A method for synchronous matching and three-dimensional positioning of snowflakes with large field of view and multiple perspectives

Abstract

The present invention provides a method for synchronously matching and three-dimensionally positioning snowflakes with a large field of view and multiple perspectives. The method comprises: performing particle detection on snowflakes using a telecentric camera to obtain single-perspective centroid coordinates; projecting the single-perspective centroid coordinates of a first plane into three-dimensional space to obtain a first projection line; projecting the first projection line onto a second plane and a third plane according to geometric mapping parameters to obtain second and third projection lines; calculating the Euclidean distances of all particles on the second and third projection lines, screening them based on the Euclidean distances to obtain candidate particles; performing multi-perspective reverse mapping on the candidate particles, and determining a three-dimensional positioning cube based on the maximum physical size of the particles; and verifying the positioning of the three-dimensional positioning cube using geometric mapping parameters to obtain a verification result. Based on a geometric constraint model, this method maps the single-perspective particle centroids into three-dimensional space to form spatial lines, improving the efficiency of three-dimensional reconstruction calculations and the accuracy of snowflake measurement.

Description

Technical Field

[0001] The present invention relates to the field of atmospheric science observation technology, and in particular to a method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple viewing angles. Background Art

[0002] Accurate measurement of microphysical characteristics of snowflakes, such as their three-dimensional shape and velocity, is essential data for atmospheric science, meteorological radar remote sensing, and quantitative estimation of winter precipitation. Among existing technologies for precise snowflake measurement, the two-dimensional video raindrop spectrometer (2DVD) based on dual-line array scanning suffers from morphological splicing distortion. The orthogonal array camera solution (ZL20161095178.0) struggles to deconstruct the microscopic fractal features of snowflakes. The Multi-Angle Snowflake Camera (MASC) achieves three-dimensional reconstruction through multi-view imaging combined with the Visual Hull algorithm. However, its narrow field of view and minimal depth of field allow it to capture only a small number of snowflakes at a time, making it unable to meet the large-scale sampling requirements of minute-level particle size distribution (PSD) statistics. Furthermore, MASC relies on matching morphological features of two-dimensional snowflake images (such as edges and fractal structures), and its narrow field of view makes it incapable of processing high-density particles in a large field of view.

[0003] To meet the needs of particle measurement in large sampling spaces, the particle multi-angle stereo imaging measurement device uses three-angle telecentric cameras to expand the effective observation volume to 775cm 3 Although the system has achieved 3D reconstruction to a certain extent, it still faces many core challenges in matching and positioning: First, the mismatching problem caused by highly similar particles: Traditional methods rely on the two-dimensional morphological features of snowflakes (such as edges and fractal structures) for cross-view matching, but in large fields of view or dense snowflake scenes, a large number of particles have highly similar morphologies, which leads to intensified matching conflicts and a significant increase in the mismatching rate; Second, the computational efficiency bottleneck under large fields of view: As the observation volume expands to 775cm 3 , the number of particles surges, and the computational complexity of the matching algorithm based on morphological feature traversal search grows exponentially, making it difficult to meet real-time requirements; thirdly, the geometric constraints of telecentric imaging fail: the parallel light imaging characteristics of the telecentric camera eliminate the influence of distance on the imaging size. The traditional morphological matching logic that relies on perspective projection (such as the size consistency assumption) is no longer applicable, and a new geometric constraint model is urgently needed to achieve spatial association; fourthly, the problem of positioning in the three-dimensional space calculation domain: the traditional method needs to traverse the entire sampling space for calculation, facing a computing power bottleneck. The increase in the observation volume causes the number of particles to grow exponentially, further exacerbating the computational burden. Therefore, it is very necessary to design a large-field-of-view multi-perspective snowflake synchronous matching and three-dimensional positioning method. Summary of the Invention

[0004] The purpose of the present invention is to provide a large-field-of-view multi-perspective snowflake synchronous matching and three-dimensional positioning method. Based on the geometric constraint model, the single-perspective particle center of mass is reversely mapped to the world coordinate system to form a spatial straight line to achieve accurate matching, thereby improving the three-dimensional reconstruction calculation efficiency and the accuracy of snowflake measurement.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A method for synchronously matching and three-dimensional positioning of snowflakes with a large field of view and multiple viewing angles comprises the following steps:

[0007] The snowflakes are detected by three telecentric cameras to obtain three single-view centroid coordinates.

[0008] Reversely project the coordinates of the centroid of the single view of the first plane into the three-dimensional space to obtain a first projection line;

[0009] Projecting the first projection line onto the second plane and the third plane respectively according to the geometric mapping parameters to obtain a second projection line and a third projection line;

[0010] Calculate the Euclidean distances of all particles on the second and third projection lines, and screen them based on the Euclidean distances to obtain candidate particles;

[0011] Perform multi-view reverse mapping on the candidate particles and determine the three-dimensional positioning cube based on the maximum physical size of the particles in the two-dimensional image;

[0012] The three-dimensional positioning cube is positioned and verified through geometric mapping parameters to obtain verification results.

[0013] Optionally, three telecentric cameras are used to perform particle detection on snowflakes respectively to obtain three single-view centroid coordinates. Specifically, the snowflake image is binarized based on the local grayscale features of the snowflakes to obtain a binary image, and the geometric center coordinates of the binarized image are calculated to obtain the single-view centroid coordinates.

[0014] Optionally, the expression for binarization processing is: T(u,v)=μ(u,v)-C; wherein T(u,v) is the segmentation threshold, (u,v) is the two-dimensional coordinate of the pixel, μ(u,v) is the neighborhood grayscale mean, and C is the sensitivity coefficient;

[0015] The calculation formula of the single-view centroid coordinates is: Where N is the total number of pixels in the connected area of ​​the binary image, u i is the horizontal coordinate of the i-th pixel, v i is the vertical coordinate of the i-th pixel.

[0016] Optionally, the single-view centroid coordinates of the first plane are reversely projected into three-dimensional space to obtain a first projection line. Specifically, the relationship between the three-dimensional coordinates and the two-dimensional coordinates of the single-view centroid coordinates is reversely mapped and solved according to the geometric constraint projection equation of telecentric imaging to obtain the first projection line.

[0017] Optionally, the expression of the geometric constraint projection equation is: Among them, KM0 is the geometric mapping parameter of the first plane, (X w , Y w , Z w ) is the three-dimensional coordinate of the single-view centroid coordinate of the first plane, and (u0, v0) is the two-dimensional coordinate of the single-view centroid coordinate of the first plane;

[0018] The expression of the first projection line is: Where U is the direction vector, V is the base point, and t is an arbitrary real number.

[0019] Optionally, the expression of the second projection line is: u1=a1t+b1; v1=c1t+d1; wherein (u1, v1) are the two-dimensional coordinates of the single-view centroid coordinates of the second plane, (a1, c1) are the direction parameters of the second projection line, and (b1, d1) are the intercept parameters of the second projection line;

[0020] The expression of the third projection straight line is: u2=a2t+b2; v2=c2t+d2; where (u2, v2) are the two-dimensional coordinates of the single-perspective centroid coordinates of the third plane, (a2, c2) are the direction parameters of the third projection straight line, and (b2, d2) are the intercept parameters of the third projection straight line.

[0021] Optionally, the Euclidean distance is calculated as: Among them, (u, v) is the two-dimensional coordinate of the pixel, d is the Euclidean distance, and a, b, and c are the coefficients of the equation.

[0022] Optionally, performing multi-view reverse mapping on the candidate particles and determining a three-dimensional positioning cube in combination with the maximum physical size of the particles in the two-dimensional image includes:

[0023] Obtaining a three-dimensional intersection point according to the first projection line and the third projection line;

[0024] Based on the three-dimensional intersection point and the maximum physical size of the particle, the side length of the minimum enclosing cube is determined to obtain a three-dimensional positioning cube.

[0025] Optionally, positioning verification is performed on the three-dimensional positioning cube using geometric mapping parameters to obtain verification results, including:

[0026] Project the three-dimensional intersection point onto the third plane through the third projection line to obtain a third projection point;

[0027] If the third projection point is within the particle outline on the third plane, the verification result is determined as successful positioning;

[0028] If the third projection point is not located within the particle outline of the third plane, the verification result is determined to be a positioning failure.

[0029] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the present invention provides a large-field-of-view multi-perspective snowflake synchronous matching and three-dimensional positioning method, the method comprising: using three telecentric cameras to perform particle detection on the snowflakes respectively to obtain three single-perspective centroid coordinates; reversely projecting the single-perspective centroid coordinates of the first plane into three-dimensional space to obtain a first projection line; projecting the first projection line onto the second plane and the third plane respectively according to geometric mapping parameters to obtain second and third projection lines; calculating the Euclidean distances of all particles on the second and third projection lines, and screening them according to the Euclidean distances to obtain candidate particles; performing multi-perspective reverse mapping on the candidate particles, and determining a three-dimensional positioning cube based on the maximum physical size of the particles in the two-dimensional image; and verifying the positioning of the three-dimensional positioning cube using geometric mapping parameters to obtain a verification result. Based on a geometric constraint model, the method reversely maps the single-perspective particle centroids to the world coordinate system to form a spatial line, achieving accurate matching and improving the efficiency of three-dimensional reconstruction calculations and the accuracy of snowflake measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 This is a flow chart of the multi-view snowflake three-dimensional positioning method of the present invention;

[0032] Figure 2 Schematic diagram of the steps for determining a three-dimensional positioning cube according to the present invention. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] like Figure 1 As shown, the present invention provides a method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives, comprising the following steps:

[0036] Step 100: Detect snowflake particles using three telecentric cameras to obtain three single-view centroid coordinates. This specifically includes:

[0037] The snowflake image is binarized using a background separation method based on the local grayscale features of snowflakes, and the segmentation threshold is adjusted based on the local grayscale mean to separate the snowflakes and the background, thereby obtaining a binary image.

[0038] Specifically, the expression for binarization is:

[0039] T(u,v)=μ(u,v)-C;

[0040] Wherein, T(u,v) is the segmentation threshold, (u,v) is the two-dimensional coordinate of the pixel, μ(u,v) is the neighborhood grayscale mean, and C is the sensitivity coefficient, which is 0.4 in this embodiment;

[0041] The geometric center coordinates are calculated based on the connected areas of the binary image to obtain the single-view centroid coordinates.

[0042] Specifically, the calculation formula for the single-view centroid coordinates is:

[0043]

[0044] Where N is the total number of pixels in the connected area of ​​the binary image, u i is the horizontal coordinate of the i-th pixel, v i is the vertical coordinate of the i-th pixel.

[0045] Step 200: reversely projecting the coordinates of the centroid of the single-view of the first plane into the three-dimensional space to obtain a first projection line;

[0046] Specifically, assuming that the coordinates of the centroid of a single view in the three-dimensional space WCS are (X w , Y w , Z w ), the two-dimensional coordinates in the first plane are (u0, v0), and the geometric mapping parameter KM0 corresponding to the first plane is a 2×4 matrix, so the expression of the geometric constraint projection equation of the first plane is: The reverse mapping of the visual column is to solve (X w , Y w , Zw ) process, and after solving, the first projection line L1 in the three-dimensional space is obtained. The parameters of L1 are expressed as:

[0047]

[0048] Where U is the direction vector, V is the base point, and t is an arbitrary real number.

[0049] Step 300: Projecting the first projection line onto the second plane and the third plane respectively according to the geometric mapping parameters to obtain a second projection line and a third projection line;

[0050] Specifically, L1 is projected onto the second plane and the third plane through the geometric mapping parameters KM1 and KM2 of the second plane and the third plane, respectively, to obtain the geometric constraint projection equations of the second plane and the third plane, respectively, and the expressions are:

[0051]

[0052] Among them, (u1, v1) is the two-dimensional coordinate of the single-view centroid coordinate of the second plane, (u2, v2) is the two-dimensional coordinate of the single-view centroid coordinate of the third plane, X w (t), Y w (t) and Z w (t) are the parametric equations of the coordinates of the projection line in three-dimensional space. After solving them, we can get the second projection line L2 and the third projection line L3. Their linear function expressions are:

[0053] L2: u1=a1t+b1; v1=c1t+d1;

[0054] L3: u2=a2t+b2; v2=c2t+d2;

[0055] Among them, the range of u1 and v1 is within the image range of the second plane, the range of u2 and v2 is within the image range of the third plane, (a1, c1) is the direction parameter of the second projection line, which is determined by the geometric mapping parameter KM1 of the second plane, (b1, d1) is the intercept parameter of the second projection line, which is jointly determined by KM1 and the base point of the first projection line, (a2, c2) is the direction parameter of the third projection line, which is determined by the geometric mapping parameter KM2 of the third plane, and (b2, d2) is the intercept parameter of the third projection line, which is jointly determined by KM2 and the base point of the first projection line.

[0056] Step 400: Calculate the Euclidean distances of all particles on the second projection line and the third projection line, and screen them based on the Euclidean distances to obtain candidate particles;

[0057] Specifically, the Euclidean distance from the center of mass of all particles on all projection lines to the corresponding projection lines is calculated. The calculation formula of the Euclidean distance is:

[0058]

[0059] Where d is the Euclidean distance, ax + by + c = 0 is the epipolar equation, and a, b, and c are the epipolar equation coefficients. These coefficients are derived from the geometric mapping parameters KM1 and KM2 of the second and third planes using the fundamental matrix, representing the mathematical constraints of the projected line in the two-dimensional plane. If d ≤ ∈, the particle is identified as a candidate particle, and the remaining particles are eliminated. The threshold ∈ in this embodiment is 2 pixels.

[0060] Step 500: Perform multi-view reverse mapping on the candidate particles, and determine a three-dimensional positioning cube based on the maximum physical size of the particles in the two-dimensional image;

[0061] Specific as Figure 2 As shown, the candidate particle is a certain particle, and its centroid coordinates in the first plane, the second plane, and the third plane are defined as P1, P2, and P3, respectively. The projection line L1 of the candidate particle is obtained through step 200; then the projection line L2 of the candidate particle is obtained through step 300, and the point P2' closest to P2 is found on L2; similarly, the projection line L3 of point P2' is obtained through step 300, and the three-dimensional intersection point P is obtained based on L1 and L3. c Because L1 and L3 are destined to intersect in the three-dimensional space WCS, P c It is considered as the center of mass of the three-dimensional positioning cube. The minimum side length of the enclosing cube is determined by the maximum physical size of the particle, and finally the three-dimensional positioning cube is obtained.

[0062] Step 600: Verify the positioning of the 3D positioning cube using geometric mapping parameters to obtain a verification result. Specifically, the steps are as follows: project the 3D intersection point onto a third plane using a third projection line to obtain a third projection point; if the third projection point is within the particle outline on the third plane, the verification result is determined to be a successful positioning; if the third projection point is not within the particle outline on the third plane, the verification result is determined to be a failed positioning.

[0063] The beneficial effects of the present invention are as follows:

[0064] 1) The three-dimensional positioning of particles is achieved by combining the intersection of visual columns, and the effective computational domain (three-dimensional positioning cube) for three-dimensional reconstruction of particles is determined;

[0065] 2) It abandons the reliance on the two-dimensional morphological features of snowflakes and achieves efficient matching of hundreds of particles per second in a large sampling space, thus improving matching efficiency;

[0066] 3) The computational domain limits the range of particle three-dimensional reconstruction, significantly reducing computational complexity and enabling efficient batch processing.

[0067] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0068] The present invention uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives, characterized in that: The steps include: The snowflakes are detected by three telecentric cameras to obtain three single-view centroid coordinates. Reversely projecting the single-view centroid coordinates of the first plane into three-dimensional space to obtain a first projection line; Projecting the first projection line onto the second plane and the third plane respectively according to the geometric mapping parameters to obtain a second projection line and a third projection line; Calculating the Euclidean distances of all particles on the second projection line and the third projection line, and screening according to the Euclidean distances to obtain candidate particles; Performing multi-view reverse mapping on the candidate particles, and determining a three-dimensional positioning cube in combination with the maximum physical size of the particles in the two-dimensional image; Positioning verification is performed on the three-dimensional positioning cube using the geometric mapping parameters to obtain a verification result.

2. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 1, characterized in that: The snowflakes are detected by three telecentric cameras respectively to obtain three single-view centroid coordinates. Specifically, the snowflake image is binarized based on the local grayscale features of the snowflakes to obtain a binary image, and the geometric center coordinates of the binarized image are calculated to obtain the single-view centroid coordinates.

3. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 2, characterized in that: The expression of the binarization process is: T(u,v)=μ(u,v)-C; wherein T(u,v) is the segmentation threshold, (u,v) is the two-dimensional coordinate of the pixel, μ(u,v) is the neighborhood grayscale mean, and C is the sensitivity coefficient; The calculation formula of the single-view centroid coordinates is: Where N is the total number of pixels in the connected area of ​​the binary image, u i is the horizontal coordinate of the i-th pixel, v i is the vertical coordinate of the i-th pixel.

4. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 1, characterized in that: The single-view centroid coordinates of the first plane are reversely projected into three-dimensional space to obtain a first projection line. Specifically, the relationship between the three-dimensional coordinates and the two-dimensional coordinates of the single-view centroid coordinates is reversely mapped and solved by the visual column according to the geometric constraint projection equation of telecentric imaging to obtain the first projection line.

5. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 4, characterized in that: The expression of the geometric constraint projection equation is: Wherein, KM0 is the geometric mapping parameter of the first plane, (X w , Y w , Z w ) is the three-dimensional coordinate of the centroid coordinate of the single view on the first plane, and (u0, v0) is the two-dimensional coordinate of the centroid coordinate of the single view on the first plane; The expression of the first projection line is: Where U is the direction vector, V is the base point, and t is an arbitrary real number.

6. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 1, characterized in that: The expression of the second projection line is: u1=a1t+b1; v1=c1t+d1; Wherein, (u1, v1) is the two-dimensional coordinate of the centroid coordinate of the single view of the second plane, (a1, c1) is the direction parameter of the second projection line, and (b1, d1) is the intercept parameter of the second projection line; The expression of the third projection straight line is: u2=a2t+b2; v2=c2t+d2; where (u2, v2) are the two-dimensional coordinates of the single-perspective centroid coordinates of the third plane, (a2, c2) are the direction parameters of the third projection straight line, and (b2, d2) are the intercept parameters of the third projection straight line.

7. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 1, characterized in that: The calculation formula of the Euclidean distance is: Among them, (u, v) is the two-dimensional coordinate of the pixel, d is the Euclidean distance, and a, b, and c are the coefficients of the equation.

8. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 1, characterized in that: Performing multi-view reverse mapping on the candidate particles and determining a three-dimensional positioning cube in combination with the maximum physical size of the particles in the two-dimensional image, including: Obtaining a three-dimensional intersection point according to the first projection straight line and the third projection straight line; Based on the three-dimensional intersection point and in combination with the maximum physical size of the particle, the minimum side length of the enclosing cube is determined to obtain the three-dimensional positioning cube.

9. The method for synchronous matching and three-dimensional positioning of snowflakes with a large field of view and multiple perspectives according to claim 8, characterized in that: Performing positioning verification on the three-dimensional positioning cube using the geometric mapping parameters to obtain a verification result includes: Projecting the three-dimensional intersection point onto the third plane through the third projection line to obtain a third projection point; If the third projection point is located within the particle outline on the third plane, the verification result is determined as successful positioning; If the third projection point is not located within the particle contour of the third plane, the verification result is determined to be a positioning failure.

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