KR20230032029A - Two-dimensional object detection system - Google Patents

Abstract

A two-dimensional object detection system according to the present invention can identify a two-dimensional object to be detected or detect a position of the two-dimensional object by using each contrast ratio according to an RGB wavelength band extracted from an optical image of the two-dimensional object to be detected. The present invention provides the two-dimensional object detection system capable of automatically detecting a two-dimensional object in a work previously performed manually by a researcher by applying the principle of optical identification based on the interference effect of the two-dimensional object to be detected by an atomic monolayer.

Description

2D object detection system {TWO-DIMENSIONAL OBJECT DETECTION SYSTEM}

The present invention relates to a 2D object detection system, and more particularly, to a 2D object detection system capable of automatically detecting a 2D material or material of an atomic monolayer obtained by mechanical exfoliation.

2D material is a source technology that can be applied to various industries such as the Internet of Things, bendable devices, ultra-low power devices, next-generation batteries, water filters, and spacecraft. A two-dimensional (2D) material refers to a material in which atoms form a crystal structure in a plane with a single atomic layer thickness (about 1 nm = 1 billionth of a meter).

In addition, the van der Waals heterostructure is not a single atomic layer structure, but belongs to the category of two-dimensional materials as a structure capable of maximizing the advantages of two-dimensional materials. Due to the precise interface control function and the selection of various materials with various electronic properties, the van der Waals heterojunction structure has been confirmed to have high device potential that cannot be achieved with conventional semiconductor heterostructures.

Two-dimensional materials can be classified into conductors, semiconductors, and insulators according to their electrical properties. Representatively, graphene with conductor properties, transition metal dichalcogenide (TMDC) with semiconductor properties, and black phosphorus (black phosphorus) phosphorous) and hexagonal boron nitride (hBN), which has non-conductive properties.

Graphene, a representative two-dimensional material, has been discovered by mechanical exfoliation, in which several atomic layers are mechanically peeled off by repeatedly attaching and peeling adhesive scotch tape to a graphite lump material, and many studies have been conducted. It is coming. The mechanical exfoliation method is used because it can obtain the highest quality 2D material even though the yield is very low and it cannot be applied to a large area.

However, after mechanical exfoliation, it takes a long time for the researcher to look for a single-layer two-dimensional material while looking through an optical microscope with his or her own eyes, and visual inspection is impossible if the work is performed inside a glove box to prevent oxidation.

Until now, high-quality two-dimensional crystals with excellent properties have been mostly manufactured by mechanical exfoliation. However, the yield is very low, and only about 1 to 2 single-layer crystal flakes are found per 1 cm ² .

In the laboratory, many researchers and graduate students spend too much time looking for a two-dimensional material obtained by mechanical exfoliation with the naked eye through an optical microscope, and it takes about 30 minutes to find one high-quality graphene. In addition, since this process is performed in air, there is a serious problem in that inherent characteristics of the raw material deteriorate due to oxidation of the two-dimensional material during this time.

The present applicant has proposed the present invention in order to solve the above problems.

Korean Patent Publication No. 10-2013-0050552 (published on May 16, 2013)

The present invention has been devised to solve the above problems, and by applying the principle of optical identification by the interference effect of the 2D detection object of the atomic monolayer, it automatically detects the 2D object, which was previously performed manually by researchers. A two-dimensional object detection system that can achieve this is provided.

The present invention provides a two-dimensional object detection system that obtains an optical image from a camera, extracts each color image of RGB, and measures the contrast ratio of the area where the single-layer flake is located and the outside thereof to determine the presence or absence of a single layer.

The present invention provides a two-dimensional object detection system that discriminates between single-layer flakes and foreign substances by determining an area by dividing one flake area from other background areas and calculating the average value, uniformity, and gradient of the contrast.

A system for detecting a 2D object according to the present invention to achieve the above object is to identify or locate the 2D object by using contrast ratios according to RGB wavelengths extracted from an optical image of the 2D object. can be detected.

a stage on which a substrate on which the two-dimensional detection object is present is placed; a photographing unit for photographing the substrate including the 2D detection target; and an object detection unit configured to identify or detect the 2D detection target using an optical image of the substrate obtained by the photographing unit, wherein the target detection unit detects an interference effect between the 2D detection target and the thin film of the substrate. It is possible to detect the 2-dimensional detection target by using.

The object detector may detect an area where the 2D detection object exists by measuring a contrast ratio between a region where the 2D detection target, the multilayer detection target, and impurities are present and other background regions in the optical image of the substrate. .

The object detector may extract color images of each RGB from the optical image, and extract estimated pixels that satisfy a set value for a difference between a contrast ratio of the background area and a contrast ratio of each RGB from the optical image.

The object detector may detect a close area where estimated pixels are gathered, determine uniformity of estimated pixels located in the close area, or obtain a size of the close area.

The object detection unit may distinguish the 2D detection object from other multi-layer detection objects and impurities by calculating an average value of brightness and darkness differences of estimated pixels existing in the close area and a uniformity or gradient of pixel values.

The object detector estimates that the 2D detection object does not exist when the pixel values of the estimated pixels present in the close area gradually increase, decrease, or change, and when the pixel values of the estimated pixels are uniform, the second It may be estimated that the 2D detection target exists, or that the 2D detection target does not exist when the size of the close area is equal to or less than a reference value.

The object detector converts (N×m)×(N×m) pixels existing in the close area in which the 2D detection target is estimated to exist into N×low-resolution images, and converts the pixel values of the low-resolution image. After determining the presence or absence of the 2D detection target by comparison, pixels existing only in the area where the 2D detection target is estimated to exist are converted into (N×m)×(N×m) high-resolution images, and then the high-resolution image It is possible to detect the edge of the 2D detection object by comparing pixel values of and store the location information.

The object detector defines a subarray composed of N×N pixels for (N×m)×(N×m) pixels existing in the close proximity area where the 2D detection target is estimated to exist, and the subarray It is possible to detect the presence or absence of the two-dimensional detection target by comparing pixel values for m×m pieces of which x is a representative value.

The object detection unit compares pixel values for m×m pieces of sub-arrays as one representative value, and stores location information of an area where the 2D detection object is estimated to exist, and stores the location information of the estimated area. It is possible to convert a pixel existing only in (N×m)×(N×m) pixels, compare pixel values, detect an edge of the 2D detection object, and store the location information.

Since the 2D object detection system according to the present invention can automatically detect a 2D object by applying the optical identification principle based on the interference effect of the 2D object of the atomic monolayer, the time required for detecting the 2D object can be reduced. there is.

The 2D object detection system according to the present invention divides one flake area from other background areas, determines the area, and calculates the average value, uniformity, and gradient of the contrast, so that the 2D object existing in the form of a single layer flake. and foreign matter can be distinguished.

Since the system for detecting a 2D object according to the present invention is implemented and operated even in a glove box, it is possible to prevent a 2D object from being oxidized in the air.

1 is a diagram schematically showing the configuration of a 2D object detection system according to the present invention.
FIG. 2 is a diagram showing a substrate and a two-dimensional detection target used in the system according to FIG. 1 as an example.
Figure 3 is a block diagram showing components of one embodiment of the system according to Figure 1;
Fig. 4 is a block diagram showing components of another embodiment of the system according to Fig. 1;
Figure 5 is a block diagram showing components of another embodiment of the system according to Figure 1;
FIG. 6 is a block diagram illustrating the configuration of an object detection unit of the system according to FIG. 1 by way of example.
FIG. 7 is a flowchart illustrating a method of detecting a 2D object using the system of FIG. 1 .
FIG. 8 is a diagram for explaining the operation of the object detection unit according to FIG. 6 .
9 to 13 are diagrams showing optical images of a substrate and a 2D detection target obtained from the system according to FIG. 1 .

Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings, but the same or similar reference numerals are given to the same or similar components, and overlapping descriptions thereof will be omitted. The suffix "part" for components used in the following description is given or used interchangeably in consideration of ease of writing the specification, and does not itself have a meaning or role distinct from each other. In addition, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of a related known technology may obscure the gist of the embodiment disclosed in this specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in this specification, the technical idea disclosed in this specification is not limited by the accompanying drawings, and all changes included in the spirit and technical scope of the present invention , it should be understood to include equivalents or substitutes.

Terms including ordinal numbers, such as first and second, may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

It should be understood that when an element is referred to as being “connected” to another element, it may be directly connected to the other element, but other elements may exist in the middle.

Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as "comprise" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

It is advised that the drawings are schematic and not drawn to scale. Relative dimensions and proportions of parts in the drawings are shown exaggerated or reduced in size for clarity and convenience in the drawings, and any dimensions are illustrative only and not limiting. And like structures, elements or parts appearing in two or more drawings, like reference numerals are used to indicate like features.

The embodiments of the present invention specifically represent ideal embodiments of the present invention. As a result, various modifications of the drawings are expected. Therefore, the embodiment is not limited to the specific shape of the illustrated area, and includes, for example, modification of the shape by manufacturing.

1 is a diagram schematically showing the configuration of a 2D object detection system according to the present invention, FIG. 2 is a diagram exemplarily showing a substrate and a 2D detection object used in the system according to FIG. 1, and FIG. 3 is a diagram of FIG. Fig. 4 is a block diagram showing components of another embodiment of the system according to Fig. 1, Figure 5 is a block diagram showing components of another embodiment of the system according to Fig. 1 FIG. 6 is a block diagram exemplarily illustrating the configuration of an object detection unit of the system according to FIG. 1 , FIG. 7 is a flow chart illustrating a 2D object detection method using the system according to FIG. 1 , and FIG. 9 to 13 are diagrams for explaining the operation of the object detection unit according to FIG. 6 , and diagrams showing optical images of a substrate and a 2D detection object obtained by the system according to FIG. 1 .

The system for detecting a 2D object (10, hereinafter referred to as a 'system') according to the present invention can automatically detect a 2D material or material of an atomic monolayer such as graphene. Hereinafter, "2-dimensional object" or "2-dimensional detection object" means an atomic monolayer 2-dimensional material or material.

Referring to FIG. 1 , a 2D object detection system 10 according to the present invention may include an observation unit 110 and a detection unit 200 . The observation unit 110 may include an observation unit 130 that enlarges the 2D detection target 101 placed on the substrate and a photographing unit 120 that obtains an optical image of the 2D detection target 101 and the substrate, and detects Unit 200 may be implemented in the form of a computer. The observation unit 110 and the detection unit 200 may communicate with each other by being wired or wirelessly connected.

The observation unit 110 includes a stage 140 moving in the X-axis and Y-axis directions, a two-dimensional detection object 101 placed on the stage 140, an observation unit 130 for observing the two-dimensional detection object 101, and two It may include a photographing unit 120 that obtains an optical image by photographing the dimensional detection object 101 . The photographing unit 120 may be provided in the form of a CMOS camera, and the observation unit 130 may be provided in the form of an optical microscope having an objective lens.

The photographing unit 120 does not photograph the detection target 101 placed on the stage 140 as a whole at once, but moves on the detection target 101 to photograph a small part and then moves again to photograph another part. will repeat

Since the photographing unit 120 and the observation unit 130 are fixed, the detection target 101 located under the photographing unit 120 must move. To this end, the stage 140 on which the object to be detected 101 is placed may be provided to be movable along the X-axis and Y-axis directions.

For example, the stage 140 may move along the X-axis and Y-axis directions so that the scan range of the photographing unit 120 is 5×5 cm ² , the scan speed is 1 mm/s, and the recognition time is 0.2 s/frame. there is. In addition, the stage 140 may be moved to detect one 2D detection object 101 per 10 minutes with a detection rate of 90% for a search area of 100 mm ² /min.

Meanwhile, the detection target 101 is not directly placed on the stage 140, but the substrate 102 on which the detection target 101 is present is placed on the stage 140 as shown in FIG.

The system 10 according to the present invention accurately detects the existing position of the 2D detection target 101 by image analysis of the 2D detection target 101 obtained by repeating the mechanical peeling method, that is, attaching and detaching the scotch tape. Referring to FIG. 2, in order to transfer the two-dimensional detection object 101 (eg, graphene) attached to the scotch tape 109 to the substrate 102 by a mechanical peeling method, the scotch tape 109 is attached to the substrate 102. ), the two-dimensional detection target 101 is transferred from the scotch tape 109 to the surface of the substrate 102. The substrate 102 on which the 2D detection target 101 is present is placed on the stage 140, and the 2D detection target 101 is analyzed and detected using an optical method.

Here, glass, silicon wafer, etc. may be used as the substrate 102 . When the substrate 102 is a silicon wafer, SiO ₂ having a thickness of several hundred nm is formed on its surface (upper surface), and the two-dimensional detection target 101 is attached to the SiO ₂ . At this time, on the surface of SiO ₂ , not only the two-dimensional detection target 101 but also thick materials, impurities, or marks of scotch tape exist together.

The optical image of the 2D detection target 101 photographed by the photographing unit 120 and the photographing position, that is, information on the X-axis or Y-axis movement of the stage 140, etc. are transferred to the detection unit 200, and based on this The detection unit 200 may detect the position of the 2D detection target 101 .

As shown in FIG. 3 , the system 10 according to the present invention receives the optical image obtained from the photographing unit 120 and the photographing unit 120 for photographing the 2D detection target 101 and performs image processing and analysis thereof. and a display unit 290 that visually displays the detection result of the object detector 210. The object detection unit 210 and the display unit 290 may be included in the detection unit 200 .

In addition, as shown in Figure 4, the system 10 according to the present invention, the lighting unit 150 for providing illumination when the photographing unit 120 photographs the two-dimensional detection target 101 and the substrate 102, A stage driver 146 for moving the stage 140 in the X-axis or Y-axis direction may be further included.

In addition, as shown in FIG. 5 , the system 10 according to the present invention may further include an object transfer unit 190 . The object transfer unit 190 moves to the coordinates where the detection object 101 is located according to the location information (coordinate values) of the 2D detection object 101 detected by the object detection unit 210, and then moves to the 2D object 102 from the substrate 102. This is a part that separates and moves the dimensional detection object 101. The system 10 according to the present invention may not only detect the position of the 2D detection target 101 but also transfer the 2D detection target 101 at the corresponding position.

In addition, in the case of the system 10 according to the present invention, since the observation unit 110 may be configured to be provided in the glove box, during the process of detecting the 2D detection target 101, the 2D detection target 101 is in the air. It can also be prevented from reacting with and being oxidized.

Referring to FIG. 6 , the object detection unit 210 includes a control unit 220, an image acquisition unit 230, an image processing unit 240, an image analysis unit 250, an image determination unit 260, a storage unit 270, and A communication unit 280 may be included. The control unit 220 controls the operation of the image acquisition unit 230, the image processing unit 240, the image analysis unit 250, the image determination unit 260, the storage unit 270, and the communication unit 280 or transmits various types of information. can give and take In addition, the controller 220 may control the operation of the lighting unit 150, the photographing unit 120, the stage driving unit 146, or the object transfer unit 190, or exchange various types of information.

First of all, the controller 220 may control whether the lighting unit 150 and the photographing unit 120 operate. For example, while the stage driving unit 146 is operating and the stage 140 is moving, the lighting unit 150 and the photographing unit 120 are not operated, and the lighting unit 150 and the photographing unit are photographed when the stage 140 is stopped. The unit 120 can be controlled to operate.

The control unit 220 may obtain positional information (coordinate values) of the 2D detection target 101 or the substrate 102 at the time when the photographing unit 120 captures the image from information related to the operation of the stage driving unit 146. It can be stored in the storage unit 270. At this time, the controller 220 may match the location information (coordinate values) with the optical image taken at the corresponding location, and store the optical image matched with the location information in the storage unit 270 .

The control unit 220 retrieves the location information (coordinate values) of the 2D detection object 101 of the thinnest atomic monolayer from the storage unit 270 and transfers it to the object transfer unit 190, thereby transferring the object transfer unit. 190 can be controlled to capture and transfer the 2D detection target 101 at the corresponding location.

The storage unit 270 is a database and may store various information and result values obtained in the process of detecting the 2D detection target 101 .

The communication unit 280 may transmit data stored in the storage unit 270 to a user's smartphone or other terminal through wireless communication.

Hereinafter, the process of detecting the two-dimensional detection target 101 will be described in more detail.

The system 10 according to the present invention includes a stage 140 on which a substrate 102 on which a two-dimensional detection target 101 is present is placed; a photographing unit 120 for photographing the substrate 102 including the two-dimensional detection target 101; and an object detection unit 210 that identifies or detects the 2D detection target 101 using the optical image of the substrate 102 obtained by the photographing unit 120 .

Here, the object detection unit 210 may detect the 2D detection object 101 by using an interference effect between the 2D detection object 101 and the thin film (eg, SiO ₂ ) of the substrate 101 .

As such, the system 10 according to the present invention can identify the 2D detection target 101 or detect its position using the optical interference effect of the 2D detection target 101 . The light emitted from the lighting unit 150 is directly reflected from the two-dimensional detection target object 101 or transmitted through the two-dimensional detection target object 101 and then reflected from the surface of the substrate 102 or transmitted through SiO ₂ of the substrate 102. can be reflected later. Therefore, a difference in transmittance of light occurs depending on the thickness or refractive index of the two-dimensional detection object 101 or SiO ₂ , which causes an interference effect. The system 10 according to the present invention can detect the detection target 101 using this interference effect.

That is, the system 10 according to the present invention analyzes the optical image obtained with respect to the surface of the substrate 102 including the 2D detection target 101 by applying an interference effect, thereby analyzing the 2D detection target 101. The location can be detected accurately and quickly.

To this end, the system 10 according to the present invention identifies the 2D detection target 101 using each contrast ratio according to the RGB wavelength band extracted from the optical image of the 2D detection target 101, or Its position can be detected.

The photographing unit 120 photographs the substrate 102 placed on the stage 140 in a stopped state after the stage 140 is moved by the stage driving unit 146. At this time, not only the substrate 102 but also 2D detection The object 101 is also photographed. Since the lighting unit 150 radiates light to the 2D detection target 101 and the substrate 102 during photographing, the photographing unit 120 may obtain an optical image of the substrate 102 .

An optical image of the substrate 102 photographed by the photographing unit 120 may be transmitted to the image acquisition unit 230 of the object detection unit 210 . The optical image of the substrate 102 transmitted to the image acquisition unit 230 is a JEPG type image. In order to perform pixel analysis, the shape of the image must be transformed. The image processing unit 240 may receive the JEPG type optical image from the image acquisition unit 230 and convert it into a BITMAP type. The image processing unit 240 may transmit an optical image in the form of a BITMAP to the image analysis unit 250 .

The image analyzer 250 may analyze the 2D detection target 101 to be found in the BITMAP type optical image by using the interference effect. Here, the optical image in the form of a BITMAP includes not only the image of the substrate 102 but also the two-dimensional detection target 101, the multilayer detection target (that is, the relatively thick detection target, not the thinnest detection target), impurities (Scotch tape 109, Including traces of (see FIG. 2)) are included. Most of the optical images are images of the substrate 102 and can be considered as background images.

First, the object detection unit 210 to the image analysis unit 250 measure the contrast ratio of the two-dimensional detection target object 101, the multi-layer detection target object, and a region in which impurities exist in the optical image of the substrate 102 and other background regions. Thus, a region in which the 2D detection target 101 exists may be detected.

The image analyzer 250 distinguishes between an area in which an object is determined to exist and other areas (background areas) of the optical image, and may distinguish the background area from other areas by measuring the contrast ratio of each area. Since there is basically nothing in the background area, it is relatively bright while the other areas are dark. The image analyzer 250 first distinguishes the background area from other areas using the contrast ratio. In addition, the image analyzer 250 may check a region estimated to contain the 2D detection target 101 by measuring the contrast ratio.

The 2D detection target 101 such as 2D graphene is very thin because it has an atomic monolayer structure. Therefore, the 2D detection target 101 is hardly visible in the optical image in the white light irradiated state. Accordingly, the image analyzer 250 may determine whether or not the 2D detection target 101 is present based on each contrast ratio according to the RGB wavelength band of the optical image. That is, the image analysis unit 250 extracts each color image of RGB from the optical image, calculates the contrast ratio of the area where the 2D detection target 101 in the form of a single layer flake is located and the outside thereof, and obtains 2 The presence or absence of the dimensional detection object 101 can be confirmed.

Since the 2D detection target 101 is very thin, it is almost invisible when viewed with white light, but when divided into RGB colors, the 2D detection target 101 can be identified because the contrast of the 2D detection target 101 is different for each RGB color. there is.

The image analyzer 250 extracts each color of RGB from the optical image, inputs a set value for a contrast ratio difference between each RGB and the background, and then extracts only image areas or pixels that satisfy the set value.

That is, the object detection unit 210 to the image analysis unit 250 extract each RGB color image from the optical image of the substrate 102, and set the difference between the contrast ratio of the background area and the contrast ratio of each RGB in the optical image. Only estimated pixels that satisfy the values can be extracted.

In more detail, the object detector 210 or the image analyzer 250 extracts each color image of RGB from the optical image of the substrate 102, and determines the difference between the contrast ratio of the R (red) color image and the background area. The set value, the set value for the difference between the contrast ratio of the G (green) color image and the background area, and the set value for the difference between the contrast ratio between the B (blue) color image and the background area are input to the system 10, and these three Image areas or pixels that satisfy the set value may be extracted. Here, pixels satisfying these three set values are defined as estimated pixels (that is, pixels estimated to be 2D detection targets).

Here, the set value for the difference in contrast ratio between each of the RGB and the background area varies depending on the type of the 2D detection object 101, the type of the substrate 102, the thickness of the substrate thin film, etc. These set values are already theoretically defined. has been

The inventors of the present application, the two-dimensional detection target 101 is graphene, the substrate 102 is a 1.5Х1.5 cm silicon wafer (Si wafer), and the thickness of the thin film (SiO2) is 300 nm between RGB and the background area. Set values for contrast ratio differences were input, and estimated pixels satisfying these set values were identified.

Meanwhile, the image area or the estimated pixels where these estimated pixels are located may include not only the two-dimensional detection target 101 to be detected, but also thick multi-layered detection targets and impurities (including scotch tape traces). Therefore, it is necessary to remove the multi-layer detection target except for the 2D detection target 101 and impurities from the estimated pixels.

The object detection unit 210 or the image analysis unit 250 detects a close area where the estimated pixels are gathered, determines the uniformity of the estimated pixels located in the close area, or obtains the size of the close area to determine the 2D detection target 101 ) and impurities can be distinguished.

In other words, the object detecting unit 210 or the image analyzing unit 250 calculates the average value of the brightness difference of the estimated pixels existing in the close area and the uniformity or gradient of the pixel values to determine the 2D detection target 101 and its It is possible to distinguish multi-layer detection targets and impurities other than

9 to 12 illustrate optical images analyzed by the object detection unit 210 or the image analysis unit 250 by way of example. An RGB color image is extracted from such an optical image, and estimated pixels are distinguished by comparing a set value for a contrast ratio difference with the background area.

Referring to (a) and (b) of FIG. 9 , it can be seen that a gray portion is the background and the remaining color portions are the 2D detection target 101 and impurities. In the case of FIG. 9 , those marked with yellow or blue colors can be easily distinguished with the naked eye, and they are likely to be thick multi-layer detection objects or impurities. As described above, the 2D detection target 101 is almost indistinguishable because it is very thin.

As a result of the comparison by the image analyzer 250 with the set value of the difference in RGB contrast ratio, it was determined that the part marked with a rectangle in FIG.

In the case of FIG. 10 , it was determined that a portion marked with a rectangle satisfies the set value, but it was confirmed that this area was not a 2D detection object 101 because the boundary was ambiguous and the color was unclear.

In the case of FIG. 11, it was determined that the area marked with a rectangle satisfies the set value, and this area was not the 2D detection target 101, but the scotch tape 109 to which the 2D detection target 101 was attached. It became.

In the case of FIG. 12 , it was determined that a portion indicated by a rectangle satisfies the set value, and it was confirmed that the same portion of this area was repeatedly photographed according to the movement of the stage 140 .

The object detecting unit 210 or the image analyzing unit 250 estimates that a 2D detection object does not exist when the pixel values of the estimated pixels present in the close area where the estimated pixels are concentrated gradually increase, decrease, or change. can judge If the pixel values of the estimated pixels existing in the close area gradually increase or decrease, that is, if there is a gradient in the pixel values, it is determined that the object 101 is not a 2D detection object 101 .

On the other hand, the object detector 210 or the image analyzer 250 may estimate or determine that the 2D detection object 101 exists when the pixel values of estimated pixels existing in the close area are uniform. .

The object detector 210 to the image analyzer 250 estimate that the 2D detection target 101 exists in the rectangular display area in the case of FIG. 9 , and impurities are present in the rectangular display area in the case of FIGS. 10 to 12 . presumed to exist.

Also, the object detector 210 to the image analyzer 250 may estimate that the 2D detection object 101 does not exist when the size of the close area is equal to or less than a reference value. For example, when the size of the close area is smaller than 5 μm, it may be determined that the 2D detection target 101 does not exist in the close area. Because, when the two-dimensional detection object 101 such as graphene is smaller than 5 μm, it is preferable not to detect it because it cannot be used for research or commercial purposes.

Meanwhile, when the image analysis unit 250 determines that the object detecting unit 210 is a close area in which the 2D detection target 101 exists, the object detector 210 transfers pixel values of the corresponding close area to the image determiner 260 and finally The presence or absence of the 2D detection target 101 can be determined.

The image determination unit 260 determines whether pixels satisfying the set value of the contrast ratio difference between the RGB and background areas are located close to each other. will do If it is determined that the pixels are not close due to a long distance between them, the corresponding pixel is discarded.

At this time, the detection unit 200 may not perform the calculation properly because calculating the distance between all pixels requires a considerable amount of calculation. For example, if the number of pixels in the rectangle indicated in (a) of FIG. 9 is 1000×1000, it is not easy to calculate the distance between all these pixels and may require a high-end computer.

The system 10 according to the present invention can reduce the amount of computation required to obtain a distance between pixels by converting the close-contact area determined by the image determination unit 260 into a low-resolution image. After it is determined that the 2D detection object 101 exists in the low-resolution image or the approximate location of the 2D detection object 101 is found, the high-resolution image is restored to find the edge or border of the 2D detection object 101. Accordingly, location information (coordinate values) is stored in the storage unit 270 .

8 shows a case where there are (N×m)×(N×m) pixels in a dense area in which the 2D detection target 101 is estimated to exist. Here, N and m are arbitrary numbers. For example, when there are 1000×1000 pixels in a dense area, N=10 and m=100 may be obtained.

The object detection unit 210 or the image determination unit 260 selects N×N (N×m)×(N×m) pixels existing in the close area where the 2D detection target 101 is estimated to exist. After conversion into two low-resolution images, pixel values of the low-resolution images are compared to determine whether or not there is a 2D detection target, and pixels present only in an area where the 2D detection target 101 is estimated to exist are (N×m) After conversion into ×(N×m) high-resolution images, pixel values of the high-resolution images are compared to detect the edge of the 2D detection object, and location information thereof may be stored.

The object detection unit 210 or the image analysis unit 260 determines N×m×(N×m) pixels existing in the close area where the 2D detection target 101 is estimated to exist. It is possible to detect the presence or absence of the 2D detection object by defining a sub-array composed of N pieces and comparing pixel values for m×m pieces of sub-arrays as one representative value.

8, if the total number of pixels is (N = 10 × m = 100) × (N = 10 × m = 100), the number of pixels is (N = 10) × (N = 10) subarray (sub array) can be defined and an array image of (m=100)×(m=100) can be created with the pixel value (P) of this sub array as one representative value. Through this process, since (1000) × (1000) pixels are reduced to (100) × (100) pixels, it can be seen that the image is converted into a low-resolution image.

The image determining unit 260 compares pixel values or distances with neighboring (N = 10) × (N = 10) pixels of (100) × (100) array images to determine proximity or not. and the amount of computation can be reduced.

The object detector 210 or the image determiner 260 compares the pixel values of (m = 100) × (m = 100) pixels with the representative pixel values of the sub-array as one representative value, and obtains 2 The location information of the area where the dimensional detection target 101 is estimated to exist is stored, and pixels existing only in the estimated area are (N=10×m=100)×(N=10×m=100) pixels. That is, by converting the image into an original high-resolution image and comparing pixel values with neighboring pixels, the edge of the 2D detection object 101 may be finally detected and the location information thereof may be stored. Such information may be stored in the storage unit 270 .

In FIG. 13 , the object detection unit 210 or the image determination unit 260 of the system 10 according to the present invention extracts RGB colors from the optical image and compares them with the set value for the contrast ratio difference between the RGB and the background area. The result of the judgment is shown.

The contrast ratio setting values of RGB used to derive the results of FIG. 13 are shown in [Table 1].

Settings Red -5.0% Green -4.0% Blue 1.0% Accuracy 97.5%

The setting values of [Table 1] are that the substrate 102 is a 1.5 × 1.5 cm silicon wafer (Si wafer), the thin film of the substrate is 300 nm thick SiO ₂ , and the two-dimensional detection target 101 is graphene. is the set value.

[Table 1] shows that graphene (i.e., a two-dimensional detection object) exists in the case of a pixel where the contrast of Red is 5.0% smaller than the contrast of the background area, the contrast of Green is 4.0% smaller, and the business card of Blue is 1.0% larger. it means.

As a result of determining a total of 9 close areas through pixel comparison with the set values in [Table 1] in the image determination unit 260, 4 two-dimensional detection objects 101, 4 multi-layer detection objects, and 1 scotch tape mark was found, and the results are shown in (a) to (c) of FIG. 13 (a) shows an image of a single-layer 2D detection target, (b) shows an image of a multi-layer detection target, and (c) shows an image of a scotch tape mark.

Meanwhile, FIG. 7 briefly describes a method of detecting a 2D object using the 2D object detection system 10 according to the present invention.

Referring to FIG. 7 , a method for detecting a 2D object according to the present invention includes acquiring an image (1100), converting an image (1200), obtaining a background color from the converted image (1300), and obtaining a sub-array of pixels. (1400), obtaining a representative pixel value from a sub-array of pixels (1500), comparing neighboring pixel values with representative pixel values (1600), extending the range of neighboring pixels (1700), presence or absence of a detection target It may include step 1800 of determining.

The image acquisition step 1100 is a process of obtaining an optical image of the 2D detection target 101 including the substrate 102 by the photographing unit 120, and may be performed by the image acquisition unit 230.

The image conversion step 1200 is a process of converting the format of the optical image obtained by the photographing unit 120 from JPEG to BITMAP, and may be performed by the image processing unit 240 .

Obtaining the background color from the converted image (1300) is a process of distinguishing the background area from other areas, and may be performed by the image analyzer 250. Step 1300 is a process of measuring the contrast ratio of the BITMAP optical image in the image analyzer 250 and classifying the background according to the result.

Obtaining a sub-array of pixels (1400), obtaining a representative pixel value from the sub-array of pixels (1500), comparing neighboring pixel values with representative pixel values (1600), extending the range of neighboring pixels Step 1700 and step 1800 of determining whether or not there is a detection target are processes performed by the image determination unit 260, and since related descriptions are the same as those of the image determination unit 260, repetitive descriptions are omitted. do.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program commands recorded on the medium may be specially designed and configured for the embodiment or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CDROMs and DVDs, and magnetic-optical media such as floptical disks. Included are hardware devices specially configured to store and execute program instructions, such as magneto-optical media and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The 2D object detection system 10 according to the present invention described above can be used to detect not only graphene but also various 2D materials (materials) such as black phosphorus, TMDC, and hBN, as long as they are manufactured by a mechanical exfoliation method.

As described above, in one embodiment of the present invention, specific details such as specific components and limited embodiments and drawings have been described, but this is only provided to help a more general understanding of the present invention, and the present invention is based on the above embodiments. It is not limited, and those skilled in the art can make various modifications and variations from these descriptions. Therefore, the spirit of the present invention should not be limited to the described embodiments and should not be determined, and all things equivalent or equivalent to the claims as well as the following claims belong to the scope of the present invention.

10: 2D object detection system
110: observation unit 120: shooting unit
130: observation unit 140: stage
146: stage driving unit 150: lighting unit
190: object transfer unit 200: detection unit
210: object detection unit 220: control unit
230: image acquisition unit 240: image processing unit
250: image analysis unit 260: image determination unit

Claims (10)

A system for detecting a 2D object, characterized in that the 2D object is identified or its position is detected using each contrast ratio according to RGB wavelengths extracted from an optical image of the 2D object.
According to claim 1,
a stage on which a substrate on which the two-dimensional detection object is present is placed;
a photographing unit for photographing the substrate including the 2D detection target; and
and an object detection unit configured to identify or detect the 2D detection target using the optical image of the substrate obtained by the photographing unit,
The 2D object detection system of claim 1 , wherein the object detection unit detects the 2D object by using an interference effect between the 2D object and the thin film of the substrate.
According to claim 2,
The object detection unit detects an area where the 2D detection target exists by measuring a contrast ratio between a region in which the 2D detection target, the multilayer detection target, and impurities are present, and other background regions in the optical image of the substrate. 2D object detection system.
According to claim 3,
The object detection unit extracts a color image of each RGB from the optical image, and extracts an estimated pixel satisfying a set value for a difference between a contrast ratio of the background area and a contrast ratio of each RGB in the optical image. 2D object detection system.
According to claim 4,
The 2D object detection system of claim 1 , wherein the object detection unit detects a close area where estimated pixels are gathered, determines uniformity of estimated pixels located in the close area, or obtains a size of the close area.
According to claim 5,
The object detection unit distinguishes the two-dimensional detection object from other multi-layer detection objects and impurities by calculating an average value of brightness and darkness differences of estimated pixels existing in the close area, and a uniformity or gradient of pixel values. object detection system.
According to claim 6,
The object detector estimates that the 2D detection object does not exist when the pixel values of the estimated pixels present in the close area gradually increase, decrease, or change, and when the pixel values of the estimated pixels are uniform, the second The system for detecting a 2D object, characterized in that it estimates that a dimensional detection object exists or that the 2D detection object does not exist when the size of the close area is equal to or less than a reference value.
According to claim 7,
The object detector converts (N×m)×(N×m) pixels existing in the close area in which the 2D detection target is estimated to exist into N×N low-resolution images, and then converts the pixels of the low-resolution image. Compare the values to determine the presence or absence of the two-dimensional detection target,
After converting pixels existing only in the area where the 2D detection target is estimated to exist into (N×m)×(N×m) high-resolution images, pixel values of the high-resolution images are compared to the edges of the 2D detection target. A 2D object detection system, characterized in that for detecting and storing the location information.
According to claim 8,
The object detector defines a subarray composed of N×N pixels for (N×m)×(N×m) pixels existing in the close proximity area where the 2D detection target is estimated to exist, and the subarray The 2D object detection system, characterized in that the presence or absence of the 2D detection object is detected by comparing pixel values of m×m pieces of m×m having as one representative value.
According to claim 9,
The object detection unit compares pixel values for m×m pieces of sub-arrays as one representative value, and stores location information of an area where the 2D detection object is estimated to exist, and stores the location information of the estimated area. 2D object detection characterized by converting pixels existing only in (N×m)×(N×m) pixels, comparing pixel values, detecting an edge of the 2D detection target, and storing the location information. system.

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