132 results about "Shape reconstruction" patented technology

The invention discloses a submarine cable shape monitoring method based on an ultra-weak fiber bragg grating, which comprises the following steps of: obtaining curvatures # imgabs0 #, # imgabs1 # and # imgabs2 # in X-axis and Y-axis directions from curvatures in two orthogonal directions of curvatures calculated by three uniformly distributed optical fibers, representing angle offset from an ith sensing unit to an X-axis positive direction, and obtaining a bending curvature, an arc angle and a direction angle; and coordinate information in the space is further obtained by combining rotation and translation matrix iterative calculation of a shape reconstruction algorithm, namely, three-dimensional space coordinates of the measured curve can be determined point by point, and finally, complete shape reconstruction and other steps are realized. According to the invention, high-precision large-scale three-dimensional deformation monitoring can be realized. By optimizing the eccentric distance and the strain transmission efficiency of the optical fiber, the tiny deformation of the submarine cable is accurately captured, and by combining an innovative three-dimensional curve reconstruction algorithm, the bending, inclination and other deformation states of the cable can be accurately reflected in different environments. Therefore, the method has obvious advantages in a monitoring task with a high-precision requirement, especially in a complex marine environment.

The invention relates to the field of continuum robot shape reconstruction, in particular to a continuum robot shape sensing method based on IMU and PVDF sensor fusion. The method comprises the following steps: acquiring node attitude information of the continuum robot based on measurement data of an inertial sensor; acquiring node pressure information of the continuum robot through a piezoelectric film sensor, and inputting the node pressure information into a pre-trained convolutional neural network model to obtain node curvature information; fitting a continuous curvature function of the continuum robot based on the node curvature information to obtain continuous curvature information; and the shape information of the continuum robot is obtained by using the node attitude information and the continuous curvature information in combination with the Cosseerat Rod theory. According to the shape sensing method, the PVDF sensor and the inertial sensor work cooperatively, and the machine learning model and the Cosseerat Rod theory are combined, so that high-precision and low-error shape sensing of the continuum robot in a dynamic complex environment is realized.

The invention discloses an evaluation and improvement method and device for a tunnel blasting effect and a medium, and relates to the technical field of tunnel engineering.The evaluation and improvement method comprises the steps that a tunnel coupling data set is collected, space registration and three-dimensional shape reconstruction are conducted, fracture space distribution is formed, risk probability mapping is conducted on the fracture space distribution, and a fracture risk thermodynamic diagram is output; the fracture risk thermodynamic diagram and tunnel rock mass data are input into a digital twin blasting model, a load mapping layer carries out load gradient distribution, a rock mass response deduction layer carries out stress wave propagation simulation and damage accumulation quantification, an optimized blasting number instruction set is generated, and a drill jumbo is driven to execute blasting operation and vibration monitoring according to the optimized blasting instruction set. And actual blasting effect parameters are obtained. According to the method, accurate simulation of geological conditions and optimal adjustment of blasting parameters are realized through the digital twin blasting model, and meanwhile, refined and interpretable evaluation of the blasting effect is realized through vibration monitoring and error propagation modeling of the actual blasting effect.

The invention discloses an optical fiber three-dimensional shape sensor based on an optical frequency domain reflection technology and an application method of the optical fiber three-dimensional shape sensor, the optical fiber three-dimensional shape sensor comprises a base material and more than three optical fibers, and all the optical fibers are spirally wound and fixed on the surface of the base material at equal intervals and constant screw pitches to form distributed sensing units; according to the application method, measurement signals of all the optical fibers are obtained, and axial strain and strain are calculated; calculating the total curvature vector of the reconstruction curve of the measured object; calculating a bending direction angle and a curvature of the reconstruction curve of the measured object; performing differential calculation on the bending direction angle to obtain the torsion rate of the reconstructed curve of the measured object; and reconstructing the three-dimensional shape of the measured object according to the curvature and the torsion of the reconstructed curve of the measured object. The invention aims to realize synchronous measurement of bending, torsion and axial strain by using a distributed sensing unit formed by a multi-fiber structure which is spirally wound at the same interval and at a constant screw pitch.

The invention discloses a non-contact local curvature measurement method and system based on a computational metasurface, and the method comprises the steps: S1, phase modulation: carrying out the phase modulation of an incident light field carrying the information of a to-be-measured object through an optical computational metasurface, so as to generate transverse displacement light field distribution related to the contour of the to-be-measured object; s2, signal extraction: separating and extracting a first-order differential signal carrying the edge information of the object to be measured by using a biorthogonal polarization filtering system; s3, reconstructing a three-dimensional shape: reconstructing the three-dimensional shape of the object to be measured according to the first-order differential signal; and S4, curvature calculation: calculating the curvature radius of any local part of the object to be measured according to the three-dimensional shape. The optical calculation metasurface is combined with a biorthogonal polarization filtering system, differential operation of a light field is achieved, the edge contour of an intensity object and the three-dimensional shape of a phase object can be obtained without difference, and therefore non-contact and high-precision measurement of the curvature of the object is achieved, the problem of physical damage of traditional contact type measurement is solved, and the measurement accuracy is improved. And the detection efficiency and adaptability are improved.

The invention relates to the technical field of structural deformation shape reconstruction, in particular to a novel inverse finite element deformation reconstruction method based on virtual deformation field physical constraint. According to the method, a virtual displacement field obtained by sparse strain through inverse finite element reconstruction is used as a strain extrapolation physical constraint; and an iteration thought is adopted, extrapolated strain and measured strain are used for inverse finite element deformation reconstruction again, a new virtual displacement field is obtained, and therefore strain extrapolation can be restrained again. And continuously iteratively reconstructing virtual deformation and extrapolation strain in this way, and finally reconstructing real structural deformation. And determining the accuracy rate of the deformation characterization values based on a plurality of actually measured actual deformation characterization values and a plurality of deformation characterization values determined by the extrapolation strain data, and determining the deformation reconstruction state based on the accuracy rate. According to the method, the strain measurement points are extrapolated through iteration in the deformation reconstruction process, and the virtual displacement field is used as physical constraint, so that the accuracy of deformation reconstruction is improved.

A method includes, in a processor, receiving example representations of geometrical shapes of a given type of organ. In a training phase, a neural network model is trained using the example representations. In a modeling phase, the trained neural network model is applied to a set of location measurements acquired in an organ of the given type, to produce a three-dimensional model of the organ.

The invention discloses a sole wear degree detection system based on image recognition, and relates to the technical field of image recognition, the system comprises an image acquisition module, an image processing module, a wear degree analysis module, a database module and a decision output module; the image acquisition module is used for acquiring a multi-angle high-definition image of the shoe sole; the image processing module is used for carrying out impurity removal processing on the multi-angle high-definition image; the database module is used for storing data of different shoe types; the wear degree analysis module is used for distinguishing normal wear from abnormal wear according to the database module and the three-dimensional distribution data; and the decision output module is used for outputting a quality guarantee judgment conclusion and a maintenance scheme. According to the shoe sole wear degree detection system based on image recognition, natural wear and abnormal wear are accurately distinguished through three-dimensional shape reconstruction and a deep learning model.

The invention discloses a stamping part measuring method and system based on double-frequency fringe projection and spectral material recognition. The method comprises the steps that phase shift patterns of low-frequency fringes and high-frequency fringes are generated; a deformation stripe image of the surface of the measured stamping part is collected; calculating a wrapped phase according to the deformed fringe image; performing dual-frequency phase unwrapping; a multispectral image of the stamping part is collected, and the relative reflectivity is calculated; performing principal component analysis dimension reduction on the multi-wavelength reflectivity data; identifying the material of the stamping part according to the spectral features, and dynamically adjusting fringe projection parameters based on an identification result; mapping the unwrapped phase into a three-dimensional coordinate; performing adaptive bilateral filtering on the point cloud data; and extracting the characteristics of the stamping part, calculating the size and comparing. By applying the method, the system has the following beneficial effects that high-precision and high-efficiency measurement of stamping parts made of various materials is realized by fusing a dual-frequency phase-shift fringe projection three-dimensional shape reconstruction algorithm and a structured spectral reflectivity analysis material recognition algorithm.

The invention discloses a new error truncation-inverse finite element deformation reconstruction method based on sparse strain data, and relates to the technical field of structural deformation shape reconstruction. Through error truncation of a strain missing sampling area, a deformation hypothesis theory is introduced, lateral shear strain is ignored, a conversion matrix between an inverse finite element reconstruction solution and a real structure solution is established, a dummy deformation field function is substituted into a matrix relational expression between the inverse finite element reconstruction solution and the real structure solution, and the transformation matrix is obtained. Establishing a matrix solution equation between an inverse finite element reconstruction solution and a dummy deformation field function coefficient, directly solving according to input sparse strain data to obtain an optimal dummy deformation field function coefficient, and substituting the field function coefficient back into a dummy deformation field function to obtain real deformation of the structure; according to the new error truncation-inverse finite element deformation reconstruction method based on the sparse strain data, the matrix relation between the inverse finite element reconstruction solution and the real solution of the structure is constructed, the theoretical format is simple, and the applicability is high.

The invention provides a nonlinear torsion compensation method and calibration device for spiral multi-core optical fiber shape sensing, and belongs to the field of optical fiber shape sensing. The method comprises the following steps: firstly, acquiring the total strain of the spiral multi-core optical fiber when the spiral multi-core optical fiber is bent and twisted through an optical frequency reflectometer; then the bending curvature, the torsional strain and the strain noise of the optical fiber to be measured are obtained according to the total strain decoupling principle; applying different torsion rates, and demodulating the torsion strain corresponding to the spiral multi-core optical fiber; then, according to the theoretical model of the spiral optical fiber subjected to external torsion, the torsion sensitivity is solved by using an iterative algorithm; and finally, fitting by utilizing the linear relationship between the torsion sensitivity and the torsion rate to obtain the nonlinear relationship between the torsion strain and the torsion rate, and further performing nonlinear torsion compensation on the bending angle in shape reconstruction. According to the method, good curve reconstruction performance can be obtained, and particularly, the reconstruction precision can be obviously improved under the condition that the optical fiber is twisted and bent at the same time.

The invention provides a semiconductor device part surface micro defect image preprocessing data processing method and system, and relates to the technical field of data processing, and the method comprises the steps: carrying out the image quality normalization processing of an obtained high-magnification amplification surface original image, and generating a quality enhancement image; performing defect feature selective enhancement processing on the quality enhanced image to generate a feature optimized image; performing three-dimensional shape reconstruction on the feature optimization image to generate surface three-dimensional shape topological data containing height information; on the basis of the surface three-dimensional topography topological data, a topography reference origin is determined at the highest point of a local topography protrusion of the preliminary defect candidate area, and a first feature radiation vector and a second feature radiation vector are generated in a fitting mode from the topography reference origin in the main direction and the normal change gradient direction of the surface texture respectively; according to the invention, precise characterization of micro defects in a high-magnification magnification scene can be realized, and the accuracy and real-time performance of defect detection are guaranteed.

The invention discloses a personal protection equipment compliance detection method, and relates to the technical field of image data processing. Comprising the steps of constructing a two-dimensional human body sensing network, a three-dimensional human body shape reconstruction network and a layered protection equipment judgment network; obtaining video data, performing feature extraction on the video data, and generating accurate coordinates of human skeleton key points and body joints; based on the human skeleton key points, a working state result is generated through a three-dimensional human body shape reconstruction network; based on the human skeleton key points and the video data, generating protective equipment wearing features through a layered protective equipment judgment network, judging whether a working state result of the target person meets a preset result, if so, continuing to judge whether the protective equipment wearing features meet a preset condition, and if the protective equipment wearing features meet the preset condition, continuing to judge whether the protective equipment wearing features meet the preset condition. And outputting wearing compliance. The invention aims to judge whether an experimenter regularly wears personal protection equipment or not by analyzing video stream data in combination with a modern image recognition technology and a video monitoring means.

The invention belongs to the technical field of cigarette production, and provides a cigarette three-dimensional shape reconstruction method and system based on laser three-dimensional scanning and application, and the method comprises the steps: collecting three-dimensional point cloud data of the whole surface of a cigarette based on a laser triangular reflection principle; preprocessing the three-dimensional point cloud data by adopting a multi-stage filtering algorithm strategy to obtain reference data; the method comprises the following steps of: dispersing reference data into a plurality of two-dimensional sections along the axial direction of a cigarette, synchronously extracting upper and lower semicircular feature points of the cigarette in different two-dimensional sections by adopting a multi-thread technology, performing offset vector calculation and mirror image translation transformation so as to reconstruct a plurality of continuous two-dimensional reference sections in a virtual space, and performing curved surface reconstruction on the continuous two-dimensional reference sections, obtaining a three-dimensional shape model of the cigarette; based on the three-dimensional shape model, the perimeter and the length of the cigarette are extracted through a mixed measurement model. The cigarette shape detection efficiency can be improved, and the detection accuracy and the data accuracy are improved.

The present application provides embodiments of an image processing method, device, and equipment. The method includes: obtaining, by an electronic device, at least two images of a target object to be processed, wherein the at least two images to be processed include images captured from at least two different shooting angles; inputting the at least two images to be processed into a target 3D reconstruction model to reconstruct a target 3D body shape corresponding to the target object; the target 3D reconstruction model is trained based on M preset dimensional key points, wherein M is a positive integer; and outputting the target 3D body shape. By inputting at least two images into the target 3D reconstruction model, the embodiments of the present application enable obtaining the target object's 3D body shape, thereby improving the convenience of body shape reconstruction and reducing costs. Additionally, as the target 3D reconstruction model is trained based on preset dimensional key points, the reconstruction achieves higher precision. Furthermore, using images captured from different angles as input improves the accuracy of human body shape reconstruction.

The invention discloses a multi-particle three-dimensional shape reconstruction method based on projection consistency. According to the method, a three-angle laser interference particle imaging system is used for collecting out-of-focus images of three visual angles, a center M * N pixel range is cut to obtain an out-of-focus speckle image, phase recovery algorithm reconstruction is carried out, a two-dimensional particle shape is obtained, a gray threshold value above 70 is set to be a target contour area, binarization segmentation is carried out, and a target contour image is obtained. And smoothing the target contour area. And carrying out three-dimensional space projection on contours of the four candidate results in Matlab, generating a three-dimensional structure in an intersection region, re-projecting the three-dimensional structure to each view angle, calculating an error S between a re-projected image and an original input projection, and selecting a final reconstruction result with the minimum S. According to the method, through systematic iterative optimization and an error evaluation mechanism, trivial fuzzy interference in a phase recovery process is effectively eliminated, and high-precision reconstruction of a multi-particle three-dimensional shape is realized.

The invention discloses a pile foundation concrete accurate pouring control system and method based on multi-source sensing fusion. The pile foundation concrete accurate pouring control system comprises a sensing layer and a control layer, wherein the sensing layer comprises a phased array ultrasonic probe, a binocular vision sensor and a laser ranging array; the modeling layer comprises a three-dimensional hole shape reconstruction module and a BIM digital modeling engine; the data layer comprises a real-time monitoring database and a multi-source data fusion center; the decision-making layer comprises a concrete dynamic evaluation model and a BIM visual platform; the execution layer comprises a self-adaptive PID controller used for adjusting the concrete pumping rate according to the decision instruction, and a three-dimensional visualization terminal used for displaying the BIM model with the tolerance zone in real time. According to the method, a BIM model containing dynamic compensation is constructed through ultrasonic three-dimensional scanning, closed-loop control is achieved by fusing multi-source sensing data, and tolerance band penetration early warning and self-adaptive PID adjustment are combined. The hidden defect discovery rate is improved, and the comprehensive construction efficiency is improved.

The invention relates to a three-dimensional shape measurement method based on space-time staggered acquisition of structured light, which comprises the following steps: placing a measured object on a translation table capable of horizontally moving, and projecting a structured light image to the surface of the measured object through a digital projection system to form an envelope structured light image; collecting image information of a corresponding position of the surface of the measured object through a linear array camera; in the process that the measured object moves along with the translation stage, the digital projection system is controlled to switch projection images every time the measured object moves by a first distance, and the line-scan digital camera is synchronously triggered to collect image information; and combining the images acquired by the linear array cameras to form a plurality of camera shooting structured light images, resolving the camera shooting structured light images, and decoding the position information of each point on the surface of the measured object in combination with a ray tracing technology to obtain a three-dimensional shape measurement result of the measured object. Compared with the prior art, the high-precision three-dimensional shape reconstruction of the high-speed moving object can be realized, and the method has the advantages of high measurement precision, high robustness and the like.

The invention discloses a steel plate cutting method and device, a medium and equipment, and belongs to the field of cutting. According to the method, three-dimensional coordinates of all points on the surface of the head of a steel plate are generated by obtaining real-time motion parameters of the steel plate and the head distance and angle detected by a millimeter-wave radar and combining a preset coordinate conversion model. And then, converting the three-dimensional coordinates into a steel plate head shape image by using a morphological reconstruction model constructed based on preset three-dimensional point cloud data and morphological feature extraction rules. According to the steel plate cutting method and device, accurate positioning and efficient cutting are achieved, the production efficiency and the material utilization rate are improved, and the problem that the steel plate cannot be accurately cut in the prior art is effectively solved.

Disclosed herein is a reconfigurable phased array and a method for determining the current configuration of a phased array. Certain disclosed embodiments include a reconfigurable phased array including a constellation of antennas configured to receive and transmit radiation towards a far field target. Each of the antennas senses incidental power from the retransmitted radiation from the other antennas of the constellation of antennas. This incidental power may be referred to as mutual coupling. The reconfigurable phased array further includes a computer system configured to: measure the incidental power sensed by the each of the antennas; perform a physical constraint mapping of the constellation of antennas; perform an array shape construction to determine a current position of all the elements based on the physical constraint mapping of the constellation of antennas and the incidental power sensed by each of the antennas.

The invention discloses a method for quantitatively evaluating the three-dimensional shape of a thinning defect in a plate under ultrasonic guided wave field undersampling scanning, belongs to the field of industrial nondestructive testing, and particularly relates to high-precision three-dimensional shape reconstruction and thickness loss quantification of a corrosion defect in a metal plate shell structure (such as aerospace skin, a pressure vessel wall, an oil pipeline and the like). According to the method, sparse sampling guided wave field reconstruction, full waveform inversion (FWI) and priori knowledge constraint are fused, Shannon sampling theorem limitation is broken through, efficient measurement of corrosion depth, contour and distribution under the conditions of a single excitation source and a limited view angle is achieved, and the method is suitable for rapid online detection in a complex industrial environment.

According to the optical fiber device for detecting the three-dimensional shape, scattering points are inscribed on a cladding of a single-mode optical fiber, the number of projections of the scattering points on the end face of the single-mode optical fiber is at least two, the scattering points corresponding to each projection form a group, each group comprises at least two scattering points, and the scattering points in each group and the scattering points in other groups are arranged in a staggered mode. By detecting the energy change of each scattering point and calculating the curvature component of the optical fiber, high-precision measurement of the bending state of the optical fiber can be realized, and meanwhile, the two-dimensional bending state of a single point is reflected by utilizing the scattering points which are distributed in multiple directions in the radial direction, and the three-dimensional bending state along the optical fiber is obtained by combining the scattering points which are distributed in the axial direction of the optical fiber in a staggered manner. According to the invention, the measurement of the three-dimensional shape is completed only by using a single-channel sensing signal measured in one optical fiber at a time, so that the size of an optical fiber shape measurement device and the complexity of signal measurement are greatly reduced.

The invention discloses a three-dimensional shape reconstruction system combined with a grating inversion technology and a sensor preparation method, and belongs to the technical field of optical fiber sensing. The system comprises a shape sensor, a grating demodulation device and a shape reconstruction device, an optical fiber bundle formed by a plurality of optical fiber grating strings or a multi-core optical fiber is attached to the outer side of the base material, but is not completely bonded, and is only subjected to point constraint to form a shape sensor; the demodulation device acquires spectral information in real time; the reconstruction device is combined with a spectrum inversion technology to restore and display a three-dimensional shape with high precision. The invention also comprises a manufacturing method of the shape sensor. The method comprises the following steps of: 1, manufacturing the optical fiber bundle or the multi-core optical fiber; secondly, the optical fiber bundle is arranged in a hollow hose bonded to the side edge of the base material, and only one end of the optical fiber bundle is fixed; the problem of low spatial resolution in the fiber bragg grating shape sensing technology is solved, meanwhile, the shape sensor structure can eliminate strain on the outer side of the base material when the base material is bent, and the optical fiber is protected.

The invention relates to the technical field of defect detection imaging, and discloses a high-precision three-dimensional imaging method and system based on continuous magnetic flux leakage data. Collecting surface magnetic flux leakage signals of a measured target to form an initial signal set, and extracting feature vectors by using a convolutional neural network model; separating three-dimensional space data, and obtaining initial three-dimensional position coordinates of the defect through an iterative mapping algorithm; mining spatial geometric features, determining potential geometric boundaries, and fusing data to construct a refined position model; extracting a detection subset, correcting a shape error, constructing a space reconstruction grid, filling holes, and obtaining a complete three-dimensional shape representation; and through precision calibration and signal matching verification, a high-precision three-dimensional image is output. According to the method, the defect positioning and shape reconstruction precision can be effectively improved, the imaging integrity and accuracy are guaranteed, the problems of fuzzy positioning and shape distortion of traditional magnetic flux leakage imaging are solved, and the defect detection requirements of a complex detected target are met.

The application discloses a kind of based on parameter mapping mechanism's unmanned aerial vehicle cluster shape reconstruction method, belongs to unmanned aerial vehicle fleet autonomous decision control technical field, including establishing unmanned aerial vehicle cluster model and unmanned aerial vehicle single body model;Establish the basic behavior rule of unmanned aerial vehicle, including motion trend adjustment and dynamic position adjustment;Set cluster macro shape, according to the unmanned aerial vehicle cluster model and unmanned aerial vehicle single body model established by macro shape parameter mapping to micro rule parameter, determine neighborhood range, according to the basic behavior rule of unmanned aerial vehicle established, generate cluster macro three-dimensional shape, and the generated cluster macro three-dimensional shape is with preset shape Accuracy analysis, according to accuracy result completes unmanned aerial vehicle shape reconstruction.The application uses the above method, can make operator directly modify macro shape parameter to directly adjust the relative distance between unmanned aerial vehicle cluster machines, to form preset macro shape in three-dimensional space.

The present application relates to the technical field of image data processing, in particular to a missing tooth shape intelligent reconstruction method based on contralateral tooth mirror image transformation. According to the patient's masseter axial ultrasound image and temporal muscle axial ultrasound image, the robustness of each side of the masticatory muscle of the patient's both cheeks is determined; the average wear degree of each side of the patient's both cheeks is measured, and then a regression equation of the average wear degree and the robustness is constructed; the coordination coefficient between the missing tooth side and the contralateral side of the patient is determined by using the regression equation, and then it is judged whether the contralateral homonym tooth of the missing tooth needs to be corrected; if correction is needed, the wear degree correction coefficient of the contralateral homonym tooth is constructed, and then the contralateral homonym tooth of the missing tooth is corrected, and the missing tooth shape reconstruction is carried out based on the corrected contralateral homonym tooth. The present application corrects the contralateral homonym tooth of the missing tooth, so that the missing tooth shape reconstruction is more consistent with the dynamic coordination of masticatory movement.

A computing system and method can be used to render 3D shapes from one or more images. Specifically, the present disclosure provides a general pipeline for learning articulated shape reconstruction from images (LASR). The pipeline can reconstruct rigid or non-rigid 3D shapes. Specifically, the pipeline can automatically decompose non-rigidly deformed shapes into rigid motions near a rigid skeleton. The pipeline incorporates synthetic analysis strategies and forward-renders contours, optical flow, and color images, which can be compared with video observations to adjust the internal parameters of the model. By inverting the rendering pipeline and incorporating optical flow, the pipeline can recover the mesh of a 3D model from one or more images input by a user.

System, methods, and other embodiments described herein relate to single-shot multi-object three-dimensional (3D) shape reconstruction and categorical six-dimensional (6D) pose and size estimation. In one embodiment, a method includes inferring a heatmap based upon a feature pyramid, where the feature pyramid is generated based upon a red green blue depth (RGB-D) image that includes objects. The method further includes sampling a 3D parameter map at locations corresponding to peaks in the heatmap, where the 3D parameter map is inferred based upon the feature pyramid, and where the locations include latent shape codes, 6D poses, and one-dimensional (1D) scales. The method further includes generating point clouds based upon the latent shape codes, the 6D poses, and the 1D scales.

The invention discloses a low-coherence interference microstructure rapid measurement method based on an FPGA, and the method comprises the steps: enabling the FPGA to respectively receive image data and single-point light intensity data collected by a CMOS sensor and a photoelectric detector, and transmitting the two types of data to an FPGA chip internal memory; a parallel pipeline architecture of the FPGA is designed, so that interference pattern contrast can be calculated in real time and displacement point-by-point calculation can be completed while a series of image data and photoelectric detector interference analog signals are received, and the processing efficiency is remarkably improved; and calculating the position of an interference envelope peak value by adopting a gravity center method, completing three-dimensional shape detection of the microstructure, and realizing three-dimensional shape reconstruction. According to the method, the processing speed of low-coherence interference measurement can be effectively increased, the microstructure morphology can be restored at a high speed, and online detection application of low-coherence interference in the fields of semiconductor packaging, lithium battery manufacturing, ultra-precision machining and the like is facilitated.

The invention relates to the field of tongue image three-dimensional shape analysis, in particular to a tongue image three-dimensional shape reconstruction method based on multi-source sensor fusion. The advantages of multi-source sensors such as a structured light depth camera, a high-resolution RGB camera, a polarization filter, a near-infrared camera and a high-speed TOF camera are fused. High-precision tongue image three-dimensional point cloud is collected through a structured light depth camera, and the geometric dimension of the tongue image is accurately described; a high-resolution RGB camera is used for complementing tongue image textures, and the problem of light reflection is solved by combining a polarization filtering technology; the near-infrared camera supplements tongue root and surface blood vessel texture information; and the high-speed TOF camera monitors the tongue image in real time and compensates the motion blur error. And finally, fusing data acquired by a multi-source sensor, and performing three-dimensional grid reconstruction to obtain a complete and high-quality three-dimensional tongue image model.