Three-dimensional measurement method of irregular particles based on dual-angle defocus interferogram

Abstract

This invention discloses a method for three-dimensional measurement of irregular particles based on dual-angle defocused interferometric images. A dual-angle laser interferometric image acquisition system is constructed to acquire defocused interferometric images I1 and I2 corresponding to the two detection angles of the irregular particle being measured. Defocused speckle images M1 and M2 are extracted. Reconstructed two-dimensional shape images L1 and L2 are obtained from the defocused speckle images M1 and M2. The reconstructed two-dimensional shape images L1 and L2 are smoothed and thresholded to extract the contour region of the irregular particle, resulting in two-dimensional shape contour region images K1 and K2. Pixel alignment processing is performed on the two-dimensional shape contour images K1 and K2 to obtain smoothed and pixel-aligned dual-angle two-dimensional shape images J1 and J2. Three-dimensional shape reconstruction is performed by projecting the contour images to obtain the three-dimensional point cloud H of the irregular particle to be recovered. This invention has better robustness compared to focused images.

Description

Technical Field

[0001] This invention belongs to the field of optical measurement technology, and in particular relates to a three-dimensional measurement method for irregular particles based on dual-angle defocused interferometric images. Background Technology

[0002] Submillimeter-sized particles mainly include industrial dust, combustion particles, and cloud particles. The morphology of particulate matter primarily affects its physical properties, such as the combustion efficiency of combustible materials and the light scattering and absorption characteristics of cloud particles. Therefore, studying the shape characteristics of irregular particles is of great significance for industrial production, environmental protection, and atmospheric research. Currently, there are relatively abundant particle measurement methods based on laser interferometry theory, but they mainly focus on the measurement of particle two-dimensional morphology and size.

[0003] Chinese patent CN108593528B discloses a "Method for Measuring the Shape and Size of Non-Spherical Rough Particles Based on Laser Interference." This method uses two CCD detectors to simultaneously acquire focused and defocused images of the particles. The focused image provides the two-dimensional shape information of the particles, while the defocused image's two-dimensional autocorrelation yields the particle's size information. This method can obtain relatively accurate two-dimensional particle information, but the acquisition of the focused image places high demands on the system's focusing accuracy, limiting its application range.

[0004] Chinese patent CN108562522B discloses a method for simultaneously measuring particle size and refractive index. This method uses two laser beams to irradiate the particle, acquiring focused and defocused images of the scattered light at a 90° scattering angle and in the side-scattering region, respectively. The particle size and refractive index are calculated based on the distance between the scattering points and the number of defocused interference fringes. This method achieves relatively accurate particle size measurement, but the measured particles are limited to transparent spherical particles.

[0005] Chinese patent CN116698708A discloses a "Method for Reconstructing the Shape of Irregular Particles Based on Phase Retrieval Algorithm." This method uses a laser interferometric particle imaging system to acquire defocused speckle images of irregular particles, and then reconstructs the two-dimensional shape of the measured particle from the defocused speckle image using a phase retrieval algorithm. This method has a simple acquisition system and achieves good particle shape reconstruction, but it is limited to two-dimensional shape measurement.

[0006] The aforementioned patents are all successful examples of measuring particle size and shape information using laser interferometric particle imaging, but there is currently a lack of methods for measuring the three-dimensional shape of particles based on laser interferometric particle imaging. Summary of the Invention

[0007] The purpose of this invention is to propose a three-dimensional measurement method for irregular particles based on dual-angle defocused interferometric images. Based on the two-dimensional shape information of the irregular particles to be measured acquired by dual-angle defocused interferometric images, the three-dimensional shape of the particles to be measured is obtained by using a contour-based three-dimensional reconstruction method.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0009] A method for three-dimensional measurement of irregular particles based on dual-angle defocused interferometry images, comprising:

[0010] Step 1: Build a dual-angle laser interferometric image acquisition system. Under the same defocus distance, use the imaging end CCD camera to detect and acquire the defocused interferometric images I1 and I2 corresponding to the two detection angles (i.e., scattering angles α and β) of the irregular particles being measured.

[0011] Step 2: Crop the defocused interference images I1 and I2, and extract the defocused speckle images M1 and M2 within the center N1×N1 pixel range of the defocused interference images I1 and I2;

[0012] Step 3: Use the phase retrieval algorithm to reconstruct the two-dimensional shape of the irregular particle being measured from the defocused speckle images M1 and M2, and obtain the reconstructed two-dimensional shape images L1 and L2.

[0013] Step 4: Smooth the reconstructed two-dimensional shape images L1 and L2 obtained in Step 3. Then, perform threshold segmentation on the smoothed reconstructed two-dimensional shape images L1 and L2 to fill the gaps caused by the threshold segmentation and extract the contour region of the irregular particles being measured to obtain two-dimensional shape contour region images K1 and K2.

[0014] Step 5: Perform pixel alignment processing on the two-dimensional shape contour images K1 and K2: Fill the perimeter of the two images with pixels with a gray value of 0. Centered on the contour region image, fill the two-dimensional shape contour images to the same pixel size N2×N2 to obtain the smoothed and pixel-aligned two-dimensional shape images J1 and J2.

[0015] Step 6: Use Matlab software to reconstruct the three-dimensional shape of the contour image projection, including projecting images J1 and J2 along the x-axis and y-axis in three-dimensional space respectively, and generating a point cloud H of the irregular particles to be recovered in the intersection of the contour regions.

[0016] Compared with existing technologies, the three-dimensional measurement method for irregular particles based on dual-angle defocused interferometric images proposed in this invention can achieve the following beneficial technical effects: 1) No additional illumination optical path is required, and the measurement system is simple; 2) Shape detection based on defocused images has better robustness than shape detection based on focused images; 3) The three-dimensional reconstruction method based on contours is computationally simple. Attached Figure Description

[0017] Figure 1 This is a flowchart of the three-dimensional measurement method for irregular particles based on dual-angle defocused interferometric images according to the present invention.

[0018] Figure 2 This is a schematic diagram of a specific embodiment of the dual-angle defocusing interferometric image acquisition system of the present invention;

[0019] Figure 3 Example diagram of particle 3D reconstruction process;

[0020] Figure 4 This is a schematic diagram illustrating a 3D contour projection example.

[0021] Figure label:

[0022] 1. Laser, 2. Beam expander and collimator, 21. Microscope objective, 22. Pinhole filter, 23. Aperture, 24. Collimating lens, 3, 5. First and second imaging lenses, 4, 6. First and second CCD cameras, 7. Irregular particles to be measured.

[0023] A. The three-dimensional shape of the particle to be tested; M1 and M2 are the centers of the defocused speckle images extracted from the two detection angles; L1 and L2 are the two-dimensional shapes obtained by the phase retrieval algorithm; J1 and J2 are the two-dimensional shapes of the particle after smoothing and pixel alignment; H is the point cloud of the particle's three-dimensional reconstruction. Detailed Implementation

[0024] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] like Figure 1 As shown, this invention provides a method for three-dimensional measurement of irregular particles based on dual-angle defocused interferometric images. The specific implementation scheme is as follows:

[0026] Step 1: Set up a dual-angle laser interferometry image acquisition system;

[0027] Step 2: At the same defocus distance, use the imaging end CCD camera to detect and acquire the defocus interference images I1 and I2 corresponding to the two detection angles (i.e., scattering angles α and β) of the irregular particles being measured. The two scattering angles α and β are used as the acquisition angles for defocus image acquisition. The acquired defocus images at this time carry the shape information of the irregular particles being measured at the two acquisition angles (i.e., scattering angles α and β). The two scattering angles α and β have an orthogonal relationship, i.e., α + β = 90° or 360° - (α + β) = 90°. Under this relationship, it can be guaranteed that the most non-repetitive particle information can be acquired.

[0028] Step 3: Crop the defocused interferometric images I1 and I2. Since the defocused interferometric image is essentially a spectral image, only a portion of the image needs to be cropped to complete the analysis and calculation. Crop the defocused speckle images M1 and M2 within the center N1×N1 pixel range of the defocused interferometric images I1 and I2. To ensure information integrity, the size of the cropped image pixels N1×N1 should be larger than the pixel size occupied by the target particle image when the camera is in the focused position.

[0029] Step 4: Use the phase retrieval algorithm to reconstruct the two-dimensional shape of the irregular particle being measured from the defocused speckle images M1 and M2, and obtain the reconstructed two-dimensional shape images L1 and L2.

[0030] Specifically, the two-dimensional shape reconstruction process of the measured irregular particle using the phase retrieval algorithm in this step includes the following iterative process:

[0031] Step 4.1: Initialize the two-dimensional shape image to be reconstructed, using a guessed two-dimensional shape as the starting point for iteration and the outgoing light field distribution;

[0032] Step 4.2: Perform forward propagation calculation on the initial guessed shape to obtain the reconstructed measured light field distribution;

[0033] Step 4.3: Replace the amplitude of the reconstructed measurement light field with the amplitude of the defocused speckle images M1 and M2 to obtain the corrected measurement light field distribution;

[0034] Step 4.4: Perform backpropagation calculation on the corrected measured light field to obtain the preliminary reconstructed particle shape;

[0035] Step 4.5: Correct the support domain constraint of the initially reconstructed two-dimensional shape. That is, apply Gaussian blur kernel to the initial reconstructed value for convolution, select an appropriate threshold for binarization, and gradually reduce the width of Gaussian kernel during the iteration process to promote the convergence of particle shape.

[0036] Step 4.6: Update the guessed 2D shape with the corrected reconstructed 2D shape;

[0037] Repeat steps 4.2 through 4.6 until the specified number of iterations.

[0038] Step 5: Smooth the reconstructed two-dimensional shape images L1 and L2 obtained in Step 4. Then, perform threshold segmentation on the smoothed reconstructed two-dimensional shape images L1 and L2. The segmentation threshold is determined by the Otsu algorithm. The threshold obtained by this method makes the foreground and background of the image have the largest inter-class variance, fills the gap caused by threshold segmentation, and extracts the contour region of the irregular particles being measured. Specifically, the contour region extraction method is as follows: Since the image has been binarized, all non-zero pixels in the image are particle regions. Find the coordinates of all non-zero pixels, and use the minimum and maximum coordinates as the diagonal coordinates of a rectangular region. The rectangular region formed is the largest rectangle containing the two-dimensional shape, and the two-dimensional shape contour region images K1 and K2 are obtained.

[0039] Step 6: Perform pixel alignment processing on the two-dimensional shape contour images K1 and K2: Fill the perimeter of each image with pixels of grayscale value 0. Centering on the contour region image, fill the two-dimensional shape contour images to the same pixel size N2×N2, resulting in smoothed and pixel-aligned dual-angle two-dimensional shape images J1 and J2. At this point, the contour regions of both images are located at the center of a matrix of the same size, thus completing pixel alignment. To reduce the computational burden in subsequent operations, N2×N2 should not be too large, but slightly larger than the pixel size of the larger image of K1 and K2.

[0040] Step 7: Use Matlab software to reconstruct the three-dimensional shape of the contour image projection: Project images J1 and J2 along the x-axis and y-axis in three-dimensional space respectively, generate point clouds at the intersection of the contour regions, and obtain the three-dimensional point cloud H of the irregular particles to be recovered.

[0041] Example 1: Interferometric Particle Imaging System

[0042] like Figure 2 As shown in the figure, a specific embodiment of the acquisition system based on dual-angle defocused interferometric images of the present invention is presented. The system includes a laser 1, a beam expander and collimator unit 2, imaging lenses 3 and 5, and CCD cameras 4 and 6. The laser 1 is a semiconductor laser with a wavelength of 532 nm. The emitted laser beam is expanded and collimated by the beam expander and collimator unit 2, outputting two beams of scattered particle light with scattering angles α and β, respectively, where α and β are the two acquisition angles. Imaging lenses 3 and 5 collect the two beams of scattered particle light, which are then imaged and detected by the first and second CCD cameras 4 and 6 to detect irregular particles 7.

[0043] Specifically, the beam expanding and collimating unit 2 further includes: a microscope objective 21 with a magnification of 10× for signal amplification of the laser beam, a pinhole 22 with a width of 10μm for forming a divergent beam, i.e., scattered light, an aperture 23 for filtering out diffraction rings, and a collimating lens 24 for collimating the scattered light of particles.

[0044] Specifically, in this embodiment, both the scattering angles α and β are 135°.

[0045] Specifically, imaging lenses 3 and 5, used to collect particle scattered light, are Nikon 50mm f / 1.4D fixed focal length lenses.

[0046] Specifically, the CCD camera used as the detector in the system has a pixel size of 5.86μm for the 4 and 6 pixels, an effective pixel count of 1080×1920, a frame rate of 165fps, a system magnification of 2.27, an object distance of 70mm, an image distance of 208mm, a defocus distance of 14mm, and the frontal size of the irregular particle to be measured is 900μm×1028μm, with a side thickness of 83μm.

[0047] Example 2: Reconstruction of Three-Dimensional Particle Structure

[0048] Based on the estimated size of the irregular particles, the magnification of the image acquisition system, and the detector pixel size, the maximum pixel scale of the area occupied by the focused image of the irregular particles is above 400 pixels. Therefore, a 512×512 pixel area is cropped from the center of the acquired defocus speckle image, and a phase retrieval algorithm is used to reconstruct the two-dimensional particle shape. The Otsu algorithm (an algorithm for determining the image binarization segmentation threshold) is used to calculate the background image segmentation threshold, obtaining a threshold mapped to a grayscale range of 0-255, which is 50. Using a grayscale value of 50 as the threshold, the binarized target contour is obtained. The target contour region is smoothed, filling in the holes generated inside the contour region due to binarization. The resulting contour region pixel sizes are 315×355 and 42×427. A rectangle slightly larger than the contour region is selected for pixel alignment, and zero pixels are filled around the contour region to a size of 500×500 pixels. In Matlab, the aligned contour is projected into three-dimensional space, generating a three-dimensional point cloud in the intersecting region.

[0049] The above description is merely an embodiment of this application and is not intended to limit the scope of protection sought by this invention. For those skilled in the art, any modifications, changes, equivalent substitutions, or variations made without departing from the spirit and principles of this invention fall within the scope of the technical content disclosed in this invention and the scope of protection sought.

Claims

1. A method for three-dimensional measurement of irregular particles based on dual-angle defocused interferometric images, characterized in that, include: Step 1: Build a dual-angle laser interferometric image acquisition system. At the same defocus distance, use a CCD camera at the imaging end to detect and acquire defocused interferometric images of the irregular particles being measured at two detection angles. I 1. I 2; The detection angle is two scattering angles that are orthogonal. α , β ,Right now α + β = 90° or 360° - ( α + β ) = 90°; Step 2: Create a defocused interference image. I 1. I 2. Cropping: Extracting the defocused interference image. I 1. I 2 centers N 1× N Defocus speckle image within a 1-pixel range M 1. M 2; Step 3: Process the defocused speckle image M 1. M 2. The phase retrieval algorithm is used to reconstruct the two-dimensional shape of the irregular particle being measured, resulting in a reconstructed two-dimensional shape image. L 1. L 2; Further processing includes the following: Step 3.1: Initialize the two-dimensional shape image to be reconstructed, using a guessed two-dimensional shape as the iteration starting point and the outgoing light field distribution; Step 3.2: Perform forward propagation calculation on the initial guessed shape to obtain the reconstructed measured light field distribution; Step 3.3: Use the defocused speckle image M 1. M The amplitude of the measured light field is reconstructed by replacing the amplitude of 2, and the corrected measured light field distribution is obtained; Step 3.4: Perform backpropagation calculation on the corrected measured light field to obtain the preliminary reconstructed particle shape; Step 3.5: Correct the support domain constraints of the initially reconstructed two-dimensional shape; Step 3.6: Update the guessed 2D shape with the corrected reconstructed 2D shape; Repeat steps 3.2 through 3.6 until the specified number of iterations is reached; Step 4: Reconstruct the two-dimensional shape image obtained in Step 3. L 1, L 2. Perform smoothing processing on the reconstructed 2D shape image after smoothing. L 1, L 2. Perform threshold segmentation to fill in the gaps caused by the threshold segmentation, extract the contour region of the irregular particles being measured, and obtain a two-dimensional shape contour region image. K 1. K 2; The threshold for threshold segmentation satisfies the condition that the foreground and background of the image have the maximum inter-class variance; Step 5: Process the two-dimensional shape contour image K 1. K 2. Perform pixel alignment processing, including filling the perimeter of both images with pixels of grayscale value 0, and filling the two-dimensional shape contour image to the same pixel size, centered on the contour region image. N 2× N 2. Obtain a smoothed and pixel-aligned two-dimensional shape image with dual angles. J 1. J 2; Step 6: Use Matlab software to reconstruct the 3D shape of the contour image projection, including the image... J 1 and J 2 along respectively x shaft and y Axial 3D spatial projection generates a point cloud at the intersection of the contour regions, which is a 3D point cloud of irregular particles to be recovered. H .

2. The method for three-dimensional measurement of irregular particles based on dual-angle defocused interferometric images according to claim 1, characterized in that, The dual-angle laser interferometry image acquisition system includes a laser, a beam expander and collimator unit, an imaging lens, and a CCD camera. The laser is a 532nm wavelength semiconductor laser. The emitted laser beam is expanded and collimated by the beam expander and collimator unit, and the output beams have two scattering angles. α and β The scattered particle light is collected by the imaging lens, and the two beams of scattered particle light are collected by the first and second CCD cameras for irregular particle imaging detection.

Images