CN114663358A - Rock composition identification method, device, electronic equipment and storage medium - Google Patents
Rock composition identification method, device, electronic equipment and storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/20—Identification of molecular entities, parts thereof or of chemical compositions
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
Abstract
The present disclosure provides a rock composition identification method, apparatus, electronic device and storage medium, wherein the method comprises: acquiring a first scanning image, wherein the first scanning image comprises a multilayer rock stratum of a rock to be identified; performing image processing on the first scanning image to generate a second scanning image, wherein the second scanning image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum; acquiring a third scanning image corresponding to any rock stratum in the multi-layer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral; determining a component segmentation threshold value of each mineral of the multilayer rock formation in the first scanning image according to the second component distribution information and the first component distribution information; the component information of each mineral of the multilayer rock layer is determined according to the component division threshold value of each mineral of the multilayer rock layer, so that the component division threshold value of each mineral of the multilayer rock layer of the rock to be identified and the component information of each mineral of the multilayer rock layer can be accurately determined.
Description
Technical Field
The present disclosure relates to the technical field of rock microstructure characterization, and in particular, to a rock composition identification method, apparatus, electronic device, and storage medium.
Background
At present, with the continuous upgrading of observation means such as a scanning electron microscope and an industrial electronic computer Tomography (Computed Tomography, abbreviated as CT) and the remarkable improvement of computer computing capability, quantitative description of the heterogeneous distribution of minerals of rocks in a three-dimensional space becomes possible by means of a digital image processing technology. Different from conventional radiation imaging, the CT scanning technology does not project a three-dimensional object to a two-dimensional plane for presentation, but independently images two-dimensional scanning images obtained by the three-dimensional object, so that the influence of different levels on overlapping is avoided, the quality and the definition of the images can be improved, and the lossless perspective and the three-dimensional reconstruction of a rock internal space structure can be realized.
However, when the CT scanning system works, the X-ray generated by the ray source penetrates through the rock to be detected, different mineral components in the rock have different absorption capacities for the X-ray, and the gray levels appearing on the CT image are slightly different, so how to accurately identify the mineral components corresponding to the gray levels on the CT image has become an urgent problem to be solved.
Disclosure of Invention
The embodiment of the first aspect of the disclosure provides a rock composition identification method.
The embodiment of the second aspect of the present disclosure provides a rock composition identification device.
An embodiment of a third aspect of the present disclosure provides an electronic device.
A fourth aspect of the present disclosure is directed to a computer-readable storage medium.
A fifth aspect of the present disclosure is directed to a computer program product.
An embodiment of a first aspect of the present disclosure provides a rock composition identification, including: acquiring a first scanning image, wherein the first scanning image comprises a multilayer rock stratum of a rock to be identified; performing image processing on the first scanning image to generate a second scanning image, wherein the second scanning image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum; acquiring a third scanning image corresponding to any rock stratum in the multilayer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral; determining a component segmentation threshold value of each mineral of the multilayer rock stratum in the first scanning image according to the second component distribution information and the first component distribution information; and determining the composition information of each mineral of the multilayer rock stratum according to the composition segmentation threshold value of each mineral of the multilayer rock stratum.
In the technical scheme of the disclosure, the component distribution information of each mineral in the third scanned image corresponding to any one of the multiple rock layers and the second component distribution information of each mineral in the second scanned image are adopted, so that the component segmentation threshold value of each mineral of the multiple rock layers of the rock to be identified and the component information of each mineral of the multiple rock layers can be accurately determined.
In addition, the rock composition identification method according to the above embodiment of the present disclosure may further have the following additional technical features:
in an embodiment of the present disclosure, the determining a component segmentation threshold of the first scan image of the multi-layered rock formation according to the second component distribution information and the first component distribution information includes: determining first component distribution information of each mineral corresponding to any rock stratum from the second scanning image; and determining a component division threshold value of each mineral in the multilayer rock formation according to the first component distribution information of each mineral corresponding to the rock formation and the second component distribution information of each mineral in the rock formation.
In an embodiment of the present disclosure, the determining a component division threshold value of each mineral of the multi-layer rock formation according to the second component distribution information of each mineral in any rock formation and the first component distribution information of each mineral corresponding to any rock formation, includes: determining a component division threshold value of any mineral in any rock stratum according to second component distribution information of any mineral and first component distribution information of each mineral corresponding to any rock stratum; and determining the composition segmentation threshold value of each mineral of the multilayer rock formation in the first scanning image according to the composition segmentation threshold value of any mineral.
In an embodiment of the present disclosure, the determining, for any mineral in the any rock formation, a composition segmentation threshold of the any mineral according to the second component distribution information and the first component distribution information of the any mineral includes: determining proportion information of the any mineral in the any rock stratum according to the second component information of the any mineral; counting the first component distribution information of each mineral corresponding to any rock stratum to obtain the cumulative proportion information of minerals corresponding to a plurality of component segmentation threshold values; and inquiring the accumulated proportion information of the minerals corresponding to the multiple component segmentation threshold values according to the proportion information, and determining the component segmentation threshold value corresponding to any mineral.
In one embodiment of the present disclosure, the image processing the first scanned image to generate a second scanned image includes: performing image enhancement on the first scanning image to obtain an enhanced first scanning image; performing noise reduction processing on the enhanced first scanning image to obtain a noise-reduced first scanning image; and removing the artifact of the first scanned image subjected to the noise reduction treatment, and taking the first scanned image subjected to the artifact removal as a second scanned image.
In one embodiment of the present disclosure, the method further comprises: and creating a rock model according to the component segmentation threshold of each mineral of the multilayer rock stratum, wherein the rock model represents the corresponding relation between each mineral and each mineral color.
An embodiment of a second aspect of the present disclosure provides a rock composition identification device, including: the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first scanning image, and the first scanning image comprises a multilayer rock stratum of a rock to be identified; the processing module is used for carrying out image processing on the first scanning image to generate a second scanning image, wherein the second scanning image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum; the second acquisition module is used for acquiring a third scanning image corresponding to any rock stratum in the multilayer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral; a first determining module, configured to determine a component segmentation threshold of each mineral of the multilayer rock formation in the first scan image according to the second component distribution information and the first component distribution information; and the second determination module is used for determining the composition information of each mineral of the multilayer rock stratum according to the composition segmentation threshold of each mineral of the multilayer rock stratum.
An embodiment of a third aspect of the present disclosure provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, when executing the program, implementing the rock composition identification method as described in the foregoing embodiments of the first aspect.
A fourth aspect of the present disclosure provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the rock composition identification method as described in the foregoing first aspect of the present disclosure.
A fifth aspect of the present disclosure provides a computer program product, wherein when the instructions of the computer program product are executed by a processor, the method for identifying rock composition according to the first aspect of the present disclosure is performed.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow diagram of a rock composition identification method according to one embodiment of the present disclosure;
FIG. 2 is a schematic illustration of a first scanned image according to another embodiment of the present disclosure;
FIG. 3 is a graph of granite mineral scale as a function of gray scale value according to another embodiment of the disclosure;
FIG. 4 is a schematic view of any one formation acquisition of a rock to be identified according to one embodiment of the present disclosure;
FIG. 5 is a graphical illustration of results of a test of any of the formations by TIMA according to one embodiment of the present disclosure;
FIG. 6 is a schematic flow diagram of a rock composition identification method according to one embodiment of the present disclosure;
FIG. 7 is a graph illustrating the ratio of mica minerals in granite as a function of gray level according to one embodiment of the present disclosure;
FIG. 8 is a schematic diagram of a component segmentation threshold corresponding to each mineral in a rock according to one embodiment of the present disclosure;
FIG. 9 is a graph illustrating minerals and corresponding grayscale values in a two-dimensional formation according to one embodiment of the present disclosure;
FIG. 10 is a schematic representation of the mineral content of granite in a two-dimensional scan image according to one embodiment of the present disclosure;
FIG. 11 is a schematic flow diagram of a rock composition identification method according to one embodiment of the present disclosure;
FIG. 12 is a schematic diagram of a rock composition identification device according to one embodiment of the present disclosure;
fig. 13 is a block diagram of an electronic device of a rock component identification method of an embodiment of the present disclosure.
Detailed Description
Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and intended to be illustrative of the present disclosure, and should not be construed as limiting the present disclosure.
The material and geometrical characteristics of the rock are heterogeneous, and the microstructure of the rock such as mineral components directly influences the macroscopic physical and mechanical properties of the rock. At present, the related technologies commonly used for researching rock mineral components include a thin slice analysis technology, an X-ray diffraction technology, a scanning electron microscope analysis and the like, and although the technologies play an important role in quantitative analysis of rock microstructures, the technologies also have obvious limitations. For example, the test resolution of the optical microscope-based flake analysis technique is limited by diffraction limit, and the identification effect on minerals with low content is poor; the sampling position of the X-ray diffraction experiment has uncertainty, and the test result may have errors. In addition, the above techniques are limited to mineral component detection in two-dimensional planes, and spatial distribution characteristic analysis and quantitative characterization of mineral composition in three-dimensional space in the whole rock cannot be realized.
In view of the above problems, the present disclosure provides a rock component identification method, apparatus, electronic device, and storage medium.
Rock component identification methods, apparatuses, electronic devices, and storage media according to embodiments of the present disclosure are described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow diagram of a rock composition identification method according to an embodiment of the present disclosure.
The disclosed embodiments are exemplified in that the rock component recognition method is configured in a rock component recognition apparatus, which can be applied to any electronic device, so that the electronic device can perform a rock component recognition function.
The electronic device may be any device having a computing capability, for example, a Personal Computer (PC), a mobile terminal, and the like, and the mobile terminal may be a hardware device having various operating systems, touch screens, and/or display screens, such as a mobile phone, a tablet Computer, a Personal digital assistant, and a wearable device.
As shown in fig. 1, the rock composition recognition method may include the steps of:
In the embodiment of the present disclosure, the rock to be identified may be placed in the CT scanning system, and the CT scanning system may scan the rock to be identified to obtain the first scan image.
As shown in fig. 2, the first scanned image may include multiple layers of rock formations of the rock to be identified.
In addition, it should be noted that, in order to improve the quality of the first scanned image, an in-situ loading imaging CT scanning comprehensive analysis system with ultra-high resolution (for example, resolution of 2um) may be adopted, and when scanning the rock to be identified, an imaging mode such as fast scanning, helical scanning or dither scanning may be selected. In addition, for rocks to be identified with a diameter greater than or equal to 50mm and a height greater than or equal to 100mm, a helical scanning imaging mode may be employed.
And 102, performing image processing on the first scanning image to generate a second scanning image, wherein the second scanning image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum.
It should be understood that, since the scanned image is susceptible to various factors during the generation process, which affect the visual presentation quality of the image, in order to further improve the display quality of the first scanned image, in the embodiment of the present disclosure, the first scanned image may be subjected to image processing to generate the second scanned image.
In the embodiment of the present disclosure, the gray values corresponding to the minerals in the second scanned image are different, and the first component distribution information of each mineral can be obtained by counting the mineral proportion data corresponding to different gray values in the second scanned image, where the first component distribution information of each mineral can represent the relationship between the mineral proportion and the gray value.
Moreover, the first component distribution information of the multiple minerals can be counted according to the change of the gray value in the second scanning image to determine the cumulative proportion of the multiple minerals corresponding to the gray value, as shown in fig. 3, for example, taking the rock to be identified as granite, as the gray value is reduced from 65535 to 0, the proportion of the divided minerals is gradually increased from 0% to 100%. It should be noted that the second scanned image may be a 16-bit unsigned binary image with a gray scale range of 0 to 65535.
As a possible implementation manner of the embodiment of the present disclosure, as shown in fig. 4, a layer of rock slice is taken in a direction perpendicular to an axial direction of a rock to be identified, and after polishing and coating, the rock slice is placed under a scanning electron microscope of TIMA, and after a scanning resolution and an acquisition mode of TIMA are set, a backscatter image and energy spectrum data of a scanning area can be generated. According to a mineral database of the TIMA, the backscattering image and the energy spectrum data can be matched and identified, mineral boundaries are effectively segmented, and pseudo-color distinguishing is carried out to obtain a third scanning image.
For example, as shown in fig. 5, taking the rock to be identified as granite as an example, matching and identifying the backscatter image and the energy spectrum data according to a mineral database of the TIMA itself, effectively segmenting mineral boundaries, and determining mineral components and content.
It should be noted that, based on the TIMA self-contained offline data processing and analyzing function, the second component distribution information of each mineral can be determined by analyzing and counting various colors in the third scanned image. For example, the results of mineral component ratio, particle size distribution, porosity, etc. can be counted. For example, the main mineral components and proportions of the granite sample can be shown in table 1:
TABLE 1 Main mineral component and volume fraction of granite sample
Wherein the main mineral components of the rock are quartz (32.75%), feldspar (including orthoclase, albite and anorthite, and total amount is 59.24%), mica (including biotite and muscovite, and total volume fraction of other minerals is 1.49%
And 104, determining a component segmentation threshold value of each mineral of the multilayer rock stratum in the first scanning image according to the second component distribution information and the first component distribution information.
In this disclosure, the first component distribution information of the rock formation corresponding to any rock formation in the third scanned image may be determined from the second scanned image, and then, the component segmentation threshold of each mineral in the multi-layered rock formation in the first scanned image may be determined according to the second component distribution information of each mineral in any rock formation and the first component distribution information corresponding to any rock formation, where the component segmentation threshold may be a gray value threshold corresponding to each mineral in the multi-layered rock formation in the first scanned image.
And 105, determining the component information of each mineral of the multilayer rock stratum according to the component division threshold value of each mineral of the multilayer rock stratum.
Furthermore, the minerals of the multi-layer rock formation in the first scan image may be distinguished based on the composition segmentation threshold of the minerals of the multi-layer rock formation to determine composition information of the minerals of the multi-layer rock formation, e.g., the types of minerals contained in the respective layers of rock formation.
In summary, the component division threshold of each mineral in the multi-layer rock stratum of the rock to be identified can be accurately determined through the component distribution information of each mineral in the third scanning image corresponding to any rock stratum in the multi-layer rock stratum and the second component distribution information of each mineral in the second scanning image, and further, the component information of each mineral in the multi-layer rock stratum can be determined according to the component division threshold of each mineral in the multi-layer rock stratum.
In order to accurately determine the composition segmentation threshold of the first scanned image multi-layer rock formation, in the embodiment of the present disclosure, as shown in fig. 6, first composition distribution information of minerals corresponding to any rock formation may be determined from the second scanned image, and the composition segmentation threshold of each mineral of the first scanned image multi-layer rock formation may be determined according to the second composition distribution information of each mineral in any rock formation and the first composition distribution information of each mineral corresponding to any rock formation, and the embodiment shown in fig. 6 may include the following steps:
In this disclosure, according to any rock stratum in the third scanned image, in the second scanned image, a rock stratum corresponding to any rock stratum is determined, and the first component distribution information of each mineral corresponding to the rock stratum corresponding to any rock stratum is obtained.
Optionally, for any mineral in any rock stratum, determining a component segmentation threshold of any mineral according to the second component distribution information of any mineral and the first component distribution information of each mineral corresponding to any rock stratum; and determining a composition segmentation threshold value of each mineral of the multilayer rock formation in the first scanning image according to the composition segmentation threshold value of any mineral.
As an example, determining proportion information of any mineral in any rock formation according to the second composition information of any mineral; the method comprises the steps of counting first component distribution information of each mineral corresponding to any rock stratum to obtain accumulation proportion information of minerals corresponding to a plurality of component segmentation threshold values, inquiring the accumulation proportion information of the minerals corresponding to the plurality of component segmentation threshold values according to the proportion information to obtain a component segmentation threshold value corresponding to any mineral, and further determining the component segmentation threshold value of each mineral of the plurality of rock strata in a first scanning image according to the component segmentation threshold value of any mineral, wherein the component segmentation threshold values of the minerals corresponding to each rock stratum in the same rock are the same.
In the embodiment of the present disclosure, the first component distribution information of each mineral corresponding to any rock stratum is counted to obtain the cumulative proportion information of the minerals corresponding to the multiple component segmentation thresholds, that is, the first component distribution information of multiple minerals is counted according to the change of the gray value, so as to determine the cumulative proportion of the multiple minerals corresponding to the gray value.
Since the greater the density of the mineral, the greater the brightness in the second scanned image (e.g., the brightest part is mica, followed by quartz and feldspar), the greater the corresponding gray value, as an example, the proportion of each mineral can be determined according to the sequence of gray values from large to small, for example, the mica proportion obtained by TIMA detection is 6.59 percent, based on the ratio, the cumulative ratio information of minerals corresponding to a plurality of component division thresholds is inquired, and the component division threshold (gray scale value range) corresponding to mica can be determined to be 12851 to 65535, and similarly, the ratios of mica and feldspar are added, according to the added result, the cumulative proportion information of the minerals corresponding to the plurality of corresponding component segmentation thresholds is inquired, the component segmentation thresholds of mica and feldspar can be determined to be 7197 to 65535, since the component division threshold value corresponding to mica is 12851 to 65535, the component division threshold value corresponding to feldspar is 7197 to 12850.
In order to accurately determine the component segmentation threshold corresponding to each mineral, optionally, a relationship graph between the change of each mineral proportion with the gray scale may be generated according to the gray scale value corresponding to each mineral in the second scanned image and each mineral proportion, and according to the relationship graph, the component segmentation threshold corresponding to each mineral may be verified.
For example, as shown in fig. 7, when the gray scale value is 12851, the mineral content has a stepwise sudden change, 12851 can be used as a component division point, and since the brightness of mica in the second scanned image is the maximum, the component division threshold value corresponding to mica can be determined to be 12581 to 65535.
Further, a composition division threshold value for each mineral of the multilayer rock formation in the first scan image is determined based on the composition division threshold value for any mineral. For example, the three mineral composition segmentation threshold of the 288 th rock layer can be as shown in fig. 8, and in fig. 8, different gray scale regions can respectively represent the marking results of mica, quartz and feldspar minerals.
In the embodiment of the present disclosure, after the component division threshold value of each mineral is determined, the component information of each mineral of the multilayer rock formation may be determined based on the component division threshold value of each mineral of the multilayer rock formation. Further, the mineral components of each pixel point in the two-dimensional plane can be assigned to show that the same mineral is displayed as the same color on the image, for example, as shown in fig. 9, the black part can represent mica, the dark gray is quartz, and the light gray is feldspar.
In embodiments of the present disclosure, after determining the composition information for each mineral of the multi-layer rock formation, the composition information for each mineral of the multi-layer rock formation may be presented.
For example, as shown in fig. 10, taking granite as an example, the proportion distribution of three minerals, mica, quartz and feldspar, in different rock layers (sliced layers) fluctuates to some extent, which shows the heterogeneity of the granite sample.
It should be noted that the execution processes of steps 601 to 603 may be implemented by any one of the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this and are not described again.
In conclusion, the first component distribution information of each mineral corresponding to any rock stratum is determined from the second scanning image; the component division threshold value of each mineral of the multi-layer rock formation of the first scanning image is determined based on the second component distribution information of each mineral in any rock formation and the first component distribution information of each mineral corresponding to any rock formation.
In order to improve the display quality of the first scanned image, improve the contrast of each mineral component in the rock to be identified, and further improve the accuracy of the component segmentation threshold of each mineral, as shown in fig. 11, in the embodiment of the present disclosure, operations such as image enhancement, noise reduction, artifact removal, and the like may be performed on the first scanned image to obtain a scanned image with a higher display quality, and the embodiment shown in fig. 11 may include the following steps:
It should be understood that, in the embodiment of the present disclosure, since the scanned image is easily interfered by various factors during the generation process to affect the visual presentation quality of the image, it is difficult for the scanned image with low quality to acquire the required digital information and characteristic parameters, and therefore, the display quality of the scanned image can be improved through image processing.
Optionally, the rock scanning process is easily affected by external environments such as instrument parameter setting, the contrast of the obtained scanning image is not high, and the perception data obtained through vision cannot effectively reflect the implicit digital information in the gray level image. The first scanned image needs to be subjected to image enhancement, the gray level difference among various mineral components in the first scanned image is enlarged, and the image visual presentation effect is subjectively improved.
It is to be understood that noise in a digital image is a waste of information generated during image acquisition and transmission, often confused with image details and degrading image quality. Therefore, the enhanced first scanned image is subjected to noise reduction processing by using a noise reduction processing method to obtain a noise-reduced first scanned image. The noise reduction processing method may include, but is not limited to: linear filtering (e.g., box filtering, mean filtering, gaussian filtering, etc.) and non-linear filtering (median filtering, bilateral filtering, etc.).
And 1104, removing artifacts from the first scanned image after the noise reduction treatment, and using the first scanned image after the artifacts are removed as a second scanned image, wherein the second scanned image contains first component distribution information of each mineral corresponding to the multilayer rock stratum.
Energy attenuation is generated after X-rays penetrate through the rock to be detected, and the attenuation degree is related to the path length of light. The scanned image of a standard rock with a circular cross section will appear brighter in the edge regions than in the inner regions, thus minimizing the effect of artifacts on the scanned image during image processing. Optionally, the first scanned image after the noise reduction processing is subjected to hardening correction to remove the artifact, and the first scanned image after the artifact removal is used as a second scanned image, where the second scanned image includes first component distribution information of each mineral corresponding to the multilayer rock formation.
In the embodiment of the present disclosure, in order to visualize various mineral components in the rock, after acquiring the component division threshold of each mineral in the multilayer rock layer, a rock model may be created according to the component division threshold of each mineral, as an example, the component division thresholds of all two-dimensional rock slices may be superimposed in a three-dimensional space using visualization software Avizo, and a rock model (three-dimensional visualization reconstruction model) may be obtained, as shown in fig. 12, the mineral components of each voxel point in the three-dimensional space are assigned, as shown in the image, the same mineral is displayed in the same color, the black part represents mica, the dark gray is quartz, and the light gray is feldspar. Based on the rock model, spatial distribution characteristics of different mineral compositions can be obtained.
It should be noted that the execution processes of step 1101 and steps 1105 to 1107 may be implemented by any one of the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this, and are not described again.
In conclusion, the first scanning image is subjected to image enhancement to obtain an enhanced first scanning image; carrying out noise reduction processing on the enhanced first scanning image to obtain a noise-reduced first scanning image; and removing the artifact from the first scanned image after the noise reduction processing, and using the first scanned image after the artifact removal as a second scanned image, wherein the second scanned image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum, so that the scanned image with high display quality can be obtained by performing image enhancement, noise reduction processing and artifact removal on the first scanned image.
According to the rock composition identification method, a first scanning image is obtained, wherein the first scanning image comprises a multilayer rock stratum of a rock to be identified; acquiring a third scanning image corresponding to any rock stratum in the multi-layer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral; determining a component segmentation threshold value of each mineral of the multilayer rock stratum in the first scanning image according to the second component distribution information and the first component distribution information; and determining the component information of each mineral of the multilayer rock stratum according to the component segmentation threshold value of each mineral of the multilayer rock stratum. Therefore, by adopting the component distribution information of each mineral in the third scanning image corresponding to any rock stratum in the multilayer rock stratum and the second component distribution information of each mineral in the second scanning image, the component segmentation threshold value of each mineral of the multilayer rock stratum of the rock to be identified and the component information of each mineral of the multilayer rock stratum can be accurately determined.
For example, the present disclosure further provides a rock composition recognition apparatus.
Fig. 12 is a schematic structural diagram of a rock composition recognition device according to an embodiment of the present disclosure.
As shown in fig. 12, the rock component recognition apparatus 1200 includes: a first acquisition module 1210, a processing module 1220, a second acquisition module 1230, a first determination module 1240, and a second determination module 1250.
The first obtaining module 1210 is configured to obtain a first scanned image, where the first scanned image includes multiple strata of rocks to be identified; the processing module 1220 is configured to perform image processing on the first scanned image to generate a second scanned image, where the second scanned image includes first component distribution information of each mineral corresponding to the multilayer rock formation; the second obtaining module 1230 is configured to obtain a third scan image corresponding to any rock stratum of the multiple rock strata, where the third scan image includes second component distribution information of each mineral; a first determining module 1240 for determining a composition segmentation threshold for each mineral of the multi-layered rock formation in the first scan image based on the second composition distribution information and the first composition distribution information; the second determining module 1250 is configured to determine composition information of each mineral of the multi-layered rock formation according to the composition segmentation threshold of each mineral of the multi-layered rock formation.
As a possible implementation manner of the embodiment of the present disclosure, the first determining module 1240 is further configured to: determining first component distribution information of each mineral corresponding to any rock stratum from the second scanning image; and determining a component segmentation threshold value of each mineral of the multi-layer rock stratum of the first scanning image according to the second component distribution information of each mineral in any rock stratum and the first component distribution information of each mineral corresponding to any rock stratum.
As a possible implementation manner of the embodiment of the present disclosure, the first determining module 1240 is further configured to: determining a component division threshold value of any mineral in any rock stratum according to second component distribution information of any mineral and first component distribution information of each mineral corresponding to any rock stratum; and determining a composition segmentation threshold value of each mineral of the multilayer rock formation in the first scanning image according to the composition segmentation threshold value of any mineral.
As a possible implementation manner of the embodiment of the present disclosure, determining, for any mineral in any rock formation, a component segmentation threshold of any mineral according to the second component distribution information and the first component distribution information of any mineral includes: determining proportion information of any mineral in any rock stratum according to the second component information of any mineral; counting the first component distribution information of each mineral corresponding to any rock stratum to obtain the cumulative proportion information of the minerals corresponding to a plurality of component segmentation threshold values; and inquiring the accumulated proportion information of the minerals corresponding to the multiple component segmentation threshold values according to the proportion information, and determining the component segmentation threshold value corresponding to any mineral.
As a possible implementation manner of the embodiment of the present disclosure, the processing module 1220 is further configured to: performing image enhancement on the first scanning image to obtain an enhanced first scanning image; carrying out noise reduction processing on the enhanced first scanning image to obtain a noise-reduced first scanning image; and removing the artifact of the first scanning image subjected to the noise reduction processing, and taking the first scanning image subjected to the artifact removal as a second scanning image.
As a possible implementation manner of the embodiment of the present disclosure, the rock composition recognition apparatus 1200 further includes: and creating a module.
The creating module is used for creating a rock model according to the component segmentation threshold of each mineral of the multilayer rock stratum, wherein the rock model represents the corresponding relation between each mineral and each mineral color.
The rock composition recognition device comprises a first scanning image acquisition unit, a second scanning image acquisition unit, a rock composition recognition unit and a rock composition recognition unit, wherein the first scanning image acquisition unit acquires a first scanning image which comprises a multilayer rock stratum of a rock to be recognized; acquiring a third scanning image corresponding to any rock stratum in the multi-layer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral; determining a component segmentation threshold value of each mineral of the multilayer rock stratum in the first scanning image according to the second component distribution information and the first component distribution information; and determining the component information of each mineral of the multilayer rock stratum according to the component segmentation threshold of each mineral of the multilayer rock stratum. Therefore, by adopting the component distribution information of each mineral in the third scanning image corresponding to any rock stratum in the multilayer rock stratum and the second component distribution information of each mineral in the second scanning image, the component segmentation threshold value of each mineral of the multilayer rock stratum of the rock to be identified and the component information of each mineral of the multilayer rock stratum can be accurately determined.
In order to implement the above embodiments, an embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the rock composition identification method according to the above-mentioned embodiment of the present disclosure.
In order to achieve the above embodiments, the present disclosure also proposes a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the rock component identification method according to the embodiments of the present disclosure.
In order to implement the foregoing embodiments, the present disclosure further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor of an electronic device, the electronic device is enabled to execute the rock composition identification method according to the embodiments of the present disclosure.
As shown in fig. 13, fig. 13 is a block diagram of an electronic device of a rock composition identification method according to an embodiment of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 13, the electronic apparatus includes: one or more processors 1301, memory 1302, and interfaces for connecting the various components, including high speed interfaces and low speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 13 illustrates an example of a processor 1301.
The memory 1302, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the first obtaining module 1210, the processing module 1220, the second obtaining module 1230, the first determining module 1240, and the second determining module 1250) corresponding to the transportation coordination control method in the above embodiments of the present disclosure. The processor 1301 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 1302, so as to implement the rock composition identification method of the present disclosure as described in the above embodiments.
The memory 1302 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the electronic device by generation of the transportation cooperative control, and the like. Further, the memory 1302 may include high speed random access memory and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 1302 may optionally include memory located remotely from the processor 1301, which may be connected to the electronics of the rock composition identification method via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the rock component identification method may further include: an input device 1303 and an output device 1304. The processor 1301, the memory 1302, the input device 1303 and the output device 1304 may be connected by a bus or other means, and fig. 13 illustrates the bus connection.
The input device 1303 may receive input numeric or character information and generate key signal inputs related to user settings and function controls of the rock component-recognized electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, or other input devices. The output devices 1304 may include a display device, auxiliary lighting devices (e.g., LEDs), tactile feedback devices (e.g., vibrating motors), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
In addition, the acquisition, storage, application and the like of the information related in the technical scheme of the disclosure all accord with the regulations of related laws and regulations, and do not violate the good custom of the public order.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions proposed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (9)
1. A rock composition identification method, comprising:
acquiring a first scanning image, wherein the first scanning image comprises a multilayer rock stratum of a rock to be identified;
performing image processing on the first scanning image to generate a second scanning image, wherein the second scanning image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum;
acquiring a third scanning image corresponding to any rock stratum in the multilayer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral;
determining a component segmentation threshold value of each mineral of the multilayer rock stratum in the first scanning image according to the second component distribution information and the first component distribution information;
and determining the composition information of each mineral of the multilayer rock stratum according to the composition segmentation threshold value of each mineral of the multilayer rock stratum.
2. The method of claim 1, wherein determining a component segmentation threshold for the first scan image for the multi-layered rock formation based on the second component distribution information and the first component distribution information comprises:
determining first component distribution information of each mineral corresponding to any rock stratum from the second scanning image;
and determining a component division threshold value of each mineral in the multilayer rock formation according to the first component distribution information of each mineral corresponding to the rock formation and the second component distribution information of each mineral in the rock formation.
3. The method according to claim 2, wherein determining the composition segmentation threshold for each mineral of the plurality of layers of the first scanned image based on the second component distribution information for each mineral in the any one of the rock layers and the first component distribution information for each mineral corresponding to the any one of the rock layers comprises:
determining a component division threshold value of any mineral in any rock stratum according to second component distribution information of any mineral and first component distribution information of each mineral corresponding to any rock stratum;
and determining the composition segmentation threshold value of each mineral of the multilayer rock formation in the first scanning image according to the composition segmentation threshold value of any mineral.
4. The method according to claim 3, wherein the determining a composition segmentation threshold for any mineral in the any rock formation from the second composition distribution information and the first composition distribution information of the any mineral comprises:
determining proportion information of the any mineral in the any rock stratum according to the second component information of the any mineral;
counting the first component distribution information of each mineral corresponding to any rock stratum to obtain the cumulative proportion information of minerals corresponding to a plurality of component segmentation threshold values;
and inquiring the accumulated proportion information of the minerals corresponding to the multiple component segmentation thresholds according to the proportion information, and determining the component segmentation threshold corresponding to any mineral.
5. The method of claim 1, wherein said image processing the first scanned image to generate a second scanned image comprises:
performing image enhancement on the first scanning image to obtain an enhanced first scanning image;
performing noise reduction processing on the enhanced first scanning image to obtain a noise-reduced first scanning image;
and removing the artifact of the first scanned image subjected to the noise reduction treatment, and taking the first scanned image subjected to the artifact removal as a second scanned image.
6. The method according to any one of claims 1-5, further comprising:
and creating a rock model according to the component segmentation threshold of each mineral of the multilayer rock stratum, wherein the rock model represents the corresponding relation between each mineral and each mineral color.
7. A rock composition recognition apparatus, comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first scanning image, and the first scanning image comprises a multilayer rock stratum of a rock to be identified;
the processing module is used for carrying out image processing on the first scanning image to generate a second scanning image, wherein the second scanning image comprises first component distribution information of each mineral corresponding to the multilayer rock stratum;
the second acquisition module is used for acquiring a third scanning image corresponding to any rock stratum in the multilayer rock stratum, wherein the third scanning image comprises second component distribution information of each mineral;
a first determining module, configured to determine a component segmentation threshold for each mineral of the multilayer rock formation in the first scan image according to the second component distribution information and the first component distribution information;
and the second determination module is used for determining the composition information of each mineral of the multilayer rock stratum according to the composition segmentation threshold of each mineral of the multilayer rock stratum.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the rock composition identification method of any one of claims 1-6.
9. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out a rock composition identification method according to any one of claims 1-6.
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| CN115561269A (en) * | 2022-10-21 | 2023-01-03 | 核工业北京地质研究院 | Method for analysing minerals in rock |
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| CN115561269A (en) * | 2022-10-21 | 2023-01-03 | 核工业北京地质研究院 | Method for analysing minerals in rock |
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