57 results about "Shape reconstruction" patented technology

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 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 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 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 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 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.

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.

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 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.

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.

The invention provides an optical fiber shape sensing system, method, medium and equipment, in the system, a sensing unit comprises a multi-core optical fiber, the multi-core optical fiber is provided with at least three eccentrically distributed sensing cores and a central core, each sensing core is inscribed with a fiber bragg grating used for sensing axial strain caused by bending and torsion, and the central core is provided with a fiber bragg grating used for sensing the axial strain caused by bending and torsion. The central core is used for providing temperature compensation reference; the signal processing unit is used for receiving the original wavelength and strain data acquired by the sensing unit and executing filtering, temperature compensation and curvature and torsion calculation processing; and the shape reconstruction and display unit reconstructs a three-dimensional space curve through numerical integration based on the geometric parameters output by the signal processing unit, and realizes real-time visual display of a three-dimensional shape. According to the invention, high-precision and high-stability optical fiber shape sensing can be realized in a complex dynamic scene, and application requirements of complex scenes such as medical catheter navigation and flexible robot control can be met.

The invention relates to the technical field of biomedical engineering, and provides a tongue body motion form reconstruction and neuromuscular lesion recognition method, which comprises the following steps: S1, acquiring a multi-modal original signal by using a flexible electrode array attached to a lingual surface, and recording a system timestamp; s2, performing targeted filtering, artifact removal and feature extraction processing on the multi-mode original signal; s3, reconstructing a local dynamic curved surface of the lingual surface by adopting a preset model, and inferring an overall position and posture sequence of the tongue body in combination with an IMU signal; s4, a joint optimization objective function is constructed, and a tongue body three-dimensional dynamic form sequence is obtained through iterative solution; s5, performing motion unit action potential MUAP decomposition and feature extraction on the surface electromyogram signal sEMG; and S6, constructing lesion feature vectors based on the multi-dimensional abnormal features, and analyzing and generating a tongue lesion risk map TDM through a machine learning model. The defects that real motion reconstruction, form inference and neuromuscular lesion positioning of the tongue cannot be achieved through an existing tongue detection technology are overcome.

The invention relates to the technical field of rail shape monitoring, in particular to a rail deformation sensing method and device based on a flat-ribbon optical cable. The device is characterized by comprising a bandlet optical cable, a conduction optical fiber, a demodulator and a computer, a fiber bragg grating array which is weak in reflectivity, determined in grating distance and capable of being calibrated in position is accurately inscribed in two optical fibers in the flat-ribbon optical cable, interference of temperature fluctuation and axial strain is effectively eliminated through double-optical-fiber cooperative measurement and differential calculation, and when a rail is subjected to sedimentation or bending deformation under the action of train loads and environmental factors, the fiber bragg grating array is accurately inscribed in the flat-ribbon optical cable. Deformation is synchronously transmitted to the bandlet optical cable and causes the wavelength change of the reflection center of each fiber bragg grating, a wavelength change signal is transmitted to the demodulator through the conduction optical fiber to be demodulated in real time and output to the computer, and the computer is based on a wavelength-strain-curvature mapping relation and combines a Freen-Serret shape reconstruction and vertex error correction algorithm. The spatial shape reconstruction of the rail is realized, and the settlement height change is output, so that the real-time, continuous and visual monitoring of the settlement process of the rail is realized. The method is suitable for the technical field of rail deformation and settlement monitoring.

The invention provides a substrate deformation measurement system based on a fiber bragg grating (FBG) and a self-adaptive layout method thereof. The substrate deformation measurement system comprises an FBG sensor network, a data acquisition module, a signal preprocessing and data analysis processing module and a visual interface, the FBG sensor network comprises a measured substrate and a fiber grating string; the data acquisition module comprises a tunable broadband light source, an optical isolator, an optical circulator, a signal transmission optical fiber, a spectrum analyzer and a corresponding demodulation algorithm; the signal preprocessing and data analysis processing module comprises hardware equipment and computer software; and the visual interface uses Labview to write a front-end interface, and is used for performing three-dimensional real-time display on a substrate shape reconstruction result and realizing an alarm function for special situations. According to the invention, through fusion of real-time data and a prior model, focusing monitoring and resource optimization configuration of a key area are realized, and the problems of high calculation complexity, low data processing efficiency and the like in a traditional distributed fiber grating morphology sensing technology are solved.

This invention provides a method and system for optical fiber shape reconstruction, comprising: acquiring an optical fiber reference signal and an optical fiber measurement signal; processing the acquired optical fiber reference signal and optical fiber measurement signal respectively to obtain an optical fiber reference spectrum and an optical fiber measurement spectrum; based on the optical fiber reference spectrum and optical fiber measurement spectrum, using a preset deviation calculation algorithm to obtain a wavelength offset including noise; performing noise reduction processing on the wavelength offset using a wavelength offset denoising model to obtain denoised strain information; and reconstructing the optical fiber shape based on the strain information using a shape reconstruction algorithm. This invention provides a method and system for optical fiber shape reconstruction that can achieve good accuracy in reconstructing the three-dimensional shape of optical fibers while effectively improving the speed of three-dimensional shape reconstruction, thus helping to meet the real-time requirements of optical fiber three-dimensional shape reconstruction applications.

A facial texture reconstruction unit reconstructs a texture of a face from a 2D video of a person. A facial shape reconstruction unit reconstructs a 3D shape of the face from the 2D video. A pose estimation unit estimates a pose of the person from the 2D video. A shape integration unit reconstructs a 3D shape of the body corresponding to the estimated pose based on the 3D shape data, and integrates the reconstructed 3D shape of the body and the reconstructed 3D shape of the face to reconstruct a 3D shape of the person. A texture reconstruction unit reconstructs a texture image of the person by blending, with an image of the reconstructed texture of the face, a texture image included in the texture data and a model generation unit generates a 3D model of the person based on the 3D shape and the texture image of the person.

The application discloses a kind of volume calculation and geometric reconstruction methods, devices, equipment and medium inside road disease, which comprises: standardization processing to the three-dimensional simulation point cloud data of inside road disease, to obtain standardization simulation point cloud data;Pretreatment data and identify disease connected sub-region, determine the internal starting point set to construct starting point set, based on starting point set Construction space step direction and step search boundary point, generate boundary point set, fusion boundary point set obtains disease space profile, based on disease space profile completes disease volume calculation and three-dimensional geometric shape reconstruction;Since the application accurately locates the disease boundary by internal starting point constraint combined with multi-direction step search, restores complete disease geometry by fusing boundary points, accurately realizes the topological reconstruction and volume calculation of complex disease network, effectively solves the problem of incomplete disease point cloud boundary and complex topology of internal complex disease of road, and improves the integrity of disease reconstruction and the accuracy of volume calculation.

This disclosure provides a point cloud processing method, apparatus, computing device, and storage medium. The point cloud processing method includes: acquiring object states in an initial point cloud frame; extracting object point clouds from the initial point cloud frame based on the object states; calculating a shape code of the initial point cloud frame based on a shape model and the object point clouds in the initial point cloud frame, wherein the shape code is used to characterize the surface shape of the object; and calculating the object states and / or shape codes of corresponding objects in other point cloud frames of the point cloud sequence based on the shape code and object states of the initial point cloud frame. Embodiments of this disclosure combine object tracking and shape reconstruction based on a shape model, improving the accuracy of object tracking and the fidelity of shape reconstruction.

The application provides a tokamak plasma boundary identification and shape reconstruction method. First, the EAST plasma boundary is identified by using a U-Net full convolutional neural network, then boundary points are selected, and finally, the pixel coordinates of the boundary points are fitted with EFIT through an XGBoost model. The application can convert the boundary from the image plane to the tokamak polar surface, and realize the plasma shape reconstruction based on a monocular visible light camera. According to the experimental results, the algorithm has high reconstruction accuracy, and the average error on the test set is only 7.36 mm.

The invention provides a lingual surface three-dimensional shape reconstruction method and system based on deep learning, and relates to the technical field of three-dimensional reconstruction, and the method comprises the steps: activating an image collection array based on a light source illumination parameter to carry out the multi-angle two-dimensional sensing of a target tongue part, and obtaining an original lingual surface image sequence; performing visual cutting, extracting a plurality of lingual surface target images, performing deep learning, and constructing a lingual surface depth map; performing three-dimensional shape analysis, constructing lingual surface three-dimensional point cloud coordinates, mapping the coordinates to a plurality of lingual surface target images for identification, and performing comparative analysis on an identification result and a standard image library to generate a comparative parameter set; and performing correction, performing three-dimensional reconstruction on the target tongue according to a correction result, and constructing a three-dimensional morphological model. The technical problems that a lingual surface analysis method in the prior art mostly depends on two-dimensional images or manual observation, subjectivity is often high, information loss is serious, and the real three-dimensional form of the lingual surface is difficult to obtain are solved.

The invention provides a fiber bragg grating flexible rod shape reconstruction method based on a double-branch neural network, and relates to the technical field of optical fiber sensing, and the method comprises the steps: laying an FBG array with the node spacing of 20 mm on a flexible rod, synchronously collecting the spectral signal of the FBG array and a two-dimensional coordinate obtained by an industrial camera, and constructing a spectrum-coordinate pairing data set. Constructing a double-branch neural network comprising a 1D-CNN and a 2D-CNN, and respectively extracting a time sequence feature and a channel space feature of the spectrum; after weighted fusion and full-connection compression, features are reconstructed into a time sequence, the time sequence is input into BiLSTM for time sequence modeling, and a channel and a sequence attention mechanism are integrated to dynamically focus key information. After training is completed, the model can directly output the two-dimensional coordinates of all monitoring points of the flexible rod for the real-time spectrum, and high-precision and end-to-end shape reconstruction is achieved.

The invention belongs to the technical field of optical fiber shape sensing, and discloses a multi-core optical fiber torsion identification compensation method, system, device and medium, and the method comprises the steps: reading and preprocessing the strain monitoring data of a multi-core optical fiber shape sensor; inputting the strain input sequence into a strain curvature mapping model; calculating a first-order derivative of a distribution curve of the first curvature component and the second curvature component along the length direction, and detecting an abnormal point of the first-order derivative through a local abnormal factor algorithm so as to identify the torsion position of the optical fiber; setting an optical fiber torsion angle range, and performing global optimization on a torsion angle of an optical fiber torsion position by taking curvature component second-order derivability as a target; and based on the optimal torsion angle set, calculating a compensated first curvature component and a compensated second curvature component of each monitoring point after torsion compensation, and realizing spatial position reconstruction of each monitoring point through a shape reconstruction algorithm. According to the invention, the precision of the optical fiber shape sensing technology in earth and rockfill dam deformation monitoring is improved.

The invention relates to the technical field of image data processing, in particular to a missing tooth form intelligent reconstruction method based on contralateral tooth mirror image transformation. According to a masseter axial ultrasonic image and a temporomuscle axial ultrasonic image of a patient, the robustness degree of masticatory muscles on each side of double cheeks of the patient is determined; the method comprises the following steps: measuring the average wear degree of each side of double cheeks of a patient, and then constructing a regression equation of the average wear degree and the robustness degree; determining a coordination coefficient between an edentulous side and an opposite side of the patient by utilizing the regression equation, and further judging whether the homonymous teeth on the opposite side of the edentulous side need to be corrected or not; and if correction is needed, constructing a wear degree correction coefficient of the opposite-side homonymous teeth, further correcting the opposite-side homonymous teeth of the missing teeth, and performing missing tooth form reconstruction based on the corrected opposite-side homonymous teeth. According to the method, the same-name teeth on the opposite side of the missing teeth are corrected, so that the form reconstruction of the missing teeth better conforms to the dynamic coordination of chewing movement.

The invention discloses a gray cast iron casting surface pore and crack defect multi-angle visual fusion detection method. The method comprises the following steps: synchronously acquiring visible light images and thermal imaging sequences of a casting surface from a plurality of preset angles; performing oil stain area identification and illumination enhancement processing on the visible light image, and extracting a thermal radiation abnormal image from the thermal imaging sequence; respectively processing the heat radiation abnormal image and the enhanced visible light image through a double-branch feature extraction network, and performing adaptive fusion to generate an initial weight image; screening pore candidate areas based on the compactness; and performing three-dimensional shape reconstruction on the initial weight image according to morphological characteristic differences of the pore candidate areas at different angles, positioning a suspected defect area, positioning an independent defect according to a local normal convergence focus of a pixel point, and outputting a defect identification result. According to the method, the limitation of a single view angle is overcome, and the image quality and the identification degree of defect characteristics are remarkably improved, so that the accuracy of defect positioning and the fineness of type judgment are improved.

This application provides a wind turbine blade mold design method and system, as well as a mold equipment. The method utilizes the coordinated linkage of six steps—parameter acquisition, shape reconstruction, aerodynamic optimization, structural design, performance evaluation, and mold derivative design—to construct an integrated and intelligent collaborative design system. Through unified constraints of the objective optimization function and intelligent application of the algorithm model, it achieves global collaborative optimization of multiple objectives such as blade aerodynamic performance, structural strength, and lightweighting, resulting in a blade design scheme with optimal overall performance. By setting a performance evaluation step, manufacturing constraint evaluation is integrated into the entire blade design process in real time, proactively avoiding potential problems during processing. Through the seamless integration of the mold derivative design step and the blade design, the mold design parameters are determined simultaneously with the finalization of the blade design, shortening the R&D cycle of the blade and mold, reducing design and manufacturing costs, and improving the efficiency and reliability of design and processing.

This invention discloses a flexible gripper for bag palletizing based on octopus biomimicry and its control method. It employs a central base inspired by an octopus head, connecting multiple independently controllable three-segment biomimetic flexible extension arms. Each arm integrates a negative pressure suction cup, a miniature binocular vision module, and a multi-dimensional sensing unit at its end. The base integrates a main control, pneumatic, communication, and sensor processing unit. The control method includes three closed-loop controls: distributed multi-view collaborative shape reconstruction and feature recognition; integrated avoidance-adhesion non-destructive gripping planning; and synchronous gripping defect identification and traceability. This invention addresses the specific characteristics of bag palletizing scenarios, achieving full-area, non-destructive gripping, detection, gripping, and palletizing simultaneously, improving production line efficiency by over 40% and completely solving the core pain points of existing bag palletizing devices, such as high reliance on manual labor and high gripping defect rates.

The application 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. A magnetic flux leakage signal of a measured target surface is collected to form an initial signal set, and a convolutional neural network model is used to extract a feature vector; three-dimensional space data is separated, and a preliminary three-dimensional position coordinate of a defect is obtained through an iterative mapping algorithm; spatial geometric features are mined, potential geometric boundaries are determined, data is fused to construct a refined position model; a detection subset is extracted and shape errors are corrected, a space reconstruction grid is constructed and holes are filled, and a complete three-dimensional shape representation is obtained; through precision calibration and signal matching verification, high-precision three-dimensional imaging is output. Through the application, the positioning and shape reconstruction precision of defects can be effectively improved, the imaging integrity and accuracy are guaranteed, the problems of traditional magnetic flux leakage imaging positioning ambiguity and shape distortion are solved, and the defect detection requirements of complex measured targets are adapted.

The application discloses a low-resolution three-dimensional hand shape reconstruction method based on UV-Map, relates to the field of image processing, and particularly relates to a three-dimensional hand reconstruction method in the field of computer vision.The application has the advantages and beneficial effects of performance improvement, reliability improvement, cost reduction, process simplification, energy saving and environmental protection and the like.The application considers a local image block of a single frame of hand, the proposed method considers using UV-Map to express the hand, and the influence of the background is removed, so that the reconstruction precision is higher, and the recovery of hand details is more accurate.