Soil aggregate MWD calculation method and device based on Micro-CT image

Abstract

The invention provides a soil aggregate MWD calculation method and device based on a Micro-CT image. The method comprises the following steps: obtaining a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample; extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image; and obtaining an average weight diameter result of the in-situ soil column sample based on the aggregate image. According to the Micro-CT image-based soil aggregate MWD calculation method and device provided by the invention, the soil matrix gray level image can be obtained according to the original gray level image of the in-situ soil column sample, then the aggregate image is generated according to the soil matrix gray level image, and finally the average weight diameter result of the in-situ soil column sample is obtained according to the aggregate image. On the basis of not destroying the soil structure, the average weight diameter structure parameter of the soil aggregate can be directly calculated by adopting an image processing technology.

Description

Technical Field

[0001] The present invention relates to the field of agricultural engineering technology, and in particular to a method and device for calculating MWD of soil aggregates based on Micro-CT images. Background Art

[0002] The mean weight-diameter (MWD) of soil aggregates is an important parameter for measuring soil structure, but it is currently difficult to calculate it in situ without destroying it. The traditional soil aggregate screening method not only destroys the original structure of the sample, but is also inefficient and time-consuming.

[0003] X-ray micro-computed tomography (micro-CT) is an emerging high-resolution, non-destructive three-dimensional imaging technology that can scan and obtain images of undisturbed soil aggregates. It has become the mainstream method for studying soil aggregates. However, domestic and foreign scholars mostly focus on the boundaries and internal structures of aggregates, and there are few studies on the MWD of aggregates in micro-CT scanning images. Some scholars have developed a non-contact virtual sieve that uses computer image processing and analysis for virtual sieving, which can obtain the same results as actual sieving. However, it is essentially still sieving and cannot achieve in-situ aggregate separation and MWD calculation.

[0004] In addition, the visualization and qualitative and quantitative analysis of aggregates currently mainly rely on basic image processing and display software produced by CT instrument manufacturers, or open source software such as Image J, while professional software such as Avizo is less used. Summary of the invention

[0005] The present invention provides a soil aggregate MWD calculation method and device based on Micro-CT images, which are used to solve the technical problem in the prior art that the original structure of the sample will be destroyed during the calculation of the average weight diameter of the soil aggregate.

[0006] The present invention provides a method for calculating the MWD of soil aggregates based on Micro-CT images, comprising the following steps.

[0007] Obtaining a soil matrix grayscale image based on the original grayscale image of the in-situ soil column sample; Extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; An average weight diameter result of the in-situ soil column sample is obtained based on the aggregate image.

[0008] In some embodiments, the step of acquiring a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample comprises: Acquire an original grayscale image of the in-situ soil column sample based on a scanning device; Determine an undisturbed area image based on the original grayscale image; Pre-processing the undisturbed area image to obtain a grayscale image to be processed; Perform image segmentation on the grayscale image to be processed to obtain the soil matrix grayscale image.

[0009] In some embodiments, the pre-treatment includes one or more of the following: Image posture correction; Remove ring artifact interference; Remove radiation hardening interference; Image filtering.

[0010] In some embodiments, performing image segmentation on the grayscale image to be processed to obtain the soil matrix grayscale image includes: Acquire image attribute data of the grayscale image to be processed; Determine a segmentation algorithm based on the image attribute data, and obtain a soil background image from the grayscale image to be processed based on the segmentation algorithm; The soil background image is used as a mask, and the intersection is taken with the original grayscale image to obtain the soil matrix grayscale image.

[0011] In some embodiments, extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, comprises: Determine the brightness threshold based on an image threshold segmentation method; Extracting a seed image from the soil matrix grayscale image based on the brightness threshold; Determining individual images of aggregates from the seed image based on the morphological watershed algorithm; The aggregate image is obtained by marking all the individual images of the aggregate.

[0012] In some embodiments, obtaining the average weight diameter result of the in-situ soil column sample based on the aggregate image includes: determining an equivalent diameter of each agglomerate and a volume fraction of each agglomerate based on the agglomerate image; The average weight diameter result of the in-situ soil column sample is determined based on the equivalent diameter of each aggregate and the volume fraction of each aggregate.

[0013] The present invention also provides a soil aggregate MWD calculation device based on Micro-CT images, comprising the following modules: A first acquisition module is used to acquire a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample; A first extraction module is used to extract a seed image from the soil matrix grayscale image based on a brightness threshold, and generate an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; The second acquisition module is used to acquire the average weight diameter result of the in-situ soil column sample based on the aggregate image.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the soil aggregate MWD calculation method based on Micro-CT images as described in any one of the above is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described soil aggregate MWD calculation methods based on Micro-CT images.

[0016] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned soil aggregate MWD calculation methods based on Micro-CT images.

[0017] The soil aggregate MWD calculation method and device based on Micro-CT images provided by the present invention can obtain a soil matrix grayscale image according to the original grayscale image of the in-situ soil column sample, then generate an aggregate image according to the soil matrix grayscale image, and finally obtain the average weight diameter result of the in-situ soil column sample according to the aggregate image. The average weight diameter structural parameters of the soil aggregates can be directly calculated by using image processing technology without destroying the soil structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a schematic diagram of the flow of the soil aggregate MWD calculation method based on Micro-CT images provided by the present invention.

[0020] Figure 2 The present invention provides a flow chart for the in-situ separation of soil aggregates.

[0021] Figure 3 It is a structural schematic diagram of a soil aggregate MWD calculation device based on Micro-CT images provided by the present invention.

[0022] Figure 4 A schematic diagram of the physical structure of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Figure 1 is a schematic diagram of the process of calculating the MWD of soil aggregates based on Micro-CT images provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 101: acquiring a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample.

[0025] Specifically, firstly, samples are selected, in-situ soil column samples are collected, and naturally air-dried to keep the aggregate structure unchanged; the selected samples are placed on a scanning device for scanning; after the scanning is completed, the scanned image is reconstructed to obtain the original grayscale image.

[0026] Then, the sample boundary voxels are removed from the original grayscale image, and pre-processing is performed to enhance the image and remove interference to obtain the grayscale image to be processed.

[0027] Finally, the grayscale image to be processed is segmented to obtain the soil matrix grayscale image.

[0028] It is worth mentioning that the above-mentioned scanning device can be a micro-CT or any scanning device that can obtain internal images of in-situ soil column samples.

[0029] Step 102: extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method.

[0030] Specifically, the in-situ separation of individual soil aggregates is achieved based on the morphological algorithm. First, the brightest part of the soil matrix grayscale image is extracted, and the threshold of the highlighted part is calculated using the image threshold segmentation method, and the image is extracted using the threshold as the seed image.

[0031] Then, based on the selected seed image, the morphological watershed algorithm is used to separate the individual clusters.

[0032] Finally, the cluster image is generated based on all the cluster individuals.

[0033] Step 103 obtains the average weight diameter result of the in-situ soil column sample based on the aggregate image.

[0034] Specifically, the aggregate structural parameters are extracted according to the aggregate image, and the average weight diameter is calculated.

[0035] First, the total volume of aggregates was calculated based on the aggregate image. Then, the total number of aggregates, the equivalent diameter and volume fraction of each aggregate were quantitatively analyzed based on the aggregate image. Finally, the average weight diameter of the soil was calculated based on the equivalent diameter and volume fraction.

[0036] The soil aggregate MWD calculation method based on Micro-CT images provided by the present invention can obtain a soil matrix grayscale image according to the original grayscale image of the in-situ soil column sample, then generate an aggregate image according to the soil matrix grayscale image, and finally obtain the average weight diameter result of the in-situ soil column sample according to the aggregate image. The average weight diameter structural parameters of the soil aggregates can be directly calculated by using image processing technology without destroying the soil structure.

[0037] In some embodiments, the step of acquiring a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample comprises: Acquire an original grayscale image of the in-situ soil column sample based on a scanning device; Determine an undisturbed area image based on the original grayscale image; Pre-processing the undisturbed area image to obtain a grayscale image to be processed; Perform image segmentation on the grayscale image to be processed to obtain the soil matrix grayscale image.

[0038] Specifically, firstly, samples are selected, in-situ soil column samples are collected, and naturally air-dried to keep the aggregate structure unchanged; the selected samples are placed on a scanning device for scanning; after the scanning is completed, the scanned image is reconstructed to obtain the original grayscale image.

[0039] When using a sampler to collect in-situ soil column samples, the soil structure must not be destroyed. According to the shape and size of the sample, the scanning equipment can select appropriate conditions such as pixel resolution and X-ray power.

[0040] Then, the sample boundary voxels are removed from the original grayscale image, and the image is cropped to obtain the undisturbed region (ROI) image. The ROI image is pre-processed to enhance the image and remove interference to obtain the grayscale image to be processed.

[0041] Finally, the grayscale image to be processed is segmented to obtain the soil matrix grayscale image.

[0042] The soil aggregate MWD calculation method based on Micro-CT images provided by the present invention can obtain the soil matrix grayscale image according to the original grayscale image of the in-situ soil column sample, and can directly calculate the average weight diameter structural parameters of the soil aggregates by using image processing technology without destroying the soil structure, thereby improving the calculation efficiency.

[0043] In some embodiments, the pre-treatment includes one or more of the following: Image posture correction; Remove ring artifact interference; Remove radiation hardening interference; Image filtering.

[0044] Specifically, for pre-processing of ROI images, Avizo software can be used to perform posture correction on ROI images and correct scanning errors; CT supporting software tools can also be used to remove ring artifacts generated during image reconstruction; CT supporting software tools can also be used to remove interference caused by radiation hardening; and adaptive median filtering methods can be used to filter images to enhance image contrast.

[0045] It is worth mentioning that image pre-processing can be selectively performed according to processing requirements, and at least one of the above methods can be selected.

[0046] The soil aggregate MWD calculation method based on Micro-CT images provided by the present invention can pre-process the ROI image, enhance the image to remove interference, obtain the grayscale image to be processed, and improve the accuracy of the calculation.

[0047] In some embodiments, performing image segmentation on the grayscale image to be processed to obtain the soil matrix grayscale image includes: Acquire image attribute data of the grayscale image to be processed; Determine a segmentation algorithm based on the image attribute data, and obtain a soil background image from the grayscale image to be processed based on the segmentation algorithm; The soil background image is used as a mask, and the intersection is taken with the original grayscale image to obtain the soil matrix grayscale image.

[0048] Specifically, the grayscale image to be processed can be imported into image processing software, such as MATLAB 2022a, to obtain the image attribute data of the grayscale image to be processed, and select the segmentation algorithm based on the image attribute data. If the image has obvious bimodal characteristics, the segmentation difficulty is relatively low, and a simple threshold segmentation algorithm can be used. If the grayscale image features are not obvious, an image segmentation algorithm based on regions and some specific theories can be selected. If the grayscale image features are complex and the traditional segmentation method is difficult to segment, advanced machine learning, deep learning and other artificial intelligence image segmentation technologies can be used.

[0049] Then, according to the determined segmentation algorithm, the image segmentation program is written, the corresponding segmentation algorithm parameters are set, and the grayscale image is divided into a soil background image and a soil pore image. The background image is used as a mask, and the intersection with the original grayscale image is taken to obtain the grayscale image of the soil matrix, and the pore part in the grayscale image is converted into the background, and the soil matrix grayscale image is saved.

[0050] The soil aggregate MWD calculation method based on Micro-CT images provided by the present invention performs image segmentation on the grayscale image to be processed to obtain a soil matrix grayscale image. The average weight diameter structural parameters of the soil aggregates can be directly calculated by using image processing technology without destroying the soil structure, thereby improving the accuracy of the calculation.

[0051] In some embodiments, extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, comprises: Determine the brightness threshold based on an image threshold segmentation method; Extracting a seed image from the soil matrix grayscale image based on the brightness threshold; Determining individual images of aggregates from the seed image based on the morphological watershed algorithm; The aggregate image is obtained by marking all the individual images of the aggregate.

[0052] Specifically, the part with high brightness in the soil matrix grayscale image is firstly extracted, and the threshold of the highlight part is calculated by using the image threshold segmentation method, and the image is extracted by using the threshold as the seed image.

[0053] Then, the image enhancement is performed by using morphological corrosion and closing process, and the boundary detection is performed to highlight the boundaries of aggregates in the soil matrix image. Based on the selected seed image, the morphological watershed algorithm is used to separate the individual aggregates.

[0054] Finally, the aggregate images were marked one by one using AVIZO software, thereby generating an aggregate image.

[0055] The soil aggregate MWD calculation method based on Micro-CT images provided by the present invention generates aggregate images based on a morphological watershed algorithm and a seed image. The average weight diameter structural parameters of soil aggregates can be directly calculated by using image processing technology without destroying the soil structure, thereby improving the calculation efficiency.

[0056] In some embodiments, obtaining the average weight diameter result of the in-situ soil column sample based on the aggregate image includes: determining an equivalent diameter of each agglomerate and a volume fraction of each agglomerate based on the agglomerate image; The average weight diameter result of the in-situ soil column sample is determined based on the equivalent diameter of each aggregate and the volume fraction of each aggregate.

[0057] Specifically, the aggregate image is passed through the Volume Edit tool of AVIZO software to obtain the mask image of the image, and the overall volume of the aggregate is calculated based on the mask image.

[0058] Based on the aggregate image, the Label Analysis tool was used to quantify the total number of aggregates, the equivalent diameter and volume of each aggregate, and obtain the label image and the volume fraction of a single aggregate.

[0059] Assuming that the density of different aggregates in the same sample is the same, the MWD calculation formula can be expressed as:

[0060] In the formula Indicates The equivalent diameter of a soil aggregate is Indicates The volume fraction of soil aggregates is calculated based on the above formula to obtain the average weight diameter of the soil.

[0061] The soil aggregate MWD calculation method based on Micro-CT images provided by the present invention can obtain a soil matrix grayscale image according to the original grayscale image of the in-situ soil column sample, then generate an aggregate image according to the soil matrix grayscale image, and finally obtain the average weight diameter result of the in-situ soil column sample according to the aggregate image. The average weight diameter structural parameters of the soil aggregates can be directly calculated by using image processing technology without destroying the soil structure.

[0062] The above method is described below with reference to a specific example.

[0063] Figure 2 is a flow chart of in-situ separation of soil aggregates provided by the present invention, such as Figure 2As shown, according to the soil aggregate MWD calculation method based on Micro-CT images provided by the present invention, the average weight diameter of in-situ soil at a depth of 0 to -70 cm under conventional tillage and no-tillage conditions is calculated, and the specific steps include: (1) A certain experimental station and its surrounding farmland were selected, and three long-term field (>10 years) experimental plots of perennial no-tillage and conventional tillage (wheat tillage / corn no-tillage) were selected. In-situ soil column samples were collected using a soil sampler (HDGSRTS 25-TS, USA). The length and diameter of the soil column samples were approximately 70 cm × 40 mm, and a total of 6 intact in-situ soil column samples were obtained. The soil column was carefully removed from the container and divided into 14 small soil column sections of approximately 5 cm in length at equal distances. The soil column sections were marked, wrapped in plastic wrap, and transported to the laboratory and stored at 4°C.

[0064] (2) The Skyscan 1275 micro-CT system (Bruker Skyscan, Belgium) was used to scan the samples. Different scanning conditions of the micro-CT were tested to obtain high-quality scanned images. The scanning parameters after preliminary research and optimization were determined as follows: acceleration voltage / current was 80 kV / 125 , pixel resolution is 30 , frame averaging is 4, scanning step is 0.2, and 360° rotation scanning is performed to obtain the tomographic image of the soil.

[0065] (3) Based on the projection image set, Bruker Skyscan Nrecon software was used to perform tomographic reconstruction using the modified Feldkamp algorithm to obtain micro-CT three-dimensional volumetric images.

[0066] (4) In order to eliminate the interference between the sample tube and the gasket boundary, the ROI (Region of Interest) is intercepted, and the size of the sample ROI is 36 mm.

[0067] (5) Pre-process the ROI image. First, correct the sample posture to make the sample image regular. Then remove the ring artifact interference generated by the scanning process. Finally, use the adaptive median filtering algorithm to reduce the influence of noise, increase the image contrast, and obtain the soil sample preprocessing image.

[0068] (6) The global clustering K-means algorithm in the unsupervised machine learning algorithm was used by Matlab R2022a (Math Works, America) software. In the algorithm parameters, the number of classifiers was set to 2, and the metric used was the Euclidean distance. The algorithm uses the kmeans function to perform iterative operations to cluster the grayscale image into two clusters, set the background elements of the clustered image to 0, and segment the volume image.

[0069] (7) A threshold of 112 (twice the threshold calculated by the Otsu method) is selected to extract the high-brightness image as the “seed”, and morphological operations are used for image enhancement. The morphological structure element is a rectangular 3 The size of the image was 3 pixels, and the Canny edge detection operator was used for boundary detection to highlight the boundaries of aggregates in the soil matrix image. The morphological watershed algorithm was used based on the selected "seed" image to perform regional clustering of the image, and the individual aggregates were separated based on the 26-neighborhood spatial connectivity rule (at least one vertex was connected).

[0070] (8) Use the Label Analysis tool of AVIZO software to obtain the equivalent diameter and volume fraction of soil aggregates, and calculate the average weight diameter of soil aggregates.

[0071] The average weight diameter parameters of the obtained aggregates are shown in Table 1.

[0072] Table 1. Average weight diameter of soil aggregates

[0073] In the table, different capital letters in the same column and different lowercase letters in the same row indicate significant differences (p<0.05).

[0074] Table 1 shows the results obtained by using the soil aggregate MWD calculation method based on Micro-CT images provided by the present invention under conventional tillage and no-tillage conditions at a depth of 0~-70cm. As can be seen from Table 1, conventional tillage changes the MWD of soil aggregates, but only affects the tillage layer (0~-20cm), and the MWD parameters do not change significantly with the change of soil depth. This result is in line with the law of soil science and verifies the accuracy of the soil aggregate MWD calculation method based on Micro-CT images provided by the present invention in calculating the MWD of soil aggregates. Therefore, with the help of the above technical solution of the present invention, by combining micro-CT scanning technology with professional three-dimensional analysis software AVIZO, the average weight diameter of soil aggregates can be calculated.

[0075] Figure 3 Schematic diagram of the structure of the soil aggregate MWD calculation device based on Micro-CT images provided by the present invention, Figure 3 As shown, the soil aggregate MWD calculation device based on Micro-CT images provided by the present invention includes: The first acquisition module 301 is used to acquire a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample; A first extraction module 302 is used to extract a seed image from the soil matrix grayscale image based on a brightness threshold, and generate an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; The second acquisition module 303 is used to acquire the average weight diameter result of the in-situ soil column sample based on the aggregate image.

[0076] Specifically, the above-mentioned soil aggregate MWD calculation device based on Micro-CT images provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned soil aggregate MWD calculation method embodiment based on Micro-CT images, and can achieve the same technical effects. The parts and beneficial effects of this embodiment that are the same as those of the method embodiment will not be described in detail here.

[0077] Figure 4 A schematic diagram of the physical structure of the electronic device provided by the present invention is as follows: Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communications interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the soil aggregate MWD calculation method based on the Micro-CT image, and the method includes: Obtaining a soil matrix grayscale image based on the original grayscale image of the in-situ soil column sample; Extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; An average weight diameter result of the in-situ soil column sample is obtained based on the aggregate image.

[0078] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, 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, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0079] On the other hand, the present invention also provides a computer program product, the computer program product includes a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute the soil aggregate MWD calculation method based on Micro-CT images provided by the above methods, the method includes: Obtaining a soil matrix grayscale image based on the original grayscale image of the in-situ soil column sample; Extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; An average weight diameter result of the in-situ soil column sample is obtained based on the aggregate image.

[0080] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform the soil aggregate MWD calculation method based on Micro-CT images provided by the above methods, the method comprising: Obtaining a soil matrix grayscale image based on the original grayscale image of the in-situ soil column sample; Extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; An average weight diameter result of the in-situ soil column sample is obtained based on the aggregate image.

[0081] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0082] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating MWD of soil aggregates based on Micro-CT images, characterized in that: include: Obtaining a soil matrix grayscale image based on the original grayscale image of the in-situ soil column sample; Extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; An average weight diameter result of the in-situ soil column sample is obtained based on the aggregate image.

2. The method for calculating MWD of soil aggregates based on Micro-CT images according to claim 1, characterized in that: The method of obtaining a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample comprises: Acquire an original grayscale image of the in-situ soil column sample based on a scanning device; Determine an undisturbed area image based on the original grayscale image; Pre-processing the undisturbed area image to obtain a grayscale image to be processed; Perform image segmentation on the grayscale image to be processed to obtain the soil matrix grayscale image.

3. The soil aggregate MWD calculation method based on Micro-CT images according to claim 2, characterized in that: The pre-treatment includes one or more of the following: Image posture correction; Remove ring artifact interference; Remove radiation hardening interference; Image filtering.

4. The method for calculating MWD of soil aggregates based on Micro-CT images according to claim 2, characterized in that: The step of performing image segmentation on the grayscale image to be processed to obtain the soil matrix grayscale image comprises: Acquire image attribute data of the grayscale image to be processed; Determine a segmentation algorithm based on the image attribute data, and obtain a soil background image from the grayscale image to be processed based on the segmentation algorithm; The soil background image is used as a mask, and the intersection is taken with the original grayscale image to obtain the soil matrix grayscale image.

5. The method for calculating MWD of soil aggregates based on Micro-CT images according to claim 1, characterized in that: The step of extracting a seed image from the soil matrix grayscale image based on a brightness threshold, and generating an aggregate image based on a morphological watershed algorithm and the seed image, comprises: Determine the brightness threshold based on an image threshold segmentation method; Extracting a seed image from the soil matrix grayscale image based on the brightness threshold; Determining individual images of aggregates from the seed image based on the morphological watershed algorithm; The aggregate image is obtained by marking all the individual images of the aggregate.

6. The method for calculating MWD of soil aggregates based on Micro-CT images according to claim 1, characterized in that: The step of obtaining the average weight diameter result of the in-situ soil column sample based on the aggregate image comprises: determining an equivalent diameter of each agglomerate and a volume fraction of each agglomerate based on the agglomerate image; An average weight diameter result of the in-situ soil column sample is determined based on the equivalent diameter of each aggregate and the volume fraction of each aggregate.

7. A soil aggregate MWD calculation device based on Micro-CT images, characterized in that: include: A first acquisition module is used to acquire a soil matrix grayscale image based on an original grayscale image of an in-situ soil column sample; A first extraction module is used to extract a seed image from the soil matrix grayscale image based on a brightness threshold, and generate an aggregate image based on a morphological watershed algorithm and the seed image, wherein the brightness threshold is determined based on an image threshold segmentation method; The second acquisition module is used to acquire the average weight diameter result of the in-situ soil column sample based on the aggregate image.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the soil aggregate MWD calculation method based on Micro-CT images as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the soil aggregate MWD calculation method based on Micro-CT images as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the soil aggregate MWD calculation method based on Micro-CT images as claimed in any one of claims 1 to 6 is implemented.

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