Method for extracting surface topography and fabric features of rock and mineral

Abstract

The application provides a rock and mineral surface morphology and fabric feature extraction method, which comprises the following steps: firstly, based on the confocal microscope image data of actual rock and mineral, an adaptive two-dimensional structure enhancement filter operator and a filter aperture in a spatial domain are constructed, and attribute data which retains and highlights the mineral structure features are obtained through azimuth scanning processing; then, a data-driven two-dimensional elevation data high-order nonlinear spline smoothing function is established, and after the optimal two-dimensional local spline smoothing function is determined, the rock surface positive and negative morphology attributes are calculated, so that the surface morphology and spatial fabric and distribution characteristics of the mineral are accurately and reliably quantitatively described, and the basic support is provided for analyzing the ore-forming process and mechanism of economic mineral, determining the mineral genesis and distribution law, and guiding the efficient exploration and development of mineral resources.

Description

Technical Field

[0001] This invention relates to the field of mineral resource exploration and development. It is a method for extracting and quantitatively describing the surface morphology and spatial structure characteristics of rocks, ores and minerals from confocal microscope image data. This method is used to analyze the mineralization process and mechanism of economic minerals in rocks and ores, determine their distribution patterns, and provide basic support for guiding efficient mineral exploration and development. Background Technology

[0002] Mineral resources are the most important material foundation for the high-quality development of my country's economy and society, and the scale of my country's mineral resource consumption will continue to remain high. Strengthening the exploration and techno-economic evaluation of mineral resources, especially strategic and critical mineral resources, and discovering new mineral resource reserve bases are crucial for the security of my country's mineral resource supply. Mineral identification and analysis are fundamental tasks. Traditional mineral identification mainly involves manual identification, textural and morphological observation, grain size statistics and analysis under a common optical microscope. However, many metallic minerals and their varieties and subspecies have subtle differences in optical and physical properties, making them difficult to distinguish with the naked eye! Typological studies of metallic minerals require extensive statistical analysis of mineral optical characteristics. Manual methods suffer from many drawbacks, such as high time consumption, low efficiency, and large errors. They also rely too heavily on the professional knowledge and skills of the identification personnel, hindering the widespread adoption of mineral identification and analysis.

[0003] Confocal microscopy provides an advanced method for observing the surface structure of rocks and ores and for analyzing their mineral phases. However, the surface structure data observed by confocal microscopy cannot directly and quantitatively reflect the surface morphology and textural characteristics of rocks and ores. Further data processing is needed to suppress and remove noise interference, separate effective features and their distribution information, and then use this data for subsequent automatic mineral identification, analysis of the physicochemical conditions and mineral genesis of mineralization, and guidance for geological prospecting. The method developed in this patented invention achieves this goal by extracting and quantitatively describing the surface morphology and spatial structure information of minerals from confocal microscopic imaging data, supporting accurate and efficient automatic mineral identification and analysis of mineralization processes and mechanisms. Summary of the Invention

[0004] The purpose of this invention is to provide a method for extracting and quantitatively describing the surface morphology and spatial structure of minerals from confocal microscopic images of rocks and minerals. The principle is to retain and highlight the effective information in the confocal microscopic images of rocks and minerals, and to establish a method for enhancing and extracting information on the discontinuities in the spatial morphology of rocks and minerals. This allows for the quantitative description of the spatial structure and distribution characteristics of minerals, supporting high-precision and high-efficiency identification of minerals and analysis of mineralization patterns. The method of this invention includes the following main steps:

[0005] Input confocal microscope image data of specific rock and mineral samples. In this context, x and y represent the horizontal and vertical coordinates of the image data, respectively, and the horizontal and vertical acquisition intervals are represented by dx and dy, respectively, with the unit being meters (m). The number of sample points in the x and y directions are I and J, respectively;

[0006] Confocal microscope image data Perform a two-dimensional spatial domain Fourier transform to obtain its two-dimensional wavenumber spectrum data M. f (K x , K y ), where K x , and K y The wavenumbers in the x and y directions of the image data are represented respectively. The wavenumber scaling factor is extracted using the following formula. :

[0007]

[0008] in, This indicates finding the maximum value;

[0009] Establish confocal microscope image data Two-dimensional structure enhancement filter operator ,in, The filter aperture in the defined spatial domain along the x and y directions constitutes the wavenumber scaling factor. The function, using Confocal microscope image data After azimuth scanning, attribute data that preserves and highlights the structural features of the minerals were obtained. ,Right now:

[0010]

[0011] Where m and n represent the sampling point numbers in the x and y directions within the filter aperture, respectively;

[0012] attribute data Each data point Establish an aperture of [missing information] as the target center control point. High-order nonlinear spline smoothing function for 3D elevation data Obtained through iterative search algorithm After obtaining the optimal feature control vector set, the optimized three-dimensional local spline smoothing function is obtained. ,in, and These represent the data point indices in the x and y directions, respectively;

[0013] use And calculate the following characteristic quantities:

[0014]

[0015] Where α and β are the baseline morphology adjustment factors;

[0016] Calculate the target center control point using characteristic quantities. Positive morphological properties of rock and mineral surfaces Negative morphology properties of rock and mineral surfaces Their definitions and calculation methods are as follows:

[0017]

[0018] Repeat steps to Until the attribute data All data points were calculated accordingly, and the positive morphological properties of the entire rock and ore surface were finally obtained. Negative morphology properties of rock and mineral surfaces It is used to quantitatively describe and analyze the surface morphology and spatial composition information of minerals. Attached Figure Description

[0019] Figure 1 These are raw data images obtained from calcite samples collected in Exploration Zone 1, observed using a confocal microscope.

[0020] Figure 2 Is with Figure 1 Correspondingly, using the method of this invention, the positive morphological properties of the rock and mineral surface are calculated ( Figure 2 (a) and negative morphological properties of rock and mineral surfaces ( Figure 2 (b) The result of the graph;

[0021] Figure 3 These are raw data images obtained from calcite minerals collected in Exploration Zone 2, observed using a confocal microscope.

[0022] Figure 4 Is with Figure 3 Correspondingly, using the method of this invention, the positive morphological properties of the rock and mineral surface are calculated ( Figure 4 (a) and negative morphological properties of rock and mineral surfaces ( Figure 4 (b) The result of the graph. Detailed Implementation

[0023] Input confocal microscope image data of calcite samples from a certain exploration area 1. (like Figure 1 As shown in the figure, the spatial sampling interval of the data in the x and y directions is 1 micrometer (μm);

[0024] For example Figure 1 Performing a two-dimensional spatial domain Fourier transform on the confocal microscope image data shown, we obtain M. f (K x , K y Extract the wavenumber scaling factor using the following formula. :

[0025]

[0026] Establish confocal microscope image data Two-dimensional structure enhancement filter operator ,in, Using wavenumber scaling factor The constructed spatial domain filter aperture in the x and y directions, utilizing Confocal microscope image data Orientation scanning was performed to obtain attribute data that preserved and highlighted the structural features of the minerals. ,Right now:

[0027]

[0028] Where m and n represent the sampling point numbers in the x and y directions within the filter aperture, respectively;

[0029] attribute data Each data point Establish an aperture of [missing information] as the central target control point. High-order nonlinear spline smoothing function for two-dimensional elevation data Obtained through iterative search algorithm After obtaining the optimal feature control vector set, the optimized two-dimensional local spline smoothing function is obtained. ,in, and These represent the data point indices in the x and y directions, respectively;

[0030] use And calculate the following characteristic quantities:

[0031]

[0032] Using characteristic quantities, calculate the central target control point according to the following formula. Positive morphological properties of rock and mineral surfaces Negative morphology properties of rock and mineral surfaces :

[0033]

[0034] Repeat steps to Until the attribute data All data points were calculated accordingly, and the positive morphological properties of the entire rock and ore surface were finally obtained. (like Figure 2 (a) shows negative morphology properties of rock and mineral surfaces. (like Figure 2 (b) shown), from Figure 2 As can be seen, it clearly shows the spatial distribution of mineral cleavage or edges in different directions, exhibiting regional and periodic alternating characteristics. In addition, the contamination of other mineral particles is also clearly visible.

[0035] For example Figure 3 The confocal microscope image data of calcite minerals in a certain exploration area 2, as shown, were used to calculate the positive morphological properties of the rock and mineral surface according to the specific implementation method described above. (like Figure 4 (a) shows negative morphology properties of rock and mineral surfaces. (like Figure 4 (b) shown), from Figure 4 The calcite minerals exhibit a periodic banded distribution, revealing differences in their structural characteristics and reflecting the differential growth of the calcite mineral surface during the mineralization process.

[0036] In conclusion, Figure 2 and Figure 4 The clear and accurate information reflected in these mineral surface morphologies and spatial structures, in Figure 1 and Figure 3 In confocal microscope image data, it is difficult to reliably identify and determine, which demonstrates the superiority of the method of the present invention. Figure 2 and Figure 4 The surface morphology of rocks and minerals can provide important support for the phase analysis of calcite minerals in different work areas, the physicochemical conditions of mineralization and the analysis of mineral genesis. The method of this invention can be used to guide the identification of economic minerals and the exploration and development of mineral resources.

[0037] The advantages of this invention are:

[0038] Based on the characteristics of actual confocal microscope image data, an adaptive two-dimensional structure enhancement filtering operator and its spatial domain filtering aperture, as well as an azimuth scanning processing algorithm, were constructed to obtain attribute data that preserves and highlights the mineral structure features.

[0039] A high-order nonlinear spline smoothing function, an optimized two-dimensional local spline smoothing function, and an optimization determination algorithm for two-dimensional elevation data driven by actual confocal microscope image data were established.

[0040] It defines the positive and negative morphological properties of rock and mineral surfaces, as well as their analytical calculation methods, which can accurately and reliably quantitatively describe the spatial composition and distribution characteristics of minerals. This provides fundamental support for high-precision and high-efficiency identification, characteristic identification, analysis of physicochemical conditions of mineralization and genetic laws of minerals, and improves the level of research in fields such as mineral resource exploration, geological diagenesis and mineralization processes, and environmental science.

[0041] The above embodiments are only used to illustrate the present invention. The implementation steps of the method can be varied. Any equivalent transformations and improvements made on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A method for extracting surface morphology and texture features of rocks, ores, and minerals, comprising the following main steps: Input confocal microscope image data of specific rock and mineral samples. ,in, x and y represent the horizontal and vertical coordinates of the image data, respectively. The horizontal and vertical acquisition intervals are represented by dx and dy, respectively, in meters. The number of sampling points in the x and y directions are I and J, respectively; Confocal microscope image data Perform a two-dimensional spatial domain Fourier transform to obtain its two-dimensional wavenumber spectrum data M. f (K x , K y ), where K x , and K y The wavenumbers in the x and y directions of the image data are represented respectively. The wavenumber scaling factor is extracted using the following formula. : ； in, This indicates finding the maximum value; Establish confocal microscope image data Two-dimensional structure enhancement filter operator ,in, The filter aperture in the defined spatial domain along the x and y directions constitutes the wavenumber scaling factor. The function, using Confocal microscope image data After azimuth scanning, attribute data that preserves and highlights the structural features of the minerals were obtained. ,Right now: ； Where m and n represent the sampling point numbers in the x and y directions within the filter aperture, respectively; attribute data Each data point Establish an aperture of [missing information] as the target center control point. High-order nonlinear spline smoothing function for 3D elevation data Obtained through iterative search algorithm After obtaining the optimal feature control vector set, the optimized three-dimensional local spline smoothing function is obtained. ,in, and These represent the data point indices in the x and y directions, respectively; use And calculate the following characteristic quantities: ； Where α and β are the baseline morphology adjustment factors; Calculate the target center control point using characteristic quantities. Positive morphological properties of rock and mineral surfaces Negative morphology properties of rock and mineral surfaces Their definitions and calculation methods are as follows: ； Repeat steps to Until the attribute data All data points were calculated accordingly, and the positive morphological properties of the entire rock and ore surface were finally obtained. Negative morphology properties of rock and mineral surfaces It is used to quantitatively describe and analyze the surface morphology and spatial composition information of minerals.

Images