preset value in the binary image, and extracting gray characteristic parameters of a region corresponding to the region of which the pixel value is the first preset value in the binary image in the detection image;
judging whether the geometric shape characteristic parameters and/or the gray characteristic parameters meet preset defect conditions or not;
if so, determining that the photoetching mask plate has defects;
if not, determining that the photoetching mask plate is not defective.
In this embodiment, referring to fig. 4, fig. 4 is a diagram of a method for detecting defects of a photolithographic mask blank according to an embodiment of the present inventionSchematic diagram of the detection area. As shown in fig. 4, the region with the pixel value of 255 in the binary image is a W region, the geometric feature parameter extraction is performed on the W region defect in the binary image, and the region corresponding to the region with the pixel value of 255 in the binary image in the detected image is a W region
Region, in the detected image
And extracting gray characteristic parameters of the region defects, and judging whether the geometric shape characteristic parameters and/or the gray characteristic parameters meet preset defect conditions. The geometrical characteristic parameters comprise perimeter, area, roundness, minimum circumscribed rectangle, duty ratio and skeleton, and the gray characteristic parameters comprise gray mean, gray variance, entropy and angular points.
The method for extracting the geometrical shape characteristic parameter-perimeter comprises the following steps: counting the number of pixel points on the outer contour line of the W area, wherein the number of the pixel points on the outer contour line of the W area represents the perimeter of the defect of the W area; the extraction method of the geometric shape characteristic parameter-area comprises the following steps: counting the number of all pixel points in the W area, wherein the number of all pixel points in the W area represents the defect area of the W area; the extraction method of the geometrical characteristic parameter-roundness comprises the following steps:
wherein R represents the roundness of the defect in the W region, A represents the defect area in the W region, and P represents the perimeter of the defect in the W region; the extraction method of the geometric shape characteristic parameter-the minimum circumscribed rectangle is as follows: solving the minimum circumscribed rectangle of the convex shell of the W area; the extraction method of the geometric shape characteristic parameter-duty ratio comprises the following steps:
wherein
representing the duty ratio of the W region defect, and representing the minimum circumscribed rectangle of the W region defect by MABR; geometric characteristics of ginsengThe extraction method of the number-skeleton is to extract the skeleton of the W region defect by zhang fast parallel refinement algorithm.
The extraction method of the gray level characteristic parameter-gray level mean value comprises the following steps:
wherein M represents
The average value of the gray levels of the area defects,
expressing the pixel value of the ith pixel point, and expressing N
The number of regional pixels; the extraction method of the gray characteristic parameter-variance comprises the following steps:
wherein
to represent
A regional defect variance; the extraction method of the gray characteristic parameter-entropy comprises the following steps:
wherein
expressing the probability of the ith pixel point appearing in the detection image, and H represents
Entropy of regional defect; the extraction method of the gray characteristic parameter-angular point comprises the following steps: through FAST corner detection algorithm pair
And extracting corner points of the region defects.
Extracting geometric shape characteristic parameters of W area defects in binary image and detecting the W area defects in the binary image
After the gray characteristic parameters of the area defects are extracted, if the preset defect conditions are that whether the defect perimeter is larger than a preset defect perimeter threshold value, whether the defect roundness is larger than a preset defect roundness threshold value and whether the defect gray average value is larger than a preset defect gray average value threshold value, then if the defect perimeter is larger than the preset defect perimeter threshold value and the defect roundness is larger than the preset defect roundness threshold value, the geometric characteristic parameters meet the preset defect conditions, and if the defect gray average value is larger than the preset defect gray average value threshold value, the gray characteristic parameters meet the preset defect conditions. If the defect perimeter is less than or equal to a preset defect perimeter threshold value or the defect roundness is less than or equal to a preset defect roundness threshold value, the geometric shape characteristic parameter does not meet the preset defect condition, and if the defect gray average value is less than or equal to a preset defect gray average value threshold value, the gray characteristic parameter does not meet the preset defect condition. The preset defect condition is customized according to a user requirement, and it is easy to think that the preset defect condition in the embodiment is only used for reference, and is not limited herein, and the preset defect condition may be any one or more of a geometric shape characteristic parameter and/or a gray scale characteristic parameter.
And if the geometric shape characteristic parameters and/or the gray characteristic parameters do not meet the preset defect conditions, determining that the photoetching mask plate is defective.
In the embodiment, any minimum repeating unit image in the image of the photoetching mask plate is taken as a detection image, and a reference image is obtained from the image of the photoetching mask plate product according to the texture period of the detection image; calculating according to the structural element direction operator and the pixel value of each pixel point in the detection image to obtain the direction morphological gradient of each pixel point in the detection image; calculating according to the structural element direction operator and the pixel value of each pixel point in the reference image to obtain the direction morphological gradient of each pixel point in the reference image; calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value; and detecting defects of the photoetching mask plate according to the difference image. According to the embodiment, the detection image and the reference image are obtained from the image of the photoetching mask plate, the direction morphological gradient of each pixel point of the detection image and the reference image is obtained through calculation, the difference image of the detection image and the reference image is obtained through the difference value of the direction morphological gradient, the photoetching mask plate is subjected to defect detection according to the difference image, whether the photoetching mask plate has defects or not can be detected quickly and accurately, the defect detection is performed on the photoetching mask plate by adopting a direction morphological gradient method instead of an adjacent unit gray contrast method, and the problems that due to the fact that the edge of the internal texture of the photoetching mask plate is not sharp enough, imaging is easy to be focused virtually and the film color difference exists between the minimum repeated units of the photoetching mask plate, and the detection result of the photoetching mask plate by the adjacent unit gray comparison method is not accurate enough are solved.
In a third aspect, an embodiment of the present invention further provides a device for detecting defects of a photolithographic mask blank.
In an embodiment, referring to fig. 5, fig. 5 is a functional module schematic diagram of an embodiment of the apparatus for detecting defects of a photolithographic mask blank according to the present invention. As shown in fig. 5, the apparatus for detecting defects of a reticle includes:
the acquisition module 10 is configured to acquire a reference image from a product image of the photolithographic mask plate according to a texture cycle of a detection image by using any minimum repetitive unit image in the image of the photolithographic mask plate as the detection image;
the first calculation module 20 is configured to calculate a directional morphological gradient of each pixel point in the detection image according to the structural element direction operator and the pixel value of each pixel point in the detection image;
the second calculation module 30 is configured to calculate a directional morphological gradient of each pixel point in the reference image according to the structural element directional operator and the pixel value of each pixel point in the reference image;
the third calculating module 40 is configured to calculate a difference value obtained by subtracting the directional morphological gradient of each pixel point at the corresponding position of the reference image from the directional morphological gradient of each pixel point of the detection image, and obtain a difference image of the detection image and the reference image according to the difference value;
and the detection module 50 is used for detecting defects of the photoetching mask plate according to the differential image.
Further, in an embodiment, the first calculating module 20 is specifically configured to:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the detection image into a first preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the detection image, wherein the first preset formula is as follows:
wherein,
representing the direction morphological gradient of each pixel point of the detection image,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and expressing the pixel value of each pixel point in the detection image.
Further, in an embodiment, the second calculating module 30 is specifically configured to:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the reference image into a second preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the reference image, wherein the second preset formula is as follows:
wherein,
the directional morphological gradient of each pixel point of the reference image is represented,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and the pixel values of all pixel points in the reference image are represented.
Further, in an embodiment, the detecting module 50 is specifically configured to:
carrying out binarization segmentation on the difference image to obtain a binary image;
and extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photoetching mask plate has defects or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters.
Further, in an embodiment, the apparatus for detecting defects of a mask blank further includes a determining module, configured to:
judging whether the pixel value of each pixel point in the differential image is larger than a threshold value or not;
assigning the pixel value of the pixel point of which the pixel value is greater than the threshold value in the differential image map to be a first preset value;
and assigning the pixel value of the pixel point of which the pixel value is less than or equal to the threshold value in the differential image as a second preset value.
Further, in an embodiment, the determining module is further configured to:
extracting geometric shape characteristic parameters of a region of which the pixel value is a first preset value in the binary image, and extracting gray characteristic parameters of a region corresponding to the region of which the pixel value is the first preset value in the binary image in the detection image;
judging whether the geometric shape characteristic parameters and/or the gray characteristic parameters meet preset defect conditions or not;
if so, determining that the photoetching mask plate has defects;
if not, determining that the photoetching mask plate is not defective.
The function implementation of each module in the apparatus for detecting defects of a photolithographic mask plate corresponds to each step in the method for detecting defects of a photolithographic mask plate, and the functions and implementation processes are not described in detail herein.
In a fourth aspect, the embodiment of the present invention further provides a readable storage medium.
The readable storage medium of the invention stores a defect detection program of the mask blank, wherein when the defect detection program of the mask blank is executed by a processor, the steps of the defect detection method of the mask blank are realized.
The method implemented when the program for detecting defects of a photolithographic mask blank is executed may refer to various embodiments of the method for detecting defects of a photolithographic mask blank of the present invention, and details thereof are not described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for causing a terminal device to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method for detecting defects of a photolithographic mask plate is characterized by comprising the following steps:
taking any minimum repeating unit image in the image of the photoetching mask plate as a detection image, and acquiring a reference image from the image of the photoetching mask plate product according to the texture period of the detection image;
calculating according to the structural element direction operator and the pixel value of each pixel point in the detection image to obtain the direction morphological gradient of each pixel point in the detection image;
calculating according to the structural element direction operator and the pixel value of each pixel point in the reference image to obtain the direction morphological gradient of each pixel point in the reference image;
calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value;
and detecting defects of the photoetching mask plate according to the difference image.
2. The method for detecting defects of a photolithographic mask plate as claimed in claim 1, wherein the step of obtaining the directional morphological gradient of each pixel point of the detected image by calculation according to the structural element directional operator and the pixel value of each pixel point in the detected image comprises:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the detection image into a first preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the detection image, wherein the first preset formula is as follows:
wherein,
representing the direction morphological gradient of each pixel point of the detection image,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and expressing the pixel value of each pixel point in the detection image.
3. The method for detecting defects of a photolithographic mask plate according to claim 1, wherein the step of calculating the directional morphological gradient of each pixel point of the reference image according to the structural element directional operator and the pixel value of each pixel point in the reference image comprises:
acquiring a corresponding structural element direction operator according to the internal texture direction of the photoetching mask plate, substituting the structural element direction operator and the pixel value of each pixel point in the reference image into a second preset formula, and calculating to obtain the direction morphological gradient of each pixel point in the reference image, wherein the second preset formula is as follows:
wherein,
the directional morphological gradient of each pixel point of the reference image is represented,
the coordinates of each pixel point are represented by,
a lateral edge detection operator that is a structuring element orientation operator,
a vertical edge detection operator that is a structuring element direction operator,
and the pixel values of all pixel points in the reference image are represented.
4. The method for detecting defects of a photolithographic mask blank according to claim 1, wherein the step of detecting defects of the photolithographic mask blank according to the differential image comprises:
carrying out binarization segmentation on the difference image to obtain a binary image;
and extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photoetching mask plate has defects or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters.
5. The method for detecting defects of a photolithographic mask blank as claimed in claim 4, wherein the step of performing binary segmentation on the difference image to obtain a binary image comprises:
judging whether the pixel value of each pixel point in the differential image is larger than a threshold value or not;
assigning the pixel value of the pixel point of which the pixel value is greater than the threshold value in the differential image map to be a first preset value;
and assigning the pixel value of the pixel point of which the pixel value is less than or equal to the threshold value in the differential image as a second preset value.
6. The method for detecting defects of a photolithographic mask blank as claimed in claim 5, wherein the steps of extracting geometric shape characteristic parameters from the binary image, extracting gray characteristic parameters from the detected image, and determining whether the photolithographic mask blank is defective or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters comprise:
extracting geometric shape characteristic parameters of a region of which the pixel value is a first preset value in the binary image, and extracting gray characteristic parameters of a region corresponding to the region of which the pixel value is the first preset value in the binary image in the detection image;
judging whether the geometric shape characteristic parameters and/or the gray characteristic parameters meet preset defect conditions or not;
if so, determining that the photoetching mask plate has defects;
if not, determining that the photoetching mask plate is not defective.
7. A defect detection device for a photolithographic mask plate is characterized by comprising:
the acquisition module is used for taking any minimum repeating unit image in the image of the photoetching mask plate as a detection image and acquiring a reference image from the image of the photoetching mask plate product according to the texture period of the detection image;
the first calculation module is used for calculating to obtain the directional morphological gradient of each pixel point of the detection image according to the structural element direction operator and the pixel value of each pixel point in the detection image;
the second calculation module is used for calculating the directional morphological gradient of each pixel point of the reference image according to the structural element directional operator and the pixel value of each pixel point in the reference image;
the third calculation module is used for calculating the difference value of the directional morphological gradient of each pixel point of the detection image minus the directional morphological gradient of each pixel point at the corresponding position of the reference image, and obtaining a difference image of the detection image and the reference image according to the difference value;
and the detection module is used for detecting defects of the photoetching mask plate according to the differential image.
8. The apparatus for detecting defects in a photolithographic mask blank as claimed in claim 7, wherein the detection module is specifically configured to:
carrying out binarization segmentation on the difference image to obtain a binary image;
and extracting geometric shape characteristic parameters of the binary image, extracting gray characteristic parameters of the detected image, and determining whether the photoetching mask plate has defects or not by combining the extraction result of the geometric shape characteristic parameters and the extraction result of the gray characteristic parameters.
9. A reticle defect inspection apparatus comprising a processor, a memory, and a reticle defect inspection program stored on the memory and executable by the processor, wherein the reticle defect inspection program when executed by the processor implements the steps of the reticle defect inspection method of any one of claims 1 to 6.
10. A readable storage medium having a reticle defect detecting program stored thereon, wherein the reticle defect detecting program when executed by a processor implements the steps of the reticle defect detecting method according to any one of claims 1 to 6.
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