Image processing method, particle analysis method, information processing device, and electron microscope

Abstract

This invention provides an image processing method that can determine whether or not an object is an inclusion in an image in a short amount of time. [Solution] The image processing method according to the present invention includes the steps of: acquiring a compositional image of a metal material; acquiring a topographic image of the metal material; binarizing the compositional image to extract particles and generate a compositional particle image; binarizing the topographic image to extract particles and generate a topographic particle image; extracting the common part of the compositional particle image and the topographic particle image to generate a common part image; and determining whether the particles extracted from the compositional image are inclusions in the metal material based on the compositional particle image and the common part image.

Description

Technical Field

[0001] The present invention relates to an image processing method, a particle analysis method, an information processing apparatus, and an electron microscope.

Background Art

[0002] In analyzers such as a scanning electron microscope (SEM) equipped with an energy dispersive X-ray spectrometer (EDS) and an electron probe microanalyzer (EPMA), particles can be extracted from an electron microscope image or an elemental map, and image analysis of the extracted particles can be performed to obtain information on particle shape such as the area and circularity of the particles.

[0003] For example, in Patent Document 1, a reflected electron image or a secondary electron image is acquired, particles are extracted using a contrast threshold value set in advance with a standard sample or the like, and characteristic X-rays are measured with an energy dispersive X-ray spectrometer. A particle analysis method is disclosed in which repeated measurements are performed until all measurements within a preset visual field range are completed while classifying particles using the intensity value or concentration value.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Particle analysis is effective for analyzing inclusions in steel materials. However, when particles are extracted using a reflected electron image, inclusions in the steel material, dust on the steel material, and debris such as sand and abrasives are displayed with the same degree of brightness in the reflected electron image, and there are cases where they cannot be distinguished.

Means for Solving the Problems

[0006] One aspect of the image processing method according to the present invention is The process of obtaining a compositional image of a metallic material, A step of obtaining a topographic image of the metal material, The process involves binarizing the aforementioned compositional image to extract particles and generating a compositional particle image. The process involves binarizing the aforementioned surface image to extract particles and generating a surface particle image, A step of extracting the common portion of the composition particle image and the surface particle image to generate a common portion image, A step of determining whether the particles extracted from the compositional image are inclusions in the metal material based on the compositional particle image and the common partial image, Includes.

[0007] This image processing method allows for the determination of whether a particle is an inclusion or not using compositional and surface texture images, thus enabling rapid determination of whether a particle is an inclusion or not.

[0008] One aspect of the particle analysis method according to the present invention is: The above image processing method is included, The process includes a step of obtaining information about the particles identified as inclusions when the particles extracted from the compositional image are determined to be inclusions.

[0009] This type of particle analysis method allows for the determination of whether a particle is an inclusion or not using compositional and surface texture images, thus enabling particle analysis to be performed in a short amount of time.

[0010] One aspect of the information processing apparatus according to the present invention is: A compositional image acquisition unit that acquires a compositional image of a metallic material, A surface surface image acquisition unit that acquires a surface surface image of the metal material, A composition particle image generation unit that binarizes the aforementioned composition image to extract particles and generates a composition particle image, A surface texture image generation unit that binarizes the surface texture image to extract particles and generates a surface texture particle image, A common portion image generation unit extracts the common portion between the compositional particle image and the surface particle image to generate a common portion image, A determination unit that determines whether the particles extracted from the compositional image are inclusions in the metal material based on the compositional particle image and the common part image; including.

[0011] In such an information processing apparatus, it is possible to determine whether particles are inclusions by using the compositional image and the uneven image, so it is possible to determine whether particles are inclusions in a short time.

[0012] One aspect of the electron microscope according to the present invention includes the above information processing apparatus.

Brief Description of the Drawings

[0013] [Figure 1] A diagram showing an example of the configuration of an electron microscope according to an embodiment of the present invention. [Figure 2] A diagram showing an example of the configuration of an information processing apparatus. [Figure 3] A cross-sectional view schematically showing a metal material. [Figure 4] A diagram for explaining the compositional image of a metal material. [Figure 5] A diagram for explaining a compositional image. [Figure 6] A diagram for explaining an uneven image. [Figure 7] A diagram for explaining a compositional particle image, an uneven particle image, and a common part image. [Figure 8] A diagram for explaining a process of determining whether a particle is an inclusion or a foreign object using a common part image and a compositional particle image. [Figure 9] A flowchart showing an example of the particle analysis process of an information processing apparatus.

Modes for Carrying Out the Invention

[0014] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. Note that the embodiments described below do not unduly limit the content of the present invention described in the claims. Also, not all of the configurations described below are essential constituent elements of the present invention.

[0015] 1. Electron microscope First, an electron microscope according to one embodiment of the present invention will be described with reference to the drawings. Figure 1 is a diagram showing an example of the configuration of an electron microscope 100 according to one embodiment of the present invention.

[0016] The electron microscope 100 includes an electron microscope body 10 and an information processing device 20. The electron microscope 100 is a scanning electron microscope that scans a sample 2 with an electron beam to acquire electron microscope images including secondary electron images and backscattered electron images. The electron microscope 100 can perform particle analysis of the sample 2.

[0017] The electron microscope body 10 includes an electron source 102, a focusing lens 104, a scanning deflector 106, an objective lens 108, a sample stage 110, a backscattered electron detector 120, a secondary electron detector 130, and an energy dispersive X-ray spectrometer (EDS) 140.

[0018] The electron source 102 emits an electron beam. The electron source 102 is, for example, an electron gun that accelerates electrons emitted from the cathode at the anode and emits an electron beam.

[0019] The focusing lens 104, together with the objective lens 108, focuses the electron beam emitted from the electron source 102 to form an electron probe. The scanning deflector 106 deflects the electron beam in two dimensions. By deflecting the electron beam with the scanning deflector 106, the sample 2 can be scanned with the electron probe. The objective lens 108 is positioned directly in front of the sample 2. The objective lens 108 is the lens used to form the electron probe.

[0020] The sample 2 is placed on the sample stage 110. The sample stage 110 supports the sample 2. The sample stage 110 has a movement mechanism for moving the sample 2. By moving the sample stage 110, the irradiation position of the electron beam on the sample 2 can be changed.

[0021] The backscattered electron detector 120 detects backscattered electrons emitted from the sample 2 when the sample 2 is irradiated with an electron beam. Backscattered electrons are high-energy electrons that are scattered backward within the sample when electrons are irradiated onto the sample. The backscattered electron detector 120 is positioned, for example, directly below the objective lens 108. A backscattered electron image can be obtained by scanning the sample 2 with an electron probe and detecting backscattered electrons with the backscattered electron detector 120. The backscattered electron image is sent from the electron microscope body 10 to the information processing device 20 as grayscale image data.

[0022] The secondary electron detector 130 detects secondary electrons emitted from the sample 2 when the sample 2 is irradiated with an electron beam. Secondary electrons are electrons that are emitted outside the atom when an electron irradiates the sample, causing it to collide with and excite an electron within the atom. A secondary electron image can be obtained by scanning the sample 2 with an electron probe and detecting secondary electrons with the secondary electron detector 130. The secondary electron image is sent from the electron microscope body 10 to the information processing device 20 as grayscale image data.

[0023] The EDS140 is a detector that discriminates X-rays by energy to obtain a spectrum. The EDS140 detects characteristic X-rays generated in sample 2 when it is irradiated with an electron beam. By detecting the characteristic X-rays generated in sample 2 with the EDS140, an EDS spectrum can be obtained.

[0024] The information processing device 20 performs particle analysis. Specifically, the information processing device 20 extracts particles from electron microscope images, performs image analysis, and obtains information on the shape and size of the particles. Furthermore, the information processing device 20 obtains information on the composition of the particles from the results of EDS analysis of the particles. The information processing device 20 statistically processes the acquired particle information.

[0025] Figure 2 shows an example of the configuration of the information processing device 20. As shown in Figure 2, the information processing device 20 includes a processing unit 200, an operation unit 210, a display unit 220, and a storage unit 230.

[0026] The operation unit 210 is for the user to input operation information and outputs the input operation information to the processing unit 200. The functions of the operation unit 210 can be realized by input devices such as a keyboard, mouse, buttons, touch panel, or touchpad.

[0027] The display unit 220 displays the image generated by the processing unit 200. The functions of the display unit 220 can be realized by an LCD (Liquid Crystal Display), a touch panel display, or the like.

[0028] The storage unit 230 stores programs for the processing unit 200 to perform various calculation and control processes. It stores data and other information. The memory unit 230 is also used as a workspace for the processing unit 200 and is used to temporarily store calculation results and other information executed by the processing unit 200 according to various programs. The functions of the memory unit 230 can be realized by RAM (Random Access Memory), ROM (Read Only Memory), and hard disk, etc.

[0029] The processing unit 200 performs various processes for particle analysis of metallic materials. The functions of the processing unit 200 can be realized by executing programs stored in the storage unit 230 using various processors such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), and DSP (Digital Signal Processor). The processing unit 200 includes a composition image acquisition unit 201, a surface topography image acquisition unit 202, a composition particle image generation unit 203, a surface topography particle image generation unit 204, a common area image generation unit 205, a determination unit 206, and a particle analysis unit 207.

[0030] The composition image acquisition unit 201 acquires a composition image of the metallic material. The composition image is an image that shows the difference in composition (difference in average atomic number) of the sample. The composition image acquisition unit 201 acquires the backscattered electron image obtained by detecting backscattered electrons with the backscattered electron detector 120 as the composition image. The surface topography image acquisition unit 202 acquires a surface topography image of the metallic material. The surface topography image is an image that shows the surface topography of the sample. The surface topography image acquisition unit 202 acquires the secondary electron image obtained by detecting secondary electrons with the secondary electron detector 130 as the surface topography image.

[0031] The composition particle image generation unit 203 binarizes the composition image to extract particles and generates a composition particle image. Binarization is a process that assigns each pixel in the image to either white or black, converting the image into two colors, black and white. The surface texture particle image generation unit 204 binarizes the surface texture image to extract particles and generates a surface texture particle image.

[0032] The common area image generation unit 205 extracts the common area between the composition particle image and the surface particle image to generate a common area image. The determination unit 206 determines whether a particle is an inclusion or not based on the composition particle image and the common area image. The particle analysis unit 207 obtains information about the particle determined to be an inclusion if it is determined to be an inclusion. The processing of the processing unit 200 will be described later.

[0033] 2. Particle analysis 2.1. Image Processing Method Figure 3 is a schematic cross-sectional view of the metallic material 4. Figure 4 is a diagram illustrating the composition of the metallic material 4.

[0034] The sample 2 to be measured is a metallic material 4. Particle analysis obtains information about inclusions 6 within the metallic material 4. This information includes, for example, the shape, size, and composition of the inclusions 6. Particle analysis statistically processes the information about the inclusions 6.

[0035] Inclusions 6 are foreign matter remaining in the metal material 4. If the metal material 4 is a steel material, then inclusions 6 are foreign matter that is generated or mixed in during the manufacturing process of the steel material and remains in the steel material, and are nonmetallic compounds such as oxides, sulfides, and nitrides.

[0036] Foreign matter 7 on the metal material 4 includes dust, sand, abrasives and shavings from when the metal material 4 was polished. Foreign matter 7 can accumulate on the metal material 4 when sand or dust floating in the air adheres to the metal material 4, or when abrasives and polishing shavings used when the metal material 4 was polished remain on the metal material 4.

[0037] In particle analysis, inclusions 6 are extracted from electron microscope images of the metallic material 4, and information on the shape and size of the inclusions 6 is obtained. By identifying the location of the inclusion 6 and performing EDS analysis, information about the composition of the inclusion 6 can be obtained. Therefore, it is necessary to distinguish between the inclusion 6 and foreign matter 7 from the electron microscope image of the metallic material 4 and extract the inclusion 6.

[0038] As shown in Figure 4, in the compositional image, if the inclusion 6 in the metal material 4 and the foreign matter 7 on the metal material 4 appear darker than the metal material 4, and the contrast difference between the inclusion 6 and the foreign matter 7 is small, it is impossible to distinguish between the inclusion 6 and the foreign matter 7. Therefore, the information processing device 20 distinguishes between the inclusion 6 and the foreign matter 7 using the compositional image and the surface topography image, and extracts the inclusion 6 from the compositional image. Furthermore, even if the inclusion 6 in the metal material 4 appears brighter than the metal material 4 in the compositional image, the information processing device 20 can extract the inclusion 6 from the compositional image using the compositional image and the surface topography image.

[0039] Figure 5 is a diagram illustrating the compositional image. Figure 6 is a diagram illustrating the surface relief image.

[0040] As shown in Figure 5, in the compositional image, if the inclusion 6 appears darker than the metallic material 4, and the contrast difference between the inclusion 6 and the foreign matter 7 is small, it is impossible to distinguish whether the particle 8 is the inclusion 6 or the foreign matter 7.

[0041] As shown in Figure 6, in the topographic image, the inclusion 6 appears darker than the metal material 4, or, although not shown, appears brighter than the metal material 4. On the other hand, the foreign matter 7 appears even brighter than the metal material 4 and the inclusion 6 in the topographic image. In particular, in the topographic image, the edges of the foreign matter 7 appear brighter due to the edge effect. The edge effect is a phenomenon in which the edges of a sample become extremely bright in a topographic image.

[0042] Furthermore, in the relief image, the shadow 9 of the foreign object 7 can be seen. The shadow 9 appears darker than the metallic material 4. The shadow 9 appears due to the illumination effect. The illumination effect is a phenomenon in scanning electron microscopy where contrast is obtained as if light were shining from the direction of the detector. The illumination effect occurs because electrons emitted from the sample toward the detector are incident on the detector, while electrons emitted from the sample in the opposite direction from the detector are not detected by the detector.

[0043] In the example shown in Figure 6, bright particles 8, dark particles 8, and dark shadows 9 can be seen in the surface relief image. The bright particles 8 correspond to foreign matter 7, and the dark particles 8 correspond to inclusions 6 or shadows 9.

[0044] Figure 7 illustrates the compositional particle image, surface texture image, and common area image. In Figure 7, the compositional image, surface texture image, and common area image of the same field of view are enclosed in dashed frames.

[0045] The compositional image of the metal material 4 is binarized to extract the particles 8 in the image, and a labeling process is performed to generate a compositional particle image for each particle 8. Each compositional particle image contains one particle 8. In the example shown in Figure 7, 10 particles 8 are extracted from one compositional image to generate 10 compositional particle images.

[0046] In the compositional image, a threshold is set and the compositional image is binarized so that particle 8 is extracted from the compositional image. For example, multiple thresholds are set and the compositional image is binarized so that areas brighter than the metal material 4 are white, areas darker than the metal material 4 are white, and the rest (i.e., the metal material 4) is black. This allows particle 8 to be extracted from the compositional image even if the inclusion 6 has parts that are brighter and parts that are darker than the metal material 4. In the compositional particle image, the particle parts appear white.

[0047] Furthermore, if the inclusion 6 is darker than the metallic material 4 in the compositional image, the brightness of the compositional image is inverted. Afterward, the compositional image with inverted brightness may be binarized. This allows for the extraction of particle 8 from the compositional image. As a method for determining the threshold when binarizing the compositional image, a method may be used in which the degree of separation is calculated from the variance on the darker side and the variance on the brighter side while changing the threshold, and the threshold with the greatest degree of separation is adopted.

[0048] Furthermore, in the compositional image, if the inclusion 6 is brighter than the metallic material 4, the foreign matter 7 is darker than the metallic material 4, so the inclusion 6 and the foreign matter 7 can be directly distinguished from the compositional image.

[0049] The topographic image of the metal material 4 is binarized to extract particles 8 from the image, and a labeling process is performed to generate a topographic particle image for each particle 8. The field of view of the topographic particle image and the field of view of the compositional particle image are the same. When generating the topographic particle image, the region of the topographic image with the same field of view as the compositional particle image is cut out from the topographic image. That is, the region of the topographic image corresponding to the region extracted as particle 8 in the compositional image is cut out from the topographic image. This makes it possible to generate a topographic particle image. In the example shown in Figure 7, 10 particles 8 are extracted from one topographic image to generate 10 topographic particle images.

[0050] In the topographic image, thresholds are set and the topographic image is binarized so that particles 8 corresponding to inclusions 6 and shadows 9 are extracted. For example, multiple thresholds are set and the topographic image is binarized so that areas brighter than the metal material 4 and darker than the foreign object 7 are white, areas darker than the metal material 4 are white, and the rest of the image is black. This allows for the extraction of particles 8 corresponding to inclusions 6 and shadows 9 from the topographic image, even if some of the inclusions 6 are brighter than the metal material 4 and others are darker than the metal material 4. In the topographic particle image, the particle areas appear white.

[0051] Furthermore, if the inclusion 6 is darker than the metallic material 4 in the topographic image, the brightness of the topographic image may be inverted, and then the topographic image with inverted brightness may be binarized. This allows the particles 8 corresponding to the inclusion 6 and shadow 9 to be extracted from the topographic image. In this case, the threshold for binarizing the topographic image may be determined, for example, by a method similar to the threshold for binarizing the compositional image described above.

[0052] The common area between the corresponding compositional particle image and the surface texture particle image is extracted to generate a common area image. The corresponding compositional particle image and surface texture particle image are images of the same field of view that contain the same particle 8.

[0053] The common area between the compositional particle image and the surface texture particle image is extracted by extracting the region where both images are white. For example, if the pixel at coordinates (a,b) in the compositional particle image is white and the pixel at coordinates (a,b) in the surface texture image is white, the pixel at coordinates (a,b) in the common area image will be white. Similarly, if the pixel at coordinates (a,b) in the compositional particle image is black and the pixel at coordinates (a,b) in the surface texture image is white, the pixel at coordinates (a,b) in the common area image will be black. Furthermore, if the pixel at coordinates (a,b) in the compositional particle image is white and the pixel at coordinates (a,b) in the surface texture image is black, the pixel at coordinates (a,b) in the common area image will be black. In this way, the common area between the compositional particle image and the surface texture particle image is extracted. In the common area image, particle 8 (white area) is the edge portion of inclusion 6 or foreign object 7.

[0054] Figure 8 illustrates the process of determining whether particle 8 is an inclusion 6 or a foreign object 7 using a common partial image and a compositional particle image. In Figure 8, the common partial image and compositional particle image of the same field of view are enclosed in a dashed frame.

[0055] Based on the compositional particle image and the common area image, it is determined whether particle 8 is an inclusion 6. Specifically, first, the area B of the particle portion of the common area image is compared to the area A of the particle portion of the compositional particle image. The ratio B / A is calculated. In the composition particle image and common part image shown in Figure 8, the area of ​​the particle portion is the area of ​​the region shown in white.

[0056] The calculated ratio B / A is compared with a threshold value. If the ratio B / A is greater than the threshold value, particle 8 is determined to be an inclusion 6. If the ratio B / A is less than or equal to the threshold value, particle 8 is determined not to be an inclusion 6, i.e., particle 8 is determined to be a foreign object 7 on the metal material 4. The threshold value can be set to any value. By increasing the threshold value, the possibility of foreign object 7 being determined to be an inclusion 6 can be reduced.

[0057] By performing a process to determine whether particle 8 is an inclusion 6 or a foreign object 7 for all compositional particle images, inclusion 6 can be extracted from the compositional image.

[0058] 2.2. Particle Analysis Processing Figure 9 is a flowchart showing an example of particle analysis processing by the information processing device 20.

[0059] First, the composition image acquisition unit 201 acquires information on the composition image of the metal material 4 (S100). In the electron microscope body 10, while scanning the metal material 4 with an electron beam, the backscattered electrons emitted from the metal material 4 are detected by the backscattered electron detector 120, thereby capturing a backscattered electron image, i.e., a composition image, of the metal material 4. The composition image information captured by the electron microscope body 10 is output to the information processing device 20. The composition image acquisition unit 201 receives the composition image information output from the electron microscope body 10.

[0060] Next, the surface topography acquisition unit 202 acquires information on the surface topography of the metal material 4 (S102). In the electron microscope body 10, a secondary electron image, i.e., a surface topography image, of the metal material 4 can be captured by scanning the metal material 4 with an electron beam and detecting the secondary electrons emitted from the metal material 4 with the secondary electron detector 130. The information on the surface topography image captured by the electron microscope body 10 is output to the information processing device 20. The surface topography acquisition unit 202 receives the surface topography information output from the electron microscope body 10.

[0061] The electron microscope body 10 can simultaneously capture compositional images and surface texture images. Therefore, the field of view for the compositional image and the surface texture image can be made the same. Furthermore, the acquisition time for both compositional and surface texture images can be reduced.

[0062] Next, the composition particle image generation unit 203 generates a composition particle image of the particle 8 (step S104). The composition particle image generation unit 203 binarizes the composition image of the metal material 4, extracts the particle 8 from the image, performs labeling, and generates a composition particle image. The composition particle image generation unit 203 generates a composition particle image for each extracted particle 8.

[0063] Next, the surface texture particle image generation unit 204 generates a surface texture particle image of the particle 8 (step S106). The surface texture particle image generation unit 204 binarizes the surface texture image of the metal material 4, extracts the particle 8 from the image, and performs labeling. The surface texture particle image generation unit 204 cuts out the same region as the composition particle image generated in step S106 and generates a surface texture particle image for each particle 8.

[0064] Next, the common area image generation unit 205 extracts the common area between the composition particle image generated by the composition particle image generation unit 203 and the surface particle image generated by the surface particle image generation unit 204, and generates a common area image (step S108).

[0065] The determination unit 206 selects one of several particles extracted from the compositional image (step S110) and calculates the ratio B / A of the area B of the particle portion of the common portion image to the area A of the particle portion of the compositional particle image (step S112).

[0066] The determination unit 206 determines whether the ratio B / A is greater than the threshold, and if the ratio B / A is greater than the threshold If the ratio B / A is greater than the threshold (Yes in step S114), the particle 8 is determined to be the inclusion 6 (step S116). On the other hand, if the ratio B / A is not greater than the threshold, i.e., if the ratio B / A is less than or equal to the threshold (No in step S114), the determination unit 206 determines that the particle 8 is the foreign matter 7 (step S118).

[0067] The determination unit 206 determines whether or not all particles 8 in the compositional image have been determined (step S120). If the determination unit 206 determines that not all particles 8 have been determined (Yes in step S120), it returns to step S110, selects one of the multiple particles extracted from the compositional image (step S110), and calculates the ratio B / A of the area B of the particle portion of the common portion image to the area A of the particle portion of the compositional particle image (step S112).

[0068] In this manner, the determination unit 206 repeats the processes of steps S110 to S120 until it determines whether or not each particle 8 extracted from the compositional image is an inclusion 6.

[0069] If the determination unit 206 determines that it has determined whether or not each particle 8 is an inclusion 6 (Yes in step S120), the particle analysis unit 207 obtains information on the shape and size of each inclusion 6 (step S122).

[0070] The particle analysis unit 207 measures the diameter, area, perimeter, circularity, aspect ratio, etc., of each particle 8 determined to be an inclusion 6 in the compositional image. This allows the unit to obtain information on the shape and size of each inclusion 6.

[0071] Next, the particle analysis unit 207 acquires information on the composition of each inclusion 6 (step S124).

[0072] The particle analysis unit 207 acquires positional information for each particle 8 identified as an inclusion 6 and controls the electron microscope body 10 so that the electron beam is irradiated to the position specified by the positional information. As a result, the electron beam is irradiated to the inclusion 6 by the electron microscope body 10, the characteristic X-rays emitted from the inclusion 6 are detected by the EDS 140, and the EDS spectrum of the inclusion 6 can be obtained. The EDS spectrum information is output to the information processing device 20. The particle analysis unit 207 receives the EDS spectrum information output from the electron microscope body 10.

[0073] The particle analysis unit 207 acquires the EDS spectrum of the inclusion 6 and analyzes the EDS spectrum of the inclusion 6 to obtain information on the composition of the inclusion 6. The particle analysis unit 207 statistically processes the information on the shape of the inclusion 6, the size of the inclusion 6, and the composition of the inclusion 6. The particle analysis unit 207 creates graphs, histograms, tables, etc., showing the results of the statistical processing of this information, and displays these on the display unit 220.

[0074] The processing unit 200 obtains information on the composition of the inclusions 6, performs statistical processing, and then terminates the particle analysis process.

[0075] Note that the order of each process shown in Figure 9 can be changed as appropriate. For example, in the above, the compositional image acquisition unit 201 acquired information on the compositional image, and then the surface texture acquisition unit 202 acquired information on the surface texture image. However, the surface texture acquisition unit 202 may acquire information on the surface texture image first, and then the compositional image acquisition unit 201 may acquire information on the compositional image.

[0076] 3. Effects The image processing method according to this embodiment includes the steps of acquiring a compositional image of the metal material 4, acquiring a surface texture image of the metal material 4, and binarizing the compositional image to extract particles 8 and generate a compositional particle image. The process includes: a step of extracting particles 8 by binarizing the surface image and generating a surface particle image; a step of extracting the common part of the composition particle image and the surface particle image and generating a common part image; and a step of determining whether or not the particles 8 are inclusions 6 in the metal material 4 based on the composition particle image and the common part image.

[0077] In the image processing method according to this embodiment, it is possible to determine whether a particle 8 is an inclusion 6 in the metal material 4 using a compositional image and a surface texture image. Therefore, in the image processing method according to this embodiment, it is possible to determine whether a particle 8 is an inclusion 6 in a shorter time and perform particle analysis in a shorter time compared to the case where EDS analysis is performed to determine whether a particle is an inclusion 6.

[0078] Conventionally, in particle analysis, particles 8 were extracted from a compositional image, and each particle 8 was subjected to qualitative analysis such as EDS analysis to determine whether or not it was an inclusion 6. In contrast, the image processing method according to this embodiment can determine whether or not a particle 8 is an inclusion 6 using the compositional image and the surface topography image. Therefore, since the image processing method according to this embodiment does not require EDS analysis of the foreign matter 7, it is possible to determine whether or not a particle 8 is an inclusion 6 in a short amount of time.

[0079] In the image processing method according to this embodiment, in the step of determining whether a particle 8 is an inclusion 6, the determination is made based on the area A of the particle portion in the composition particle image and the area B of the particle portion in the common portion image. Thus, in the image processing method according to this embodiment, it is possible to determine whether a particle 8 is an inclusion 6 using the composition image and the surface relief image, and therefore it is possible to determine whether a particle 8 is an inclusion 6 in a short amount of time.

[0080] In the image processing method according to this embodiment, the step of determining whether a particle 8 is an inclusion 6 includes the steps of: calculating the ratio B / A of the area B of the particle portion of the common portion image to the area A of the particle portion of the composition particle image; determining whether the ratio B / A is greater than a threshold; determining that the particle 8 is an inclusion 6 if the ratio B / A is greater than the threshold; and determining that the particle 8 is a foreign object 7 on the metal material 4 if the ratio B / A is less than or equal to the threshold. Therefore, in the image processing method according to this embodiment, it is possible to determine whether a particle 8 is an inclusion 6 or a foreign object 7 using the composition image and the surface relief image.

[0081] The particle analysis method according to this embodiment includes the image processing method described above, and when a particle 8 is determined to be an inclusion 6, it includes a step of acquiring information about the particle 8 determined to be an inclusion 6. Therefore, the particle analysis method according to this embodiment can perform particle analysis in a short amount of time.

[0082] The information processing device 20 includes a composition image acquisition unit 201 that acquires a composition image of the metal material 4, a surface texture image acquisition unit 202 that acquires a surface texture image of the metal material 4, a composition particle image generation unit 203 that binarizes the composition image to extract particles 8 and generates a composition particle image, a surface texture particle image generation unit 204 that binarizes the surface texture image to extract particles and generates a surface texture particle image, a common part image generation unit 205 that extracts the common part of the composition particle image and the surface texture particle image and generates a common part image, and a determination unit 206 that determines whether the particles 8 are inclusions 6 in the metal material 4 based on the composition particle image and the common part image.

[0083] Therefore, the information processing device 20 can determine whether or not a particle 8 is an inclusion 6 in the metal material 4 using the compositional image and the surface topography image. Consequently, the information processing device 20 can determine whether or not a particle 8 is an inclusion 6 in a shorter time compared to the case where EDS analysis is performed to determine whether or not a particle 8 is an inclusion 6.

[0084] In the information processing device 20, the determination unit 206 performs the following processes: calculate the ratio B / A of the area B of the particle portion of the common portion image to the area A of the particle portion of the composition particle image; determine whether the ratio B / A is greater than a threshold; if the ratio B / A is greater than the threshold, determine that the particle 8 is an inclusion 6; and if the ratio B / A is less than or equal to the threshold, determine that the particle 8 is a foreign object 7 on the metal material 4. The information processing device 20 performs a discontinuation process. Therefore, it can determine whether the particle 8 is an inclusion 6 or a foreign object 7 using the compositional image and the surface texture image.

[0085] The information processing device 20 includes a particle analysis unit 207 that acquires information about particle 8 that has been determined to be an inclusion 6. Therefore, the information processing device 20 can perform particle analysis in a short amount of time.

[0086] Since the electron microscope 100 includes an information processing device 20, particle analysis can be performed in a short time.

[0087] The electron microscope 100 includes a backscattered electron detector 120 that detects backscattered electrons emitted from the metal material 4 by irradiating the metal material 4 with an electron beam, and a secondary electron detector 130 that detects secondary electrons emitted from the metal material 4 by irradiating the metal material 4 with an electron beam. Therefore, the electron microscope 100 can capture compositional images and surface topography images simultaneously, enabling particle analysis in a short time.

[0088] 4. Variations It should be noted that the present invention is not limited to the embodiments described above, and various modifications can be implemented within the scope of the gist of the present invention.

[0089] 4.1. First variation In the embodiment described above, in the particle analysis of inclusions 6 in the metal material 4, the compositional image and the common partial image were used to determine whether the particles 8 in the compositional image are inclusions 6 or not. However, for example, in the particle analysis of a target substance in a resin-embedded mineral, the compositional image and the common partial image may be used to determine whether the particles in the compositional image are the target substance in the mineral or not. In this case as well, similar to the embodiment described above, the compositional image and the common partial image can be used to distinguish between the target substance in the mineral and foreign matter on the mineral.

[0090] Thus, using the method of this embodiment, it is possible to distinguish between the target substance in the sample and foreign matter on the sample. This allows for particle analysis of the target substance in a short amount of time.

[0091] 4.2. Second Variation In the embodiment described above, as shown in Figure 1, the electron microscope 100 is equipped with an EDS 140, and information on the composition of the inclusions 6 is obtained by EDS analysis. However, the means for obtaining information on the composition of the inclusions 6 are not limited to the EDS. For example, the electron microscope 100 may be equipped with an Auger electron spectrometer, and information on the composition of the inclusions 6 may be obtained by Auger electron spectroscopy using the Auger electron spectrometer. Alternatively, the electron microscope 100 may be equipped with both an EDS and an Auger electron spectrometer.

[0092] 4.3. Third Variation In the embodiments described above, a case was explained in which a backscattered electron image obtained using a backscattered electron detector 120 was used as the compositional image and a secondary electron image obtained using a secondary electron detector 130 was used as the surface relief image. However, the compositional image and secondary electron image are not limited to these.

[0093] For example, compositional images and surface topography images may be acquired using a segmented detector in which a backscattered electron detector having an annular detection region is divided into multiple regions. For example, in a segmented detector in which the detection region is divided into two regions, a compositional image can be acquired by taking the sum of the output signals of the two regions, and a surface topography image can be acquired by taking the difference of the output signals of the two regions. Even when using compositional images and surface topography images acquired in this way, it is possible to determine whether or not a particle is an inclusion in a short time, similar to the embodiment described above. The number of divisions in the detection region of the segmented detector is not particularly limited, and for example, it may be divided into four sections.

[0094] The present invention is not limited to the embodiments described above, and various further modifications are possible. For example, the present invention includes configurations that are substantially identical to those described in the embodiments. A substantially identical configuration is, for example, a configuration that has the same function, method, and result, or a configuration that has the same purpose and effect. The present invention also includes configurations in which non-essential parts of the configuration described in the embodiments are replaced. Furthermore, the present invention includes configurations that produce the same effects or achieve the same purpose as the configuration described in the embodiments. Furthermore, the present invention includes configurations that add known technology to the configuration described in the embodiments. [Explanation of Symbols]

[0095] 10...Electron microscope main unit, 20...Information processing device, 100...Electron microscope, 102...Electron source, 104...Focusing lens, 106...Scanning deflector, 108...Objective lens, 110...Sample stage, 120...Backscattered electron detector, 130...Secondary electron detector, 200...Processing unit, 201...Composition image acquisition unit, 202...Topographic image acquisition unit, 203...Composition particle image generation unit, 204...Topographic particle image generation unit, 205...Common part image generation unit, 206...Determination unit, 207...Particle analysis unit, 210...Operation unit, 220...Display unit, 230...Storage unit

Claims

1. The process of obtaining a compositional image of a metallic material, A step of obtaining a topographic image of the metal material, The process involves binarizing the aforementioned compositional image to extract particles and generating a compositional particle image. The process involves binarizing the aforementioned surface image to extract particles and generating a surface particle image, A step of extracting the common portion of the composition particle image and the surface particle image to generate a common portion image, A step of determining whether the particles extracted from the compositional image are inclusions in the metal material based on the compositional particle image and the common partial image, Image processing methods, including those mentioned above.

2. In claim 1, An image processing method that, in the step of determining whether or not an inclusion is present, determines whether or not a particle extracted from the compositional image is an inclusion based on the area of ​​the particle portion of the compositional particle image and the area of ​​the particle portion of the common portion image.

3. In claim 2, The step of determining whether or not it is an inclusion is, A step of calculating the ratio of the area of ​​the particle portion of the common portion image to the area of ​​the particle portion of the composition particle image, A step of determining whether the aforementioned ratio is greater than a threshold, If the aforementioned ratio is greater than the aforementioned threshold, the step of determining that the particles extracted from the compositional image are the aforementioned inclusions, A step in which, if the aforementioned ratio is less than or equal to the aforementioned threshold, the particles extracted from the compositional image are determined to be foreign matter on the metal material, Image processing methods, including those mentioned above.

4. The image processing method includes the method described in any one of claims 1 to 3, A particle analysis method comprising the step of obtaining information on particles determined to be inclusions when particles extracted from the compositional image are determined to be inclusions.

5. A compositional image acquisition unit that acquires a compositional image of a metallic material, A surface surface image acquisition unit that acquires a surface surface image of the metal material, A composition particle image generation unit that binarizes the aforementioned composition image to extract particles and generates a composition particle image, A surface texture image generation unit that binarizes the surface texture image to extract particles and generates a surface texture particle image, A common portion image generation unit extracts the common portion between the compositional particle image and the surface particle image to generate a common portion image, A determination unit that determines whether the particles extracted from the compositional image are inclusions in the metal material based on the compositional particle image and the common partial image, Information processing device, including

6. In claim 5, The determination unit is an information processing device that determines whether or not the particles extracted from the compositional image are inclusions, based on the area of ​​the particle portion of the compositional particle image and the area of ​​the particle portion of the common portion image.

7. In claim 6, The determination unit, A process to determine the ratio of the area of ​​the particle portion of the common portion image to the area of ​​the particle portion of the composition particle image, A process to determine whether the aforementioned ratio is greater than a threshold, If the aforementioned ratio is greater than the aforementioned threshold, the process involves determining that the particles extracted from the compositional image are the aforementioned inclusions. If the aforementioned ratio is less than or equal to the aforementioned threshold, the process of determining that the particles extracted from the compositional image are foreign matter on the metal material, An information processing device that performs this function.

8. In claim 5, An information processing apparatus including a particle analysis unit that acquires information on particles determined to be inclusions when particles extracted from the compositional image are determined to be inclusions.

9. An electron microscope comprising an information processing device according to any one of claims 5 to 8.

10. In claim 9, A backscattered electron detector for detecting backscattered electrons emitted from a metal material by irradiating the metal material with an electron beam, and for obtaining the compositional image, A secondary electron detector for detecting secondary electrons emitted from a metal material by irradiating the metal material with an electron beam, and for acquiring the surface topography image, An electron microscope, including one.

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