Method and device for calculating uniformity and porosity of mixed materials based on graph features

Abstract

The present application relates to a method for calculating the uniformity and porosity of a mixed material based on graph features, comprising: performing a threshold segmentation on a CT image of the mixed material to obtain a solid particle region; determining the position of each solid particle in the solid particle region; determining multiple Delaunay triangles based on the position of each solid particle; determining graph features based on the side lengths of the multiple Delaunay triangles; determining the uniformity of the mixed material based on the graph features; performing a secondary threshold segmentation on the CT image of the mixed material to obtain a polymer material main region, the polymer material main region including regions where multiple pores are located; and determining the porosity of the mixed material based on the number of pixels in the regions where the multiple pores are located and the number of pixels in the polymer material main region. The method for calculating the uniformity and porosity of a mixed material based on graph features of the present application can automatically and accurately obtain the uniformity and porosity of the mixed material, and has a relatively fast calculation speed.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular, to a method and device for calculating the uniformity and porosity of mixed materials based on image features. Background Art

[0002] The uniformity and porosity of mixed materials are particularly important for evaluating the mixing quality of powder blends. Powder mixing is the process of mixing two or more components in a dry state or in the presence of a small amount of liquid, using external forces to continuously reduce their heterogeneity. The two or more components can be different substances or the same substance with different physical properties, such as different moisture content, particle diameter, color, etc.

[0003] Because the internal structure of a mixed material system cannot be observed with the naked eye, CT images must be processed using computer methods to objectively determine the uniformity and porosity of the mixed material system. Existing methods for determining the uniformity and porosity of mixed material systems suffer from complex calculations and large errors. Summary of the Invention

[0004] In order to overcome at least one deficiency in the prior art, embodiments of the present application provide a method and apparatus for calculating the uniformity and porosity of a mixed material based on graph features.

[0005] In a first aspect, a method for calculating the uniformity and porosity of a mixed material based on graph features is provided, comprising:

[0006] Perform a threshold segmentation on the CT image of the mixed material to obtain the solid particle area; the mixed material is a mixture of polymer material and multiple solid particles, and the solid particle area is the area where the multiple solid particles are located;

[0007] determining a position of each solid particle in the solid particle region;

[0008] Determine multiple Delaunay triangles based on the position of each solid particle;

[0009] Determine the graph features based on the side lengths of multiple Delaunay triangles;

[0010] Determine the homogeneity of the mixed material based on the graph characteristics;

[0011] Performing secondary threshold segmentation on the CT image of the mixed material to obtain the main area of the polymer material, which includes the areas where multiple pores are located;

[0012] Determining the number of pixels in the region where the plurality of pores are located and the number of pixels in the region where the polymer material is located;

[0013] The porosity of the mixed material is determined according to the number of pixels in the region where the multiple pores are located and the number of pixels in the region where the polymer material is located.

[0014] In one embodiment, the graph features include the mean and variance of the side lengths of all Delaunay triangles.

[0015] In one embodiment, determining the uniformity of the mixed material based on the graph features includes:

[0016] The larger the mean, the more dispersed the solid particles are; the smaller the mean, the denser the solid particles are.

[0017] The larger the variance, the more uneven the distribution of solid particles; the smaller the variance, the more uniform the distribution of solid particles.

[0018] In one embodiment, the porosity is the ratio of the number of pixels in the region where the multiple pores are located to the number of pixels in the region where the polymer material is located.

[0019] In one embodiment, the method further comprises:

[0020] The CT image of the mixed material is preprocessed to remove redundant areas of the CT image of the mixed material.

[0021] In a second aspect, a device for calculating the uniformity and porosity of a mixed material based on graph features is provided, comprising:

[0022] The solid particle region acquisition module is used to perform a threshold segmentation on the CT image of the mixed material to obtain the solid particle region; the mixed material is a mixture of a polymer material and multiple solid particles, and the solid particle region is the area where the multiple solid particles are located;

[0023] a solid particle position determination module, used to determine the position of each solid particle in the solid particle area;

[0024] A triangle determination module, for determining a plurality of Delaunay triangles based on the position of each solid particle;

[0025] A graph feature determination module, configured to determine graph features based on the side lengths of multiple Delaunay triangles;

[0026] a uniformity determination module for determining the uniformity of the mixed material based on the graph characteristics;

[0027] A main region determination module is used to perform secondary threshold segmentation on the CT image of the mixed material to obtain the main region of the polymer material, which includes the region where multiple pores are located;

[0028] A pixel number determination module is used to determine the number of pixels in the region where the multiple pores are located and the number of pixels in the main region of the polymer material;

[0029] The porosity determination module is used to determine the porosity of the mixed material according to the number of pixels in the area where the multiple pores are located and the number of pixels in the main area of the polymer material.

[0030] In one embodiment, the graph features include the mean and variance of the side lengths of all Delaunay triangles.

[0031] In one embodiment, the uniformity determination module is further configured to:

[0032] The larger the mean, the more dispersed the solid particles are; the smaller the mean, the denser the solid particles are.

[0033] The larger the variance, the more uneven the distribution of solid particles; the smaller the variance, the more uniform the distribution of solid particles.

[0034] In one embodiment, the porosity is the ratio of the number of pixels in the region where the multiple pores are located to the number of pixels in the region where the polymer material is located.

[0035] In one embodiment, the apparatus further includes a preprocessing module for preprocessing the CT image of the mixed material to remove redundant areas of the CT image of the mixed material.

[0036] Compared with the existing technology, the present application has the following beneficial effects: the method and device for calculating the uniformity and porosity of mixed materials based on graph features of the present application can realize automatic and accurate acquisition of the uniformity and porosity of mixed materials, and the calculation speed is relatively fast. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present application may be better understood by referring to the following description in conjunction with the accompanying drawings, which together with the following detailed description are incorporated into and form a part of this specification. In the drawings:

[0038] Figure 1 A flowchart of a method for calculating uniformity and porosity of mixed materials based on graph features according to an embodiment of the present application is shown;

[0039] Figure 2 The following is a structural block diagram of a device for calculating uniformity and porosity of mixed materials based on graph features according to an embodiment of the present application;

[0040] Figure 3 A schematic diagram showing the uniformity of a mixed material obtained by a method for calculating the uniformity and porosity of a mixed material based on graph features according to an embodiment of the present application is shown;

[0041] Figure 4 A schematic diagram of the porosity of a mixed material obtained by the method for calculating the uniformity and porosity of a mixed material based on graph features according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0042] Exemplary embodiments of the present application are described below with reference to the accompanying drawings. For the sake of clarity and conciseness, not all features of actual embodiments are described in this specification. However, it should be understood that in the process of developing any such actual embodiment, many implementation-specific decisions may be made to achieve the developer's specific goals, and these decisions may vary from one implementation to another.

[0043] It is also necessary to explain here that, in order to avoid obscuring the present application due to unnecessary details, the accompanying drawings only show the device structure closely related to the solution according to the present application, while other details that are not closely related to the present application are omitted.

[0044] It should be understood that the present application is not limited to the described embodiments due to the following description with reference to the accompanying drawings. In this document, where feasible, the embodiments may be combined with each other, features between different embodiments may be replaced or borrowed, and one or more features may be omitted in one embodiment.

[0045] Figure 1 A method for calculating the uniformity and porosity of mixed materials based on graph features according to an embodiment of the present application is shown.

[0046] The method begins with step S110, performing a threshold segmentation on the CT image of the mixed material to obtain a solid particle area; the mixed material is a mixture of a polymer material and a plurality of solid particles, and the solid particle area is the area where the plurality of solid particles are located; in this step, it is necessary to first obtain an internal image of the mixed material formed by the polymer material and the plurality of solid particles, and the CT image of the mixed material can be obtained by CT scanning; then, the CT image is threshold segmented, and the white spots appearing on the CT image are solid particles. The white spots are segmented from the CT image by threshold segmentation to form a solid particle area; the fixed value used in the threshold segmentation process can be adjusted according to the actual application process, as long as the solid particle area can be obtained, and is not specifically limited here.

[0047] Then, in step S120, the position of each solid particle in the solid particle area is determined; in this step, the position of each solid particle can be obtained by using a flux identification method.

[0048] Then, in step S130, a plurality of Delaunay triangles are determined based on the position of each solid particle;

[0049] Then, in step S140, a graph feature is determined based on the side lengths of the multiple Delaunay triangles. In one implementation, the mean and variance of the side lengths of all Delaunay triangles are calculated and used as the graph feature. In other implementations, the skewness and kurtosis of the side lengths of all Delaunay triangles may be calculated and used as the graph feature.

[0050] Then, in step S150, the uniformity of the mixed material is determined based on the graph features. In one implementation, a larger mean indicates a more dispersed distribution of solid particles; a smaller mean indicates a denser distribution of solid particles; a larger variance indicates a more uneven distribution of solid particles; and a smaller variance indicates a more uniform distribution of solid particles. In other implementations, the uniformity of the mixed material can also be determined based on the skewness and kurtosis of the side lengths of all Delaunay triangles.

[0051] Then, in step S160, a secondary threshold segmentation is performed on the CT image of the mixed material to obtain the main polymer material region, which includes the multiple pore regions. In this step, the main polymer material region obtained after the secondary threshold segmentation includes the multiple pore regions. The fixed value used in the threshold segmentation process can be adjusted according to the actual application process, as long as the main polymer material region and the pore region can be obtained, and is not specifically limited here.

[0052] Then, in step S170, the number of pixels in the region where the plurality of pores are located and the number of pixels in the region where the polymer material is located are determined;

[0053] Then, in step S180, the porosity of the mixed material is determined based on the number of pixels in the region where the plurality of pores are located and the number of pixels in the main region of the polymer material. In one implementation, the porosity of the mixed material is obtained by calculating the ratio of the number of pixels in the region where the plurality of pores are located to the number of pixels in the main region of the polymer material.

[0054] In one embodiment, the method further comprises:

[0055] The CT image of the mixed material is preprocessed to remove redundant areas of the CT image of the mixed material.

[0056] In this embodiment, when other information irrelevant to the main image of the mixed material exists in the CT image of the mixed material, such as camera parameter information, the CT image can be cropped to remove redundant areas containing other information irrelevant to the main image of the mixed material, and obtain an area of interest for subsequent processing steps; here, the cropping process can, for example, remove 65 pixel values on the left side of the image and remove 15 pixel values on the bottom side of the image.

[0057] Based on the same inventive concept as the method for calculating the uniformity and porosity of mixed materials based on graph features, this embodiment also provides a corresponding device for calculating the uniformity and porosity of mixed materials based on graph features. Figure 2 The following is a block diagram of a device for calculating the uniformity and porosity of a mixed material based on graph features according to an embodiment of the present application. The device includes:

[0058] The solid particle region acquisition module 210 is used to perform a threshold segmentation on the CT image of the mixed material to obtain the solid particle region; the mixed material is a mixture of a polymer material and a plurality of solid particles, and the solid particle region is the region where the plurality of solid particles are located; here, it is necessary to first obtain the internal image of the mixed material formed by the polymer material and the plurality of solid particles, and the CT image of the mixed material can be obtained by CT scanning; then, the CT image is threshold segmented, and the white dots that appear on the CT image are solid particles. The white dots are segmented from the CT image by threshold segmentation to form a solid particle region; the fixed value used in the threshold segmentation process can be adjusted according to the actual application process, as long as the acquisition of the solid particle region can be achieved, and no specific limitation is made here.

[0059] The solid particle position determination module 220 is used to determine the position of each solid particle in the solid particle area; here, the position of each solid particle can be obtained by using a flux identification method.

[0060] A triangle determination module 230 is configured to determine a plurality of Delaunay triangles based on the position of each solid particle;

[0061] The graph feature determination module 240 is configured to determine graph features based on the side lengths of multiple Delaunay triangles. In one implementation, the mean and variance of the side lengths of all Delaunay triangles are calculated and used as the graph features. In other implementations, the skewness and kurtosis of the side lengths of all Delaunay triangles may be calculated and used as the graph features.

[0062] Uniformity determination module 250 is configured to determine the uniformity of the mixed material based on the graph features. In one implementation, a larger mean indicates a more dispersed distribution of solid particles; a smaller mean indicates a denser distribution of solid particles; a larger variance indicates a more uneven distribution of solid particles; and a smaller variance indicates a more uniform distribution of solid particles. In other implementations, the uniformity of the mixed material can also be determined based on the skewness and kurtosis of the side lengths of all Delaunay triangles.

[0063] The main region determination module 260 is configured to perform secondary threshold segmentation on the CT image of the mixed material to obtain the main region of the polymer material. The main region of the polymer material includes multiple pore regions. The main region of the polymer material obtained after secondary threshold segmentation includes multiple pore regions. The fixed value used in the threshold segmentation process can be adjusted according to the actual application process, as long as the main region of the polymer material and the pore region can be obtained, and is not specifically limited here.

[0064] A pixel number determination module 270 is used to determine the number of pixels in the region where the plurality of pores are located and the number of pixels in the region where the polymer material is located;

[0065] Porosity determination module 280 is configured to determine the porosity of the mixed material based on the number of pixels in the region where the multiple pores are located and the number of pixels in the main polymer material region. In one implementation, the porosity of the mixed material is determined by calculating the ratio of the number of pixels in the region where the multiple pores are located to the number of pixels in the main polymer material region.

[0066] The method for calculating the uniformity and porosity of mixed materials based on graph features of the embodiment of the present application is used. Based on the GUI visualization interface in MATLAB App Designer, the uniformity and porosity of the image are automatically calculated after loading the CT image of the mixed material, and an intuitive display of the fully automatically processed image is provided, such as Figure 3 and Figure 4 As shown, Figure 3 A schematic diagram of the uniformity of a mixed material obtained by the method for calculating the uniformity and porosity of a mixed material based on graph features according to an embodiment of the present application is shown, wherein the green circle represents the area where the solid particles are located. Figure 4 A schematic diagram of the porosity of a mixed material obtained by the method for calculating the uniformity and porosity of a mixed material based on graph features according to an embodiment of the present application is shown, wherein the red area represents the pore area; industrial practitioners can select images and data for saving based on the results analyzed by the software and their own needs, which is convenient, fast and easy to use; it can make industrial practitioners more efficient in daily diagnosis of material mixing conditions and greatly reduce errors.

[0067] After experimental analysis, the following results can be achieved: 1. Standard deviation of uniformity calculation is 5%; 2. Standard deviation of porosity calculation is 5%; 3. Software operation time: Depending on the specific specifications of the image file and the different combinations of selected algorithm parameters, the operation time of single image analysis is (0.001-15) seconds.

[0068] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0069] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0070] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0071] The above descriptions are merely examples of various embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any modifications or substitutions that can be readily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for calculating the uniformity and porosity of mixed materials based on graph features, characterized in that: include: Performing a threshold segmentation on the CT image of the mixed material to obtain a solid particle region; the mixed material is a mixture of a polymer material and a plurality of solid particles, and the solid particle region is the region where the plurality of solid particles are located; determining a position of each of the solid particles in the solid particle region; determining a plurality of Delaunay triangles based on the position of each of the solid particles; Determining a graph feature according to side lengths of the plurality of Delaunay triangles; determining the uniformity of the mixed material based on the graph characteristics; Performing secondary threshold segmentation on the CT image of the mixed material to obtain a main region of the polymer material, wherein the main region of the polymer material includes regions where a plurality of pores are located; Determining the number of pixels in the region where the plurality of pores are located and the number of pixels in the region where the polymer material is located; The porosity of the mixed material is determined according to the number of pixels in the region where the multiple pores are located and the number of pixels in the region where the polymer material is located.

2. The method according to claim 1, wherein in, The graph features include the mean and variance of the side lengths of all the Delaunay triangles.

3. The method according to claim 2, wherein in, Determining the uniformity of the mixed material according to the graph features includes: The larger the mean value is, the more dispersed the solid particles are distributed; the smaller the mean value is, the denser the solid particles are distributed; The larger the variance is, the more uneven the solid particles are distributed; and the smaller the variance is, the more uniform the solid particles are distributed.

4. The method according to claim 1, wherein The porosity is the ratio of the number of pixels in the region where the multiple pores are located to the number of pixels in the main region of the polymer material.

5. The method according to claim 1, wherein The method further comprises: The CT image of the mixed material is preprocessed to remove redundant areas of the CT image of the mixed material.

6. A device for calculating the uniformity and porosity of mixed materials based on graph features, characterized in that: include: A solid particle region acquisition module is used to perform a threshold segmentation on the CT image of the mixed material to obtain a solid particle region; the mixed material is a mixture of a polymer material and a plurality of solid particles, and the solid particle region is the region where the plurality of solid particles are located; a solid particle position determination module, configured to determine the position of each of the solid particles in the solid particle area; a triangle determination module, configured to determine a plurality of Delaunay triangles based on the position of each of the solid particles; A graph feature determination module, configured to determine graph features according to the side lengths of the plurality of Delaunay triangles; a uniformity determination module, configured to determine the uniformity of the mixed material according to the graph features; a main region determination module, configured to perform secondary threshold segmentation on the CT image of the mixed material to obtain a main region of the polymer material, wherein the main region of the polymer material includes regions where a plurality of pores are located; a pixel number determination module, configured to determine the number of pixels in the region where the plurality of pores are located and the number of pixels in the region where the polymer material is located; The porosity determination module is used to determine the porosity of the mixed material according to the number of pixels in the area where the multiple pores are located and the number of pixels in the main area of the polymer material.

7. The device according to claim 6, characterized in that The graph features include the mean and variance of the side lengths of all the Delaunay triangles.

8. The device according to claim 7, wherein The uniformity determination module is further configured to: The larger the mean value is, the more dispersed the solid particles are distributed; the smaller the mean value is, the denser the solid particles are distributed; The larger the variance is, the more uneven the solid particles are distributed; and the smaller the variance is, the more uniform the solid particles are distributed.

9. The device according to claim 6, wherein The porosity is the ratio of the number of pixels in the region where the multiple pores are located to the number of pixels in the main region of the polymer material.

10. The device according to claim 6, wherein The device further includes a preprocessing module for preprocessing the CT image of the mixed material to remove redundant areas of the CT image of the mixed material.

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