Image management system, image management device, image management method, and image management program

Abstract

The invention provides an image management system, an image management device, an image management method, and an image management program capable of more appropriately associating and managing evaluation results of a mother sample and a child sample. An image management system (control device (20)) includes: a first storage unit (storage unit (23)) that stores a first image of a first sample related to quality information; a second storage unit (storage unit (23)) that stores evaluation results of a second sample cut from the first sample; and a third storage unit (storage unit (23)) that stores information on a cut position of the first sample or the second sample and a feature amount at a position selected from the first image, and the image management system associates the evaluation results of the first image and the second sample, the information on the cut position, and the feature amount.

Description

Technical Field

[0001] The present invention relates to an image management system, an image management device, an image management method and an image management program. Background Art

[0002] In recent years, composite materials have attracted much attention. Not only the material itself, but also the fine internal structure of the material has a great influence on the mechanical properties of the parts. For example, in the case of CFRP (Carbon Fiber Reinforced Plastics), the mechanical strength is greatly affected by the fiber orientation and fiber density, because the carbon fiber has a three-dimensional structure depending on the weaving method and orientation of the carbon fiber.

[0003] Not limited to composite blanks, in the initial stage of resin development, in order to produce a large number of test samples (mother samples) of simple shapes such as dumbbell-shaped test pieces and flat plates with different materials and molding conditions and evaluate the internal state of the molded products, it is generally cut from the test sample to a size that can be analyzed. In addition, using the cut samples (sub-samples), the state of the surface and the inside of the test piece is confirmed by fiber quantity / fiber length measurement after ash measurement, μCT or optical microscope, ultrasonic diagnostic device, SEM. In addition, as an evaluation of material properties, tensile strength tests, Charpy impact tests, bending tests, electromagnetic wave shielding performance tests, or reliability tests based on repeated deformation, chemical coating, etc. are implemented.

[0004] However, there is a problem that it is difficult to manage which sample is cut from which part and in which direction. In particular, it is difficult to distinguish defects such as fiber state, voids, cracks, etc., which are the internal state of the test sample, from the appearance, and it is difficult to manage.

[0005] In contrast, Patent Document 1 discloses the following structure: after taking an aerial view of the entire sample as an image of the parent sample (parent image), a specific part of the sample is enlarged and photographed and saved as a child image, and the parent image and the child image are associated with each other and saved and displayed.

[0006] Patent Document 1: Japanese Patent No. 3366352

[0007] However, in Patent Document 1, it is known from which position of the parent sample the sample was cut, but no information is associated with why the sample was cut at that position. Therefore, it is difficult to appropriately associate and manage the evaluation results of the parent sample and the child sample. Summary of the invention

[0008] An object of the present invention is to more appropriately associate and manage evaluation results of a parent sample and a child sample.

[0009] In order to solve the above problems, the image management system of the present invention includes:

[0010] A first storage unit storing a first image of a first sample related to quality information;

[0011] a second storage unit storing an evaluation result of a second sample cut out from the first sample; and

[0012] a third storage unit for storing information on a cutout position of the first sample or the second sample and a feature value at a position selected from the first image;

[0013] The image management system associates the first image, the evaluation result of the second sample, the information of the cutout position, and the feature amount.

[0014] In addition, the image management device of the present invention includes:

[0015] A first storage unit storing a first image of a first sample related to quality information;

[0016] a second storage unit storing an evaluation result of a second sample cut out from the first sample; and

[0017] a third storage unit for storing information on a cutout position of the first sample or the second sample and a feature value at a position selected from the first image;

[0018] The image management device associates the first image, the evaluation result of the second sample, the information of the cutout position, and the feature amount.

[0019] In addition, the image management method of the present invention includes:

[0020] the step of storing a first image of a first sample associated with quality information;

[0021] a step of storing an evaluation result of a second sample cut out from the first sample;

[0022] A step of storing information of a cutout position of the first sample or the second sample and a feature value at a position selected from the first image; and

[0023] A step of associating the first image, the evaluation result of the second sample, the information of the cut-out position, and the feature amount.

[0024] In addition, the image management program of the present invention causes the computer of the image management device to function as a control unit.

[0025] The control unit:

[0026] causing the first storage unit to store a first image of a first sample associated with the quality information,

[0027] causing the second storage unit to store the evaluation result of the second sample cut out from the first sample,

[0028] The third storage unit stores information on the cutout position of the first sample or the second sample and a feature value at the position selected from the first image,

[0029] The first image, the evaluation result of the second sample, the information of the cut-out position, and the feature amount are associated with each other.

[0030] According to the present invention, it is possible to more appropriately associate and manage the evaluation results of the parent sample and the child sample. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a schematic diagram showing the entire image of the X-ray Talbot imaging device and the object storage unit.

[0032] Figure 2 This is a block diagram showing a schematic configuration of an X-ray imaging system.

[0033] Figure 3 This is a block diagram showing a schematic configuration of a storage unit.

[0034] Figure 4 This is an example of the user information database 23g.

[0035] Figure 5 It is a flowchart which shows the association process.

[0036] Fig. 6A This is an example of the image analysis result display screen.

[0037] Figure 6B This is an example of the image analysis result display screen.

[0038] Figure 7 This is an example of the area selection screen display.

[0039] Figure 8 This is an example of the display of the cut area registration screen.

[0040] Fig. 9 This is an example of the display of the cut area registration screen.

[0041] Fig.10 This is a display example of the evaluation result registration screen.

[0042] Fig.11 This is a display example of the evaluation result display screen.

[0043] Fig.12 This is an example of the analysis result display screen.

[0044] Fig.13 This is a flowchart showing information association processing related to area selection.

[0045] Fig.14 Flowchart showing the automatic detection process of the cutting position.

[0046] Fig.15 This is an example showing the correspondence between a parent sample image and a sub-sample image.

[0047] Fig.16 This is an example of pattern matching between a parent sample image and a child sample image.

[0048] Fig.17 : is a flowchart showing the cutting impact determination process.

[0049] Fig.18 This is an example of a difference comparison between a parent sample image and a sub-sample image.

[0050] Fig.19 : is a flowchart showing the similar sample information display process.

[0051] Fig. 20 This is an example of similarity calculation.

[0052] Fig.21 This is an example of a display similar to an image display screen. DETAILED DESCRIPTION

[0053] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, various technically preferred limitations are added to the embodiments described below in order to implement the present invention, but the technical scope of the present invention is not limited to the following embodiments and the illustrated examples.

[0054] (First Embodiment)

[0055] In this embodiment, an X-ray imaging system is described. In the X-ray imaging system, a first image capable of identifying specified quality information, which is obtained by imaging a first sample (parent sample, object H) by an X-ray Talbot imaging device 1, an evaluation result of a second sample (sub-sample) cut out from the first sample, information on a cutting position of the second sample in the first sample, and a feature value at a position corresponding to the cutting position of the first image are stored, and the first image, the evaluation result of the second sample, the information on the cutting position, and the feature value are associated with each other.

[0056] Various processes including the correlation process are performed by the control device 20 connected to the X-ray Talbot imaging device 1 .

[0057] [About the subject]

[0058] The subject H in this embodiment is composed of a composite blank (also called a composite material) and is used as a structural component of various products represented by electrical / electronic / home appliance parts, parabolic antennas, bathtubs, floor materials, roofing materials, etc., in addition to space / aircraft relations, automobiles, ships, fishing rods, etc.

[0059] As such composite blanks, for example, CFRP (Carbon-Fiber-Reinforced Plastics), CFRTP (Carbon Fiber Reinforced Thermo Plastics), GFRP (Glass-Fiber-Reinforced Plastics) represented by FRP (Fiber-Reinforced Plastics) using carbon fiber and glass fiber as reinforcing fibers, and CMC (Ceramic Matrix Composites) using ceramic fiber as reinforcing material are known. In addition, in a broad sense, composite blanks composed of multiple types of wood, such as plywood, may also be included. In addition, composite materials composed of no fibers, such as MMC (Metal Matrix Composites) concrete, reinforced concrete, etc. may also be included.

[0060] In addition, the resin used in the composite material is, for example, general-purpose plastics, engineering plastics, and super engineering plastics, but is not limited thereto. The resin is used as a resin composite material to which fillers having micro-size or nano-size structures are added in order to provide specified properties such as additional strength, and is often used as a plastic molded product. The filler includes organic materials, inorganic materials, magnetic materials, and metal materials. For example, when strength and rigidity are required for plastic molded products, a composite material is sometimes used in which PPS, POM, PA, PC, PP, etc. are used as a resin, and aromatic polyamide fibers, talc, cellulose fibers, etc. are used as fillers. In addition, when the plastic molded product is a plastic, a composite material is sometimes used in which nylon is used as a resin, and strontium ferrite, samarium cobalt, etc. are used as a filler.

[0061] [About the X-ray Talbot device]

[0062] In the present embodiment, as the X-ray Talbot imaging device 1, a device using a Talbot / Laue interferometer is used, and the Talbot / Laue interferometer has a line source grid (also called a multi-grid, a multi-slit, a G0 grid, etc.) 12. In addition, an X-ray Talbot imaging device using a Talbot interferometer can also be used, which does not have the line source grid 12 but only has a first grid (also called a G1 grid) 14 and a second grid (also called a G2 grid) 15.

[0063] Figure 1 1 is a schematic diagram showing an overall image of the X-ray Talbot imaging device 1 .

[0064] The X-ray Talbot imaging device 1 of this embodiment includes an X-ray generator 11 , the source grid 12 , a subject table 13 , the first grid 14 , the second grid 15 , an X-ray detector 16 , a support column 17 , and a base unit 18 .

[0065] According to such an X-ray Talbot imaging device 1, by imaging a moiré image Mo of a subject H located at a predetermined position relative to the subject stage 13 using a method based on the principle of the fringe scanning method, or analyzing the moiré image Mo using the Fourier transform method, at least three types of images (two-dimensional images) (referred to as reconstructed images) can be reconstructed. That is, there are three types of images: an absorption image (the same as a normal X-ray absorption image) obtained by imaging the average component of the moiré fringes in the moiré image Mo, a differential phase image obtained by imaging the phase information of the moiré fringes, and a small-angle scattering image obtained by imaging the visibility of the moiré fringes. In addition, it is also possible to generate more types of images by resynthesizing these three types of reconstructed images.

[0066] In addition, the fringe scanning method refers to a method of reconstructing a high-precision reconstructed image by moving one of the multiple grids one by one along the slit period direction according to 1 / M (M is a positive integer, M>2 for absorption image, M>3 for differential phase image and small-angle scattering image) of the grid and taking M shots to obtain the moiré image Mo.

[0067] The Fourier transform method is a method of capturing a moiré image Mo using an X-ray Talbot imaging device in the presence of a subject, and reconstructing and generating an image such as a differential phase image by Fourier transforming the moiré image Mo in image processing.

[0068] The structure of other parts in the X-ray Talbot imaging device 1 of this embodiment is described. In this embodiment, it is a so-called vertical type, and the X-ray generator 11, the source grid 12, the object table 13, the first grid 14, the second grid 15, and the X-ray detector 16 are arranged in this order in the z direction which is the gravity direction. That is, in this embodiment, the z direction is the irradiation direction of the X-ray from the X-ray generator 11.

[0069] The X-ray generator 11 includes, for example, a Kulig X-ray source or a rotating anode X-ray source widely used in medical fields as an X-ray source 11a. In addition, other X-ray sources may be used. The X-ray generator 11 of this embodiment emits X-rays in a cone beam from a focal point. That is, Figure 1 As shown, the X-ray irradiation axis Ca that coincides with the z direction is the central axis, and the X-rays are irradiated in a manner that becomes wider as the distance from the X-ray generator 11 increases (ie, the X-ray irradiation range).

[0070] Furthermore, in the present embodiment, a line source grid 12 is provided below the X-ray generator 11. At this time, in order to prevent the vibration of the X-ray generator 11 generated by the rotation of the anode of the X-ray source 11a, etc. from being transmitted to the line source grid 12, in the present embodiment, the line source grid 12 is not mounted on the X-ray generator 11, but is mounted on a fixing member 12a mounted on a base portion 18 provided on a support column 17.

[0071] Furthermore, in this embodiment, a buffer member 17 a is provided between the X-ray generator 11 and the support 17 to prevent the vibration of the X-ray generator 11 from propagating to other parts of the X-ray Talbot imaging device 1 such as the support 17 (or to reduce the propagated vibration).

[0072] In this embodiment, in addition to the line source grid 12, the above-mentioned fixed component 12a is also equipped with a filter (also called an additional filter) 112 for changing the line quality of the X-rays passing through the line source grid 12, an irradiation field aperture 113 for narrowing the irradiation field of the irradiated X-rays, and an irradiation field lamp 114 for irradiating the subject with visible light instead of X-rays for positioning before irradiating X-rays.

[0073] The line source grid 12, the filter 112, and the irradiation field aperture 113 do not necessarily need to be provided in this order. In addition, in the present embodiment, a first cover unit 120 is disposed around the line source grid 12 and the like for protecting them.

[0074] In addition, in this embodiment, the controller 19 (see Figure 1) is composed of a computer connected to a bus, such as a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), an input / output interface, etc., which are not shown in the figure. In addition, the controller 19 may be configured as a dedicated control device instead of a general-purpose computer in the present embodiment. In addition, in the controller 19, although not shown in the figure, appropriate units and devices such as an input unit including an operating unit, an output unit, a storage unit, and a communication unit are provided.

[0075] The output unit includes a display unit (not shown) that displays information necessary for performing various operations of the X-ray Talbot imaging device 1 and a generated reconstructed image.

[0076] The controller 19 performs overall control of the X-ray Talbot imaging device 1. That is, for example, the controller 19 is connected to the X-ray generator 11 and can set the tube voltage, tube current, irradiation time, etc. for the X-ray source 11a. In addition, for example, the controller 19 can also be configured to relay the transmission and reception of signals and data between the X-ray detector 16 and the external image processing device 2, etc.

[0077] That is, the controller 19 in the present embodiment functions as a control unit that performs a series of imaging for acquiring a plurality of moiré images Mo (one moiré image in the case of the Fourier transform method) required for generating a reconstructed image of the subject H.

[0078] [About the control device]

[0079] In this embodiment, a general-purpose computer device (control PC) is used as the control device 20 that executes various processes. However, this is not limited to this, and each process can be executed by placing part of the functions of the control device 20 on a network and transmitting and receiving data through communication.

[0080] like Figure 2 As shown, the control device 20 is configured to include a CPU 21 (Central Processing Unit), a RAM 22 (Random Access Memory), a storage unit 23, an input unit 24, a display unit 25, a communication unit 26, and the like.

[0081] The CPU 21 reads various programs such as the system program and the processing program stored in the storage unit 23 and develops them in the RAM 22, and executes various processes including the related process described below according to the developed programs. That is, the CPU 21 functions as a control unit in the entire X-ray imaging system.

[0082] CPU21 causes the first storage unit described later to store the first image (mother image) of the first sample (mother sample), causes the second storage unit described later to store the evaluation result of the second sample (sub-sample) cut out from the first sample, causes the third storage unit described later to store the information of the cutting position of the second sample in the first sample and the feature value at the position corresponding to the cutting position of the first image, and associates the first image with the evaluation result of the second sample based on the feature value and the information of the cutting position.

[0083] The CPU 21 also functions as an acquisition unit that acquires proficiency information of a user who inputs information related to selection of an area described later.

[0084] The RAM 22 functions as a work area for temporarily storing various programs executable by the CPU 21 , input or output data, parameters, and the like read from the storage unit 23 in various processes executed and controlled by the CPU 21 .

[0085] The storage unit 23 is composed of a HDD (Hard Disk Drive), a semiconductor nonvolatile memory, etc. In addition to storing the above-mentioned various programs, the storage unit 23 also has various processing such as the processing described below. Figure 3 The database shown.

[0086] The storage unit 23 functions as a first storage unit that stores a first image (mother image) obtained by imaging a first sample (mother sample) and in which predetermined quality information can be identified.

[0087] Furthermore, the storage unit 23 functions as a second storage unit that stores the evaluation results of the second sample (sub-sample) cut out from the first sample.

[0088] Furthermore, the storage unit 23 functions as a third storage unit that stores information on the cutout position of the second sample in the first sample and a feature amount at a position corresponding to the cutout position of the first image.

[0089] Here, specifically, regarding the database (DB) stored in the storage unit 23, use Figure 3 Provide explanation.

[0090] The mother sample information database 23a is a database for storing information related to the photographed object H (mother sample). For example, the mother sample information database 23a stores information such as sample ID, material, molding conditions, and metal mold. As information on materials, there is the resin that becomes the mother material, and in the case of composite materials, there is the name of the filler and the content of the filler, and as mixing conditions of the resin that becomes the mother material and the filler, there are the screw shape of the mixer, back pressure, resin temperature, etc. As molding conditions, in the case of injection molding, there is information related to the temperature, pressure, and molding time during molding, such as the resin temperature in the screw, back pressure, injection speed, metal mold temperature, and cooling temperature. As information on the metal mold, there is design drawing, gate position, gate diameter, runner shape, shape of the molded product (flat plate shape, dumbbell shape), size of the molded product (information related to width, height, thickness), etc.

[0091] The parent image database 23 b is a database that stores image data of the subject H. For example, the parent image database 23 b stores Talbot images (parent images) captured by using the X-ray Talbot imaging device 1 .

[0092] The parent sample-child sample intermediate table 23 c is a database that associates the parent sample information database 23 a with the child sample information database 23 d using sample IDs.

[0093] The subsample information database 23d is a database for storing information related to the subsamples cut out from the subject H. For example, the subsample information database 23d stores sample ID, cutting position information, feature values ​​of the selected position (area, range), selection know-how (reason for subsample selection, expected evaluation results, know-how inputter, etc.). Here, the feature value of the selected position refers to a value extracted from the parent image and reflects quality information, such as the average value and deviation of the pixels in the selected area. As another example, after binarizing the selected area of ​​the parent image, the area of ​​the area above a certain threshold is set as the feature value of the area with a large amount of fibers, or the contour of the area above a certain threshold is extracted by combining binarization and contour extraction, and the value obtained by counting the number of areas surrounded by the contour is set as the number of areas after fiber coagulation. In addition, information in the database related to the reason for subsample selection (reason for cutting out the second sample) is set as reason information. In addition, information in the database related to selected know-how (reasons for subsample selection, expected evaluation results, know-how inputters, etc.) is set as information related to selection of the region.

[0094] The sub-image-sub-sample intermediate table 23 e is a database that associates the sub-sample information database 23 d with the sub-sample evaluation result database 23 f.

[0095] The sub-sample evaluation result database 23f is a database for storing the measurement results of the sub-samples. For example, the sub-sample evaluation result database 23f stores the sub-sample evaluation results and the Talbot image (sub-image) captured by the X-ray Talbot imaging device 1. In addition, the sub-image is not limited to the Talbot image, and may be an optical image, an ultrasonic diagnostic image, a SEM (Scanning Electron Microscope) image, a μCT image, etc.

[0096] Furthermore, the evaluation of the material properties of the sub-samples may be a tensile strength test, a Charpy impact test, a bending test, or a reliability test based on repeated deformation, chemical coating, or the like.

[0097] The user information database 23g is a database that stores information related to users who use the control device 20. For example, Figure 4 As shown, the user information database 23g stores user names, proficiency (user proficiency information), business years, etc. In addition, the user proficiency information refers to information corresponding to the user's business experience. Figure 4 As shown, by inputting the number of years of experience in the business of materials, molding, and physical property evaluation, the proficiency information is set to consider those with more than 5 years of experience in the business of materials as proficient users. In addition, it is also possible to clearly prepare categories such as beginners, intermediates, advanced, novice, and proficient, and classify them according to each user.

[0098] As described above, the first image (parent image), the evaluation results of the second sample (sub-sample), the information of the cutting position of the second sample in the first sample (parent sample), and the feature value at the position (selected position) corresponding to the cutting position of the first image are associated.

[0099] In addition, the above-mentioned various databases are not only stored in the storage unit 23 of the control device 20, but may also be provided on a network.

[0100] Here, the quality information will be described.

[0101] The quality information is related to the quality of the photographed object H, and includes fiber orientation, voids, cracks, foreign matter, density unevenness, fiber unevenness, etc. Specifically, the density of resin and fiber, the presence or absence of foreign matter such as metal in the resin, the presence or absence of voids between the resin and the fiber, the presence or absence of voids in the resin, the presence or absence of fiber bundles formed by a plurality of fibers, the orientation direction / degree of orientation of the fiber, the density of the fiber or filler (e.g., talc) (unevenness in the amount of fiber), welding (occurrence position, shape), the flow direction of the resin (flow direction near the gate, the end of the gate, etc.), micro cracks (cracks with a width of μm, etc.) generated by tensile tests / thermal cycle tests / chemical erosion, etc., and micro bubbles in the adhesive layer (detection of bubbles at the μm level), etc. are listed.

[0102] The orientation information refers to the orientation and density of fibers included in the object H. For example, a portion with low orientation and a small amount of fibers is a void, and the orientation information also includes voids and cracks.

[0103] That is, the quality information includes the orientation information.

[0104] The input unit 24 is configured to include a keyboard and a pointing device such as a mouse, and the keyboard includes cursor keys, numeric input keys, and various function keys. The input unit 24 outputs a pressing signal of a key pressed on the keyboard and an operation signal from the mouse as an input signal to the CPU 21. The CPU 21 can execute various processes based on the operation signal from the input unit 24.

[0105] The input unit 24 functions as an information input unit for inputting information related to the selection of the above-mentioned area.

[0106] The display unit 25 is configured to include a monitor such as a CRT (Cathode Ray Tube) or an LCD (Liquid Crystal Display). The display unit 25 displays various screens in accordance with instructions of a display signal input from the CPU 21. In addition, when a touch panel is used as the display unit 25, the display unit 25 also has a function as the input unit 24.

[0107] The communication unit 26 includes a communication interface and communicates with an external device on the network.

[0108] The external devices on the network include a controller 19 of the X-ray Talbot imaging device 1 , and the controller 19 and the control device 20 are connected to each other via a communication unit 26 so as to be communicable.

[0109] The control device 20 (CPU 21 ) performs various processes such as association processing using the above-mentioned various databases. However, these processes are executed based on the programs stored in the storage unit 23 .

[0110] [About association processing]

[0111] The following describes the association processing performed in the control device 20. The association processing is a processing for establishing association between the first image (parent image), the evaluation result of the second sample (sub-sample), the information of the cut-out position of the second sample in the first sample, and the feature value at the position corresponding to the cut-out position of the first image.

[0112] First, the CPU 21 registers information of the first sample (parent sample) input by the user via the input unit 24 in the parent sample information database 23 a (step S1 ).

[0113] Next, the CPU 21 controls the controller 19 to control the X-ray Talbot imaging device 1 to perform Talbot imaging of the first sample and obtain a Talbot image (first image) of the parent sample (step S2 ).

[0114] Next, the CPU 21 registers the Talbot image of the parent sample in the parent image database 23b (step S3). When the Talbot image is registered in the parent image database 23b, the parent sample information database 23a is associated with the parent image database 23b.

[0115] Next, the CPU 21 analyzes the Talbot image (step S4 ).

[0116] Specifically, as shown in the display area D described later, the color is distinguished according to the signal value of each pixel of the Talbot image. In addition, for easy judgment, all pixels below the threshold value are white.

[0117] In addition, it is preferable to set the grouping area according to the shape of the sample to be cut. For example, in the case of measuring the ash content (using the Figure 8 In the case of the cut area registration screen shown in the figure), it is preferred to cut out a 10 mm square, so the following mosaic processing is performed: the image equivalent to the 10 mm square is grouped and the representative feature value of the area is derived. For example, in the case of a Talbot image area of ​​50 mm × 50 mm, it is displayed as a 5 × 5 area.

[0118] When the sample cut out is in the shape of a dumbbell (dumbbell-shaped test piece) (using the Fig. 9 In the case of the cut-out area registration screen shown in FIG. 1 ), if the width of the representative dumbbell-shaped test piece (for example, the width of the short side) is 8 mm, the area for grouping is changed to 8 mm square.

[0119] This allows the user to determine which position of the Talbot image should be focused on, and also allows the position to be cut out to be clearly indicated.

[0120] Next, the CPU 21 causes the display unit 25 to display the Talbot image and the image analysis result on the display. Fig. 6A The image analysis result display screen shown (step S5) is shown. That is, the parent sample is evaluated using the Talbot image (first image). Fig. 6A The image analysis result display screen shown is used to perform the area selection described later.

[0121] Here, yes Fig. 6A The image analysis result display screen shown is explained.

[0122] The display area A is an area for displaying the sample ID selected by the user.

[0123] The display area B is an area where information on the sample corresponding to the sample ID displayed in the display area A is displayed.

[0124] Display area C is an area where the Talbot image is displayed.

[0125] Display area D is an area where image analysis results are displayed.

[0126] also, Figure 6B This is a screen showing past evaluation results. Users can also refer to Figure 6B The past evaluation result display screen shown is used to select an area to be described later.

[0127] Next, CPU21 Figure 7 In the region selection screen shown, the second sample cutting position selection result, the selection reason, and the second sample measurement prediction result input by the user via the input unit 24 are acquired (step S6).

[0128] Here, yes Figure 7 The area selection screen shown is explained below.

[0129] The display area E is an area where the user selects an area (cut-out area) for cutting out a sub-sample from a parent sample. A specific method of registering a cut-out area will be described below.

[0130] For example, when using Figure 8 In the cut area registration screen shown, when a 10 mm square sub-sample for ash content measurement is cut from a 50 mm flat plate as the parent sample, guide lines are displayed at 10 mm intervals on the Talbot image. One of the divided areas is selected and the registration button is pressed to register the cut position information. Figure 8 In the cut area registration screen shown, the Talbot image can be displayed directly, or Fig. 6AThe CPU 21 displays the feature quantity of each segment corresponding to the size of the sample cut out, as shown in D. Furthermore, the CPU 21 stores the cut out shape, the upper left XY coordinates of the cut out position, and the cut out size as the cut out position information together with the sub-sample ID in the DB (sub-sample information database 23d).

[0131] In addition, for example, when using Fig. 9 In the cut area registration screen shown, when the master sample is a flat plate and a dumbbell-shaped sample is cut for a tensile test (the width of the short side of the dumbbell-shaped test piece is 10 mm), guide lines are displayed at 10 mm intervals on the Talbot image, and the user can specify the cutting position by moving the cursor on the image to the predetermined dumbbell shape to be cut and pressing the registration button. Then, the CPU 21 stores the dumbbell shape as the cutting shape, the upper left XY coordinates of the cutting position, and the angle information of the cutting direction as the cutting position information in the DB (sub-sample information database 23d) together with the ID of the sub-sample.

[0132] In addition, although the region is cut out, it is also possible to further perform image processing on the selected region without cutting out in step S7 described later.

[0133] Display area F is an area for displaying information of the parent sample.

[0134] Display area G is an area where feature quantities extracted from the image portion of the cutout area selected in display area E, the user's selection reason, and the expected quality are displayed. Figure 7 In the example of , the average value and deviation of the pixels are displayed as feature quantities. In addition, the user can input (or select) technical tips such as selection reasons (signal value, unevenness), expectations (fiber amount, defibrination), etc.

[0135] In addition, Figure 7 In the example, information input is performed by selecting from the options prepared in advance using the input unit 24. In this way, it is easy to analyze the corresponding relationship between the options and the proficiency of the know-how inputter described later. For example, there is a tendency for intermediate users to select option A, but there is a tendency for advanced users to select option B.

[0136] The display area H is an area for displaying user information.

[0137] Furthermore, when a cutout region of a subsample is selected in the display region E, the CPU 21 performs image analysis on the cutout region to extract feature quantities, and displays the feature quantities in the display region G.

[0138] When the selection of the cutout region is completed, the CPU 21 registers the information such as the cutout position information, the feature value, the selected know-how, and the know-how inputter in the sub-sample information database 23d. The sub-sample information database 23d is associated with the parent sample information database 23a via the parent sample-sub-sample intermediate table 23c. In addition, the user information database 23g is associated as the know-how inputter's information.

[0139] In addition, when associating the sub-sample information database 23d with the parent sample information database 23a, the CPU 21 may control whether to associate information related to the selection of the region (selection know-how; sub-sample selection reason, evaluation result prediction, know-how inputter, etc.) with the parent sample information database 23a based on the proficiency information included in the user information database 23g. Figure 4 When the proficiency is shown as intermediate or above, the information related to the selection of the region is associated with the parent sample information database 23a, but when the proficiency is beginner, the association is not established. Alternatively, the information to be associated may be weighted according to the proficiency. This process is described later as the process of associating the information related to the selection of the region.

[0140] Next, the sub-sample cutting device is used to cut the cutting area selected by the user from the main sample as a sub-sample. The CPU 21 controls the controller 19 to control the X-ray Talbot imaging device 1 to perform imaging of the sub-sample (step S7). In addition, in the present embodiment, the cutting position B is set to perform Talbot imaging, imaging using an optical microscope, ash content measurement, evaluation of the fiber content based on the weight change before and after the resin is evaporated or dissolved, and evaluation of the distribution of the fiber length of the residual fiber or filler. In addition, the evaluation method of the sub-sample is not limited to this.

[0141] Next, CPU21 Fig.10 In the evaluation result registration screen shown, image data and fiber amount data input by the user via the input unit 24 are acquired (step S8).

[0142] Display area I is a selection area where the user selects an area to cut a sub-sample from a parent sample.

[0143] Display area J is a data (image data, fiber amount data) registration area. In this embodiment, the parent image is a Talbot image, but the registered child image is not limited to the Talbot image, and may also be an optical image, a SEM (Scanning Electron Microscope) image, a μCT image, etc.

[0144] The display area K is for displaying the selection reason and the expected area inputted in the area selection screen.

[0145] When the input is completed, the subsample evaluation result database 23f is registered. The subsample evaluation result database 23f is associated with the subsample information database 23d via the subimage-subsample intermediate table 23e.

[0146] Next, the CPU 21 causes the display unit 25 to display Fig.11 The evaluation result display screen (step S9) is shown. In this embodiment, in order to cut out position B, Talbot photography, photography using an optical microscope, and ash content measurement are performed, and position B is selected, and the Talbot image / optical image / fiber amount data of the subsample, the selection reason entered in the area selection screen, and the expectation are displayed.

[0147] Next, the CPU 21 causes the display unit 25 to display Fig.12 The analysis result display screen (step S10) shown in FIG. 1 can display, for example, a graph with the feature quantity (statistic) extracted from the Talbot image as the horizontal axis and the evaluation result of the sub-sample as the vertical axis.

[0148] Thus, the feature quantity can be compared with the evaluation result, and the meaning of the evaluation result can be easily understood. For example, the value of the pixel of the parent image (Talbot image) and the corresponding evaluation result of the tensile strength can be confirmed. In addition, it is possible to visually determine which feature quantity may be related to the tensile strength.

[0149] In addition, if Fig.12 As shown in the center figure of the lower section, the first and second components of the principal component analysis can be selected and displayed as the feature quantities of the Talbot image. This is an example of setting the first and second principal components as the vertical and horizontal axes, and displaying the results of the tensile strength associated with each sample as a bubble chart. In this way, in addition to simple feature quantities such as average values ​​and deviations, it is easy to visually grasp the presence or absence of correlation based on the feature quantities extracted by the inductive method (principal component analysis), and it is easy to understand the meaning of the evaluation results.

[0150] In addition, if Fig.12 The lower left figure in the lower section shows the results of tensile strength tests on 9 samples of weldable dumbbells with different molding conditions and material conditions. The Talbot image (an image after enlarging the welded part) of the parent sample of each sample is drawn, and the results of the tensile strength test are associated. In this way, the relationship between the tensile strength and the state of the welded part can be visually grasped, and it is easy to determine what feature quantity should be introduced.

[0151] [Regarding information association processing related to area selection]

[0152] As mentioned above, if Figure 7 After the input of the area selection screen shown in FIG. 1 is completed, the sub-sample information database 23d is associated with the parent sample information database 23a via the parent sample-sub-sample intermediate table 23c. Figure 4 The information on the proficiency (proficiency information) shown in FIG. 1 controls whether to associate the information on the selection of the region with the parent sample information database 23a (processing of associating the information on the selection of the region). Fig.13 , the information association processing related to the selection of the area is explained.

[0153] First, the CPU 21 obtains the Figure 7 The information of the inputter (user) of the area selection screen shown is displayed (step S21).

[0154] Next, the CPU 21 determines whether the proficiency of the input user is, for example, above the intermediate level (step S22). Here, whether the user is above the intermediate level is used as the judgment criterion, but the judgment is not limited to this, and whether the user is above the advanced level may also be used as the judgment criterion. In step S22, if the user is above the intermediate level (step S22; yes), the process proceeds to step S23. In addition, in step S22, if the user is less than the intermediate level (step S22; no), the process of associating the information related to the selection of the region ends, and the information related to the selection of the region is not associated with the parent sample information database 23a.

[0155] Next, the CPU 21 associates the information related to the selection of the region with the parent sample information database 23a (step S23). Then, the process of associating the information related to the selection of the region ends.

[0156] In this way, it is possible to confirm the selection know-how of highly skilled people. Specifically, when other users confirm past test results, if they open Figure 6B , Fig.11 The evaluation result display screen shown shows the reasons for sub-sample selection and sub-sample evaluation prediction of the highly skilled inputter. Therefore, even a beginner can extract an accurate sample by confirming the technical know-how of the highly skilled inputter.

[0157] (Second Embodiment)

[0158] In the first embodiment described above, the second sample is cut out in step S7, but the cutting position is input manually by the user, which may cause a deviation in the input position, input errors, and time-consuming input.

[0159] Therefore, in the second embodiment, the cutting position is automatically detected. Fig.14, the automatic detection process of the cutting position is explained.

[0160] First, the X-ray Talbot imaging device 1 is used to perform Talbot imaging on the parent sample (first sample). The CPU 21 of the control device 20 obtains Fig.15 The parent sample image as shown in the upper section (step S21).

[0161] Next, a sub-sample (second sample) is physically cut from the parent sample.

[0162] Next, the sub-sample is subjected to Talbot imaging using the X-ray Talbot imaging device 1. The CPU 21 of the control device 20 acquires Fig.15 The sub-sample image as shown in the lower row (step S22).

[0163] Next, if Fig.16 As shown, CPU 21 performs pattern matching on the image of the parent sample and the image of the sub-sample to infer the position of the sub-sample in the parent sample (step S23), for example, using a general position search method such as opencv.

[0164] Next, the CPU 21 registers the estimated position information as the cut-out position in the subsample information database 23 d (step S24 ).

[0165] Thus, the cutting position is not input, but estimated after cutting and registered in the database, thereby preventing the input position from being misplaced, inputting errors, and time-consuming input.

[0166] (Third Embodiment)

[0167] In the first and second embodiments described above, subsamples are physically cut out, but damage caused by cutting (processing the sample) is known.

[0168] Therefore, in the third embodiment, the influence of the sub-sample cutting is understood by comparing the parent image before the sub-sample cutting with the sub-image captured after the sub-sample is physically cut. Fig. 20 , the cutting impact determination process is explained.

[0169] First, the X-ray Talbot imaging device 1 is used to perform Talbot imaging on the parent sample (first sample). The CPU 21 of the control device 20 obtains Fig.18 The mother sample image as shown in the upper section (step S31).

[0170] Next, a sub-sample (second sample) is physically cut from the parent sample.

[0171] Next, the sub-sample is subjected to Talbot imaging using the X-ray Talbot imaging device 1. The CPU 21 of the control device 20 acquires Fig.18 The sub-sample image is as shown in the lower row (step S32).

[0172] Next, the CPU 21 of the control device 20 extracts an image of the cutout position of the image of the mother sample ( Fig.18 The CPU 21 of the control device 20 generates Fig.18 A differential image like the one on the right (step S33).

[0173] Next, the CPU 21 determines the affected part caused by the cutting from the differential image (step S34). Fig.18 In the example of the right differential image, the CPU 21 determines that there are two cracks on the right side of the sub-sample.

[0174] Alternatively, the signal value of the difference image may be subjected to calculation processing (such as addition as absolute value) to obtain a quantitative amount of change as an indicator of damage caused by processing.

[0175] (Fourth Embodiment)

[0176] When deciding the cutting position, people with sufficient cutting experience are less likely to be confused about the cutting position, but people with little experience may be confused.

[0177] Therefore, in the fourth embodiment, when determining the cutting position of the sample, past insights are used. That is, from the images of the mother sample taken in the past and the sub-images cut out from the mother image, examples similar to the mother image of the sample to be targeted are searched, and information such as the cutting position, the reason for cutting, and the evaluation results of the sub-sample are provided. Fig.19 , the display processing of similar sample information is explained.

[0178] First, the X-ray Talbot imaging device 1 is used to perform Talbot imaging on the parent sample (first sample). The CPU 21 of the control device 20 obtains Fig. 20 A new mother sample image as shown on the right (step S41).

[0179] Next, the CPU 21 calculates the similarity between the new parent sample image and the parent sample image or the sub-sample image (image of the second sample) captured in the past (step S42 ).

[0180] Next, the CPU 21 extracts a parent sample image or a child sample image having a high similarity based on the calculated similarity (step S43 ).

[0181] Specifically, the CPU 21 extracts only the image with the highest similarity, or extracts a plurality of images (for example, three images) in ascending order of the highest similarity.

[0182] Next, the CPU 21 acquires information associated with the extracted parent sample image or child sample image from the storage unit 23 (step S44 ).

[0183] Next, CPU 21 Fig.21 The parent sample with high similarity or the parent sample of the child sample with high similarity displays information of the cut-out position, the reason for the cut-out, the evaluation result performed on the child sample, etc. on the display unit 25 (step S45).

[0184] Specifically, similarity calculation methods include a method using a histogram (using the histogram similarity function of openCv), a method using template matching, and a method combining AKAZE features with kNN (k-nearest neighbor algorithm).

[0185] In addition, as image processing before similarity calculation, it is preferable to perform zero-filling processing on the background. Specifically, contour extraction is performed, and processing of zero-filling is performed on the signal outside the contour of the sample.

[0186] In addition, since the small-angle scattering image and the orientation image have signal value dependence based on thickness, when comparing objects with different thicknesses, the levels of absolute values ​​do not match and the similarity decreases. When it is desired to reduce the influence of the different thicknesses of the objects for comparison, it is preferable to use (A) an image obtained by dividing the small-angle scattering image by the absorption image, (B) an eccentricity Ecc image, or (C) an image obtained by dividing the Amp image by the Ave image.

[0187] In addition, the Amp image refers to an image representing the amplitude value (signal value amp) of each pixel, and the Ave image refers to an image representing the average value (signal value ave) of each pixel (Japanese Patent Gazette No. 2021-089195). In addition, the eccentricity Ecc image refers to an image representing the eccentricity ecc of each pixel. When the signal values ​​amp and ave obtained from the orientation image are used to calculate σ1=ave+amp (equivalent to the maximum value of the small-angle signal value) and σ2=ave-amp (equivalent to the minimum value of the small-angle signal value), the following formula is used to calculate the eccentricity ecc.

[0188] [Mathematical formula 1]

[0189]

[0190] (Effect)

[0191] As described above, the image management system (control device 20) includes: a first storage unit (storage unit 23) for storing a first image of a first sample related to quality information; a second storage unit (storage unit 23) for storing an evaluation result of a second sample cut out from the first sample; and a third storage unit (storage unit 23) for storing information on a cutting position of the first sample or the second sample and a feature value at a position selected from the first image. The image management system (control device 20) associates the first image, the evaluation result of the second sample, the information on the cutting position, and the feature value, so that the evaluation results of the parent sample and the child sample can be more appropriately associated and managed.

[0192] In addition, the image management system (control device 20) includes a control unit (CPU21), which causes the first storage unit (storage unit 23) to store the first image of the first sample, causes the second storage unit (storage unit 23) to store the evaluation result of the second sample cut out from the first sample, and causes the third storage unit (storage unit 23) to store the information of the cutting position of the first sample or the second sample and the feature value at the position selected from the first image, and establishes association between the first image, the evaluation result of the second sample, the information of the cutting position, and the feature value, so that the evaluation results of the parent sample and the child sample can be more appropriately associated and managed.

[0193] Furthermore, since the evaluation method for the quality information of the first image is different from the evaluation method for the second sample, the evaluation results can be managed without limiting the evaluation method.

[0194] In addition, since the first image is a Talbot image, information such as fiber unevenness, defects, and voids can be obtained, and the quality of the cut sample, that is, the orientation anisotropy and the amount of voids can be determined based on the image.

[0195] In addition, the second image obtained by photographing the second sample is photographed using the same shooting method as the first image, and the control unit (CPU21) determines the cutting position of the second sample by analyzing the first image and the second image. This can prevent the situation where, when cutting the sample, it is not known which sample the sample is cut from and the cutting direction, as well as the offset of the input position, input errors, and input troubles caused by the user manually entering the cutting position.

[0196] In addition, the second image obtained by photographing the second sample is photographed using the same shooting method as the first image. The control unit (CPU21) compares the image at the position selected from the first image with the second image to determine the changes before and after the second sample is cut, thereby being able to confirm the damage caused by processing the sample.

[0197] Furthermore, the control unit (CPU 21) associates the reason information on the reason for cutting out the second sample with the cutting position information of the second sample in the first sample, so that past knowledge can be fully utilized when determining the cutting position of the sample.

[0198] In addition, the control unit (CPU21) obtains an image similar to the first sample from the first storage unit (storage unit 23) and the second storage unit (storage unit 23), obtains information associated with the obtained image from the third storage unit (storage unit 23), and displays the obtained information on the display unit (display unit 25), so that past insights can be fully utilized when determining the cutting position of the sample.

[0199] In addition, the image management device (control device 20) includes: a first storage unit (storage unit 23) for storing a first image of a first sample related to quality information; a second storage unit (storage unit 23) for storing an evaluation result of a second sample cut out from the first sample; and a third storage unit (storage unit 23) for storing information on a cutting position of the first sample or the second sample and a feature value at a position selected from the first image. The image management device (control device 20) associates the first image, the evaluation result of the second sample, the information on the cutting position, and the feature value, so that the evaluation results of the parent sample and the child sample can be more appropriately associated and managed.

[0200] In addition, the image management method includes: a step of storing a first image of a first sample related to quality information; a step of storing an evaluation result of a second sample cut out from the first sample; a step of storing information on a cutting position of the first sample or the second sample and a feature value at a position selected from the first image; and a step of associating the first image, the evaluation result of the second sample, the information on the cutting position, and the feature value, so that the evaluation results of the parent sample and the child sample can be more appropriately associated and managed.

[0201] In addition, the program causes the computer of the image management device (control device 20) to function as a control unit (CPU21), and the control unit (CPU21) causes the first storage unit (storage unit 23) to store the first image of the first sample related to quality information, causes the second storage unit (storage unit 23) to store the evaluation result of the second sample cut out from the first sample, and causes the third storage unit (storage unit 23) to store information on the cutting position of the first sample or the second sample and a feature value at the position selected from the first image, and associates the first image, the evaluation result of the second sample, the information on the cutting position, and the feature value, so that the evaluation results of the parent sample and the child sample can be more appropriately associated and managed.

[0202] As mentioned above, although embodiment of this invention was demonstrated, the description in this embodiment mentioned above is a preferable example of this invention, and is not limited to this.

[0203] For example, the first to fourth embodiments may be appropriately combined.

[0204] In the above description, the first image is a Talbot image, but the present invention is not limited thereto and may be, for example, an image captured using an optical microscope or an inspection device capable of visually displaying cracks or the like.

[0205] In addition, the position (coordinates) of the cut-out region may be based on a certain point of the first sample or a certain point of the second sample.

[0206] In addition, in the fourth embodiment, the CPU 21 Fig.21 The mother sample with high similarity and the mother sample of the sub-sample with high similarity are shown, and the information of the cutting position, the reason for cutting, the evaluation results implemented on the sub-sample, etc. are displayed on the display unit 25. The user cuts the sub-sample based on this information, but it can also be not displayed on the display unit 25, and the cutting position, etc. can be automatically set for the cutting device.

[0207] In addition, in the above description, an example of using a hard disk, a semiconductor nonvolatile memory, etc. as a computer-readable medium of the program involved in the present invention is disclosed, but the present invention is not limited to this example. As other computer-readable media, a removable recording medium such as a CD-ROM can be applied.

[0208] Furthermore, the detailed structure and detailed operation of each device can be appropriately changed without departing from the gist of the invention.

[0209] Industrial Applicability

[0210] The present disclosure can be used for an image management system, an image management device, an image management method, and an image management program.

[0211] Explanation of the reference numerals: 1…X-ray Talbot imaging device; 11…X-ray generating device; 19…controller; 2…image processing device; 20…control device; 21…CPU (control unit); 22…RAM; 23…storage unit; 23a…parent sample information database; 23b…parent image database; 23c…parent sample-sub-sample intermediate table; 23d…sub-sample information database; 23e…sub-image-sub-sample intermediate table; 23f…sub-sample evaluation result database; 23g…user information database; 24…input unit (information input unit); 25…display unit; 26…communication unit; H…object to be photographed (object to be inspected).

Claims

1. An image management system, wherein: include: A first storage unit storing a first image of a first sample related to quality information; a second storage unit for storing an evaluation result of a second sample cut out from the first sample; as well as a third storage unit for storing information on a cutout position of the first sample or the second sample and a feature value at a position selected from the first image, The image management system associates the first image, the evaluation result of the second sample, the information of the cutout position, and the feature amount.

2. The image management system according to claim 1, wherein: The image management system comprises a control unit, The control unit: causing the first storage unit to store a first image of a first sample, causing the second storage unit to store an evaluation result of a second sample cut out from the first sample, causing the third storage unit to store information on a cutout position of the first sample or the second sample and a feature value at a position selected from the first image, The first image, the evaluation result of the second sample, the information of the cut-out position, and the feature amount are associated with each other.

3. The image management system according to claim 1, wherein: The quality information includes orientation information of fibers in the first sample.

4. The image management system according to claim 1 or 2, wherein: An evaluation method for the quality information of the first image is different from an evaluation method for the second sample.

5. The image management system according to claim 1 or 2, wherein: The first image is a Talbot image.

6. The image management system according to claim 2, wherein: The second image obtained by photographing the second sample is obtained by using the same photographing method as the first image. The control unit determines a cutting position of the second sample by analyzing the first image and the second image.

7. The image management system according to claim 2, wherein: The second image obtained by photographing the second sample is obtained by using the same photographing method as the first image. The control unit determines a change before and after the second sample is cut out by comparing an image at a position selected from the first image with the second image.

8. The image management system according to claim 2, wherein: The control unit associates reason information related to a reason for cutting out the second sample with cutting position information of the second sample in the first sample.

9. The image management system according to claim 8, wherein: The control unit acquires an image similar to the first sample from the first storage unit and the second storage unit, acquires information associated with the acquired image from the third storage unit, and causes the display unit to display the acquired information.

10. An image management device, wherein: include: A first storage unit storing a first image of a first sample related to quality information; a second storage unit for storing an evaluation result of a second sample cut out from the first sample; as well as a third storage unit for storing information on a cutout position of the first sample or the second sample and a feature value at a position selected from the first image, The image management device associates the first image, the evaluation result of the second sample, the information of the cutout position, and the feature amount.

11. An image management method, wherein: include: the step of storing a first image of a first sample associated with quality information; a step of storing an evaluation result of a second sample cut out from the first sample; A step of storing information of a cutting position of the first sample or the second sample and a feature amount at a position selected from the first image; as well as A step of associating the first image, the evaluation result of the second sample, the information of the cut-out position, and the feature amount.

12. An image management program for causing a computer of an image management device to function as a control unit, wherein: The control unit: causing the first storage unit to store a first image of a first sample associated with the quality information, causing a second storage unit to store an evaluation result of a second sample cut out from the first sample, causing a third storage unit to store information on a cutout position of the first sample or the second sample and a feature value at a position selected from the first image, The first image, the evaluation result of the second sample, the information of the cut-out position, and the feature amount are associated with each other.

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