CN115115587A - Aggregate morphology feature characterization method and system based on Fourier transform interference function - Google Patents
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Abstract
The invention provides a method and a system for characterizing aggregate morphology features based on Fourier transform interference functions, wherein the method comprises the following steps: collecting a digital image of the aggregate morphology feature; automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of the aggregate surface 1 (x, y); three-dimensional coordinate matrix z for the aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x, y); aggregate morphological characteristics, including angle and texture, were analyzed to yield the final aggregate surface three-dimensional coordinate matrix z (x, y). The invention relates to a three-dimensional aggregate reconstructed from digital imagesOn the basis of the surface image, the shape, the angle and the texture of the aggregate are quantified, the angle and the texture are separated through a two-dimensional Fourier transform interference function, the morphological characteristics of the aggregate are analyzed, and the aggregate morphology can be rapidly and reliably characterized.
Description
Technical Field
The invention belongs to the technical field of road aggregate detection, and particularly relates to an aggregate morphology feature characterization method and system based on a Fourier transform interference function.
Background
Aggregates are an important component of asphalt concrete, cement concrete and granular substrates. The morphological characteristics of the aggregate, including shape, angle and surface texture, have a significant impact on its mechanical properties and performance. These morphological characteristics affect the aggregate interaction and the strength of the connection between the aggregate and the binder. Therefore, quantification of aggregate morphological characteristics is critical to better control aggregate quality and improve the performance of asphalt and cement concrete.
In the past decades, methods for studying and measuring aggregate morphological characteristics have been divided into two main categories: direct measurement and indirect measurement. The direct measurement method adopts a measurement method of visual observation or data image analysis, such as measuring the three-dimensional size of the aggregate by using a vernier caliper; however, the direct measurement method has long test time, large test amount and high subjectivity. The indirect measurement method estimates the shape characteristics of the aggregate according to the porosity or the shear strength of the aggregate, the measurement objects are the particle shape and the macro texture characteristics of the aggregate, the contour shape, the contour and the surface roughness cannot be separated, the true surface texture roughness is not, and the evaluation index is also empirical.
Whether a direct manual measurement method or an indirect measurement method is adopted, the morphological characteristics are difficult to measure accurately in time. Digital imaging technology provides another solution to this problem. Digital imaging techniques have been widely used for aggregate morphology characterization by analyzing digital images of the aggregate using various computational algorithms.
The evaluation method of the aggregate shape characteristics based on the digital image comprises the following steps: image erosion-dilation method, wavelet transform method. The image analyzer (UIAIA) of Illinois university adopts an image erosion-expansion method to research the surface roughness of aggregate, firstly, the image of aggregate particles is processed by an erosion-first expansion method, surface parameter ST values are adopted to characterize the surface roughness characteristics on the boundary, the rougher the surface, the more serious the loss of boundary information, and the larger the relative difference ST value of the area of the front surface and the back surface of the image processing. A second generation aggregate image Analyzer (AIMSII) adopts a wavelet transformation method to carry out multi-scale decomposition on an aggregate image to obtain the surface texture characteristics of aggregate particles; the rougher the aggregate surface texture, the greater its surface roughness parameter. These convergent imaging techniques use different imaging methods and incompatible computational theories to quantify shapes, angles, and surface textures in digital images, sometimes resulting in morphological feature values that cannot be compared. Some of these imaging techniques analyze morphological features based on 2D or semi-3D coordinates of the collection surface calculated from the digital image. These methods have limited accuracy because the two-dimensional or semi-three-dimensional aggregate coordinates cannot accurately represent the actual three-dimensional surface of the real aggregate.
Disclosure of Invention
The embodiment of the invention provides a method and a system for characterizing aggregate morphology features based on Fourier transform interference functions, which are used for solving the problem that the real aggregate morphology features cannot be rapidly and accurately characterized in the prior art.
The embodiment of the invention provides an aggregate morphology feature characterization method based on a Fourier transform interference function, which comprises the following steps:
s1: collecting a digital image of the aggregate morphology feature;
s2: automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of the aggregate surface 1 (x，y)；
S3: three-dimensional coordinate matrix z for the aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain the three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)；
S4: three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) analyzing aggregate morphological characteristics including angle and texture to obtain the final aggregateA three-dimensional coordinate matrix z (x, y) of the surface, wherein when analyzing the angle and texture of aggregate morphological features:
firstly, a three-dimensional coordinate matrix z of the aggregate surface is determined 2 (x, y) performing a discrete Fourier transform as a non-zero discrete function over a finite region in the spatial domain, x ≦ 0 ≦ N-1 and y ≦ 0 ≦ N-1, as follows:
then, the characterization of the angle and texture is performed as follows:
wherein, Z 2 (p, q) is z 2 (x, y) matrix of discrete Fourier transform coefficients in the frequency domain, p, q being the matrix Z 2 P-th row and q-th column in (p, q), j being a virtual root, a 0 Is z 2 Average value of (x, y), a (p, q) and b (p, q) are real part and imaginary part of the two-dimensional Fourier transform coefficient of the p-th row and the q-th column, N A Is a threshold value.
Preferably, the step S1 includes:
the method for acquiring the digital image of the aggregate morphology features comprises the following steps:
firstly, placing aggregate on a tray, and erecting a reflector above the tray in an inclined manner;
then, emitting laser with different set wavelengths into a reflector to obtain laser stripes, and projecting the laser stripes onto the top surface of the aggregate through reflection;
and finally, shooting a plurality of images of the aggregate projected by the laser stripes in the reflector, wherein the images comprise digital images shot by visible light and digital images shot by lasers with different set wavelengths.
Preferably, the digital image shot by visible light is used for carrying out edge detection on the boundary of the surface of the aggregate; the digital image shot by the laser with the first wavelength in different set wavelengths is used for generating a projection stripe pattern on the surface of the aggregate; the digital image shot by the laser with the second wavelength in different set wavelengths is used for stripe recognition, the projected stripe pattern is a main reference stripe, and the stripe pattern is a secondary reference stripe.
Preferably, the step S3 includes:
three-dimensional coordinate matrix z for the aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 The method of (x, y) is:
correcting by reprocessing the secondary reference stripe and combining the alternative phase data and the original phase diagram by utilizing the user-defined surface error to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)。
Preferably, when the secondary reference stripe is reprocessed, a data area with an error in positioning at the edge of each aggregate is calculated, error data is deleted from the image, and the secondary reference stripe is selected near the center of the defective data area.
Preferably, the three-dimensional coordinate matrix z of the aggregate surface is combined with the original phase map 1 The (x, y) phase map is shifted to match the quadratic reference fringe.
Preferably, the step S4 includes:
when the aggregate morphological characteristics are analyzed, the method also comprises the analysis of the shape, wherein the shape is expressed by sphericity, flatness ratio and elongation, and is specifically expressed as follows:
wherein SP represents sphericity, Fr represents flatness ratio, Δ represents elongation, and D s Denotes the shortest dimension, D, of the aggregate particles l Denotes the longest dimension, D, of the aggregate particles m Represents perpendicular to D s 、D l The dimension in the direction of the axis.
Preferably, the step S4 includes:
and the data in the three-dimensional coordinate matrix z (x, y) is characterized by the vertical distance between each point on the top surface of the aggregate and the bottom tray.
The embodiment of the invention provides an aggregate morphology feature characterization system based on a Fourier transform interference function, which comprises the following steps:
the digital image acquisition module: the digital image is used for collecting the aggregate morphology characteristics;
the digital image preprocessing module: is used for automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of an aggregate surface 1 (x，y)；
An aggregate error correction module: an aggregate error correction module: three-dimensional coordinate matrix z for aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)；
An aggregate analysis module: for a three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) analyzing the aggregate morphological characteristics, including angle and texture, to obtain a final aggregate surface three-dimensional coordinate matrix z (x, y), wherein the aggregate surface three-dimensional coordinate matrix z is analyzed for aggregate morphological characteristics angle and texture 2 (x, y) performing a discrete Fourier transform as a non-zero discrete function over a finite region in the spatial domain, 0 ≦ x ≦ N-1 and 0 ≦ y ≦ N-1The method specifically comprises the following steps:
angle and texture characterization was performed as follows:
wherein Z is 2 (p, q) is z 2 (x, y) matrix of discrete Fourier transform coefficients in the frequency domain, p, q being the matrix Z 2 P-th row and q-th column in (p, q), j being a virtual root, a 0 Is z 2 Average value of (x, y), a (p, q) and b (p, q) are real part and imaginary part of the two-dimensional Fourier transform coefficient of the p-th row and the q-th column, N A Is a threshold value.
The embodiment of the invention provides aggregate morphology feature characterization equipment based on a Fourier transform interference function, which is characterized by comprising a computer and used for executing the aggregate morphology feature characterization method based on the Fourier transform interference function.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a method and a system for characterizing aggregate morphology based on a Fourier transform interference function.
Drawings
In order to illustrate embodiments of the present invention or technical solutions in the prior art more clearly, the drawings which are needed in the embodiments will be briefly described below, so that the features and advantages of the present invention can be understood more clearly by referring to the drawings, which are schematic and should not be understood as limiting the present invention in any way, and for those skilled in the art, other drawings can be obtained based on these drawings without creative efforts. Wherein:
FIG. 1 is a flow chart of an aggregate morphology feature characterization method based on Fourier transform interference function;
FIG. 2 is an aggregate morphology feature characterization device based on Fourier transform interference function;
FIG. 3 is a sphericity profile of different aggregates;
FIG. 4 is a plot of flatness versus characterization values for different aggregates;
FIG. 5 is a graph of elongation eigenvalues for different aggregates;
FIG. 6 is an angular profile of different aggregates;
FIG. 7 is a graph of textural characteristics of different aggregates;
FIG. 8 is an aggregate morphology characterization system based on Fourier transform interference functions.
Reference numerals: 201-tray, 202-aggregate, 203-reflector, 204-Young double-pinhole interferometer, 205-optical fiber switch, 206-charge coupled device camera, 207-computer.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Example one
The aggregate morphology feature characterization method based on the Fourier transform interference function, as shown in FIG. 1, comprises the following steps:
s101: collecting a digital image of the aggregate morphology feature;
s102: automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of the aggregate surface 1 (x，y)；
S103: three-dimensional coordinate matrix z for the aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)；
S104: three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) aggregate morphological characteristics, including angle and texture, were analyzed to obtain the final aggregate surface three-dimensional coordinate matrix z (x, y).
The invention provides a method and a system for characterizing aggregate morphology based on a Fourier transform interference function.
The technical solution of the present invention is further illustrated by the following specific examples.
This example analytically characterizes 7 aggregates: blast furnace slag, copper ore, marble, crushed gravel, round gravel, iron ore, and limestone, each aggregate size being about 3/4 inches.
Further, in the step of S101, the method specifically includes:
as shown in fig. 2, a digital image of the aggregate morphology was acquired using a characterization instrument:
firstly, placing aggregates 202 on a tray 201, erecting a reflector 203 with an inclination angle of 45 degrees right above the tray 201, and respectively collecting 30 different samples for each aggregate 202 particle, wherein 210 aggregate particles are counted to obtain a statistically stable result;
then, using a Young double-pinhole interferometer 204 to emit laser with the wavelengths of 675nm and 805nm into a reflector to obtain laser fringes, and projecting the laser fringes onto the top surface of the aggregate through reflection;
finally, the CCD camera 206 is used to capture three images of the aggregate projected by the laser stripes in the mirror, one digital image captured with visible light and two digital images captured with laser light of 675nm and 805nm wavelength, respectively.
The laser shot stripe pattern with the wavelength of 675nm is a main reference stripe, and the laser shot stripe pattern with the wavelength of 805nm is a secondary reference stripe.
The digital image shot by visible light is used for carrying out edge detection on the surface boundary of the aggregate; the digital image shot by the laser with the wavelength of 675nm is used for generating a projection stripe pattern on the surface of the aggregate; the stripe pattern shot by the laser with the wavelength of 805nm is used for stripe recognition, the projection stripe pattern is a main reference stripe, and the stripe pattern is a secondary reference stripe.
Further, in the step S102, the method specifically includes:
the shot digital image is imported into a computer 207, and a three-dimensional coordinate matrix z of the aggregate surface is obtained by automatically identifying and reconstructing an aggregate surface map from the digital image by using 3D modeling software 1 (x，y)。
Further, in the step S103, the method specifically includes:
correcting the three-dimensional coordinate matrix z of the aggregate surface by reprocessing the secondary reference stripe and combining the alternate phase data with the original phase diagram by utilizing the user-defined surface error 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)，
Reprocessing of the secondary reference stripes: calculating a data area with error positioning at the edge of each aggregate, deleting error data from the image, and selecting a secondary reference stripe near the center of the bad data area to ensure that an error point is positioned between the primary reference stripe and the secondary reference stripe;
merging the alternating phase data with the raw phase map: three-dimensional coordinate matrix z of aggregate surface 1 The (x, y) phase map is shifted to match the quadratic reference fringe. At this point, the system has two data sets available: main reference stripe (M) th ) Of the original phase
And a secondary reference stripe (N) th ) Alternating phases of
Further, in the step of S104, the method specifically includes:
three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) aggregate morphology features including shape, angle and texture were analyzed. Sphericity characteristic map, flatness characteristic value map and elongation characteristic value map of different aggregates can be obtained, as shown in fig. 3, 4 and 5; angular characteristic maps and texture characteristic maps of different aggregates are obtained, as shown in fig. 6 and 7.
The shape is expressed in terms of sphericity, flatness ratio and elongation, and is specifically expressed as follows:
wherein SP represents sphericity, Fr represents flatness ratio, Δ represents elongation, and D s Denotes the shortest dimension, D, of the aggregate particles l Presentation setLongest dimension of the charge particles, D m Represents perpendicular to D s 、D l The dimension in the direction of the axis.
The angles and the textures are characterized on the basis of a two-dimensional Fourier transform method, and the method for characterizing on the basis of the two-dimensional Fourier transform method comprises the following steps:
firstly, a three-dimensional coordinate matrix z of the aggregate surface is determined 2 (x, y) performing a discrete Fourier transform as a non-zero discrete function over a finite region in the spatial domain, x ≦ 0 ≦ N-1 and y ≦ 0 ≦ N-1, as follows:
then, the characterization of the angle and texture is performed as follows:
wherein Z is 2 (p, q) is z 2 (x, y) matrix of discrete Fourier transform coefficients in the frequency domain, p, q being the matrix Z 2 P-th row and q-th column in (p, q), j being a virtual root, a 0 Is z 2 Average value of (x, y), a (p, q) and b (p, q) are real part and imaginary part of the two-dimensional Fourier transform coefficient of the p-th row and the q-th column, N A Is a threshold value.
And finally outputting a three-dimensional coordinate matrix z (x, y), wherein data in the three-dimensional coordinate matrix z (x, y) are represented as vertical distances between each point on the top surface of the aggregate and the bottom tray.
From the simulations fig. 3 to 7 it can be derived:
1) in the characterization of sphericity, the sphericity values of crushed gravel and blast furnace slag are larger than those of other types of aggregates, while those of marble and iron ore are smaller, and the spherical distributions of round gravel and limestone are very close;
2) in the representation of the flatness ratio, the flatness ratio of marble and round gravel is smaller, and the flatness ratio of iron ore is the largest;
3) in the characterization of the elongation, the elongation of crushed gravel is the largest, the elongation of iron ore is the smallest, and the elongation distribution of all other types of aggregates is very close;
4) in the characterization of the angle, the angle value of broken gravel is the largest, and the angle values of round gravel and iron ore are much smaller than those of other aggregates;
5) in the characterization of the texture, the surface of the round gravel is the smoothest, while the surface of the blast furnace slag is the roughest, the copper ore and the marble have similar surface textures, and the surface textures of the iron ore and the limestone are similar.
In conclusion, the aggregate characterization result obtained by simulation is consistent with the actual aggregate characteristics.
Example two
The embodiment of the invention also provides an aggregate morphology feature characterization system based on the fourier transform interference function, as shown in fig. 8, the aggregate morphology feature characterization system comprises:
digital image acquisition module 801: the digital image is used for collecting the aggregate morphology characteristics;
digital image pre-processing module 802: is used for automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of an aggregate surface 1 (x，y)；
Aggregate error correction module 803: three-dimensional coordinate matrix z for aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)；
An aggregate analysis module 804: for three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) analyzing aggregate morphological characteristics including angle and texture to obtain a three-dimensional coordinate matrix of the final aggregate surfacez (x, y), wherein the three-dimensional coordinate matrix z of the aggregate surface is used in analyzing the angles and textures of the aggregate morphological features 2 (x, y) performing a discrete Fourier transform as a non-zero discrete function over a finite region in the spatial domain, x ≦ 0 ≦ N-1 and y ≦ 0 ≦ N-1, as follows:
angle and texture characterization was performed as follows:
wherein Z is 2 (p, q) is z 2 (x, y) matrix of discrete Fourier transform coefficients in the frequency domain, p, q being the matrix Z 2 P-th row and q-th column in (p, q), j being a virtual root, a 0 Is z 2 Average value of (x, y), a (p, q) and b (p, q) are real part and imaginary part of the two-dimensional Fourier transform coefficient of the p-th row and the q-th column, N A Is a threshold value.
The system is used for realizing the aggregate morphology feature characterization method based on the Fourier transform interference function in the first embodiment, and details are not repeated here.
EXAMPLE III
The embodiment of the invention also provides aggregate morphology feature characterization equipment based on the Fourier transform interference function, and as shown in FIG. 2, the equipment comprises a computer 207.
The device is used for realizing the aggregate morphology feature characterization method based on the Fourier transform interference function in the first embodiment, and details are not repeated here.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. It will be apparent to those skilled in the art that other variations and modifications may be made on the basis of the above description. And are neither required nor exhaustive of all embodiments. And obvious modifications or variations such as would be apparent to one skilled in the art are intended to be included within the scope of the invention.
Claims (10)
1. A method for characterizing aggregate morphology features based on Fourier transform interference functions is characterized by comprising the following steps:
s1: collecting a digital image of the aggregate morphology feature;
s2: automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of the aggregate surface 1 (x，y)；
S3: three-dimensional coordinate matrix z for the aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)；
S4: three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) analyzing aggregate morphological features, including angle and texture, to obtain a final aggregate surface three-dimensional coordinate matrix z (x, y), wherein when analyzing aggregate morphological features angle and texture:
firstly, a three-dimensional coordinate matrix z of the aggregate surface is determined 2 (x, y) performing a discrete Fourier transform as a non-zero discrete function over a finite region in the spatial domain, x ≦ 0 ≦ N-1 and y ≦ 0 ≦ N-1, as follows:
then, characterization of angles and textures is performed, specifically as follows:
wherein Z is 2 (p, q) is z 2 (x, y) matrix of discrete Fourier transform coefficients in the frequency domain, p, q being the matrix Z 2 P-th row and q-th column in (p, q), j being a virtual root, a 0 Is z 2 Average value of (x, y), a (p, q) and b (p, q) are real part and imaginary part of the two-dimensional Fourier transform coefficient of the p-th row and the q-th column, N A Is a threshold value.
2. The method for characterizing the aggregate morphology feature based on the Fourier transform interference function as claimed in claim 1, wherein the method for acquiring the digital image of the aggregate morphology feature in the step S1 is as follows:
firstly, placing aggregate on a tray, and erecting a reflector above the tray in an inclined manner;
then, emitting laser with different set wavelengths into a reflector to obtain laser stripes, and projecting the laser stripes onto the top surface of the aggregate through reflection;
and finally, shooting a plurality of images of the aggregate projected by the laser stripes in the reflector, wherein the images comprise digital images shot by visible light and digital images shot by lasers with different set wavelengths.
3. The aggregate morphology feature characterization method based on Fourier transform interference function according to claim 2, wherein the digital image shot by visible light is used for edge detection of aggregate surface boundary; the digital image shot by the laser with the first wavelength in different set wavelengths is used for generating a projection stripe pattern on the surface of the aggregate; the fringe pattern shot by the laser with the second wavelength in different set wavelengths is used for fringe identification, the projection fringe pattern is a main reference fringe, and the fringe pattern is a secondary reference fringe.
4. The method for characterizing the aggregate morphology based on Fourier transform interference function according to claim 3, wherein the three-dimensional coordinate matrix z of the aggregate surface in the step S3 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 The method of (x, y) is:
correcting by reprocessing the secondary reference stripe and combining the alternate phase data and the original phase diagram by utilizing the user-defined surface error to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)。
5. The method for characterizing the aggregate morphology based on the Fourier transform interference function according to claim 4, wherein when the secondary reference fringes are reprocessed, a data area with a wrong positioning at the edge of each aggregate is calculated, the wrong data is deleted from the image, and the secondary reference fringes are selected near the center of a poor data area.
6. The method for characterizing the aggregate morphology based on Fourier transform interference function according to claim 4, wherein the three-dimensional coordinate matrix z of the aggregate surface is combined with the original phase map when the alternate phase data is combined with the original phase map 1 The (x, y) phase map is shifted to match the quadratic reference fringe.
7. The method for characterizing the morphology of the aggregate according to claim 1, wherein the step of analyzing the morphology of the aggregate in step S4 further comprises analyzing the shape, wherein the shape is represented by sphericity, flatness ratio and elongation, and is specifically represented as follows:
wherein SP represents sphericity, Fr represents flatness ratio, Δ represents elongation, and D s Denotes the shortest dimension, D, of the aggregate particles l Denotes the longest dimension, D, of the aggregate particles m Represents perpendicular to D s 、D l The dimension in the direction of the axis.
8. The method for characterizing aggregate morphology features based on Fourier transform interference function according to claim 1, wherein the data in the three-dimensional coordinate matrix z (x, y) in the step S4 is characterized in that the data is the vertical distance between each point on the top surface of the aggregate and the bottom tray.
9. An aggregate morphology characterization system based on a Fourier transform interference function, comprising:
the digital image acquisition module: the digital image is used for collecting the aggregate morphology characteristics;
the digital image preprocessing module: is used for automatically identifying and reconstructing an aggregate surface map from the digital image to obtain a three-dimensional coordinate matrix z of an aggregate surface 1 (x，y)；
An aggregate error correction module: three-dimensional coordinate matrix z for aggregate surface 1 (x, y) reprocessing to modify and improve the reconstructed aggregate surface map to obtain a three-dimensional coordinate matrix z of the aggregate surface 2 (x，y)；
An aggregate analysis module: for three-dimensional coordinate matrix z based on the aggregate surface 2 (x, y) analysis of aggregate morphologyObtaining a final three-dimensional coordinate matrix z (x, y) of the aggregate surface, wherein the three-dimensional coordinate matrix z of the aggregate surface is obtained when analyzing the angles and textures of the aggregate morphological characteristics 2 (x, y) performing a discrete Fourier transform as a non-zero discrete function over a finite region in the spatial domain, x ≦ 0 ≦ N-1 and y ≦ 0 ≦ N-1, as follows:
angle and texture characterization was performed as follows:
wherein Z is 2 (p, q) is z 2 (x, y) matrix of discrete Fourier transform coefficients in the frequency domain, p, q being the matrix Z 2 P-th row and q-th column in (p, q), j being a virtual root, a 0 Is z 2 Average value of (x, y), a (p, q) and b (p, q) are real part and imaginary part of the two-dimensional Fourier transform coefficient of the p-th row and the q-th column, N A Is a threshold value.
10. An apparatus for characterizing the morphology of an aggregate based on fourier transform interference functions, comprising a computer for performing the method of any one of claims 1 to 8.
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