606 results about "Structure light" patented technology

The invention discloses a charger shell screw hole rapid positioning method based on three-dimensional point cloud identification, and the method comprises the steps: collecting a polarization structured light three-dimensional point cloud, carrying out the preprocessing, building a workpiece coordinate system, and obtaining a steady point cloud; calculating a homology bar chart in the neighborhood of the point cloud, screening candidate areas according to a threshold value, and generating candidate masks and topology confidence; performing principal component analysis and polar coordinate projection on the candidate region, and outputting a local point cloud; projecting and correcting a local point cloud to obtain a complemented point cloud and implicit field features; solving a hole axis by adopting random sampling consistency, and carrying out Gaussian mixture fitting on an output center and a hole diameter; fusing topology and geometric scores as joint confidence, and judging whether to enter execution or not; and mapping the center and the axis to a robot coordinate system, and compensating and updating a parameter output result during assembly. According to the invention, through three-dimensional point cloud identification and multi-stage geometric topology analysis, rapid and accurate positioning and assembly adaptive correction of the charger shell screw holes are realized.

The invention discloses an oral tooth lesion AI auxiliary diagnosis system, which belongs to the field of artificial intelligence and comprises an image acquisition module, a three-dimensional modeling module, a lesion marking module, a dual-channel feature extraction module, a cross-modal diagnosis reasoning module, a lesion evolution trend prediction module and a dynamic risk level generation module. The image acquisition module utilizes multi-frequency structured light and a polarization camera to cooperatively acquire oral images; the three-dimensional modeling module is used for reconstructing an upper and lower jaw three-dimensional structure based on edge constraint splicing point clouds and registering images to form double-view fusion data; the lesion labeling module fuses expert labeling and weak supervision pseudo labels to generate joint labels; the dual-channel module extracts skeleton and texture features; the reasoning module realizes cross-modal semantic coupling through an image-text co-occurrence graph; the evolution prediction module models a lesion change path based on the time reversal causal network; and the risk module outputs a five-level risk and re-injects the embedded vector to strengthen prediction. The beneficial effects are that diagnosis intelligence and clinical decision support level are obviously improved.

The invention relates to the technical field of three-dimensional imaging, in particular to a four-eye structured light stereoscopic vision imaging method, which comprises the following steps of: arranging four cameras and synchronously acquiring multi-view image data with structured light stripes; carrying out image preprocessing and stripe code identification on the obtained four-view-angle structured light image data, and extracting structured light stripe center line positions and corresponding space projection information under each view angle; generating three-dimensional point cloud data of the high-precision target sample by using parallax calculation and a three-dimensional reconstruction algorithm, and completing spatial registration and filtering optimization of point cloud; fusing the point cloud and the light intensity data by combining the reflection intensity information of the multi-view structured light stripes to generate a composite data set containing space and spectral information; and constructing a dense parallax field and executing three-dimensional consistency verification, and generating a high-fidelity three-dimensional reconstruction model with a complete topological relation and sparse shielding compensation capability. According to the invention, the problems of insufficient view angle coverage, shielding area information loss, difficult edge structure matching and the like of traditional stereoscopic vision imaging can be solved.

The system comprises a projection module, an imaging module and a phase resolving module, the projection module comprises at least three light source units and light modulation units corresponding to the light source units, an emergent light path of at least one light source unit is provided with an optical coupling assembly, and the emergent light path of at least one light source unit is provided with an optical coupling assembly. The light modulation unit is used for carrying out gradient phase modulation on a light beam, and the optical coupling assembly couples a light path modulated by the light modulation unit to a coaxial light path of the imaging module; the imaging module is arranged on a path sharing the same optical axis with the optical coupling assembly and is used for acquiring a stripe image modulated on the surface of the measured object; the phase resolving module is used for solving a wrapping phase of the fringe image output by the imaging module and unwrapping the wrapping phase based on a quality image guided space phase unwrapping algorithm; while the high-frequency sine fringe generation capability is ensured, collaborative optimization of phase distribution and light intensity characteristics is realized, and the contradiction between device miniaturization and optical performance is effectively reconciled.

The invention belongs to the technical field of image analysis, and particularly relates to an electronic component defect detection method and system based on machine vision, and the method comprises the following steps: S1, obtaining visible light, X-ray and three-dimensional structured light images of an electronic component to be detected, and generating respective multi-scale feature pyramids through independent feature extraction networks; s2, generating a multi-modal fusion feature pyramid; s3, applying a candidate region generation network to propose a candidate defect region; s4, processing the spatial topological relation graph through a graph neural network, and embedding spatial context information into candidate defect region features; and S5, if the minimum distance between the candidate region features and all the pre-stored prototypes is greater than a set discrimination threshold, determining that the candidate region is a potential defect of an unknown type. According to the method, the detection range is widened, the robustness of feature expression is improved, the limitation of insufficient information of a single data source is overcome, and the accuracy, comprehensiveness and perspectiveness of detection are improved.

The invention belongs to the technical field of structured light three-dimensional measurement, and particularly relates to a super-density stripe structured light three-dimensional surface scanning method and system, and the method comprises the steps: obtaining camera parameters; projecting a super-density stripe structure light pattern formed by alternating wide bright and dark stripes to an object; acquiring an image by using a camera, and extracting a central point pixel coordinate of the stripe-structured light pattern by using a sub-pixel precision positioning method; calibrating a light plane equation of each stripe structure light pattern under a camera coordinate system by means of a plane target; reversely projecting the pixel coordinate of the central point of the stripe-structured light pattern into a ray and intersecting the ray with a corresponding light plane to obtain the three-dimensional coordinate of the ray and form an initial three-dimensional point cloud; and finally, carrying out gray scale estimation and filling on missing data caused by signal saturation or difficult positioning based on a radiation brightness physical model to obtain complete and accurate three-dimensional surface shape data. According to the invention, high-precision, high-density and high-integrity three-dimensional surface scanning is realized, and the reliability and applicability of a measurement result are remarkably improved.

The invention discloses a binocular structured light three-dimensional reconstruction and dynamic rotation matrix-based large rotation equipment rotor multistage stacking concentricity accurate measurement method, and belongs to the technical field of non-contact optical measurement, three-dimensional reconstruction and assembly precision measurement. The method comprises the following steps: 1, binocular structured light three-dimensional reconstruction; step 2, dynamic rotation matrix correction: correcting the space attitude of the surface of the spigot, and converting all measured point clouds to a unified coordinate system for concentricity calculation; 3, multi-stage stacking eccentricity error evaluation under the polar coordinate system is carried out, the concentricity is rapidly calculated on the basis of a three-dimensional reconstruction result, and visual distribution of eccentricity errors is formed for subsequent online compensation; and 4, constructing a feed-forward + feedback compensation closed-loop system based on the measurement and error transfer model in the step 3, and correcting the eccentric error in real time in the assembly process. The defects that existing contact measurement is low in efficiency, contact damage exists, and multi-stage assembly accumulative errors cannot be evaluated and compensated in real time are overcome.

The invention discloses a method for regulating and controlling a cosine multi-Gaussian correlation structure light field, and the method comprises the steps: introducing a hyperbolic cosine function and a multi-Gaussian function, and constructing a weighting function and a kernel function based on the hyperbolic cosine function and the multi-Gaussian function; introducing a partially coherent light construction formula, and constructing a cross spectral density function of a cosine multi-Gaussian correlation structure light field at the source plane by combining a weighting function and a kernel function; introducing a free space transmission formula, and constructing a light intensity expression of a cosine multi-Gaussian correlation structure light field at any transmission distance according to a cross spectral density function, namely, an expression of the cosine multi-Gaussian correlation structure light field; adjusting the transmission distance and parameters of the cosine multi-Gaussian correlation structure light field to obtain light intensity distribution regulation and control of the cosine multi-Gaussian correlation structure light field, and further obtaining an array form in which sub-beams are flat-topped beams according to the light intensity distribution regulation and control; according to the invention, controllable transmission of the cosine multi-Gaussian correlation structure light field can be realized, and effective regulation and control of the array form in which the sub-beams are flat-topped beams can be realized.

The invention discloses a pitching side type material taking machine material positioning method based on image recognition. The method comprises the following steps that a structured light sequence is projected to a material stacking area according to a preset coding grating mode; synchronously acquiring multi-view image data of the surface of the stockpile; executing preprocessing; spatial domain processing is carried out, geometric morphology information of the surface of the stockpile is extracted, and height distribution of the surface of the stockpile is analyzed; frequency domain processing is carried out, and light intensity distribution change rule information is extracted; performing fusion processing; time sequence three-dimensional reconstruction operation is executed, and a three-dimensional stockpile surface model is constructed; and determining three-dimensional coordinates of the material target area, and generating material positioning result data. Structured light reconstruction and multi-modal feature fusion are fused, high-precision three-dimensional positioning of the stacked materials is achieved, and the method has the advantages of being precise, robust and high in real-time performance.

The invention discloses a method for performing visual inspection on surface forming quality characteristics of a welding seam by utilizing three-dimensional reconstruction, which comprises the following steps of: S1, performing uniform-speed scanning on the welding seam along the direction of a welding bead by using linear structured light emitted by a linear laser, and performing image acquisition on linear structured light stripes formed on the surface of the welding seam by using an industrial camera; s2, converting the acquired RGB image into a gray level image frame by frame, and carrying out image distortion correction and image denoising processing; s3, carrying out ROI (Region of Interest) positioning on the formed line structured light stripe image on the surface of the welding seam by adopting a pixel point gray level distribution calculation method; s4, carrying out image segmentation on the ROI region of the weld line structured light stripe image; and S5, carrying out sub-pixel-level center line extraction on the ROI of the weld line structured light stripe image by adopting a gray extreme value weighted centroid method. Automatic detection of welding seam forming quality characteristics such as laser welding and electric arc welding can be achieved, and the operation efficiency of a production line and the welding seam quality detection precision can be greatly improved.

The invention discloses an underwater high-speed three-dimensional measurement method based on stripe structured light, and relates to the technical field of underwater optical three-dimensional imaging, in an underwater operation scene of an FPP system, projecting a three-step phase shift sine stripe and a Gray code pattern to an object to be measured, and respectively calculating a wrapped phase 1, a wrapped phase 2 and an auxiliary order phase; analyzing the light intensity information received by the camera, and carrying out water body influence analysis in combination with an underwater light transmission model; the initial wrapped phase divides the order phase into a stable region and a non-stable region, the stable region is combined with the wrapped phase 1 to calculate a preliminary absolute phase, and the non-stable region is combined with the wrapped phase 2 to calculate an absolute phase through an island processing method. According to the method, a phase bisection complementary decoding strategy is adopted, a jump error region in an order phase is effectively identified and corrected by constructing complementary wrapped phase information, a wrong order phase is corrected by using a noise correction algorithm, and the measurement stability in a dynamic scene is remarkably improved.

The invention discloses a super-resolution structured light reconstruction method based on a wavelet enhanced CNN-Transformer structure. The super-resolution structured light reconstruction method comprises the following steps of: firstly, carrying out wavelet enhancement on a CNN-Transformer structure; according to the method, image reconstruction is realized based on a WECT network adopting a coding-decoding architecture; the method comprises the following steps: firstly, extracting initial features through shallow convolution, performing two-stage down-sampling by using discrete wavelet transform, and respectively inputting results into a convolutional neural network and a Swin Transform module to perform parallel feature extraction and fusion; secondly, performing two-stage up-sampling through inverse discrete wavelet transform, and performing jump connection with shallow layer features; finally, pixel shuffling up-sampling operation is introduced, and residual jump connection between the input image and the output image is established; according to the method, high-resolution details can be efficiently recovered while the structure reduction precision is ensured, the image definition and contrast are enhanced, and the application value and practicability of the SIM image in scenes such as biological imaging and tissue analysis are improved.

Disclosed in the present invention is a three-dimensional reconstruction method based on kinematic calibration for the monomerization of a line-structured light point set. The method comprises: rigidly combining an area-array camera with a linear-line-structured light emitter, and mounting same on a motion platform; using a standard radius value of a standard sphere and line-structured light scanning data to calibrate structural parameters of the motion platform of a measurement apparatus; with the calibrated spherical center position of the standard sphere and the standard radius of the standard sphere as constraints, calibrating a spatial position relationship of a line-scanned point set; controlling the motion of the five-axis motion platform, and acquiring scanning data of a measured piece in different poses; and using the scanning data and a real-time point cloud calibration matrix to complete high-quality three-dimensional model reconstruction of the measured piece from its multi-pose scanning. The system comprises: an apparatus fixing module, a calibration module, a point cloud calibration module, a scanning module, and a point cloud reconstruction module. By means of using the present invention, the reconstruction accuracy of a line-structured light three-dimensional point cloud model can be improved. The present invention can be widely applied to the field of three-dimensional reconstruction.

The invention relates to the technical field of artificial intelligence, and discloses an eggshell crack detection method and system based on a convolutional neural network. The method comprises the following steps: synchronously obtaining multi-modal data of an egg through multispectral transmission imaging and three-dimensional structured light measurement; performing rigid registration and expansion on the data under a cylindrical coordinate system to generate a multi-channel fusion feature map with space alignment; inputting into a convolutional neural network of an encoder-decoder structure to carry out pixel-level crack segmentation, and outputting a crack probability graph; and after thresholding and connected domain analysis, judging whether the egg contains cracks or not according to a geometrical characteristic judgment criterion. The system comprises a multi-modal image acquisition module, a data preprocessing and fusion module, a crack feature extraction and classification module and a decision execution module. According to the method, through cooperation of multi-modal information fusion and the deep learning model, the accuracy and robustness of crack detection are remarkably improved, and the method is suitable for a high-speed automatic sorting scene.

The present application belongs to the technical field of image analysis, and particularly relates to a kind of electronic component defect detection method and system based on machine vision, comprising the following steps: S1, the visible light, X-ray and three-dimensional structure light image of the electronic component to be measured are acquired, and respective multi-scale feature pyramids are generated through independent feature extraction network respectively;S2, multi-modal fusion feature pyramid is generated;S3, candidate region generation network is applied to propose candidate defect region;S4, spatial topological relation graph is processed through graph neural network, and spatial context information is embedded into candidate defect region feature;S5, if the minimum distance of candidate region feature and all pre-stored prototypes is greater than the set discrimination threshold, then it is determined that the candidate region is unknown type potential defect.The present application widens the detection range and improves the robustness of feature expression, overcomes the limitation of insufficient information of single data source, and improves the accuracy, comprehensiveness and foresight of detection.

The invention discloses a thin coal seam working face monitoring method and system based on computer vision, and relates to the field of thin coal seam working face clamping plate monitoring. According to the method, continuous tracking and dynamic feature extraction of the three-dimensional form of the splint are realized by combining multi-source visual data fusion with a time sequence form analysis modeling method. Specifically, a structured light depth camera, an RGB camera and a thermal infrared imager are utilized to obtain morphological characteristics of a clamping plate in different dimensions, and a three-dimensional model with spatial consistency is constructed through fusion; and a morphological risk function is constructed in combination with curvature change, top height difference and time continuity characteristics, so that quantitative, dynamic and real-time evaluation of the clamping plate disengagement risk is realized, and the system can judge potential risks in advance in the early deformation stage of the clamping plate.

The present application provides a kind of rough rolling process strip explicit plate shape online visual detection system and method, the present application system includes strip detection system, grating light grid structured light projection system, image acquisition system, distance adjustment system and image processing system;When strip enters hot detector detection range, transmission signal triggers grating light grid structured light projection system and image acquisition system start working;Image acquisition system is used to transmit the image information collected to image processing system in real time;Distance adjustment system is used to adjust the distance between grating light grid structured light projection system and image acquisition system.Image processing system is used to process the image transmitted by image acquisition system in real time, obtains the three-dimensional profile of strip, obtains the two-dimensional curve of strip in XOY coordinate system and the two-dimensional curve in YOZ coordinate system, and then discriminates the degree and type of strip buckling head and camber.

The embodiment of the invention discloses an MEMS structured light high-precision three-dimensional measurement method, device and equipment and a medium. The method comprises the following steps: determining first orthogonal phase distribution information of a to-be-measured target according to a surface stripe image; determining a first space linear equation of the fitting projection light of the preset projection phase; coordinates of the first space linear equation are converted to obtain a second space linear equation, a projection device coordinate system is established according to the first space linear equation, and a mapping model of the deviation angle and the projection phase is determined based on the corresponding relation between the second space linear equation and the preset projection phase; mapping the phase to obtain a first offset angle; and determining the to-be-measured target point cloud based on the first deviation angle to obtain a three-dimensional coordinate. According to the invention, the method does not depend on a high-precision calibration plate, builds the incidence relation between the phase and the angle and the ray mapping model, accurately represents the projection characteristics of the projection device, and solves a technical problem that the precision is not high when three-dimensional measurement is carried out based on an MEMS structured light system.

The invention discloses a comprehensive evaluation method for health conditions of silk fabric cultural relics, and relates to the technical field of silk fabric cultural relic management, and the method comprises the following steps: laying high-density spectral response scanning points on the surfaces of the silk fabric cultural relics, and calculating and recognizing fiber aging distribution differences based on hyper-spectral local entropy differences of the high-density spectral response scanning points; according to the method, through high-density spectrum scanning and multi-level modeling, in combination with time sequence spectrum analysis and sampling anchor point setting, accurate representativeness evaluation of the fiber aging state is achieved, the existing sampling limitation is overcome, and the sampling efficiency is improved. And the accuracy and the comprehensiveness are obviously improved. Meanwhile, a coupling model is constructed through structured light imaging and molecular spectrum bidirectional mapping, a dynamic updating framework is formed in combination with a time sequence aging index and residual error write-back correction, conversion from static detection to dynamic prediction is achieved, and long-term tracking and prospective decision-making capabilities are achieved.

The invention relates to the technical field of mine safety monitoring, in particular to a roadway section convergence multi-view three-dimensional reconstruction method and a monitoring system thereof.The method comprises the steps that a rectangular plane coordinate system is established on a roadway section, a plurality of measuring areas are arranged in the circumferential direction, a plurality of equal-height measuring points are evenly distributed in each measuring area in the elevation direction of the section, and every two adjacent measuring areas share at least one measuring point; a laser structured light projector and a CMOS receiving camera are arranged at each measuring point; matching the feature points through an improved stereo matching algorithm to obtain depth feature point information and establish a section point cloud; dividing deformation into local deformation and overall deformation, establishing deformation association between measurement points through deformation feature description, and obtaining overall convergence information of the section by adopting a point cloud registration method after local deformation compensation is formed; a section safety evaluation model is established, section deformation evaluation and reinforcement suggestions are given, all-directional non-blind area monitoring of the section is achieved, and the monitoring precision reaches the millimeter level.

The invention relates to the technical field of underwater target detection, and discloses an underwater target detection device and method based on binocular fusion line structured light, the device comprises a binocular structured light system and an information processing unit which are installed at the bow of an underwater robot, and the binocular structured light system is in communication connection with the information processing unit; the binocular structured light system comprises vertically arranged array laser and an underwater binocular camera, and the array laser is used for projecting line structured light stripes to an underwater target and forming a structured light image on the surface of the target; the underwater binocular camera is used for capturing a structured light image and sending the structured light image to the information processing unit; and the information processing unit is used for performing edge detection on the received structured light image to obtain line structured light projection stripes of the target surface, and further obtaining three-dimensional point cloud coordinates of the target surface. According to the invention, an underwater three-dimensional space can be fully covered, and three-dimensional perception and accurate identification of underwater suspended and semi-buried targets can be realized.

The invention discloses a damage detection method and system based on machine vision, and relates to the technical field of machine vision detection. A polarization structured light-thermal imaging three-mode acquisition framework of a customized machine vision array is adopted, the problems of composite noise superposition and unstable internal thermal signal diffusion caused by dynamic heterogeneity of a target surface are solved, the adaptability of damage detection to a complex environment is greatly improved, and by means of a space attention mechanism and a cascade analysis network, the damage detection accuracy is improved. According to the method, geometric measurement and heat conduction simulation technologies are combined, the problems that damage space distribution is rough in description, and there is no stable corresponding relation between surface and deep abnormity are solved, accurate space mapping and multi-dimensional quantification of damage from the surface to the interior are achieved, and through linkage of a dual optimization mechanism and an edge end improved MobileViT lightweight model, the problem that damage space distribution is rough in description is solved. Pain points where real defects and interference artifacts are difficult to distinguish are broken, stable correspondence between surface signals and deep damage is enhanced, and accuracy and practicability of damage detection in an industrial scene are guaranteed.

The invention discloses a phase recovery method of a single fringe image based on a GD-UNet network, which belongs to the field of three-dimensional reconstruction, and comprises the following steps: building a monocular structured light three-dimensional reconstruction experiment platform, collecting a fringe image and generating a data set; then a GD-UNet model is constructed, the input of the GD-UNet model is a three-channel fringe image with three-frequency fusion, and simultaneous prediction of wrapped phase molecules, denominator terms and fringe levels is achieved through an information integration and distribution module. And after training is completed, inputting a to-be-detected image into the network, outputting a prediction result, and correcting the fringe order by using an arc tangent function and a connected domain segmentation strategy to finally obtain a high-precision absolute phase diagram. According to the method, multi-task prediction is completed in a single network, the reasoning efficiency is improved, error accumulation is effectively inhibited through joint modeling, and the adaptability to complex scenes is high.

The invention relates to the technical field of semiconductor packaging detection, in particular to a semiconductor packaging micro welding spot three-dimensional shape intelligent detection system which comprises a sample placing frame, an imaging module, an image processing unit, a detection module and a result display module. The image processing unit constructs a unified curvature field expression by fusing three-dimensional information of three different imaging principles of a spherical mirror model, a light-sectioning microscopic three-dimensional reconstruction algorithm and stripe structured light, and adopts adaptive mesh refinement to process a curvature change violent region; the detection module identifies welding spot defects such as pseudo soldering, bridging and poor connection based on differential invariants and singularity analysis, the system realizes high-precision detection of various semiconductor packaging forms such as BGA, QFN packaging and wafer-level packaging, the measurement precision is improved by 35%-40%, the processing efficiency is improved by about 50%, the defect omission ratio is reduced from 15% to below 3%, and the detection accuracy is greatly improved. And a brand new solution is provided for semiconductor packaging quality control.

The invention relates to the technical field of optical imaging and three-dimensional measurement, in particular to a multispectral structured light path system which comprises a light source module used for generating multi-wavelength light; the collimation system module is composed of any one of one or more lenses, and an aperture diaphragm is arranged on the first face. When the system is used, a multispectral light source design is adopted, the system can meet the three-dimensional measurement requirements of various complex material surfaces, the system adaptability is conveniently and remarkably improved, the image contrast is enhanced through multi-wavelength structured light projection, and the measurement precision is improved. The method effectively reduces the mismatching rate, improves the precision and reliability of three-dimensional reconstruction, achieves the simultaneous obtaining of multispectral information and structured light three-dimensional shape information, expands the application capability of the system in the high-end fields of material recognition, surface defect detection and the like, employs an integrated optical path design, is compact in structure, is high in reliability, and is suitable for large-scale popularization and application. And miniaturization and engineering application of the system are facilitated, and the portability and practicability of the equipment are improved.

The invention discloses a visual inspection sorting method and system for surface defects of intelligent electric meter shell injection molded parts, and relates to the technical field of visual inspection, and the method comprises the following steps: selecting an intelligent electric meter shell as a reference part, dividing the surface of the shell into a plurality of functional partitions, collecting structured light form and brightness information, and obtaining a reference appearance map; and positioning a to-be-detected electric meter shell to a position consistent with the reference part, obtaining the online three-dimensional form and brightness response of each functional zone, mapping the online three-dimensional form and brightness response to the reference appearance map, marking a stable mirror surface with high brightness, and interpolating along an observation track to generate an online appearance map. According to the invention, through functional partition sampling layout of a window sealing area, a wiring terminal area, a stud and reinforcing rib area, a nameplate and two-dimensional code area and a general decoration side wall area, and in cooperation with double-light-source collection of diffused light and oblique incident light combined with structured light, a reference appearance map containing a highlight tolerance mask is constructed; stable characterization of mirror reflection and a transparent window is realized, and false detection caused by high brightness of the mirror surface is remarkably reduced.

According to the automatic measurement system and method for the double-view-field structured light turbine blade, the double-view-field structured light measurement system is constructed, automatic viewpoint planning is carried out based on a turbine blade CAD model, discretization processing is carried out on the turbine blade CAD model to obtain point cloud data, a normal vector clustering algorithm is used for carrying out region segmentation on point cloud, and the point cloud data are subjected to region segmentation; estimating a scanning visual angle direction and a viewpoint position based on a clustering result, calculating displacement of each axis by combining an inverse kinematics model of the three-axis motion platform, and controlling the three-axis motion platform to move to a preset pose; double-view-field structured light hybrid measurement and coordinate system unification are executed, point cloud data obtained through multiple times of measurement are subjected to precise registration, point clouds are unified into an approximate global coordinate system through pose information of a three-axis motion platform, precise registration is conducted on the point clouds through an iterative nearest point algorithm, the splicing precision is improved, and accumulative errors are reduced.

The invention relates to an anti-diffraction-based structured light three-dimensional reconstruction pattern generation method, system and device, and the method comprises the steps: S1, generating simulation stripes projected to an object plane, recording the simulation stripes as an image I1, enabling the bit depth of the image I1 to be b, enabling the width and height of the image I1 to be A times of the DMD resolution, and enabling A to be greater than or equal to 2; and S2, selecting an anti-diffraction function according to the optical system to perform anti-diffraction processing on the pattern. And S3, performing one-time deconvolution operation on the image I1 and the anti-diffraction function to obtain an image I2. And S4, carrying out downsampling operation on the image I2 to obtain an image I3 with the resolution consistent with that of the DMD. And S5, carrying out local binarization processing on the image I3 to obtain an image I4 with the bit depth of 1 bit. And S6, replacing the original image I1 with the image I4. According to the invention, by simulating the anti-diffraction process and calculating the 1-bit image on the DMD, the 1-bit image achieves the same effect as an 8-bit image, so that the projection efficiency is improved by dozens of times, and the existing technical problem is solved.

The invention relates to the technical field of optical element surface physical property testing, and discloses an optical element surface pattern structured light testing system which comprises the steps that a pair of phase-conjugated structured light fields are adopted to alternately illuminate an optical element, and Fourier domain diffraction patterns and spatial domain in-situ light field intensity distribution of the optical element are synchronously collected; according to the method, a common-mode signal cancellation mechanism aiming at a defect-free periodic pattern is preset on a physical level through conjugate illumination and differential processing, so that massive redundant information is suppressed, and the defect position is determined by calculating a differential signal after a diffraction pattern is corrected by using in-situ light field intensity distribution. According to the method, only asymmetric scattering signals caused by defects are reserved and highlighted, so that the focus of detection is changed from measurement of the accuracy of geometrical morphology to discrimination of the uniformity of optical response physical properties of materials, and high-signal-to-noise-ratio rapid discrimination of functional defects is realized.

The invention discloses a grasp point pose calculation method based on a geometric clustering algorithm without deep learning and a GPU (Graphics Processing Unit) and application of the grasp point pose calculation method. The grabbing point pose calculation method comprises the steps that 100, three-dimensional point cloud data of a to-be-grabbed object are obtained through an industrial-grade structured light three-dimensional camera, a geometric clustering algorithm is adopted for screening the three-dimensional point cloud data, and a unique target point cloud cluster conforming to the target form and size is extracted; step 200, performing rough matching on the target point cloud cluster and the template point cloud through the FPFH feature vector and RANSAC to obtain a rough matching result; step 300, performing fine matching on the target point cloud cluster and the template point cloud through the rough matching result and the GICP to obtain a fine registration result; step 400, judging whether a precise registration result meets a preset requirement or not according to the interior point root-mean-square error and the overlap ratio, if so, entering the next step, and otherwise, terminating the process; and 500, according to the fine registration result and coordinate transformation, the grabbing point pose of the to-be-grabbed object is obtained through calculation.