KR20230036270A - Apparatus and method generating 3d image of target metalic grain - Google Patents

Abstract

The present disclosure relates to a method by which an electronic device generates a three-dimensional image of a target metal microstructure and an electronic device that performs the same. According to one embodiment, the method by which an electronic device generates a three-dimensional image of a target metal microstructure may comprise the steps of: acquiring a plurality of measurement images including at least one microstructure appearing on a target metal surface while physically or chemically processing the target metal surface; determining an average height value of the target metal surface appearing in the measurement images; generating region-of-interest images including the at least one microstructure from the measurement images; identifying a boundary of at least one microstructure appearing on the target metal surface in the generated region-of-interest images; and generating a three-dimensional image by stacking the region of interest images in which the boundary of the at least one microstructure is identified based on the determined average height value. Accordingly, a metal surface can be monitored effectively.

Description

Method and apparatus for generating a three-dimensional image of a target metal microstructure

The present disclosure relates to methods and apparatus for generating three-dimensional images of metal microstructures. More specifically, it relates to a method and apparatus for generating an image including a three-dimensional shape of a microstructure observed on a target metal surface.

3D observation of metal structures can be used for higher-order finite element analysis as well as basic research to overcome the limitations of non-destructive testing methods such as ultrasonic testing, magnetic particle testing, and eddy current testing. The finite element method is used to analyze the relationship between load, stress-strain and fracture resistance of a structure. According to previous studies, the size and shape of a microstructure affects the strength, toughness and creep resistance of a structure. However, since the element used in the finite element method is the shape of the structure and does not include the microstructure of the structure itself, it is not easy to reflect it to the finite element method, and an example in which the size of the microstructure is inserted as an analysis condition in the finite element method has not been disclosed. .

On the other hand, the size and shape of metal crystals can affect the analysis results of non-destructive tests such as ultrasonic inspection, magnetic particle inspection, and eddy current inspection, and some analysis or qualitative analysis techniques considering only the average size of microstructures are disclosed. A technique for ultrasonic scattering targeting the size and shape of a target metal microstructure has not been disclosed.

In the magnetic particle inspection method, a sample is magnetized and magnetic particle adsorption by leakage magnetic flux generated around defects is observed. At this time, a strong external magnetic field is applied and then removed, resulting in residual magnetization, which causes magnetic particles to be adsorbed even in areas without defects. There are limits to which similar error signals can be generated. In addition, in welding where heat and residual stress are generated by an external force, residual magnetization also frequently occurs. Since the magnetic domains are distributed in three dimensions inside the metal crystal, it is necessary to understand the distribution of the remanent magnetization inside the metal crystal in order to further understand the nature of the remanent magnetization.

In addition, in the eddy current inspection method, an induced current is applied to the object to be measured and the distortion of the induced current generated around the defect, that is, the impedance change and phase difference due to the eddy current are measured. There are limitations that make it difficult to determine the presence or size. In order to understand the effects of these effects, that is, the formation of magnetic domains, residual magnetization, and the effects of edges according to shape and size, it is necessary to develop a technology that provides a means to quantitatively measure and express the three-dimensional shape of a metal crystal.

In addition, according to crystal nano-radiography and tomography, metal crystals can be imaged in three dimensions. Nevertheless, this requires very high accuracy and expensive equipment, including X-ray shielding. Moreover, it is difficult to measure the magnetic domain distribution in a metal crystal in three dimensions.

Therefore, in order to effectively analyze the shape and size of the metal microstructure at a low cost, the development of a technology for shaping the shape of the microstructure in three dimensions is required.

Japanese Laid-open Patent No. 1992-072551

According to an embodiment, a method of generating a 3D image of a target metal microstructure and an electronic device performing the same may be provided.

More specifically, a method of reconstructing a metal microstructure into a 3D image by stacking microstructure images and an electronic device performing the same may be provided.

As a technical means for achieving the above-mentioned technical problem, according to an embodiment, a method for generating a three-dimensional image of a target metal microstructure by an electronic device is to physically or chemically treat the target metal surface while at the target metal surface. obtaining a plurality of measurement images including at least one microstructure appearing; determining an average height value of a target metal surface appearing in the measured images; generating ROI images including the at least one microstructure from the measurement images; identifying a boundary of at least one microstructure appearing on the target metal surface from the generated ROI images; and generating a 3D image by stacking ROI images in which a boundary of the at least one microtissue is identified, based on the determined average height value. can include

According to another embodiment for achieving the above-described technical problem, an electronic device generating a three-dimensional image of a target metal microstructure includes a display; a memory that stores one or more instructions; and at least one processor executing the one or more instructions; wherein the at least one processor obtains a plurality of measurement images including at least one microstructure appearing on the target metal surface while physically or chemically treating the target metal surface by executing the one or more instructions; Determining an average height value of a target metal surface appearing in the measurement images, generating ROI images including the at least one microstructure from the measurement images, and generating the target metal surface from the generated ROI images. A 3D image may be generated by identifying a boundary of at least one microstructure appearing in , and stacking ROI images in which the boundary of the at least one microstructure is identified based on the determined average height value.

According to another embodiment for achieving the above-described technical problem, in a method for generating a three-dimensional image of a target metal microstructure by an electronic device, while physically or chemically treating the target metal surface, the surface of the target metal appears. acquiring a plurality of measurement images including at least one microstructure; determining an average height value of a target metal surface appearing in the measured images; generating ROI images including the at least one microstructure from the measurement images; identifying a boundary of at least one microstructure appearing on the target metal surface from the generated ROI images; and generating a 3D image by stacking ROI images in which a boundary of the at least one microtissue is identified, based on the determined average height value. A computer-readable recording medium in which a program for performing the method including a may be provided.

According to an embodiment, a 3D image of a microstructure of a target metal may be generated.

According to an embodiment, a metal surface can be effectively monitored using a 3D image of a microstructure of a target metal.

1 is a diagram schematically illustrating a process of generating a 3D image of a microstructure of a target metal surface by an electronic device according to an exemplary embodiment.
2 is a diagram for explaining a process of acquiring a plurality of measurement images of a target metal specimen mounted through a microscope by an electronic device according to an embodiment.
3 is a flowchart of a method of generating a 3D image of a target metal microstructure by an electronic device according to an exemplary embodiment.
4 is a diagram for explaining a process of measuring a height of a target metal surface by an electronic device according to an exemplary embodiment.
5 is a table including height values of a target metal surface measured after physical polishing and chemical etching of the target metal surface by an electronic device according to an embodiment.
6 illustrates measurement images acquired through a microscope after an electronic device polishes a target metal surface three times, four times, and five times, and reference images and targets selected to identify a region of interest in the measurement images according to an embodiment. represents an image.
7 is a diagram for explaining a process of generating ROI images by performing a local positioning algorithm on measurement images by an electronic device according to an embodiment.
8 is a view for explaining an image of a region of interest extracted by applying a local positioning algorithm to a specific region of measurement images obtained after polishing a target metal surface three times and four times.
9 is a flowchart of a method of identifying, by an electronic device, a boundary of a microtissue in ROI images according to an embodiment.
10 is a diagram for explaining an example in which an electronic device identifies a boundary of microstructure in ROI images according to an exemplary embodiment.
11 is a flowchart of a method of resizing, by an electronic device, a boundary of a microtissue identified in ROI images according to an embodiment.
12 is a diagram for explaining an example in which an electronic device resizes a boundary of a microtissue identified in ROI images according to an embodiment.
13 is a flowchart of a specific method of generating a 3D image by an electronic device according to an embodiment.
14 is an example of ROI images showing predetermined microstructures used by an electronic device to generate a 3D image according to an embodiment.
15 is a diagram illustrating a result of stacking a plurality of ROI images for each microstructure by an electronic device according to an embodiment.
FIG. 16 is a diagram for explaining a 3D image generated by surface-processing the boundary of microstructures appearing in the stacked ROI images of FIG. 15 by the electronic device according to an exemplary embodiment.
17 is a block diagram of an electronic device according to an embodiment.
18 is a block diagram of an electronic device according to another embodiment.

Terms used in this specification will be briefly described, and the present disclosure will be described in detail.

The terms used in the present disclosure have been selected from general terms that are currently widely used as much as possible while considering the functions in the present disclosure, but they may vary according to the intention or precedent of a person skilled in the art, the emergence of new technologies, and the like. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, terms used in the present disclosure should be defined based on the meaning of the term and the general content of the present disclosure, not simply the name of the term.

When it is said that a certain part "includes" a certain component throughout the specification, it means that it may further include other components without excluding other components unless otherwise stated. In addition, terms such as "...unit" and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software. .

Hereinafter, with reference to the accompanying drawings, embodiments of the present disclosure will be described in detail so that those skilled in the art can easily carry out the present disclosure. However, the present disclosure may be implemented in many different forms and is not limited to the embodiments described herein. And in order to clearly describe the present disclosure in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

1 is a diagram schematically illustrating a process of generating a 3D image of a microstructure of a target metal surface by an electronic device according to an exemplary embodiment.

According to an embodiment, the electronic device 1000 obtains a plurality of measurement images 102 and 104 including at least one microstructure appearing on a target metal surface, and uses the obtained plurality of measurement images to obtain a 3D image. Image 160 may be created. According to an embodiment, the electronic device 1000 may generate 3D images 162, 164, and 166 for each microstructure of the target metal, but may generate a 3D image 168 including a plurality of microstructures. may be

According to an embodiment, the electronic device 1000 may include a memory 120 storing one or more instructions and at least one processor 140 executing the one or more instructions. The processor may perform a method of generating a 3D image of a target metal microstructure by executing one or more instructions stored in the memory 120 .

According to an embodiment, the electronic device 1000 may include a microscope device, but may acquire a plurality of measurement images of a target metal from the microscope device by being connected to the microscope device. Also, although not shown in FIG. 1 , the electronic device 1000 may further include a polishing device for physically polishing the surface of the target metal or an etching device for chemically etching the target metal surface.

According to an embodiment, the electronic device 1000 may acquire a plurality of measurement images as a tissue picture through a metal microscope while polishing a target metal specimen mounted on a microscope device, and perform local positioning on the acquired measurement images ( 3D images can be created by performing LOCAL POSITIONING, METAL SELECTION, BINARYZATION, RESIZEING, STACKING, and SURFACING. In the present disclosure, a metal crystal observed in a target metal may correspond to a microstructure.

According to an embodiment, the target metal measured by the electronic device may be carbon steel SA106, but is not limited thereto. In addition, according to an embodiment, the target metal to be measured by the electronic device 1000 may be cut to a width of 25 mm, a length of 9 mm, and a height of 25 mm, and is mounted on a cylindrical resin having a diameter of 35 mm and a height of 27 mm. It can be fixed on a stage of a microscope device. In addition, the electronic device 1000 may use a polishing device and an etching device to polish the observation surface and the back surface of the target metal mounted on the microscope device to be exposed to the outside of the resin, and through this, the average surface of the target metal after polishing is more accurate. height can be measured.

The electronic device 1000 may measure the height change of the measurement surface of the target metal polished through the polishing device and the etching device using a micrometer. Errors caused by compression can be avoided. The electronic device 1000 according to the present disclosure can accurately and objectively measure a metal microstructure by imaging or imaging the microstructure of a target metal in 3D.

2 is a diagram for explaining a process of acquiring a plurality of measurement images of a target metal specimen mounted through a microscope by an electronic device according to an embodiment.

Referring to figure 202 of FIG. 2, a state in which the side surface of the target metal is polished to be deflected by 1,84 mm is shown, and after being polished to be deflected in this way, the polished surface (eg, key hole) is set as a reference surface for microscopic observation. It can be. Referring to figure 204 of FIG. 2, a jig for uniformly polishing the polishing surface is shown, and referring to figure 206, the polishing surface (eg, key hole) is polished on the target metal specimen mounted on the jig. is shown

As shown in Figure 208, the mounted sample may be mounted on the jig of the XY stage of the microscope device and fixed by a key. The electronic device 1000 may fix the target metal with a repetition accuracy of about 10 to 20 micrometers using an XY stage and a key.

3 is a flowchart of a method of generating a 3D image of a target metal microstructure by an electronic device according to an exemplary embodiment.

In operation S310, the electronic device 1000 may acquire a plurality of measurement images including at least one microstructure appearing on the target metal surface while physically or chemically treating the target metal surface. According to an embodiment, the electronic device 1000 may acquire a plurality of measurement images from the microscope by being connected to the microscope. According to an embodiment, the electronic device 1000 obtains a measurement image by physically polishing a target metal surface, chemically etching the target metal surface, and photographing the chemically etched target metal surface. can do. According to an embodiment, the electronic device 1000 may acquire a plurality of measurement images by repeatedly performing an operation of obtaining measurement images after polishing and etching a target metal surface.

In S320, the electronic device 1000 may determine an average height value of the target metal surface appearing in the measurement images. For example, the electronic device 1000 may measure the height of the target metal surface using a micrometer at several points and determine an average height value of the measured height values. The electronic device 1000 may match the measured average height value with a measurement image or an ROI image obtained from the measurement image and store the measured average height value in a memory.

In operation S330, the electronic device 1000 may generate ROI images including at least one microstructure from the measured images. For example, a plurality of measurement images acquired by the electronic device 1000 may change reference positions for photographing the target metal during the process of polishing and etching the target metal specimen and then repositioning the target metal specimen on the stage of the microscope. Accordingly, the electronic device 1000 may generate ROI images whose positions are corrected by performing a local positioning algorithm on a plurality of measurement images.

In operation S340, the electronic device 1000 may identify a boundary of at least one microstructure appearing on the target metal surface in the generated ROI images. According to an embodiment, the electronic device 1000 identifies microtissue boundaries appearing in ROI images, and based on the identified microtissue boundaries, the number of microtissues appearing inside the ROI images, identification information, etc. may be matched and stored together with the ROI images.

In operation S350, the electronic device 1000 may generate a 3D image by stacking ROI images in which at least one microtissue boundary is identified based on the average height value. For example, the electronic device 1000 may generate ROI images in which a boundary of a microtissue is identified based on measurement images or an average height value of a target metal surface matched to ROI images generated from the measurement images. A 3D image can be created by stacking in a 3D space. The average height value of the ROI images measured by the electronic device 1000 may be a value representing a Z-axis position on the 3D image.

4 is a diagram for explaining a process of measuring a height of a target metal surface by an electronic device according to an exemplary embodiment.

In S410, when a plurality of measurement images including at least one microstructure appearing on the target metal surface are obtained, the electronic device 1000 calculates center height values from the center of corners of the target metal surface whenever each measurement image is acquired. can be measured For example, when measurement images are obtained, the electronic device 1000 may measure an average height of a target metal surface appearing in the measurement images using a micrometer.

According to an embodiment, when the electronic device 1000 measures the height of a sample with a micrometer after polishing the surface of a target metal, the electronic device 1000 uses a resin (RESIN), not the surface of the sample, as a measurement criterion, resulting in compression of the resin. possible errors can be avoided. According to an embodiment, the target metal surface observed by the electronic device 1000 may have a rectangular surface shape, and the electronic device 1000 uses a micrometer at the center of each corner of the target metal surface to determine the height of the target metal surface. values can be measured. The electronic device 1000 may determine an average value of center height values measured at the center of edges of the target metal surface as an average height value of the target metal for each measured image.

5 is a table including height values of a target metal surface measured after physical polishing and chemical etching of the target metal surface by an electronic device according to an embodiment.

According to an embodiment, the electronic device 1000 may perform physical polishing and chemical etching on the surface of the target metal, measure height values of a plurality of points of the target metal, and determine an average value of the measured height values. there is. The electronic device 1000 may store height values for each point measured at each physical polishing and chemical etching treatment of the target metal surface and an average value of the measured height values in a table format.

For example, the electronic device 1000 may polish the observation surface of the target metal using at least one of FEPA P200, P400, P800, P1200, and P2000, which are SiC polishing pads provided in the polishing device. According to an embodiment, the grid size of the P2000 used for final polishing may be 10.3 micrometers, and the electronic device 1000 finally uses a polishing cloth and a polycrystalline diamond paste having a grid size of 1 micrometer. and fine polishing can be performed for 20 seconds. The electronic device 1000 may perform chemical etching after performing physical polishing on the target metal using a polishing device.

For example, when the fine polishing is completed, the electronic device 1000 exposes an etchant obtained by diluting 3 g of nitric acid in 65 g of ethanol to the observation surface of the target metal for 5 seconds, performs ultrasonic cleaning with distilled water for 15 seconds, and performs ultrasonic cleaning. Thereafter, the surface of the target metal may be chemically etched by washing with ethanol for 10 seconds. According to one embodiment, after physical polishing, chemical etching of the target metal surface may be repeated three times in total, but is not limited thereto. The electronic device 1000 according to the present disclosure obtains a plurality of measurement images by repeating fine polishing, chemical etching, and height measurement, determines height values for each point in the obtained measurement images and an average value of the height values, The determined height values and average values may be matched with a plurality of measured images and stored. The electronic device 1000 may capture a microscope image after physically polishing and chemically etching the target metal surface until microstructure crystals appear on the target metal surface.

Referring to FIG. 5 , a layer 502 of the table may indicate the number of times of physical and chemical polishing and a layer number of an image measured at the corresponding number of times. In addition, the point identification numbers 512, 514, 516, and 518 may represent height values measured for each point in the measurement image of the corresponding layer number. Also, the average 520 may indicate an average value of height values measured for each point in the measurement image of the corresponding layer number. As will be described later, the electronic device 1000 may generate a 3D image by stacking ROI images based on the determined average height value 520 . The electronic device 1000 may perform polishing and chemical etching until crystals appear, and may perform monitoring through a microscope until crystals appear.

6 illustrates measurement images acquired through a microscope after an electronic device polishes a target metal surface three times, four times, and five times, and reference images and targets selected to identify a region of interest in the measurement images according to an embodiment. represents an image.

The electronic device 1000 according to the present disclosure obtains a microscope picture through repeated polishing and etching in order to three-dimensionally image a metal crystal image, which is a microscopic image obtained by photographing a target metal surface. In this process, the target metal Positional errors may occur in polishing the specimen and observing the same area. The electronic device 1000 generates ROI images for each measurement image in order to correct positional error appearing for each measured image, and generates a 3D image based on the generated ROI images, thereby more accurately measuring the target metal surface. can indicate

For example, referring to drawings 602 , 604 , and 606 of FIG. 6 , pictures taken after polishing an area of 130 μm×98 μm 3, 4, and 5 times using a microscope with a magnification of 500 are shown. For comparison, each figure (602, 604, 606) is marked with a crosshair in the center. Based on Figure 602, the position of Figure 604 is moved to the upper left direction, and based on Figure 604, Figure 606 is moved to the right. Therefore, the position of the target metal specimen appearing in measurement images obtained by the electronic device 1000 through a microscope may not be the same.

The electronic device 1000 according to the present disclosure may automatically correct position errors appearing in the measurement images by performing a local positioning algorithm on the measurement images. Figure 612 is a measurement image taken after the nth polishing, Figure 614 is a measurement image taken after the n+1th polishing, and is two adjacent images among a plurality of measurement images. The electronic device 1000 may use the nth measurement image shown in Figure 612 as a reference image and use the n+1th measurement image shown in Figure 614 as a target image. As described above with reference to FIG. 7 , the electronic device 1000 performs a matrix operation while moving a matrix for a predetermined area within the reference image within the taxic image, and each of the reference image and the target image is based on the result of the matrix operation. Region-of-interest images can be generated from

7 is a diagram for explaining a process of generating ROI images by performing a local positioning algorithm on measurement images by an electronic device according to an embodiment.

In S710, the electronic device 1000 may identify adjacent measurement images among measurement images. For example, the electronic device 1000 may identify two measurement images having adjacent layer numbers according to the number of polishings among measurement images. In S720, the electronic device 1000 may determine one of the two images as a reference image and the other target image based on the layer number indicating the number of physical or chemical treatments for the target metal surface.

In S730, the electronic device 1000 may perform a matrix operation while moving a matrix for a predetermined area in the reference image in the target image. Specifically, the electronic device 1000 may perform a matrix operation based on the following equations, and generate an ROI image from a plurality of measurement images based on a result of the operation.

,

는 해석 영역의 가로변과 세로변의 길이이다. 도 6의 그림 612의 경우 (251, 201)과 (1900, 1300)을 꼭지점으로 하고,

는 1650,

는 1100인 영역을 선택한 예이다.(x ₁ , y ₁ ) and (x ₂ , y ₂ ) shown in Equation 1 may be coordinates of vertices in a diagonal direction of a region selected to apply the local positioning algorithm. and,

,

is the length of the horizontal and vertical sides of the analysis domain. In the case of figure 612 in FIG. 6, (251, 201) and (1900, 1300) are vertices,

is 1650,

is an example of selecting an area of 1100.

In Equation 2, the area of Figure 612 of FIG. 6 is selected from the measurement image having the first layer number, which may indicate that it is used as a reference image. That is, in stacking the measurement images, the first defined measurement image may be placed as a reference.

In addition, the electronic device 1000 uses Equations 3 and 4 to determine the analysis region of the reference image and the analysis region to be compared in the measurement image having the second layer number, which is the target image to which the local positioning algorithm is applied. can choose For example, the electronic device 1000 uses Equations 3 and 4 to obtain (x ₁ -h, y ₁ -h) and (x _{2 -h} , y ₂ -h) regions. +h, y ₁ +h) and (x ₂ +h, y ₂ +h), a total of 4h square cases can be selected. Here, +h and -h represent the maximum position error in the measured image for each layer number.

Figure 614 of FIG. 6 shows that a total of 40,000 cases are selected from the areas of (151, 101) and (1800, 1200) to the areas of (351, 301) and (2000, 1400) in the case of h = 100. it did

S ₁ (i,j) of Equation 5 may represent a sum of absolute values of difference values (pixel difference values) between elements (eg, pixels) in the matrix of each selected region in the reference image and the target image. there is. In this specification, a sum of absolute values of difference values between elements in a matrix may correspond to a result value of matrix operation.

과 열

을 의미할 수 있다. 일 실시 예에 의하면,

일 수 있다. 일 실시 예에 의하면 S₁(i,j)의 최소 값은 레퍼런스 이미지 및 타겟 이미지가 거의 일치하는 위치에서 생성될 수 있다. 전자 장치(1000)는 상기 수학식 1 내지 6에 기초하여, 레퍼런스 이미지 및 타겟 이미지에 대하여 매트릭스 연산을 수행할 수 있다.Equation 6 above is the row with the minimum value in S ₁ (i, j)

overheat

can mean According to one embodiment,

can be According to an embodiment, the minimum value of S ₁ (i,j) may be generated at a position where the reference image and the target image almost coincide. The electronic device 1000 may perform a matrix operation on the reference image and the target image based on Equations 1 to 6 above.

과

를 반영한 영역을 레퍼런스로 하고, 타겟이 되는 N+1 번째 레이어 번호의 측정 이미와 서로 비교함으로써 로컬 포지셔닝 알고리즘을 반복적으로 수행할 수 있다.In S740, the electronic device 1000 generates ROI images from each of the reference image and the target image based on the result of the matrix operation. The electronic device 1000 according to the present disclosure may repeatedly perform the above process on two adjacent images among a plurality of measurement images. For example, the electronic device 1000 uses the following Equations 7 to 9 in the measurement image of the Nth layer number.

class

The local positioning algorithm can be repeatedly performed by using the area reflecting ? as a reference and comparing it with the measured image of the N+1 th layer number, which is the target.

과

을 이용하면, 하기 수학식 11에 나타난 바와 같이, 첫번째 레이어 번호의 측정 이미지에서의 관심 영역, 즉 (X1, Y1)과 (X2, Y2)를 대각선 꼭지점으로 하는 영역의 각 로컬 포지셔닝 알고리즘이 적용된 관심 영역 이미지를 생성할 수 있다.In the measured image according to each layer number obtained using the process using Equations 7 to 9 and Equation 10 below,

class

As shown in Equation 11 below, as shown in Equation 11 below, the region of interest in the measurement image of the first layer number, that is, the interest to which each local positioning algorithm of the region having (X1, Y1) and (X2, Y2) as diagonal vertices is applied. You can create an area image.

는 로컬 포지셔닝 알고리즘 적용을 위해 선택된 상기 수학식 1, 2, 7 및 8의

와 독립적일 수 있다.In Equation 11 above,

of Equations 1, 2, 7 and 8 selected for applying the local positioning algorithm.

can be independent of

8 is a view for explaining an image of a region of interest extracted by applying a local positioning algorithm to a specific region of measurement images obtained after polishing a target metal surface three times and four times.

및

에서, 로컬 포지셔닝 알고리즘을 수행하였고, 그 결과, 도 8의 그림 802, 806에 도시된 3번째 레이어 넘버의 측정 이미지에서

및

와 같은 결과 값을 획득하였고, 그림 804 및 808에 도시된 4번째 레이어 넘버의 측정 이미지에서

및

와 같은 결과를 획득하였다. 그리고, 전자 장치(1000)는

를 조정함으로써, 그림 802 및 806에서,

픽셀들, 그림 804 및 808에서,

픽셀들의 영역을 각각 관심 영역 이미지로 선택할 수 있다.According to an embodiment, the electronic device 1000

and

, a local positioning algorithm was performed, and as a result, in the measurement images of the third layer number shown in Fig. 8, 802 and 806,

and

The same result value was obtained, and in the measurement image of the 4th layer number shown in Figures 804 and 808

and

The same result was obtained. And, the electronic device 1000

By adjusting , in figures 802 and 806,

pixels, in Figures 804 and 808,

Each region of pixels may be selected as a region of interest image.

9 is a flowchart of a method of identifying, by an electronic device, a boundary of a microtissue in ROI images according to an embodiment.

10 is a diagram for explaining an example in which an electronic device identifies a boundary of microstructure in ROI images according to an exemplary embodiment.

A process of identifying the boundary of the microstructure by the electronic device 1000 will be described in detail with reference to FIGS. 9 and 10 .

In S910, the electronic device 1000 may determine a threshold based on a difference between pixel values of two arbitrary points in the ROI images. For example, referring to FIG. 1002 shown in FIG. 10 , the electronic device 1000 identifies a brightness value (or pixel value) of a point 1021 inside the microtissue boundary in the ROI image, and identifies the microtissue boundary. A brightness value (or pixel value) of a point 1022 located in the area may be identified. According to an embodiment, the electronic device 1000 may determine a half value of a difference between brightness values of the two points 1021 and 1022 as a threshold value. According to another embodiment, the electronic device 1000 may determine half of the difference between pixel values of the two points 1021 and 1022 as the threshold.

In S920, the electronic device 1000 may binarize the ROI images based on the threshold. For example, the electronic device 1000 may binarize the ROI images based on a threshold. According to an embodiment, the electronic device 1000 determines a pixel value of a pixel having a value brighter than the threshold as 1 based on a threshold and determines a pixel value of a pixel having a value darker than the threshold as 0, thereby determining the region of interest. Images can be binarized.

In S930, the electronic device 1000 may identify whether a pixel value has changed while moving a point generated at an arbitrary point in the binarized ROI images. In operation S940, the electronic device 1000 identifies a boundary of the at least one microstructure in ROI images based on whether the identified pixel value changes. For example, in the drawing 1002, the horizontal direction may be a column and the vertical direction may be a row. Further, row numbers may increase toward the right, and column numbers may increase toward the bottom of a column. Thus, in Figure 1004, an upward arrow may mean that the row is getting smaller. The electronic device 1000 may identify the starting point of the microstructure boundary by adding 1 to a row where the first 0 appears.

According to one embodiment, there is a problem that voids occur inside the tissue by micrographs or can be expressed as black dots due to dropout, and the existence of these dots confuses the position of the row where the first 0 appears. There are problems that can be given. Accordingly, according to an embodiment of the present disclosure, the electronic device 1000 may change all of the small 0's surrounded by the wide distribution of 1's to 1's in the binarized ROI image, as shown in FIG. 1006 . The electronic device 1000 may accurately identify the boundary of the microstructure in the ROI image by binarizing the ROI images and finely adjusting pixel values representing some 0s in the binarized ROI image.

Referring to Figure 1008, after the electronic device 1000 finds the starting point of the border in Figure 1006, a process of finding coordinates of the border is shown. Since the current electronic device 1000 recognizes the positions of the first 0 and the last 1, it can check the presence or absence of 1 and 0 in four adjacent pixels including the two pixels.

Point 1023 may be a fixed condition as it moves upward and stops at the boundary of 1 and 0. Including this fixed condition, a total of four cases can be assumed. For example, it can be assumed that the top right and right sides are 1-1, 0-1, 0-0, 1-0. For example, in the case of 0-1, the boundary is on the right as in the case of the break point shown in Figure 1008, and in the case of 1-1, the boundary is in the upper right as shown in Figure 1008, and 0-0 In the case of , as shown in the figure 1008, the arrow may be a peak in the portion shown.

11 is a flowchart of a method of resizing, by an electronic device, a boundary of a microtissue identified in ROI images according to an embodiment.

12 is a diagram for explaining an example in which an electronic device resizes a boundary of a microtissue identified in ROI images according to an embodiment.

A process of resizing the boundary of the microstructure by the electronic device 1000 will be described in detail with reference to FIGS. 11 and 12 . When the metal microscope used by the electronic device according to the present disclosure is set at a magnification of 500 times, the resolution (eg, resolution) per pixel is about 0.063 micrometers, and the accuracy of the micrometer for height measurement may be 0.01 micrometers. As a result, the boundary expressed by the (x,y) coordinates obtained from the measured image of the target metal surface can be expressed with a relatively high number of nodes compared to the height z and a higher spatial resolution than necessary.

Therefore, when the electronic device 1000 generates a 3D image based on an image acquired by photographing the target metal surface, there are problems in that calculation speed is reduced and acicular planes may be formed vertically. However, since the shape of the tissue may be distorted when the number of nodes is reduced, it may be necessary to select the number of nodes or resize the microstructure boundary to optimize the amount of calculation required for generating a 3D image while minimizing the shape distortion of the tissue.

In operation S1110, the electronic device 1000 resizes the boundary of at least one microstructure included in the ROI images based on the average height value of the target metal surface pre-matched to the measurement images from which the ROI images are generated. can For example, the electronic device 1000 according to the present disclosure may determine the optimal number of nodes based on Equations 12 to 15 below, and resize the boundary within the ROI image based on the determined number of nodes.

The electronic device 1000 may define a pixel of a camera (or microscope device) based on Equation 12 above. In general, the ratio m/n of vertical and horizontal pixels may be 4/3, but is not limited thereto. The spatial resolution of an image obtainable by the electronic device 1000 through the microscope device may vary depending on the optical lens system and may be defined as Equation 13.

In Equation 13, w and h mean the width and height values of each measured image. The quantitative distance between each pixel can be derived based on Equation 14 below.

According to an embodiment, when m = 2048 and w = 130um, in Equation 14 above, P may be 130/2048 (um/pixels) corresponding to 0.063 (um/pixels). However, as shown in the table in Figure 5, since the height of the measured image at each layer number after polishing is 1-2um, if P=0.063 (um/pixels) is used, the lateral surface of the crystal is a needle-shaped rectangle. It is expressed as needle-like squares, and the surface is not uniform. Therefore, in order to generate a good result, it is necessary to define P' according to Equation 15 below.

이고,

일 수 있다. S1120에서, 전자 장치(1000)는 상기 수학식 12 내지 15에 기초하여 리사이징된 적어도 하나의 미세 조직의 경계를 관심 영역 이미지들 내 미세조직의 경계로 식별할 수 있다.In Equation 15 above

ego,

can be In operation S1120, the electronic device 1000 may identify the boundary of at least one microstructure resized based on Equations 12 to 15 as the boundary of the microstructure in the ROI images.

Specifically, the drawing 1202 of FIG. 12 shows a polygon according to the microstructure boundary coordinates determined from the microstructure image of the drawing 806 of FIG. 3 . Referring to figure 1202, a blue solid line 1212 defined by 3084 polygon vertices, a green solid line 1214 defined by 1028 polygon vertices by 3 skips, and 343 polygon vertices by 9 skips. A red solid line 1216 defined by , and a black dotted line 1218 defined by 114 polygon vertices skipped by 27 are shown.

Referring to the drawing 1220 in which the bay (dented part) of the polygon 1219 shown in the drawing 1202 is enlarged, it cannot be accurately expressed with the black dotted line 1218, but using the red solid line 1216 It can be seen that the shape of the bay is displayed. This indicates that a detailed area of the polygon 1219 in the drawing 1202 can be expressed with a spatial resolution of about 0.57 μm. Figure 1204 shows the area of a polygon according to the number of vertices of the polygon. The area of a polygon drawn with 60 vertices skipped by 27 is reduced by about 50%, but it can be seen that the area ratio hardly changes when skipped by 13 or less. Accordingly, the electronic device 1000 according to an embodiment may identify the boundary of the microstructure having a spatial resolution of 0.57 μm skipped by 9 as the boundary of the microstructure of the target metal surface.

The electronic device 1000 according to the present disclosure may identify an optimal microstructure boundary compared to the amount of computation by resizing the boundary of the microstructure in the ROI image according to Equations 12 to 15.

13 is a flowchart of a specific method of generating a 3D image by an electronic device according to an embodiment.

In operation S1310, the electronic device 1000 may stack the ROI images in which at least one microtissue boundary is identified based on the average height value. For example, the electronic device 1000 obtains a measurement image by photographing the surface of the target metal through a microscope after polishing the surface of the target metal, and determines an average height value of the target metal using a micrometer. The electronic device 1000 may stack the ROI images in which the boundary of the microstructure is identified by using the average height value measured for each polishing as a Z-axis value on the 3D image.

In operation S1320, the electronic device 1000 may surface-process a boundary of at least one microstructure appearing in the stacked ROI images based on the average height value. For example, when the electronic device 1000 stacks the ROI images on the 3D space based on the average height value matched with the ROI images in advance, the electronic device 1000 stacks the stacked ROI images with respect to the z-axis of the 3D space. The boundaries of can be stacked. The electronic device 1000 may generate a predetermined surface by surface processing between the stacked boundaries.

In operation S1330, the electronic device 1000 may generate a boundary of at least one surface-processed microstructure as a 3D image. A specific example in which the electronic device 1000 generates a 3D image by stacking ROI images will be described with reference to FIGS. 14 to 16 described later.

14 is an example of ROI images showing predetermined microstructures used by an electronic device to generate a 3D image according to an embodiment.

Figures 1402, 1404, 1406, and 1408 shown in FIG. 14 show ROI images having different z-axis heights according to polishing 3, 7, 10, and 26, respectively. In the drawings (1402, 1404, 1406, 1408), the spatial resolution of the xy cross-sectional images of the microscope is 0.57um, and the microstructures (e.g., metal grain, mg) divided into #1, #3, and #5 are bordered. The state divided by is shown. From Figure 1402 to Figure 1408, it can be seen that as the number of polishing increases, the area of some microstructures gradually narrows and the area of other parts of microstructures gradually widens.

For example, from Figure 1402 to Figure 1408, it is observed that #1 and #2 microstructures become narrower as they are polished, and that #1 microstructure can finally be divided into several microstructures. can do.

15 is a diagram illustrating a result of stacking a plurality of ROI images for each microstructure by an electronic device according to an embodiment.

A drawing 1502 shown in FIG. 15 is a result of stacking partial ROI images of microstructure #1 appearing in the ROI images 1402, 1404, 1406, and 1408 of FIG. 14, and a drawing 1504 is a drawing 1504. This is a result of stacking partial ROI images for microstructure #3 appearing in the ROI images of FIG. 14, and a figure 1506 shows stacking partial ROI images for microstructure #5 appearing in the ROI images of FIG. 14. As a result, figure 1508 is a result of stacking partial ROI images of microstructure #6 shown in the ROI images of FIG. 14 .

As shown in FIG. 15, in order to express the result of stacking boundaries in each ROI image as a volume, a plane connecting coordinate points within the boundary appearing in each ROI image and an adjacent height position is formed. Needs to be. The electronic device 1000 may generate 3D images illustrated in FIG. 16 described later by surface-processing the boundaries of microstructures appearing in the stacked ROI images.

FIG. 16 is a diagram for explaining a 3D image generated by surface-processing the boundary of microstructures appearing in the stacked ROI images of FIG. 15 by the electronic device according to an exemplary embodiment.

Referring to FIG. 16 , in figures 1602 , 1604 , and 1606 , 3D images generated by face-processing the boundaries of microstructures appearing in the stacked ROI images are shown. The electronic device 1000 according to the present disclosure may generate a 3D image for each of a plurality of microstructures observed on the surface of a target metal, but may also generate a 3D image 1608 including a plurality of microstructures.

The electronic device 1000 according to an embodiment stacks partial ROI images for a specific microstructure among ROI images, and surface-processes microtissue boundaries on the stacked partial ROI images, thereby forming a 3D image for each microtissue. s 1602, 1604, and 1606 may be generated, but 3 regions including a plurality of microstructures may be generated by stacking the ROI images including a plurality of microstructure boundaries and surface-processing the boundary appearing in the stacked ROI images. A dimensional image 1608 may also be created. The electronic device 1000 according to the present disclosure can objectively observe the microstructure of the target metal by imaging the microstructure of the target metal in 3D.

17 is a block diagram of an electronic device according to an embodiment.

18 is a block diagram of an electronic device according to another embodiment.

According to an embodiment, the electronic device 1000 may be implemented in various forms. For example, the electronic device 1000 described in this specification includes a digital camera, a mobile terminal, a smart phone, a laptop computer, a tablet PC, an electronic book terminal, a digital broadcasting terminal, and a personal digital assistant (PDA). Digital Assistants), PMP (Portable Multimedia Player), navigation, MP3 player, etc. may exist, but are not limited thereto.

According to an embodiment, the electronic device 1000 may include a display 1210, a processor 1300, and a memory 1700. However, it is not limited thereto, and may further include other devices for performing a method for 3D imaging a microstructure of a target metal. According to an embodiment, as shown in FIG. 18 , the electronic device 1000 includes a user input interface 1100, an audio output unit 1220 provided as an output unit 1200, a polishing device 1400, and an etching device. 1410, a network interface 1500, an A/V input unit 1600, and a memory 1700 may be further included.

The user input unit 1100 means a means through which a user inputs data for controlling the electronic device 1000 . For example, the user input unit 1100 includes a key pad, a dome switch, a touch pad (contact capacitance method, pressure resistive film method, infrared sensing method, surface ultrasonic conduction method, integral type tension measuring method, piezo effect method, etc.), a jog wheel, a jog switch, and the like, but are not limited thereto.

The user input unit 1100 may receive at least one user input for the electronic device 1000 to generate a 3D image of the target metal microstructure.

The output unit 1200 may output an audio signal, a video signal, or a vibration signal, and the output unit 1200 may include a display unit 1210 and a sound output unit 1220.

The display unit 1210 includes a screen for displaying and outputting information processed by the electronic device 1000 . Also, the screen may display an image. For example, the display unit 1210 may output a result of stacking a plurality of measurement images, a plurality of ROI images, and a plurality of ROI images, and a 3D image or video generated by face-processing the stacked result. .

The audio output unit 1220 outputs audio data received from the communication unit 1500 or stored in the memory 1700 . Also, the sound output unit 1220 outputs sound signals related to functions performed by the electronic device 1000 (eg, a call signal reception sound, a message reception sound, and a notification sound).

The processor 1300 typically controls overall operations of the electronic device 1000 . For example, the processor 1300 executes the programs stored in the memory 1700, so that the user input unit 1100, the output unit 1200, the polishing device 1400, the etching device 1410, the micrometer 1420 , the network interface 1500, the A/V input unit 1600, etc. can be generally controlled. Also, the processor 1300 may perform the functions of the electronic device 1000 described in FIGS. 1 to 16 by executing programs stored in the memory 1700 .

According to an embodiment, the at least one processor obtains a plurality of measurement images including at least one microstructure appearing on the target metal surface while physically or chemically treating the target metal surface by executing the one or more instructions. determine an average height value of a target metal surface appearing in the measured images, generate ROI images including the at least one microstructure from the measured images, and generate the target from the generated ROI images. A boundary of at least one microstructure appearing on the metal surface may be identified, and a 3D image may be generated by stacking ROI images in which the boundary of the at least one microstructure is identified based on the determined average height value.

According to an embodiment, the processor 1300 controls a polishing device and an etching device for polishing the target metal surface to physically polish the target metal surface, and chemically etch the target metal surface after physically polishing the target metal surface. The plurality of measurement images may be obtained by repeating an operation of acquiring a measurement image by photographing the chemically etched target metal surface and photographing the physically polished and chemically etched target metal surface.

According to an embodiment, when a measurement image is obtained, the processor 1300 may measure center height values at the center of corners of the target metal surface and determine an average value of the center height values as the average height value.

According to an embodiment, the processor 1300 identifies adjacent measurement images among the measurement images, and generates two adjacent images among the plurality of measurement images based on the number of physical or chemical treatments for the target metal surface. A reference image and a target image are determined, a matrix operation is performed while moving a matrix for a predetermined area in the determined reference image within the target image, and each of the reference image and the target image is performed based on the matrix operation result value. Region-of-interest images can be generated from

According to an embodiment, the processor 1300 determines a threshold based on a difference between pixel values of two arbitrary points in the ROI images, binarizes the ROI images based on the threshold, and performs the binarized ROI images. It is possible to identify whether a pixel value has changed while moving a point generated at an arbitrary point within the region images, and to identify a boundary of the at least one microtissue of the ROI images based on the change in the identified pixel value. can

According to an embodiment, the processor 1300 determines the at least one fine detail included in the ROI images based on an average height value of the target metal surface previously matched to measurement images from which the ROI images are generated. The boundary of the tissue may be resized, and the boundary of the resized at least one microstructure may be identified as the boundary of the microstructure.

According to an embodiment, the at least one processor stacks the ROI images in which the boundary of the at least one microtissue is identified based on the determined average height value, and stacks the ROI images based on the average height value. A boundary of at least one microstructure appearing in the field may be face-processed, and the face-treated boundary of the at least one microstructure may be generated as the 3D image.

The network interface 1500 may include one or more components that allow the electronic device 1000 to communicate with other devices (not shown) or servers. Another device (not shown) may be a computing device such as the electronic device 1000 or a sensing device, but is not limited thereto. For example, the network interface 1500 may include a short-distance communication unit, a mobile communication unit, and a broadcast reception unit.

The polishing device 1400 may polish the target metal surface under the control of the processor 1300 . According to one embodiment, the polishing apparatus may include a stage on which a polishing pad of a preset type is mounted, a driving motor for rotating or moving the stage, and a driving module for moving the stage on which the polishing pad is mounted. , but is not limited thereto. The polishing device 1400 may physically polish the target metal surface a preset number of times under the control of the processor 1300 .

The etching device 1410 may etch a target metal surface under the control of the processor 1300 . According to an embodiment, the etching apparatus 1410 may include a plurality of types of storage units for storing etching liquid, cleaning liquid, or distilled water, and a plurality of channels for supplying the etching liquid, cleaning liquid, or distilled water to the target metal. It is not limited. The micrometer 1420 may measure the height of a target metal specimen. For example, the micrometer 1420 may be provided as other height measuring devices for electronically measuring the height of a target metal specimen under the control of a processor.

An audio/video (A/V) input unit 1600 is for inputting an audio signal or a video signal, and may include a camera 1610 and a microphone 1620. The camera 1610 may obtain an image frame such as a still image or a moving image through an image sensor in a video call mode or a photographing mode. An image captured through the image sensor may be processed through the processor 1300 or a separate image processing unit (not shown).

The microphone 1620 receives external sound signals and processes them into electrical voice data. For example, the microphone 1620 may receive a sound signal from an external device or a user. The microphone 1620 may receive a user's voice input. The microphone 1620 may use various noise cancellation algorithms to remove noise generated in the process of receiving an external sound signal.

The memory 1700 may store programs for processing and control of the processor 1300 and may store data input to or output from the electronic device 1000 . In addition, the memory 1700 includes a plurality of measurement images obtained by observing the target metal surface a plurality of times, ROI images, and 3 images generated by surface-processing the boundary of the stacked ROI images as a result of stacking the ROI images. Dimensional images may be stored.

Also, according to an embodiment, the memory 1700 may store one or more instructions for performing a method of generating a 3D image of a target metal microstructure. According to one embodiment, the memory 1700 may include one or more instructions operable by a processor in general-purpose software such as MATLAB, C language, and Python.

The memory 1700 may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (eg SD or XD memory, etc.), RAM (RAM, Random Access Memory) SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk , an optical disk, and at least one type of storage medium.

A method of generating a 3D image of a target metal microstructure by an electronic device according to an embodiment may be implemented in the form of program instructions that can be executed by 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 instructions recorded on the medium may be those specially designed and configured for the present invention or those known and usable to those skilled in computer software. In addition, according to an embodiment of the present disclosure, a computer program device including a recording medium storing a program for performing a method of generating a 3D image of a target metal microstructure may be provided.

Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes 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.

Some embodiments may be implemented in the form of a recording medium including instructions executable by a computer, such as program modules executed by a computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. Also, computer readable media may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Also, some embodiments may be implemented as a computer program or computer program product including instructions executable by a computer, such as a computer program executed by a computer.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by those skilled in the art using the basic concept of the present invention defined in the following claims are also included in the scope of the present invention. fall within the scope of the right

Claims (15)

A method for generating a three-dimensional image of a target metal microstructure by an electronic device,
obtaining a plurality of measurement images including at least one microstructure appearing on the target metal surface while physically or chemically treating the target metal surface;
determining an average height value of a target metal surface appearing in the measured images;
generating ROI images including the at least one microstructure from the measurement images;
identifying a boundary of at least one microstructure appearing on the target metal surface from the generated ROI images; and
generating a 3D image by stacking ROI images in which a boundary of the at least one microtissue is identified, based on the determined average height value; Including, method. The method of claim 1 , wherein acquiring the plurality of measurement images comprises:
physically polishing the target metal surface;
chemically etching the target metal surface after physically polishing it;
obtaining a measurement image by photographing the chemically etched target metal surface; and
acquiring the plurality of measurement images by repeating the polishing step, the etching step, and the acquiring the measurement image; Including, method. 3. The method of claim 2, wherein determining the average height value comprises:
measuring center height values at centers of corners of the target metal surface when the measurement image is obtained; and
determining an average value of the central height values as the average height value; Including, method. 2. The method of claim 1, wherein generating the region-of-interest images
identifying adjacent measurement images among the measurement images;
determining two adjacent images among the plurality of measured images as a reference image and a target image based on the number of physical or chemical treatments for the target metal surface;
performing a matrix operation while moving a matrix for a predetermined area within the determined reference image within the target image; and
generating ROI images from each of the reference image and the target image based on the resultant value of the matrix operation; Including, method. The method of claim 1 , wherein identifying the boundary of the at least one microstructure comprises:
determining a threshold value based on a difference between pixel values of two arbitrary points in the ROI images;
binarizing the ROI images based on the threshold;
identifying whether a pixel value has changed while moving a point generated at an arbitrary point within the binarized ROI images; and
identifying a boundary of the at least one microstructure of the ROI images based on whether the identified pixel value changes; Including, method. 6. The method of claim 5, wherein identifying the boundary of the at least one microstructure comprises
resizing a boundary of the at least one microstructure included in the ROI images based on an average height value of the target metal surface pre-matched to measurement images from which the ROI images are generated; and
identifying a boundary of the at least one resized microstructure as a boundary of the at least one microstructure; Including, method. The method of claim 1, wherein generating the three-dimensional image
stacking ROI images in which a boundary of the at least one microtissue is identified, based on the determined average height value;
surface-processing a boundary of at least one microstructure appearing in the stacked ROI images based on the average height value; and
generating a boundary of the at least one surface-processed microstructure as the 3D image; Including, method. An electronic device for generating a three-dimensional image of a target metal microstructure,
display;
a memory that stores one or more instructions; and
at least one processor to execute the one or more instructions; including,
By executing the one or more instructions, the at least one processor:
Obtaining a plurality of measurement images including at least one microstructure appearing on the target metal surface while physically or chemically treating the target metal surface;
Determining an average height value of a target metal surface appearing in the measured images;
generating region-of-interest images including the at least one microstructure from the measured images;
identifying a boundary of at least one microstructure appearing on the target metal surface in the generated ROI images;
The electronic device generates a 3D image by stacking ROI images in which a boundary of the at least one microtissue is identified, based on the determined average height value. The method of claim 8, wherein the electronic device
a polishing device for polishing the target metal surface; and
an etching device that chemically etches the target metal surface; Including more,
The at least one processor controls the polishing device and the etching device, thereby
physically polishing the target metal surface;
Chemically etching after physically polishing the target metal surface,
Obtaining a measurement image by photographing the chemically etched target metal surface;
Acquiring the plurality of measurement images by repeating an operation of physically polishing the target metal surface, chemically etching, and photographing the chemically etched target metal surface to obtain a measurement image. 10. The method of claim 9, wherein the at least one processor
When the measured image is acquired, measure center height values at the center of corners of the target metal surface;
An electronic device that determines an average value of the center height values as the average height value. 9. The method of claim 8, wherein the at least one processor
Identifying adjacent measurement images among the measurement images;
determining two adjacent images among the plurality of measured images as a reference image and a target image based on the number of physical or chemical treatments for the target metal surface;
Performing a matrix operation while moving a matrix for a predetermined area in the determined reference image in the target image;
The electronic device generates ROI images from each of the reference image and the target image based on the result of the matrix operation. 9. The method of claim 8, wherein the at least one processor
determining a threshold based on a difference between pixel values of two arbitrary points in the ROI images;
binarizing the ROI images based on the threshold;
Identifying whether a pixel value is changed while moving a point generated at an arbitrary point within the binarized ROI images;
The electronic device may identify a boundary of the at least one microstructure of the ROI images based on whether the identified pixel value changes. 13. The method of claim 12, wherein the at least one processor
Resizing a boundary of the at least one microstructure included in the ROI images based on an average height value of the target metal surface pre-matched to measurement images from which the ROI images are generated;
and identifying a boundary of the at least one resized microstructure as a boundary of the at least one microstructure. 9. The method of claim 8, wherein the at least one processor
Stacking ROI images in which a boundary of the at least one microtissue is identified based on the determined average height value;
Surface-processing a boundary of at least one microstructure appearing in the stacked ROI images based on the average height value;
An electronic device generating a boundary of the at least one surface-processed microstructure as the 3D image. A method for generating a three-dimensional image of a target metal microstructure by an electronic device,
obtaining a plurality of measurement images including at least one microstructure appearing on the target metal surface while physically or chemically treating the target metal surface;
determining an average height value of a target metal surface appearing in the measurement images;
generating ROI images including the at least one microstructure from the measurement images;
identifying a boundary of at least one microstructure appearing on the target metal surface from the generated ROI images; and
generating a 3D image by stacking ROI images in which a boundary of the at least one microtissue is identified, based on the determined average height value; A computer-readable recording medium in which a program for performing the method is stored, including a.

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