Representative tissue photograph determination method, representative tissue photograph determination apparatus, imaging apparatus, and program

Abstract

To provide a representative structure photograph determination method, a representative structure photograph determination device, an imaging device and a program capable of objectively and efficiently determining a representative structure photograph from a plurality of structure photographs of a metal material.SOLUTION: A representative structure photograph determination method includes: an input step (S11) of acquiring a plurality of structure photographs taken at two or more photographing magnifications for at least two or more visual fields of a metallic material; a phase classification step (S12) of classifying phases in the plurality of structure photographs; a quantitative value calculation step (S13) of calculating a quantitative value of the classified phase; a magnification determination step (S14) of determining the representative photographing magnification based on the quantitative value; and an output step (S17) of outputting the representative photographing magnification.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present disclosure relates to a representative structure photograph determination method, a representative structure photograph determination apparatus, a photographing apparatus, and a program. In particular, the present disclosure relates to a representative structure photograph determination method, a representative structure photograph determination apparatus, a photographing apparatus, and a program for determining a representative structure photograph of a structure photograph of a metal material.

Background Art

[0002] Generally, even if metal materials including steel have the same composition, their properties strongly depend on the metal structure at the scale of an optical microscope or an electron microscope level (for example, a scale of mm to μm).

[0003] For example, in the development of high-strength steel sheets, methods of changing the composition such as a solid solution strengthening method by adding a solid solution strengthening element and a precipitation strengthening method by adding a precipitation strengthening element are used. In addition to these methods, a method of changing the final metal structure by changing the heat treatment conditions with the same composition may also be used.

[0004] As described above, in the development of high-strength steel sheets and the like, not only the control of the composition but also the control of the metal structure is important. Therefore, it is important to observe a metal material with an optical microscope, an electron microscope, or the like and quantitatively evaluate its metal structure. For example, Patent Document 1 discloses a method for producing an observation sample for observation with an electron microscope.

[0005] When a metal material such as a steel sheet is observed with a known photographing apparatus such as an electron microscope after performing sample preparation such as a known polishing method and etching method, generally, since the contrast is different for each phase, each phase can be classified. For example, when a typical steel sheet composed of a ferrite phase and a pearlite phase in a steel material is sample-prepared by a known method and then photographed with an optical microscope, the ferrite phase is observed with a gray contrast and the pearlite phase is observed with a black contrast. Therefore, the ferrite phase and the pearlite phase can be classified. Development is being carried out by observing the metal structure by such a method and feeding back the results of the observation.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] Here, when newly developing a metal material, it is often unclear what the appropriate magnification for observing the metal structure is. In such cases, conventionally, the magnification has been determined and the imaging field of view has been selected based on the observer's subjectivity. Therefore, there is a risk of misinterpreting the correlation between the metal structure and the material properties due to inappropriate selection. If the manufacturing process is determined based on the misinterpreted correlation, there is a risk that products with desired properties cannot be manufactured. Also, in determining the representative micrograph, the work of comparing and selecting a plurality of fields of view while the observer changes the magnification takes time, and the work efficiency may decrease.

[0008] In view of such circumstances, an object of the present disclosure is to provide a representative micrograph determination method, a representative micrograph determination apparatus, an imaging apparatus, and a program capable of objectively and efficiently determining a representative micrograph from a plurality of micrographs of a metal material.

Means for Solving the Problems

[0009] A representative micrograph determination method according to an embodiment of the present disclosure is an input step of acquiring a plurality of micrographs taken at two or more magnifications for at least two or more fields of view of a metal material, a phase classification step of classifying phases in the plurality of micrographs, a quantitative value calculation step of calculating quantitative values of the classified phases, a magnification determination step of determining a representative magnification based on the quantitative values, an output step of outputting the representative magnification, and includes.

[0010] A representative tissue photograph determination method according to an embodiment of the present disclosure includes: an input step of acquiring a plurality of tissue photographs taken at a predetermined magnification for at least two or more fields of a metal material; a phase classification step of classifying phases in the plurality of tissue photographs; a quantitative value calculation step of calculating quantitative values of the classified phases; a deviation calculation step of calculating a deviation of the quantitative values; a selection step of selecting a representative tissue photograph from the plurality of tissue photographs based on the deviation; an output step of outputting the representative tissue photograph; and is provided with.

[0011] A representative tissue photograph determination method according to an embodiment of the present disclosure includes: an input step of acquiring a plurality of tissue photographs taken at two or more magnifications for at least two or more fields of a metal material; a phase classification step of classifying phases in the plurality of tissue photographs; a quantitative value calculation step of calculating quantitative values of the classified phases; a magnification determination step of determining a representative photographing magnification based on the quantitative values; a deviation calculation step of calculating a deviation of the quantitative values for the plurality of tissue photographs corresponding to the representative photographing magnification; a selection step of selecting a representative tissue photograph from the plurality of tissue photographs corresponding to the representative photographing magnification based on the deviation; an output step of outputting the representative tissue photograph; and is provided with.

[0012] A representative tissue photograph determination apparatus according to an embodiment of the present disclosure includes: an input unit that acquires a plurality of tissue photographs taken at two or more magnifications for at least two or more fields of a metal material; a phase classification unit that classifies phases in the plurality of tissue photographs; a quantitative value calculation unit that calculates quantitative values of the classified phases; a magnification determination unit that determines a representative photographing magnification based on the quantitative values; an output unit that outputs the representative shooting magnification; It includes.

[0013] The representative tissue photo determination device according to an embodiment of the present disclosure includes an input unit that acquires a plurality of tissue photos taken at a predetermined shooting magnification for at least two or more fields of view of a metal material; a phase classification unit that classifies phases in the plurality of tissue photos; a quantitative value calculation unit that calculates a quantitative value of the classified phase; a deviation calculation unit that calculates a deviation of the quantitative value; a selection unit that selects a representative tissue photo from the plurality of tissue photos based on the deviation; an output unit that outputs the representative tissue photo; It includes.

[0014] The representative tissue photo determination device according to an embodiment of the present disclosure includes an input unit that acquires a plurality of tissue photos taken at two or more shooting magnifications for at least two or more fields of view of a metal material; a phase classification unit that classifies phases in the plurality of tissue photos; a quantitative value calculation unit that calculates a quantitative value of the classified phase; a magnification determination unit that determines a representative shooting magnification based on the quantitative value; a deviation calculation unit that calculates a deviation of the quantitative value for the plurality of tissue photos corresponding to the representative shooting magnification; a selection unit that selects a representative tissue photo from the plurality of tissue photos corresponding to the representative shooting magnification based on the deviation; an output unit that outputs the representative tissue photo; It includes.

[0015] The imaging device according to an embodiment of the present disclosure shoots the plurality of tissue photos acquired by the above representative tissue photo determination device.

[0016] The program according to an embodiment of the present disclosure causes a computer to An input unit that acquires a plurality of tissue photographs taken at two or more shooting magnifications for at least two or more fields of a metal material, A phase classification unit that classifies phases in the plurality of tissue photographs, A quantitative value calculation unit that calculates a quantitative value of the classified phase, A magnification determination unit that determines a representative shooting magnification based on the quantitative value, An output unit that outputs the representative shooting magnification, and causes it to function.

[0017] A program according to an embodiment of the present disclosure causes a computer to function as an input unit that acquires a plurality of tissue photographs taken at a predetermined shooting magnification for at least two or more fields of a metal material, a phase classification unit that classifies phases in the plurality of tissue photographs, a quantitative value calculation unit that calculates a quantitative value of the classified phase, a deviation calculation unit that calculates a deviation of the quantitative value, a selection unit that selects a representative tissue photograph from the plurality of tissue photographs based on the deviation, an output unit that outputs the representative tissue photograph, and causes it to function.

[0018] A program according to an embodiment of the present disclosure causes a computer to function as an input unit that acquires a plurality of tissue photographs taken at two or more shooting magnifications for at least two or more fields of a metal material, a phase classification unit that classifies phases in the plurality of tissue photographs, a quantitative value calculation unit that calculates a quantitative value of the classified phase, a magnification determination unit that determines a representative shooting magnification based on the quantitative value, a deviation calculation unit that calculates a deviation of the quantitative value for the plurality of tissue photographs corresponding to the representative shooting magnification, a selection unit that selects a representative tissue photograph from the plurality of tissue photographs corresponding to the representative shooting magnification based on the deviation, an output unit that outputs the representative tissue photograph, Function as.

Advantages of the Invention

[0019] According to the present disclosure, it is possible to provide a representative texture photograph determination method, a representative texture photograph determination device, a photographing device, and a program that can objectively and efficiently determine a representative texture photograph from a plurality of texture photographs of a metal material.

Brief Description of the Drawings

[0020]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Modes for Carrying Out the Invention

[0021] Hereinafter, a representative tissue photograph determination method, a representative tissue photograph determination apparatus, a photographing apparatus, and a program according to an embodiment of the present disclosure will be described with reference to the drawings. In each figure, the same or corresponding parts are denoted by the same reference numerals. In the following description of the embodiments, the description of the same or corresponding parts will be omitted or simplified as appropriate.

[0022] [First Embodiment] (Representative Tissue Photograph Determination System) FIG. 1 is a block diagram of a representative tissue photograph determination system 1 including a representative tissue photograph determination apparatus 10 according to the first embodiment. The representative tissue photograph determination system 1 includes a representative tissue photograph determination apparatus 10 and a photographing apparatus 30. The representative tissue photograph determination apparatus 10 includes an input unit 11, an output unit 12, and an arithmetic unit 13. The arithmetic unit 13 includes a phase classification unit 14, a quantitative value calculation unit 15, and a magnification determination unit 17. The arithmetic unit 13 may further include a deviation calculation unit 16 as in the present embodiment.

[0023] (Photographing Apparatus) The photographing apparatus 30 photographs a plurality of tissue photographs of a metal material acquired by the representative tissue photograph determination apparatus 10. The photographing apparatus 30 is, for example, an optical microscope or a scanning electron microscope, but is not limited thereto as long as it has a function of photographing the structure of a metal material.

[0024] (Representative Tissue Photograph Determination Apparatus) The representative tissue photograph determination apparatus 10 executes a process for determining a representative tissue photograph from a plurality of tissue photographs of a metal material photographed by the photographing apparatus 30. Here, the metal material is a steel material or a metal material having a plurality of metal phases. The representative tissue photograph is a tissue photograph capable of quantitatively evaluating the metal structure. The representative tissue photograph determination apparatus 10 may directly determine the representative tissue photograph or may determine the properties of the representative tissue photograph. The properties of the determined representative tissue photograph are, for example, magnification or scale. In the present embodiment, the representative tissue photograph determination apparatus 10 determines the representative photographing magnification (the magnification of the representative tissue photograph).

[0025] (Input Unit) The input unit 11 is an input interface of the representative tissue photo determination device 10 that acquires data necessary for the process of determining the representative tissue photo. In the present embodiment, the input unit 11 acquires a plurality of tissue photos taken at two or more shooting magnifications for at least two or more fields of view of the metal material. The data format of the plurality of tissue photos may be a generally used image data format such as TIFF or BMP.

[0026] (Output unit) The output unit 12 is an output interface of the representative tissue photo determination device 10 that outputs the determined representative tissue photo or the properties of the representative tissue photo. The output unit 12 may transmit information on the determined representative tissue photo or the properties of the representative tissue photo to other devices or the like. Further, the output unit 12 may display the determined representative tissue photo or the properties of the representative tissue photo on a display device such as various displays. In the present embodiment, the output unit 12 outputs the representative shooting magnification.

[0027] (Calculation unit) The calculation unit 13 performs calculations for determining the representative tissue photo or the properties of the representative tissue photo. Further, the calculation unit 13 may have a function as a control unit that controls the entire representative tissue photo determination device 10. The calculation unit 13 may be one or more processors. The processor may be, for example, a general-purpose processor or a dedicated processor specialized for a specific process, but is not limited thereto and can be any processor.

[0028] As described above, in the present embodiment, the calculation unit 13 includes a phase classification unit 14, a quantitative value calculation unit 15, a deviation calculation unit 16, and a magnification determination unit 17. The functions of the phase classification unit 14, the quantitative value calculation unit 15, the deviation calculation unit 16, and the magnification determination unit 17 may be realized by software. For example, one or more programs may be stored in a storage device accessible by the calculation unit 13. When the program stored in the storage device is read by the calculation unit 13 which is a processor, the calculation unit 13 may function as the phase classification unit 14, the quantitative value calculation unit 15, the deviation calculation unit 16, and the magnification determination unit 17.

[0029] (Phase classification unit) The phase classification unit 14 classifies the phases in a plurality of tissue photographs. Details of the process executed by the phase classification unit 14 will be described later.

[0030] (Quantitative value calculation unit) The quantitative value calculation unit 15 calculates the quantitative value of the phase classified by the phase classification unit 14. Details of the quantitative value and the process executed by the quantitative value calculation unit 15 will be described later.

[0031] (Magnification determination unit) The magnification determination unit 17 determines the representative photographing magnification based on the quantitative value calculated by the quantitative value calculation unit 15. Details of the process executed by the magnification determination unit 17 will be described later.

[0032] (Deviation calculation unit) When there are a plurality of candidates for the representative photographing magnification determined by the magnification determination unit 17, the deviation calculation unit 16 calculates the deviation of the quantitative value in order to determine the final representative photographing magnification. Details of the process executed by the deviation calculation unit 16 will be described later.

[0033] Here, the representative tissue photograph determination device 10 is not limited to a specific device, but can be realized by a computer as an example. As the computer, for example, a commercially available general-purpose one can be used. The computer includes storage devices such as a memory and a hard disk drive, a CPU, and an input / output device. The arithmetic unit 13 may be realized by a CPU. The program read by the arithmetic unit 13 may be stored in the storage device. Also, the input unit 11 and the output unit 12 may be realized by an input / output device.

[0034] (Method for determining representative tissue photograph) FIG. 2 is a flowchart showing the processing of the representative tissue photograph determination method executed by the representative tissue photograph determination apparatus 10 according to the present embodiment. Briefly, the representative tissue photograph determination method includes an input step of acquiring a plurality of tissue photographs taken at two or more shooting magnifications for at least two or more fields of view of a metal material, a phase classification step of classifying phases in the plurality of tissue photographs, a quantitative value calculation step of calculating quantitative values of the classified phases, a magnification determination step of determining a representative shooting magnification based on the quantitative values, and an output step of outputting the representative shooting magnification, which are performed in this order. However, when there are a plurality of candidates for the representative shooting magnification, a deviation calculation step of calculating the deviation of the quantitative values is additionally performed in order to determine the final representative shooting magnification. Here, the representative tissue photograph determination method may be executed again after adding the tissue photographs acquired in the input step when the representative shooting magnification cannot be determined.

[0035] (Input step) The input step is a step in which the input unit 11 acquires a plurality of tissue photographs taken at two or more shooting magnifications for at least two or more fields of view of the metal material (step S11).

[0036] For the tissue photograph, after sample preparation is performed by polishing the surface of a metallic material (sample) by a known method such as polishing, it is preferably taken by a known photographing device such as an optical microscope or a scanning electron microscope. Sample preparation generally involves rough polishing followed by finish polishing. The rough polishing and the finish polishing may be performed by known methods. The rough polishing by a known method is, for example, polishing that uses a commercially available paper file (such as emery paper) with abrasive grains applied to the paper to remove scratches visible at the naked-eye level. The finish polishing by a known method is polishing that is performed using an abrasive of 0.05 μm - 2 μm until the sample becomes mirror-finished. As the abrasive, known abrasives such as diamond and silica can be used. Mirror polishing is performed until polishing scratches become inconspicuous when observed at a magnification of 10 - 500 times with an optical microscope. Since remaining a large number of polishing scratches causes an error factor when performing phase classification in the phase classification process, it is desirable to perform polishing so that as few scratches as possible remain. After the mirror polishing is performed, etching with nital or the like may be performed to clarify the contrast of the phases. Etching may be omitted when targeting samples for which phase classification can be performed without etching.

[0037] The number of fields of view of the tissue photograph shall be at least 2 or more. The larger the number of fields of view, the smaller the variation in the quantitative values of the phases for each photographing magnification. The number of fields of view of the tissue photograph is preferably 3 or more. The number of fields of view of the tissue photograph is more preferably 5 or more. The fields of view are preferably determined randomly. Also, two or more fields of view may be obtained by continuously taking photographs while changing the fields of view little by little. Further, when the photographing device 30 is equipped with a function of automatically determining the fields of view, such as by using random numbers in a program, such a function may be utilized.

[0038] The photographing magnification of the tissue photograph shall be at least 2 or more. The larger the number of levels of the photographing magnification, the higher the accuracy of the relationship between the obtained photographing magnification and the quantitative value of each phase for each photographing magnification, and the easier it is to determine an appropriate photographing magnification. The photographing magnification of the tissue photograph is preferably 3 or more. The photographing magnification of the tissue photograph is more preferably 5 or more. The photographing magnification is preferably selected randomly. For example, when observing DP steel (Dual Phase steel) composed of a ferrite phase and a martensite phase, it is preferable to select the photographing magnification in the range of 500 times to 3000 times. For example, when observing the plating layer of a plated steel sheet, it is preferable to select the photographing magnification in the range of 1000 times to 5000 times.

[0039] (Phase classification step) The phase classification step is a step in which the phase classification unit 14 classifies the phases in a plurality of tissue photographs (step S12).

[0040] Since the contrast of each phase is generally different in a tissue photograph, phase classification is possible. For example, phases are identified in a tissue photograph, and each phase is labeled with a different color or the like for classification. Phase classification may be performed by identifying the phase with the naked eye and manually painting for classification, may be performed using binarization of image luminance values, or may be performed by an advanced image analysis method. It is preferable to apply a method that can classify as accurately as possible.

[0041] However, phase classification by manual painting lacks objectivity. Therefore, it is preferable to use binarization or an advanced image analysis method. It is more preferable to use the advanced image analysis method exemplified below.

[0042] In the advanced image analysis method, after designating a plurality of regions of each phase from the photographed tissue photograph, a feature value is calculated from the luminance values of the images of the designated regions, and classification is performed using a method such as a random forest model, a neural network model, or a support vector machine that repeats N-valued conversion from the calculated feature values. As the feature value, it is preferable to use one or more of the following eight specific examples (C1 to C8).

[0043] (C1: Identity feature value) The identity eigenvalue is an eigenvalue indicating the luminance value of the tissue photograph itself.

[0044] (C2: Mean eigenvalue) The Mean eigenvalue is an eigenvalue indicating the average value of the luminance values in a predetermined range of the tissue photograph. That is, the Mean eigenvalue is obtained by extracting a predetermined range of "(number of pixels x) × (number of pixels y)" from each phase of the tissue photograph and averaging the luminance values therein. "Number of pixels x" and "number of pixels y" may be of the same size or different sizes. Also, the area of "(number of pixels x) × (number of pixels y)" does not have to be rectangular. When the tissue photograph is spherical in shape, it is preferably a spherical area, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of "number of pixels x" and "number of pixels y" is preferably set to be larger than, for example, the noise included in the tissue photograph and to be in a range including less than 1 / 2 of the size of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably set to be in a range including less than 1 / 2 of the crystal grain size of the larger crystal grain size because if the range of the number of pixels is made too large, it may be affected by the grain boundary or the influence of other adjacent phases.

[0045] Here, the "noise included in the tissue photograph" indicates, for example, a portion where the luminance value suddenly increases in the tissue photograph. And "making the number of pixels x and y larger than the noise" means making it larger than the width of the noise.

[0046] (C3: Gaussian eigenvalue) The Gaussian eigenvalue is an eigenvalue that represents the average value of luminance values with a greater weight the closer it is to the center within a predetermined range of the tissue photograph. That is, the Gaussian eigenvalue is obtained by extracting a predetermined range of "(number of pixels x) × (number of pixels y)" from each phase of the tissue photograph and taking the average value with a greater weight for the pixels closer to the center. The "number of pixels x" and the "number of pixels y" may be of the same size or different sizes. Also, the area of "(number of pixels x) × (number of pixels y)" does not have to be rectangular. When the tissue photograph has a spherical shape, it is preferably a spherical area, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of the "number of pixels x" and the "number of pixels y" is preferably, for example, larger than the noise included in the tissue photograph and within a range that includes less than 1 / 2 of the size of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably within a range that includes less than 1 / 2 of the size of the larger crystal grain size because if the pixel range is made too large, it may be affected by the grain boundary or the influence of adjacent other phases.

[0047] (C4: Median eigenvalue) The Median eigenvalue is an eigenvalue that represents the median value of luminance values within a predetermined range of the tissue photograph. That is, the Median eigenvalue is obtained by extracting a predetermined range of "(number of pixels x) × (number of pixels y)" from each phase of the tissue photograph and taking the median value from the luminance values therein. The "number of pixels x" and the "number of pixels y" may be of the same size or different sizes. Also, the area of "(number of pixels x) × (number of pixels y)" does not have to be rectangular. When the tissue photograph has a spherical shape, it is preferably a spherical area, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of the "number of pixels x" and the "number of pixels y" is preferably, for example, larger than the noise included in the tissue photograph and within a range that includes less than 1 / 2 of the size of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably within a range that includes less than 1 / 2 of the size of the larger crystal grain size because if the pixel range is made too large, it may be affected by the grain boundary or the influence of adjacent other phases.

[0048] (C5: Max eigenvalue) The Max eigenvalue is an eigenvalue indicating the maximum value of the luminance values within a predetermined range of the tissue photograph. That is, the Max eigenvalue is obtained by extracting a predetermined range of "(number of pixels x) × (number of pixels y)" from each phase of the tissue photograph and then extracting the maximum value from the luminance values therein. "Number of pixels x" and "number of pixels y" may have the same size or different sizes. Also, the region of "(number of pixels x) × (number of pixels y)" does not have to be rectangular. When the tissue photograph has a spherical shape, it is preferably a spherical region, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of "number of pixels x" and "number of pixels y" is preferably set to be larger than, for example, the noise included in the tissue photograph and to be within a range that includes less than 1 / 2 of the size of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably set to be within a range that includes less than 1 / 2 of the crystal grain size of the larger crystal grain size because if the pixel range is made too large, it may be affected by the grain boundary or the influence of adjacent other phases.

[0049] (C6: Min eigenvalue) The Min eigenvalue is an eigenvalue indicating the minimum value of the luminance values within a predetermined range of the tissue photograph. That is, the Min eigenvalue is obtained by extracting a predetermined range of "(number of pixels x) × (number of pixels y)" from each phase of the tissue photograph and then extracting the minimum value from the luminance values therein. "Number of pixels x" and "number of pixels y" may have the same size or different sizes. Also, the region of "(number of pixels x) × (number of pixels y)" does not have to be rectangular. When the tissue photograph has a spherical shape, it is preferably a spherical region, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of "number of pixels x" and "number of pixels y" is preferably set to be larger than, for example, the noise included in the tissue photograph and to be within a range that includes less than 1 / 2 of the size of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably set to be within a range that includes less than 1 / 2 of the crystal grain size of the larger crystal grain size because if the pixel range is made too large, it may be affected by the grain boundary or the influence of adjacent other phases.

[0050] (C7: Derivative eigenvalue) The Derivative eigenvalue is obtained by extracting a predetermined range of "(number of pixels x) × (number of pixels y)" from each phase of the tissue photograph and calculating the derivative values in the x - direction and y - direction for the pixels at the edges thereof. The "number of pixels x" and "number of pixels y" may be of the same size or different sizes. Also, the region of "(number of pixels x) × (number of pixels y)" does not necessarily have to be rectangular. When the tissue photograph is spherical in shape, it is preferably a spherical region, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of the "number of pixels x" and "number of pixels y" is preferably set to be larger than, for example, the noise contained in the tissue photograph and within a range that includes a size less than 1 / 2 of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably set to a range that includes a size less than 1 / 2 of the larger crystal grain size because if the pixel range is made too large, it may be affected by the grain boundary or the influence of an adjacent other phase.

[0051] (C8:Derivative addition eigenvalue) The Derivative addition eigenvalue is obtained by performing operations on the above - mentioned Mean eigenvalue, Gaussian eigenvalue, Median eigenvalue, Max eigenvalue, and Min eigenvalue with respect to the above - mentioned Derivative eigenvalue, and then convolving the Derivative eigenvalue. The "number of pixels x" and "number of pixels y" may be of the same size or different sizes. Also, the region of "(number of pixels x) × (number of pixels y)" does not necessarily have to be rectangular. When the tissue photograph is spherical in shape, it is preferably a spherical region, and it may be calculated for a plurality of numbers of pixels x and y. The lower limit of the "number of pixels x" and "number of pixels y" is preferably set to be larger than, for example, the noise contained in the tissue photograph and within a range that includes a size less than 1 / 2 of the smaller crystal grain size among the plurality of phases of the metal structure. The upper limit is preferably set to a range that includes a size less than 1 / 2 of the larger crystal grain size because if the pixel range is made too large, it may be affected by the grain boundary or the influence of an adjacent other phase.

[0052] Here, when analyzing an image by an advanced image analysis method, a process of cutting off the boundary part (outer peripheral part) may be performed for accurate analysis.

[0053] (Quantitative value calculation step) The quantitative value calculation step is a step in which the quantitative value calculation unit 15 calculates the quantitative value of the phase classified by the phase classification unit 14. As the quantitative value, at least one of the following (1) to (6) is calculated, for example.

[0054] Among the specific examples described below, the quantitative values (1) to (5) are calculated for each crystal grain of the phase that has been classified and specified. Therefore, a plurality of numerical values can be obtained for a single microstructure photograph. In addition to the specific examples described below, if there are parameters that can digitize the microstructure photograph, those parameters may be used.

[0055] (1) Area ratio The area ratio is obtained by finding the ratio of the area of each crystal grain of the specified phase to the area of the entire microstructure photograph in each microstructure photograph. The area ratio of each crystal grain is calculated according to the following formula.

[0056] [Number]

[0057] Here, f is the area ratio of each crystal grain. A i is the area of each crystal grain. A sum is the area of the entire microstructure photograph. Also, for the specified phase, by calculating the sum of the area ratios of each crystal grain, the area ratio of the specified phase per microstructure photograph is calculated.

[0058] (2) Ellipsoid size The ellipsoid size is calculated by approximating the shape of each crystal grain of the specified phase as an ellipse in each microstructure photograph. The ellipsoid size is at least one of the major axis, minor axis, and aspect ratio of the approximated ellipsoid. Also, for the specified phase, by calculating the average value of the ellipsoid sizes of each crystal grain, the average ellipsoid size of the specified phase per microstructure photograph is calculated.

[0059] (3) Feret diameter In each microstructure photograph, after drawing a straight line from the interface of each crystal grain of the specified phase, the Feret diameter at which the straight-line distance is maximized is calculated. Further, by calculating the average value of the Feret diameters calculated for each crystal grain, the average Feret diameter of the specified phase per microstructure photograph is calculated.

[0060] (4) Average diameter In each microstructure photograph, the area of each crystal grain of the specified phase is determined, and by taking the square root of the area, the average diameter of the crystal grain is calculated. Further, for the specified phase, by calculating the average value from the average diameters calculated for each crystal grain, the average average diameter of the specified phase per microstructure photograph is calculated.

[0061] (5) Circularity In each microstructure photograph, by determining the area and perimeter of each crystal grain of the specified phase, the circularity of each crystal grain is calculated according to the following formula.

[0062] [Number]

[0063] Here, C is the circularity. S is the area. P is the perimeter. When the crystal grain is a perfect circle, the circularity is 1.0. Conversely, the more the shape of the crystal grain deviates from a circle, the smaller the circularity becomes from 1.0. Further, for the specified phase, by calculating the average value from the circularities calculated for each crystal grain, the average circularity of the specified phase per microstructure photograph is calculated.

[0064] (6) Number density In each microstructure photograph, the number of crystal grains of the specified phase is counted, and by dividing the number of crystal grains by the area of the entire microstructure photograph, the number density per microstructure photograph is calculated.

[0065] As quantitative values, it is preferable to use one or more of (1) to (6), and more preferably two or more. In particular, when determining the representative photographing magnification, it is preferable to use a quantitative value including the area ratio of (1).

[0066] (Magnification Determination Step) The magnification determination step is a step in which the magnification determination unit 17 determines a representative shooting magnification based on the quantitative value calculated by the quantitative value calculation unit 15 (step S14).

[0067] As described above, it is preferable that the quantitative value of the crystal grains of the specified phase includes the area ratio. The magnification determination unit 17 can determine the shooting magnification as follows.

[0068] For a microstructure photograph at a certain shooting magnification, when the number of microstructure photographs in which there are two or more crystal grains with an area ratio exceeding 10% exceeds 1 / 3 of the total number of microstructure photographs at that shooting magnification acquired in the input step, the magnification determination unit 17 adopts a smaller shooting magnification. This is because in the microstructure photograph where there are two or more crystal grains with an area ratio exceeding 10%, there may be a break in the crystal grains at the boundary (peripheral part) of the microstructure photograph, or the distribution of the crystal grain sizes cannot be correctly evaluated due to the small number of crystal grains to be photographed. Also, exceeding 1 / 3 of the total number indicates a tendency in the microstructure photographs at that shooting magnification, rather than a feature of some exceptional microstructure photographs.

[0069] Also, for a microstructure photograph at a certain shooting magnification, when the number of microstructure photographs in which the crystal grain with the largest area ratio is less than 3% of the entire microstructure photograph exceeds 1 / 3 of the total number of microstructure photographs at that shooting magnification acquired in the input step, the magnification determination unit 17 adopts a larger shooting magnification. This is because in the microstructure photograph where the crystal grain with the largest area ratio is less than 3% of the entire microstructure photograph, there are many small crystal grains and the shape of the crystal grains cannot be appropriately evaluated. Also, exceeding 1 / 3 of the total number indicates a tendency in the microstructure photographs at that shooting magnification, rather than a feature of some exceptional microstructure photographs.

[0070] Hereinafter, for a tissue photograph at a certain shooting magnification, "the number of crystal grains with an area ratio exceeding 10% is not more than 1 / 3 of the total number of tissue photographs at that shooting magnification obtained in the input process" is also referred to as "Condition A". Also, for a tissue photograph at a certain shooting magnification, "the tissue photograph in which the crystal grain with the largest area ratio is less than 3% of the entire tissue photograph is not more than 1 / 3 of the total number of tissue photographs at that shooting magnification obtained in the input process" is also referred to as "Condition B". In the magnification determination step, the magnification determination unit 17 sets the shooting magnification that satisfies Condition A and Condition B as the representative shooting magnification.

[0071] Here, the upper limit value (10%) and the lower limit value (3%) of the area ratio in Condition A and Condition B of the magnification determination step are examples, and any values can be used as long as they can appropriately evaluate the size and shape of the crystal grains of the target metal material, and they are not limited. The quantitative value used in the conditions of the magnification determination step is the area ratio in this embodiment, but it may be, for example, the ellipsoid size or the Feret diameter. Also, when the shape or number of each crystal grain has a great influence on the material properties, the quantitative value used in the conditions of the magnification determination step may be, for example, the circularity or the number density. In this embodiment, since generally the area ratio of the phase has a large influence on the material properties in many cases, an example using the area ratio is described.

[0072] (Deviation calculation step) Here, there may be two or more shooting magnifications that satisfy both Condition A and Condition B. When there are multiple candidates for such representative shooting magnifications (Yes in step S15), the deviation calculation step is executed in this embodiment (step S16). The deviation calculation step is a step in which the deviation calculation unit 16 calculates the deviation of the quantitative value obtained by the quantitative value calculation unit 15.

[0073] The deviation calculation unit 16 calculates the standard deviation of each quantitative value for each shooting magnification that is a candidate for the representative shooting magnification. The shooting magnification with the smallest standard deviation is determined as the representative shooting magnification. Here, when the order of the standard deviations differs depending on the quantitative value, it is preferable to determine as the representative shooting magnification the shooting magnification with the smallest standard deviation of the quantitative value that is regarded as important. For example, in the case of a DP steel sheet, it is considered that the area ratio most affects the mechanical properties. Therefore, it is preferable to determine as the representative shooting magnification the shooting magnification with the smallest standard deviation of the area ratio. Also, it is not necessary to calculate the deviation of all the quantitative values calculated in the quantitative value calculation step. For example, for quantitative values that have little influence on the properties of the metal material, the deviation does not need to be calculated.

[0074] When the deviation calculation step is executed, the magnification determination step is executed again. In the second magnification determination step, the magnification determination unit 17 determines one final representative shooting magnification based on the deviation calculated by the deviation calculation unit 16 from among the candidates for the representative shooting magnification that have already been selected.

[0075] (Output step) When one representative shooting magnification is determined (No in step S15), the output step is executed (step S17). The output step is a step of outputting the representative shooting magnification determined by the output unit 12.

[0076] In this way, by the representative tissue photograph determination method executed by the representative tissue photograph determination apparatus 10 according to the present embodiment, an appropriate shooting magnification for observing a metal structure is determined without depending on the subjectivity of the observer. Also, the conventional operation of the observer comparing and selecting while changing the magnification can be made unnecessary, and the work efficiency can be improved.

[0077] [Second Embodiment] FIG. 3 is a block diagram of a representative tissue photo determination system 1 including a representative tissue photo determination device 10 according to the second embodiment. The representative tissue photo determination device 10 according to the present embodiment selects a representative tissue photo having an appropriate field of view, for example, when the representative photographing magnification is known. The representative tissue photo determination device 10 according to the present embodiment includes many common components as compared with the representative tissue photo determination device 10 according to the first embodiment, but includes a selection unit 18 instead of the magnification determination unit 17. In order to avoid redundant explanation, the configuration different from that of the first embodiment will be described below.

[0078] (Selection unit) The selection unit 18 selects a representative tissue photo from a plurality of tissue photos based on the deviation of the quantitative value. The deviation of the quantitative value is calculated by the deviation calculation unit 16. Here, although the deviation of the quantitative value was calculated when there were a plurality of candidate representative photographing magnifications in the first embodiment, in the present embodiment, the calculation of the deviation of the quantitative value is always executed. Further, in the first embodiment, the standard deviation of the quantitative value was obtained for each photographing magnification, but in the present embodiment, the deviation is calculated for each field of view.

[0079] Also, in the present embodiment, the input unit 11 acquires a plurality of tissue photos taken at a predetermined photographing magnification for at least two or more fields of view of the metal material. The predetermined photographing magnification is, for example, a known representative photographing magnification.

[0080] (Representative tissue photo determination method) FIG. 4 is a flowchart showing the processing of the representative tissue photograph determination method executed by the representative tissue photograph determination apparatus 10 according to the present embodiment. Briefly, the representative tissue photograph determination method includes an input step of acquiring a plurality of tissue photographs taken at a predetermined magnification for at least two or more fields of view of a metal material, a phase classification step of classifying phases in the plurality of tissue photographs, a quantitative value calculation step of calculating quantitative values of the classified phases, a deviation calculation step of calculating a deviation of the quantitative values, a selection step of selecting a representative tissue photograph from the plurality of tissue photographs based on the deviation, and an output step of outputting the representative tissue photograph, which are performed in this order. Here, when the representative tissue photograph cannot be selected because the sum of the deviations described later exceeds a predetermined value (for example, 0.5), the representative tissue photograph determination method may be executed again after adding the tissue photographs acquired in the input step.

[0081] The input step (step S21) is substantially the same as the input step (step S11) of the first embodiment. However, as described above, the input unit 11 acquires a plurality of tissue photographs taken at a predetermined magnification for at least two or more fields of view of the metal material.

[0082] The phase classification step (step S22) is the same as the phase classification step (step S12) of the first embodiment. Also, the quantitative value calculation step (step S23) is the same as the quantitative value calculation step (step S13) of the first embodiment.

[0083] (Deviation calculation step) The deviation calculation step (step S24) calculates the deviation of the quantitative values in the same manner as the deviation calculation step (step S14) of the first embodiment. However, as described above, it is always executed, and the deviation is calculated for each field of view. The deviation calculation unit 16 calculates the average value N i for the quantitative value i of the tissue photographs of all fields of view for the specified phase. Also, the deviation calculation unit 16 calculates the average value μ ij for the quantitative value i of the tissue photograph of the field of view j for the specified phase. The deviation calculation unit 16 divides the average value μ ij of the quantitative value i of the tissue photograph of the field of view j by the average value N i of the quantitative value i of the tissue photographs of all fields of view to obtain the normalized quantitative value i (μ ij / Ni ) is calculated. Further, the deviation calculation unit 16 calculates the sum of the deviations. The sum of the deviations is calculated as the sum of "the absolute value of the value obtained by subtracting 1 from each normalized quantitative value i", and is represented by the following formula.

[0084]

Equation

[0085] Here, S j is the sum of the deviations in the visual field j. n is the number of adopted quantitative values.

[0086] Here, hereinafter, the normalized quantitative value i is denoted with "normalized" at the beginning. For example, "normalized area ratio" means the area ratio normalized in the above deviation calculation step. Similarly, "normalized Feret diameter" and "normalized roundness" mean the normalized Feret diameter and the normalized roundness, respectively. Further, hereinafter, the deviation calculation step for each shooting magnification as in the first embodiment may be referred to as the first deviation calculation step. Further, hereinafter, the deviation calculation step for each visual field as in the second embodiment may be referred to as the second deviation calculation step.

[0087] (Selection step) The selection step (step S25) is a step in which the selection unit 18 selects a representative tissue photograph from a plurality of tissue photographs based on the deviation of the quantitative value. The selection unit 18 first determines an appropriate visual field (representative visual field) based on the sum of the deviations calculated by the deviation calculation unit 16, and selects the tissue photograph having the determined appropriate visual field as the representative tissue photograph. For example, a visual field with a relatively small sum of deviations is determined to be appropriate. Here, if there is a quantitative value that greatly affects the characteristics of the material, the selection unit 18 may specify the representative visual field based on such a quantitative value instead of the sum of the deviations.

[0088] When the representative tissue photograph is selected, the output step is executed (step S26). The output step is a step in which the output unit 12 outputs the selected representative tissue photograph.

[0089] In this way, by the representative structure photo determination method executed by the representative structure photo determination apparatus 10 according to the present embodiment, a representative structure photo having an appropriate field of view for observing the metallic structure, independent of the observer's subjectivity, is selected. Further, it is possible to eliminate the conventional operation in which the observer compares and selects a plurality of fields of view, and the work efficiency can be improved.

[0090] [Third Embodiment] FIG. 5 is a block diagram of a representative structure photo determination system 1 including the representative structure photo determination apparatus 10 according to the third embodiment. The representative structure photo determination apparatus 10 according to the present embodiment determines a representative magnification and selects a representative structure photo having an appropriate field of view at the determined representative magnification. The representative structure photo determination apparatus 10 according to the present embodiment includes the components of the representative structure photo determination apparatus 10 according to the first and second embodiments, and includes, for example, not only the magnification determination unit 17 but also the selection unit 18. In order to avoid redundant description, the configurations different from those of the first and second embodiments are described below.

[0091] In the present embodiment, the input unit 11, similar to the first embodiment, acquires a plurality of structure photos taken at two or more shooting magnifications for at least two or more fields of view of the metallic material. Further, the deviation calculation unit 16 and the selection unit 18 execute the processes of the second deviation calculation step and the selection step, respectively, for a plurality of structure photos corresponding to the representative magnification determined by the magnification determination unit 17.

[0092] (Representative Structure Photo Determination Method) FIG. 6 is a flowchart showing the processing of the representative structure photo determination method executed by the representative structure photo determination apparatus 10 according to the present embodiment. Generally speaking, the representative structure photo determination method includes an input step of acquiring a plurality of structure photos taken at two or more shooting magnifications for at least two or more fields of view of the metallic material, a phase classification step of classifying phases in the plurality of structure photos, a quantitative value calculation step of calculating quantitative values of the classified phases, a magnification determination step of determining a representative magnification based on the quantitative values, and For a plurality of tissue photographs corresponding to a representative photographing magnification, a deviation calculation step of calculating a deviation of quantitative values, a selection step of selecting a representative tissue photograph from the plurality of tissue photographs corresponding to the representative photographing magnification based on the deviation, and an output step of outputting the representative tissue photograph are performed in this order. Here, when the representative tissue photograph cannot be selected because the sum of the deviations exceeds a predetermined value or the like, the method may be executed again after adding the tissue photograph acquired in the input step.

[0093] The input step (step S31), the phase classification step (step S32), the quantitative value calculation step (step S33), and the magnification determination step (step S34) are the same as the steps of the same names in the first embodiment, respectively. Also, as in the first embodiment, when there are a plurality of candidates for the representative photographing magnification (Yes in step S35), the first deviation calculation step is executed (step S36).

[0094] When one representative photographing magnification is determined (No in step S35), the second deviation calculation step is executed (step S37). The second deviation calculation step is the same as the deviation calculation step (step S24) of the second embodiment. Also, the selection step (step S38) and the output step (step S39) are the same as the steps of the same names in the second embodiment, respectively.

[0095] In this way, by the representative tissue photograph determination method executed by the representative tissue photograph determination device 10 according to the present embodiment, a representative tissue photograph having an appropriate photographing magnification and field of view for observing a metal structure, which is not dependent on the observer's subjectivity, is selected. Also, the conventional operation in which the observer compares and selects a plurality of fields of view while changing the magnification can be made unnecessary, and the work efficiency can be improved.

[0096] (Example) Hereinafter, the effects of the present disclosure will be specifically described based on examples, but the present disclosure is not limited to these examples.

[0097] A DP steel sheet composed of a ferrite phase and a martensite phase was rough ground, then finish ground using diamond paste, and then etched with nital. After that, using an electron microscope, microstructure photos of 10 random fields were taken at magnification ratios of 500 times, 1000 times, 1500 times, and 2000 times. A plurality of taken microstructure photos were obtained (input process). Figure 7 shows a part of the obtained microstructure photos. Here, the phase showing a white contrast is martensite, and the phase showing a black contrast is ferrite.

[0098] Next, for the obtained microstructure photos, using the random forest model, which is one of the above advanced image analysis methods, the ferrite phase and the martensite phase were classified as a binary image (phase classification process). Figure 8 shows the microstructure photo of Figure 7 after the phase classification process. Here, black represents the martensite phase and white represents the ferrite phase.

[0099] Next, based on the obtained binary image, for the martensite phase of each microstructure photo, as quantitative values, the area ratio, Feret diameter, and circularity of each crystal grain were calculated (quantitative value calculation process).

[0100] Next, for the martensite phase of each microstructure photo, a process of counting the number of microstructure photos in which there are two or more crystal grains with an area ratio exceeding 10% was executed for each magnification ratio. Here, four or more fields corresponding to 1 / 3 of the number of microstructure photos at each magnification ratio were targeted. Table 1 shows the magnification ratios meeting the conditions with an ○ mark and those not meeting the conditions with an × mark. Here, in Table 1, Condition A is that "the number of microstructure photos in which there are two or more crystal grains with an area ratio exceeding 10% does not exceed 1 / 3 of the total number of microstructure photos at that magnification ratio obtained in the input process". Also, Condition B is that "the number of microstructure photos in which the crystal grain with the largest area ratio is less than 3% of the entire microstructure photo does not exceed 1 / 3 of the total number of microstructure photos at that magnification ratio obtained in the input process".

[0101]

Table 1

[0102] As shown in the column of Condition A in Table 1, the shooting magnification at 2000 times was determined to be inappropriate, while the shooting magnifications at 500 times, 1000 times, and 1500 times were determined to be appropriate. For example, in FIG. 8, it was confirmed that in the tissue photograph taken at 2000 times, all martensite phases reached the boundary of the screen, and the size of the martensite phase could not be appropriately evaluated.

[0103] Also, for the martensite phase of each tissue photograph, a process of counting the number of tissue photographs in which the crystal grains with the largest area ratio are less than 3% was executed for each shooting magnification. Here, four or more visual fields corresponding to 1 / 3 of the number of tissue photographs at each shooting magnification were targeted. Table 1 indicates the shooting magnifications that meet the conditions with a ○ mark and those that do not meet the conditions with a × mark. As shown in the column of Condition B in Table 1, it was determined that any of the shooting magnifications of 500 times, 1000 times, and 1500 times are appropriate.

[0104] For each quantitative value of each tissue photograph for each shooting magnification, the average value and the standard deviation were calculated (the first deviation calculation step). As shown in Table 1, it was found that the standard deviation of each quantitative value at each shooting magnification is the smallest when shooting at 500 times. From this result, 500 times was determined as the representative shooting magnification (the magnification determination step).

[0105] After the representative shooting magnification was determined, the quantitative values of each tissue photograph taken at the representative shooting magnification were normalized, and the sum of the deviations was calculated (the second deviation calculation step). Table 2 shows the calculated values for each visual field. Since the sum of the deviations in the 5th visual field is the smallest, the tissue photograph having the 5th visual field was selected as the representative tissue photograph (the selection step). Here, the Feret diameter in Table 2 indicates the average Feret diameter per tissue photograph.

[0106]

Table 2

[0107] The representative tissue photograph determined according to the present disclosure is shown as an example in FIG. 9. The two comparative examples in FIG. 9 are tissue photographs that were not determined as representative tissue photographs.

[0108] It can be seen that the representative tissue photograph is appropriate as a representative tissue photograph because it has no relatively large martensite crystal grains and has an average tissue. On the other hand, in the comparative example, relatively large martensite crystal grains and the like can be seen.

[0109] Thus, in this embodiment, the representative tissue photograph of the metal material could be objectively determined without arbitrariness. As a result, the correlation with the material properties can be objectively considered, and efficient material development is expected. Further, in the evaluation of steel materials or metal materials having a plurality of metal phases, since the quantitative values of each phase can be appropriately evaluated, efficient development of steel materials or metal materials having a plurality of metal phases is expected.

[0110] As described above, the representative tissue photograph determination method, the representative tissue photograph determination apparatus, the imaging apparatus, and the program according to the present embodiment can objectively and efficiently determine the representative tissue photograph from a plurality of tissue photographs of the metal material by the above-described configuration and steps.

[0111] Although the embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can easily make various modifications or corrections based on the present disclosure. Therefore, it should be noted that these modifications or corrections are included in the scope of the present disclosure. For example, the functions included in each component or each step can be rearranged so as not to be logically contradictory, and a plurality of components or steps can be combined into one or divided. The embodiment according to the present disclosure can also be realized as a storage medium recording a program executed by a processor included in the apparatus. It should be understood that these are also included in the scope of the present disclosure.

Explanation of Reference Numerals

[0112] 1 Representative tissue photograph determination system 10 Representative tissue photograph determination apparatus 11 Input section 12 Output section 13 Calculation section 14 Phase classification section 15 Quantitative value calculation section 16 Deviation calculation section 17 Magnification determination section 18 Selection section 30 Imaging device

Claims

1. An input step of acquiring a plurality of tissue photographs taken at a predetermined photographing magnification for at least two or more fields of a metal material; A phase classification step of classifying phases in the plurality of tissue photographs; A quantitative value calculation step of calculating a quantitative value of the classified phase; A deviation calculation step of calculating a deviation of the quantitative value; A selection step of selecting a representative tissue photograph from the plurality of tissue photographs based on the deviation; An output step of outputting the representative tissue photograph; comprising: The phase is an area observed with different contrasts, The quantitative value is at least one of an area ratio, an ellipsoid size, a Feret diameter, an average diameter, a circularity, and a number density, and a method for determining a representative tissue photograph.

2. An input step of acquiring a plurality of tissue photographs taken at two or more photographing magnifications for at least two or more fields of a metal material; A phase classification step of classifying phases in the plurality of tissue photographs; A quantitative value calculation step of calculating a quantitative value of the classified phase; A magnification determination step of determining a representative photographing magnification based on the quantitative value; A deviation calculation step of calculating a deviation of the quantitative value for the plurality of tissue photographs corresponding to the representative photographing magnification; A selection step of selecting a representative tissue photograph from the plurality of tissue photographs corresponding to the representative photographing magnification based on the deviation; An output step of outputting the representative tissue photograph; comprising: The phase is an area observed with different contrasts, The quantitative value is at least one of an area ratio, an ellipsoid size, a Feret diameter, an average diameter, a circularity, and a number density, and a method for determining a representative tissue photograph.

3. An input unit that acquires a plurality of tissue photographs taken at a predetermined photographing magnification for at least two or more fields of a metal material; A phase classification unit that classifies phases in the plurality of tissue photographs; A quantitative value calculation unit that calculates a quantitative value of the classified phase; A deviation calculation unit that calculates a deviation of the quantitative value; A selection unit that selects a representative tissue photograph from the plurality of tissue photographs based on the deviation; An output unit that outputs the representative tissue photograph; comprising: The phase is an area observed with different contrasts, The quantitative value is at least one of an area ratio, an ellipsoid size, a Feret diameter, an average diameter, a circularity, and a number density, and a representative tissue photograph determination device.

4. An input unit that acquires a plurality of tissue photographs taken at two or more photographing magnifications for at least two or more fields of a metal material; A phase classification unit that classifies phases in the plurality of tissue photographs; A quantitative value calculation unit that calculates a quantitative value of the classified phase; A magnification determination unit that determines a representative shooting magnification based on the quantitative value; A deviation calculation unit that calculates the deviation of the quantitative value for the plurality of tissue photographs corresponding to the representative shooting magnification; A selection unit that selects a representative tissue photograph from the plurality of tissue photographs corresponding to the representative shooting magnification based on the deviation; An output unit that outputs the representative tissue photograph; Comprising; The phase is a region observed with different contrasts, The quantitative value is at least one of an area ratio, an ellipsoid size, a Feret diameter, an average diameter, a circularity, and a number density, a representative tissue photograph determination device.

5. A photographing device that photographs the plurality of tissue photographs acquired by the representative tissue photograph determination device according to claim 3 or 4.

6. The photographing device according to claim 5, wherein the photographing device is an optical microscope or a scanning electron microscope.

7. A computer, An input unit that acquires a plurality of tissue photographs taken at a predetermined shooting magnification for at least two or more fields of a metal material; A phase classification unit that classifies the phases in the plurality of tissue photographs; A quantitative value calculation unit that calculates the quantitative value of the classified phase; A deviation calculation unit that calculates the deviation of the quantitative value; A selection unit that selects a representative tissue photograph from the plurality of tissue photographs based on the deviation; An output unit that outputs the representative tissue photograph; Function as, The phase is a region observed with different contrasts, The quantitative value is at least one of an area ratio, an ellipsoid size, a Feret diameter, an average diameter, a circularity, and a number density, a program.

8. A computer, An input unit that acquires a plurality of tissue photographs taken at two or more shooting magnifications for at least two or more fields of a metal material; A phase classification unit that classifies the phases in the plurality of tissue photographs; A quantitative value calculation unit that calculates the quantitative value of the classified phase; A magnification determination unit that determines a representative shooting magnification based on the quantitative value; A deviation calculation unit that calculates the deviation of the quantitative value for the plurality of tissue photographs corresponding to the representative shooting magnification; A selection unit that selects a representative tissue photograph from the plurality of tissue photographs corresponding to the representative shooting magnification based on the deviation; An output unit that outputs the representative tissue photograph; Function as, The phase is a region observed with different contrasts, The quantitative value is at least one of an area ratio, an ellipsoid size, a Feret diameter, an average diameter, a circularity, and a number density, a program.

Images