CN117252870B - Image processing method of nano-imprint mold - Google Patents
Image processing method of nano-imprint mold Download PDFInfo
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- 238000004519 manufacturing process Methods 0.000 description 5
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- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
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- 238000003384 imaging method Methods 0.000 description 1
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- 238000001127 nanoimprint lithography Methods 0.000 description 1
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
- G03F7/0002—Lithographic processes using patterning methods other than those involving the exposure to radiation, e.g. by stamping
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30144—Printing quality
Abstract
The invention discloses an image processing method of a nano-imprinting mold, which belongs to the technical field of image processing and comprises the following steps: s1, acquiring a real-time image of a nano-imprinting mold, and acquiring the color of photoresist between the nano-imprinting mold and a material to be processed; s2, flattening the real-time image to generate a flattened image; s3, determining an interested detection area of the flat image according to the color of the photoresist between the nano-imprinting mold and the material to be processed, and finishing image processing. According to the invention, the quality influence of the flatness of the surface of the die on the die image is considered, the die image is subjected to flattening treatment, and the detection accuracy is improved; meanwhile, the interested detection area where residues possibly exist in the image is determined by combining the colors of the photoresist, so that the area needing key detection is further accurately detected, and the algorithm flow is reduced.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to an image processing method of a nano-imprinting mold.
Background
The nano-imprint lithography technology is used as a platform type micro-nano processing technology, can be theoretically applied to all micro-nano structure application scenes, and is an optimal scheme for perfectly solving the mass and low-cost manufacturing of the current silicon optical core devices and optical core elements. The method can be widely applied to the fields of consumer electronics (face recognition, 3D sensing, fingerprint recognition under a screen and the like), AR glasses, vehicle optics (AR-HUD, welcome light blanket, 3D sensing and the like), biochips and display fields (WGP, microlens arrays, imaging and the like), lens modules and the like. The nanoimprint technique is divided into three steps: the first step is the processing of the nanoimprint mold: generally, electron beam etching or other means are used to process a desired structure on silicon or other substrates as a nanoimprint mold; since the diffraction limit of electrons is much smaller than photons, a resolution much higher than that of lithography can be achieved. The second step is pattern transfer: coating photoresist on the surface of a material to be processed, pressing a nano imprinting mold on the surface of the material, and transferring a pattern onto the photoresist in a pressurizing mode; note that the photoresist cannot be removed entirely, preventing the template from directly contacting the material, damaging the nanoimprint mold. The third step is processing of the substrate: and (3) solidifying the photoresist by using ultraviolet light, removing the nano imprinting mold, etching the photoresist which is not completely removed in the previous step by using etching liquid to expose the surface of the material to be processed, then processing by using a chemical etching method, and removing all the photoresist after the completion of the processing to finally obtain the material processed with high precision. The nano-imprint mold is used as an important tool for processing, and residues often exist to influence the accuracy of processing, so the invention provides an image processing method of the nano-imprint mold, which is used for determining a region needing to be subjected to residue detection.
Disclosure of Invention
The invention provides an image processing method of a nano-imprint mold for solving the problems.
The technical scheme of the invention is as follows: an image processing method of a nanoimprint mold includes the steps of:
s1, acquiring a real-time image of a nano-imprinting mold, and acquiring the color of photoresist between the nano-imprinting mold and a material to be processed;
s2, obtaining the flatness of the surface of the nanoimprint mold, and flattening the real-time image according to the flatness of the surface of the nanoimprint mold to generate a flattened image;
s3, determining an interested detection area of the flat image according to the color of the photoresist between the nano-imprinting mold and the material to be processed, and finishing image processing.
Further, S2 comprises the following sub-steps:
s21, obtaining brightness values of all pixel points in a real-time image of the nano-imprint mold, and calculating the flattening brightness values of all pixel points in the real-time image according to the flatness of the surface of the nano-imprint mold;
s22, constructing primary flattening conditions, judging whether flattening brightness values of all pixel points in the real-time image and brightness values of eight surrounding adjacent pixel points meet the primary flattening conditions, if so, entering S23, otherwise, entering S24;
s23, taking the average value of the flattening brightness values of all the pixel points in the real-time image as the brightness value of each pixel point in the flattening image, and finishing flattening treatment;
s24, taking the average value of the flattening brightness value of each pixel point in the real-time image and the brightness values of eight adjacent surrounding pixels as the temporary brightness value of each pixel point in the real-time image, and determining the brightness value of each pixel point in the flattening image according to the temporary brightness value of each pixel point in the real-time image to finish flattening processing.
The beneficial effects of the above-mentioned further scheme are: in the invention, the nano-imprinting mold has the defect of uneven surface of the mold caused by production or uneven surface caused by loss of the mold surface caused by working in the production or working process, and negative influence is generated on judging whether the nano-imprinting mold has residues, so that the real-time image of the nano-imprinting mold is flattened, and errors caused by residue detection due to uneven surface of the mold are reduced. According to the invention, the flattening brightness value of each pixel point is calculated according to the flatness of the surface of the die, whether one flattening condition is met is judged according to the flattening brightness value, if yes, the average value of the flattening brightness values of all the pixel points in the real-time image is directly used as the brightness value of each pixel point in the flattening image, otherwise, the temporary brightness value of each pixel point is needed to finish flattening.
Further, in S21, the flat brightness value of the pixel point in the real-time imageThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing the flatness of the nanoimprint mold surface, +.>Luminance value representing pixel point in real-time image, < >>Representing maximum value operation, ++>Representing a logarithmic operation.
In the invention, logarithmic operation and absolute value operation based on e are carried out on the brightness value of each pixel point in the real-time image, and multiplication operation is carried out on the brightness value and the maximum value between the brightness value and the flatness, so as to determine the coefficient capable of reflecting the flatness degree and the brightness degree of the pixel point.
Further, in S22, the expression of the primary flattening condition is:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing flat luminance values of pixels in the real-time image, and (2)>Representing the brightness value of the first adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing pixel point correspondence in real-time imagesLuminance value of a second adjacent pixel, for example, for a pixel of the display device>Representing the brightness value of the third adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the fourth adjacent pixel point corresponding to the pixel point in the real-time image,/->Representing the brightness value of the fifth adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the sixth adjacent pixel point corresponding to the pixel point in the real-time image,/->Representing the brightness value of the seventh adjacent pixel corresponding to the pixel in the real-time image,/->And representing the brightness value of the eighth adjacent pixel point corresponding to the pixel point in the real-time image.
Further, in S24, the brightness value of the pixel point in the image is flattenedThe calculation formula of (2) is as follows: />The method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Temporary brightness value representing pixel point in real-time image, < >>Maximum temporary luminance value representing a pixel point in a real-time image,/or->Representing the minimum temporary luminance value of a pixel in the real-time image.
Further, S3 comprises the following sub-steps:
s31, determining a color interest threshold of the flat image according to the color of the photoresist between the nano imprinting mold and the material to be processed and the color value of each pixel point in the flat image;
s32, calculating the color interest weight of each pixel point in the flat image according to the color value of each pixel point in the flat image;
s33, taking the pixel point corresponding to the maximum color interest weight as a standard pixel point, calculating the difference value between the color interest weight of the standard pixel point in the flat image and the color interest weights of the rest pixel points, and taking the region where the pixel point with the difference value smaller than the color interest threshold value is located as an interest detection region of the flat image.
The beneficial effects of the above-mentioned further scheme are: in the invention, during the working process of the nano-imprinting mold, photoresist is coated on the surface of a material to be processed, then the nano-imprinting mold is pressed on the surface of the material to be processed, and the pattern is transferred onto the photoresist in a pressurizing mode. The photoresist cannot be completely removed, so that the nanoimprint mold is prevented from being directly contacted with the material to be processed, and the nanoimprint mold is prevented from being damaged. Thus, the photoresist may become a residue, so the present invention extracts an approximate region of the residue by the color value of the photoresist.
Further, in S31, the color interest threshold of the image is flattenedThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing the%>Red channel value of each pixel, +.>Representing the%>Green channel value of each pixel, +.>Representing the first of the flattened imagesBlue channel value of each pixel, < >>Red channel value representing the color correspondence of the photoresist, is->A green channel value representing the color correspondence of the photoresist, is->Blue channel value corresponding to the color representing the photoresist, ">The number of pixels representing a flat image, +.>Representing a constant.
Further, in S32, the color interest weight of the pixel point in the image is flattenedThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Red channel value representing pixel point in flat image,/->Green channel value representing pixel point in flat image,/->Blue channel value representing pixel point in flat image,/->Representing an index.
The beneficial effects of the invention are as follows: the invention provides an image processing method of a nano-imprinting mold, which considers the quality influence of the flatness of the mold surface on the mold image, performs flattening processing on the mold image and improves the detection accuracy; meanwhile, the interested detection area where residues possibly exist in the image is determined by combining the colors of the photoresist, the area which is required to be detected in a key way is further accurately determined, the algorithm flow is reduced, and effective support is provided for detecting the residues of the nanoimprint mold.
Drawings
Fig. 1 is a flowchart of an image processing method of a nanoimprint mold.
Detailed Description
Embodiments of the present invention are further described below with reference to the accompanying drawings.
As shown in fig. 1, the present invention provides an image processing method of a nanoimprint mold, comprising the steps of:
s1, acquiring a real-time image of a nano-imprinting mold, and acquiring the color of photoresist between the nano-imprinting mold and a material to be processed;
s2, obtaining the flatness of the surface of the nanoimprint mold, and flattening the real-time image according to the flatness of the surface of the nanoimprint mold to generate a flattened image;
s3, determining an interested detection area of the flat image according to the color of the photoresist between the nano-imprinting mold and the material to be processed, and finishing image processing.
In the scheme, the interested detection area of the flat image is the area with the high probability of residues in the nano imprinting mold, and the important observation is needed, so that whether the residues exist in the interested detection area of the flat image can be determined by using a deep learning algorithm. The deep learning algorithm can complete residue detection by adopting a convolutional neural network, and has high accuracy and efficiency.
In an embodiment of the present invention, S2 comprises the following sub-steps:
s21, obtaining brightness values of all pixel points in a real-time image of the nano-imprint mold, and calculating the flattening brightness values of all pixel points in the real-time image according to the flatness of the surface of the nano-imprint mold;
s22, constructing primary flattening conditions, judging whether flattening brightness values of all pixel points in the real-time image and brightness values of eight surrounding adjacent pixel points meet the primary flattening conditions, if so, entering S23, otherwise, entering S24;
s23, taking the average value of the flattening brightness values of all the pixel points in the real-time image as the brightness value of each pixel point in the flattening image, and finishing flattening treatment;
s24, taking the average value of the flattening brightness value of each pixel point in the real-time image and the brightness values of eight adjacent surrounding pixels as the temporary brightness value of each pixel point in the real-time image, and determining the brightness value of each pixel point in the flattening image according to the temporary brightness value of each pixel point in the real-time image to finish flattening processing.
In the invention, the nano-imprinting mold has the defect of uneven surface of the mold caused by production or uneven surface caused by loss of the mold surface caused by working in the production or working process, and negative influence is generated on judging whether the nano-imprinting mold has residues, so that the real-time image of the nano-imprinting mold is flattened, and errors caused by residue detection due to uneven surface of the mold are reduced. According to the invention, the flattening brightness value of each pixel point is calculated according to the flatness of the surface of the die, whether one flattening condition is met is judged according to the flattening brightness value, if yes, the average value of the flattening brightness values of all the pixel points in the real-time image is directly used as the brightness value of each pixel point in the flattening image, otherwise, the temporary brightness value of each pixel point is needed to finish flattening.
In the embodiment of the invention, in S21, the flat brightness value of the pixel point in the real-time imageThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing the flatness of the nanoimprint mold surface, +.>Luminance value representing pixel point in real-time image, < >>Representing maximum value operation, ++>Representing a logarithmic operation.
In the invention, logarithmic operation and absolute value operation based on e are carried out on the brightness value of each pixel point in the real-time image, and multiplication operation is carried out on the brightness value and the maximum value between the brightness value and the flatness, so as to determine the coefficient capable of reflecting the flatness degree and the brightness degree of the pixel point.
In the embodiment of the present invention, in S22, the expression of the primary leveling condition is:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing flat luminance values of pixels in the real-time image, and (2)>Representing the brightness value of the first adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the second adjacent pixel corresponding to the pixel in the real-time image,/->Representing a real objectWhen the brightness value of the third adjacent pixel point corresponding to the pixel point in the image is +.>Representing the brightness value of the fourth adjacent pixel point corresponding to the pixel point in the real-time image,/->Representing the brightness value of the fifth adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the sixth adjacent pixel point corresponding to the pixel point in the real-time image,/->Representing the brightness value of the seventh adjacent pixel corresponding to the pixel in the real-time image,/->And representing the brightness value of the eighth adjacent pixel point corresponding to the pixel point in the real-time image.
In the embodiment of the present invention, in S24, the brightness value of the pixel point in the image is flattenedThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Temporary brightness value representing pixel point in real-time image, < >>Maximum temporary luminance value representing a pixel point in a real-time image,/or->Representing the minimum temporary luminance value of a pixel in the real-time image.
In an embodiment of the present invention, S3 comprises the following sub-steps:
s31, determining a color interest threshold of the flat image according to the color of the photoresist between the nano imprinting mold and the material to be processed and the color value of each pixel point in the flat image;
s32, calculating the color interest weight of each pixel point in the flat image according to the color value of each pixel point in the flat image;
s33, taking the pixel point corresponding to the maximum color interest weight as a standard pixel point, calculating the difference value between the color interest weight of the standard pixel point in the flat image and the color interest weights of the rest pixel points, and taking the region where the pixel point with the difference value smaller than the color interest threshold value is located as an interest detection region of the flat image.
In the invention, during the working process of the nano-imprinting mold, photoresist is coated on the surface of a material to be processed, then the nano-imprinting mold is pressed on the surface of the material to be processed, and the pattern is transferred onto the photoresist in a pressurizing mode. The photoresist cannot be completely removed, so that the nanoimprint mold is prevented from being directly contacted with the material to be processed, and the nanoimprint mold is prevented from being damaged. Thus, the photoresist may become a residue, so the present invention extracts an approximate region of the residue by the color value of the photoresist.
In the embodiment of the present invention, in S31, the color interest threshold of the image is flattenedThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing the%>Red channel value of each pixel, +.>Representing the%>Green channel value of each pixel, +.>Representing the first of the flattened imagesBlue channel value of each pixel, < >>Red channel value representing the color correspondence of the photoresist, is->A green channel value representing the color correspondence of the photoresist, is->Blue channel value corresponding to the color representing the photoresist, ">The number of pixels representing a flat image, +.>Representing a constant.
In the embodiment of the present invention, in S32, the color interest weight of the pixel point in the image is flattenedThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Red channel value representing pixel point in flat image,/->Green channel value representing pixel point in flat image,/->Blue channel value representing pixel point in flat image,/->Representing an index.
Those of ordinary skill in the art will recognize that the embodiments described herein are for the purpose of aiding the reader in understanding the principles of the present invention and should be understood that the scope of the invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific modifications and combinations from the teachings of the present disclosure without departing from the spirit thereof, and such modifications and combinations remain within the scope of the present disclosure.
Claims (1)
1. An image processing method of a nanoimprint mold, comprising the steps of:
s1, acquiring a real-time image of a nano-imprinting mold, and acquiring the color of photoresist between the nano-imprinting mold and a material to be processed;
s2, obtaining the flatness of the surface of the nanoimprint mold, and flattening the real-time image according to the flatness of the surface of the nanoimprint mold to generate a flattened image;
s3, determining an interested detection area of the flat image according to the color of the photoresist between the nano imprinting mold and the material to be processed, and finishing image processing;
the step S2 comprises the following substeps:
s21, obtaining brightness values of all pixel points in a real-time image of the nano-imprint mold, and calculating the flattening brightness values of all pixel points in the real-time image according to the flatness of the surface of the nano-imprint mold;
s22, constructing primary flattening conditions, judging whether flattening brightness values of all pixel points in the real-time image and brightness values of eight surrounding adjacent pixel points meet the primary flattening conditions, if so, entering S23, otherwise, entering S24;
s23, taking the average value of the flattening brightness values of all the pixel points in the real-time image as the brightness value of each pixel point in the flattening image, and finishing flattening treatment;
s24, taking the average value of the flattening brightness value of each pixel point in the real-time image and the brightness values of eight adjacent surrounding pixel points as the temporary brightness value of each pixel point in the real-time image, and determining the brightness value of each pixel point in the flattening image according to the temporary brightness value of each pixel point in the real-time image to finish flattening treatment;
in S21, the flat brightness value of the pixel point in the real-time imageThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing the flatness of the nanoimprint mold surface, +.>Luminance value representing pixel point in real-time image, < >>Representing maximum value operation, ++>Representing a logarithmic operation;
in S22, the expression of the primary leveling condition is:the method comprises the steps of carrying out a first treatment on the surface of the In the method, in the process of the invention,representing flat luminance values of pixels in the real-time image, and (2)>Representing the brightness value of the first adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the second adjacent pixel corresponding to the pixel in the real-time image,/->Representing the brightness value of the third adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the fourth adjacent pixel point corresponding to the pixel point in the real-time image,/->Representing the brightness value of the fifth adjacent pixel point corresponding to the pixel point in the real-time image, +.>Representing the brightness value of the sixth adjacent pixel point corresponding to the pixel point in the real-time image,/->Representing the brightness value of the seventh adjacent pixel corresponding to the pixel in the real-time image,/->Representing brightness values of eighth adjacent pixel points corresponding to the pixel points in the real-time image;
in S24, the brightness value of the pixel point in the image is flattenedThe calculation formula of (2) is as follows: />The method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Temporary brightness value representing pixel point in real-time image, < >>Maximum temporary luminance value representing a pixel point in a real-time image,/or->Representing a minimum temporary brightness value of a pixel point in the real-time image;
the step S3 comprises the following substeps:
s31, determining a color interest threshold of the flat image according to the color of the photoresist between the nano imprinting mold and the material to be processed and the color value of each pixel point in the flat image;
s32, calculating the color interest weight of each pixel point in the flat image according to the color value of each pixel point in the flat image;
s33, taking the pixel point corresponding to the maximum color interest weight as a standard pixel point, calculating the difference value between the color interest weight of the standard pixel point in the flat image and the color interest weights of the rest pixel points, and taking the region where the pixel point with the difference value smaller than the color interest threshold value is located as an interest detection region of the flat image;
in S31, the color interest threshold of the flat imageThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Representing the%>Red channel value of each pixel, +.>Representing the%>Green color of individual pixelsChannel value->Representing the first of the flattened imagesBlue channel value of each pixel, < >>Red channel value representing the color correspondence of the photoresist, is->A green channel value representing the color correspondence of the photoresist, is->Blue channel value corresponding to the color representing the photoresist, ">The number of pixels representing a flat image, +.>Representing a constant;
in S32, the color interest weight of the pixel point in the image is flattenedThe calculation formula of (2) is as follows:the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Red channel value representing pixel point in flat image,/->Green channel value representing pixel point in flat image,/->Blue channel value representing pixel point in flat image,/->Representing an index.
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