32results about How to "Realize 3D reconstruction" patented technology

The invention discloses a power transmission tower three-dimensional reconstruction method and device based on a standard model library, and relates to the technical field of three-dimensional reconstruction or other related fields, and the method comprises the steps: collecting the point cloud data of a power transmission tower through a mobile scanning device, carrying out the filtering and coordinate transformation of the point cloud data, and obtaining the point cloud data of a unified coordinate system, the method comprises the following steps: obtaining different types of tower standard information, establishing a standard model library, classifying point cloud data, capturing tower key points, obtaining a matching model from the standard model library based on the key points, carrying out geometric transformation on the matching model to obtain a preliminary three-dimensional model, and obtaining a final three-dimensional model based on physical and prior constraint conditions of the tower. And refining the preliminary three-dimensional model by adopting a random iterative algorithm to obtain a refined three-dimensional model, aligning and fusing the preliminary three-dimensional model and the refined three-dimensional model to obtain a target three-dimensional model, and generating a formatted file. According to the invention, the technical problems of low accuracy, low applicability and low automation degree of three-dimensional reconstruction of the power transmission tower in the prior art are solved.

The invention discloses a matrix completion sparse meshless chromatography SAR (Synthetic Aperture Radar) super-resolution three-dimensional imaging method, which comprises the following steps of: constructing a multi-channel observation vector in a data field, and then further constraining an observation signal in an MMV (Modulation Modulation Virtualization) into a Hankel Lift matrix with a joint low-rank structure characteristic by utilizing an elevation consistency hypothesis between neighborhood pixels. And constructing a corresponding low-rank matrix completion model in combination with the tomographic SAR signal model. And modeling is carried out on the joint matrix completion problem. The model is solved based on a symmetric projection gradient descent algorithm, Root-Music solution is utilized to obtain elevation normalization frequency, the normalization frequency is inverted to obtain elevation information, and a scene three-dimensional imaging result is obtained by combining distance-orientation two-dimensional information of a target scene. According to the method, the elevation information of the tomographic SAR model is solved through a joint matrix completion method, tomographic SAR three-dimensional point cloud imaging is realized, a clear and complete imaging result is obtained, and a good miscellaneous point suppression effect is achieved.

The invention relates to the technical field of bridge detection and data processing, in particular to a bridge appearance detection method and system based on cooperation of an unmanned aerial vehicle and a workstation. The technical problems are as follows: the modern bridge detection technology is complex in bridge environment, most of the existing unmanned aerial vehicle detection schemes depend on manual control flight, the flight difficulty is high, and high-definition pictures are difficult to shoot, so that a large amount of rework is caused; according to the technical scheme, the bridge appearance detection system based on cooperation of the unmanned aerial vehicle and the work station comprises an unmanned aerial vehicle platform and a ground work station; real-time data acquisition is performed on the bridge and the surrounding environment thereof through the unmanned aerial vehicle, a bridge digital map is produced by integrating a multi-sensor fusion technology and a three-dimensional modeling and deep learning technology, and a fine acquisition path is planned; and automatic, high-precision and high-coverage data acquisition of the bridge appearance in a complex environment is completed, so that the precision and efficiency of disease detection are greatly improved.

The invention provides a photoacoustic microimaging brain electrode implantation site and path planning method and system, and the method comprises the steps: an image extraction step: employing a brain blood vessel enhanced extraction algorithm to extract an input photoacoustic microscanning imaging result, and obtaining brain blood vessel information; the cerebrovascular information comprises two-dimensional image information and a three-dimensional reconstruction result of the cerebrovascular; and an implantation site and path acquisition step: processing the cerebrovascular information by using a brain electrode implantation site path planning algorithm to obtain an implantation site on the two-dimensional image and an implantation path in the three-dimensional structure. According to the invention, the brain blood vessel enhanced extraction algorithm is adopted, so that the problems of high photoacoustic scanning imaging noise and poor imaging quality are solved, and accurate extraction and three-dimensional reconstruction of the brain blood vessel are realized.

The invention belongs to the technical field of non-intrusive underwater collection, and particularly discloses a liquid concentration and underwater terrain collection method and system based on Kinect, and the method comprises the following steps: obtaining water surface point cloud data and underwater terrain point cloud data based on a Kinect camera; the method comprises the following steps of: fitting a relation curve of a gray value and liquid concentration by preparing mixed liquid with different sediment volume concentrations; importing the water surface point cloud data into point cloud visualization software for processing to obtain an RGB value of the measured liquid, and obtaining the liquid concentration of the measured liquid through a relation curve of a gray value and the liquid concentration; correcting the obtained underwater topography point cloud data to obtain corrected point cloud data of the underwater topography; and importing the corrected point cloud data into point cloud visualization software to carry out underwater terrain three-dimensional reconstruction. According to the invention, one-to-one correspondence color maps and depth maps are obtained based on the Kinect camera, the liquid level liquid concentration can be effectively collected, and meanwhile, three-dimensional reconstruction of the underwater terrain can be quickly realized.

The invention relates to the technical field of robot tactile perception, aims to solve the technical problems that an existing visual tactile sensor is low in precision, poor in real-time performance, incapable of adapting to large deformation and the like during three-dimensional reconstruction, and particularly relates to a binocular visual tactile sensor based on a color block mark point array and a real-time high-precision three-dimensional reconstruction method. According to the method, high-precision three-dimensional reconstruction is completed based on a binocular visual tactile sensor, image preprocessing, color block mark point identification, center coordinate calculation and color discrimination are included, the position of a color block in a mark point array is determined based on coding information and mark point tracking, matching is completed, and finally point cloud is calculated to achieve three-dimensional reconstruction. According to the method, the time spent on part matching is less than 10ms, 400 pieces / cm < 2 > dense point cloud data can be obtained, the method can adapt to the loss of mark points under the condition of large deformation, and the method has an important value for improving the performance and safety of a robot in various complex tasks.

The invention discloses an electric power operation safety risk identification method and system based on fine granularity detection, relates to the field of electric power operation safety management, and solves the problems that the area proportion of substances on the surface of equipment is difficult to obtain through image analysis software, and the parallax value of a target pixel point is difficult to obtain through an SAD algorithm. The method solves the technical problems that a model is not constructed by taking a convolutional neural network as a basic framework to carry out region judgment and double early warning is not carried out, and comprises the following steps: obtaining a corrosion area proportion and a wear area proportion through image analysis software to obtain an equipment comprehensive damage proportion; a high-resolution binocular camera is used for collecting video data of an electric power operation site; obtaining a parallax value of a target pixel point and a corresponding parallax map, and obtaining a depth value and a three-dimensional coordinate of a corresponding point after obtaining the parallax value through an SAD algorithm; and a model is constructed by taking the convolutional neural network as a basic framework to judge the vehicle type, and whether an early warning signal is triggered or not is judged according to two judgment conditions.

The invention provides a three-dimensional reconstruction and rendering method for a scene containing a transparent object, relates to the technical field of computer vision, and aims to shoot the panorama of the transparent object and the surrounding environment, construct different types of transparent object data sets in the scene with bright color for network training, and finally obtain a reconstruction result of the whole scene. According to the method, a multi-module rendering network model is used, and a network is trained according to information of different angles in a learning picture through an angle network and a reflection network. Due to the fact that the scene comprises transparent objects, when the light propagation path is considered, it cannot only be assumed that the light path is propagated along a straight line, and special links such as refraction and reflection in the scene need to be considered. The method provided by the invention comprises the reconstruction of the refraction area and the reflection area at the same time, and realizes the reconstruction and rendering of the whole scene comprising the transparent object.

The present invention discloses a nonlinear calibration method and device for a line structured light 3D camera laser surface, including: performing reverse projection according to the camera's intrinsic parameter matrix, lens distortion parameters and extrinsic parameter matrix to obtain the three-dimensional coordinates of the center point of the laser line in the two-dimensional image captured by the line structured light 3D camera in the camera coordinate system; fitting the surface using a trained neural network model according to the three-dimensional coordinates of the center point of the laser line to obtain the surface model of the line structured light 3D camera laser surface in the camera coordinate system; obtaining the ray corresponding to each pixel according to the three-dimensional coordinates of each pixel on the center contour of the laser line in the two-dimensional image captured by the line structured light 3D camera; calculating the intersection of the ray corresponding to each pixel and the surface model of the line structured light 3D camera laser surface to complete the three-dimensional reconstruction of the line structured light 3D camera laser surface. The present invention can effectively improve the accuracy of laser surface calibration and the accuracy of three-dimensional reconstruction results.

The invention discloses an underwater concrete defect three-dimensional reconstruction system and a reconstruction method thereof, and belongs to the technical field of underwater laser image shooting, the underwater concrete defect three-dimensional reconstruction system comprises a water tank, a stepping motor scanning system, an underwater image acquisition device, a system parameter calibration system and a three-dimensional laser point cloud reconstruction system, the stepping motor scanning system drives the underwater image acquisition equipment to do horizontal reciprocating rectilinear motion in the water tank, the underwater image acquisition equipment is used for shooting underwater concrete defect images with strong characteristic laser, and the system parameter calibration system is used for calibrating parameters of the underwater image acquisition equipment. According to the three-dimensional laser point cloud reconstruction system, three-dimensional reconstruction of underwater concrete defects is realized for underwater concrete defect images with strong characteristic laser, so that the detection efficiency and the detection precision of the underwater concrete defects are greatly improved, and the problem that the underwater three-dimensional reconstruction effect is limited by existing underwater camera equipment is solved; and the defect precision of the underwater concrete is low.

The invention discloses a mechanical arm fan blade morphology measurement method based on ICP algorithm splicing. The method comprises the following steps that 1, a measurement system is calibrated; 2, blade measurement path planning is carried out based on model driving; and step 3, carrying out point cloud splicing based on an ICP algorithm. According to the method, the theoretical model of the blade flexible measurement system is established, the scanning path is automatically planned according to the CAD model of the blade, and the multi-view collection point cloud is subjected to fine matching through the ICP algorithm, so that the influence of the multi-view splicing error on the subsequent feature extraction precision is effectively reduced, and the three-dimensional reconstruction of the processed complete point cloud is visualized.

The invention discloses a high-precision numerical control machine tool workpiece positioning system based on machine vision, and aims to improve the machining precision and the production efficiency of a numerical control machine tool through an automatic and high-precision vision technology. The system comprises an image acquisition and processing unit, a feature extraction and recognition unit, a three-dimensional reconstruction positioning unit, an algorithm optimization unit and a user interface. The image acquisition unit is responsible for acquiring a workpiece image, the feature extraction unit extracts workpiece features by using an image processing algorithm, the three-dimensional reconstruction unit reconstructs a three-dimensional model from a two-dimensional image and determines a position, and the algorithm optimization unit adopts a parallel computing method to improve the processing speed and precision. And the user interface provides real-time image display and operation instruction input. According to the system, through automatic image acquisition, efficient feature extraction, accurate three-dimensional reconstruction and parallel computing optimization, rapid and accurate positioning of workpieces is achieved, the system is suitable for variable machining environments and workpiece types, and the machining precision and production efficiency of a numerical control machine tool are remarkably improved.

The invention relates to the technical field of intelligent traffic, and discloses an expressway three-dimensional reconstruction method and system based on GNSS high-precision positioning and orientation, and the method comprises the following steps: 1, obtaining the real-time position and speed information of a vehicle through employing at least one GNSS receiver with advanced signal processing capability, high positioning precision can be maintained under the coverage of urban canyons and trees; 2, at least one I MU is utilized, the IMU adopts a machine learning algorithm to conduct self-calibration so as to adapt to dynamic changes in long-time operation, and future drift of the sensor can be predicted and compensated. Through an advanced GNSS receiver and a multi-frequency multi-system receiving technology, the system can realize high-precision positioning even in complex environments such as urban canyons and tree coverage, the I MU is equipped with a machine learning algorithm, self-calibration can be realized, dynamic change can be adapted, future sensor drift can be predicted and compensated, and long-term stable operation is ensured.

The invention discloses an environment situation scanning three-dimensional reconstruction method based on infrared and SLAM, and belongs to the technical field of computer vision and three-dimensional reconstruction. According to the method, thermal radiation information and environment image information of a target environment are obtained through infrared sensing and visual imaging respectively, after feature extraction and matching processing are conducted on the two kinds of information, synchronous positioning and map construction are completed, and environment pose data and environment map data are generated; a sensing uncertainty probability model is established, after multi-source data denoising is completed through Bayesian filtering, feature level fusion is carried out to obtain fusion environment data, and finally a three-dimensional reconstruction model of a target environment is constructed based on the fusion environment data. According to the method, the full-process closed loop of environment situation scanning and three-dimensional reconstruction is realized, the application limitation of single sensing information is made up, the comprehensiveness of environment sensing data and the scene adaptability of three-dimensional reconstruction are improved, and the digital reconstruction requirements in various complex environments can be met.

The application provides a three-dimensional reconstruction method based on multi-dimensional information fusion and a convolutional neural network, and comprises the following steps: acquiring polarized sub-images of a measured object under four transmission polarization directions and including multiple detection spectral bands through a multispectral polarization camera; performing image registration and joint denoising on all images; calculating polarization parameters of the measured object, combining spectral information and polarization information to calculate an azimuth angle and a zenith angle of the measured object; and acquiring surface normal vector component three-dimensional data of the measured object through a surface normal reconstruction model constructed based on a convolutional neural network and with the aid of physical prior knowledge. The method provided by the application can effectively restore the texture details of the surface of the measured object, can realize fast three-dimensional information acquisition of a measured object with a surface simultaneously having a diffuse reflection and a specular reflection characteristic in a complex indoor or outdoor scene under illumination conditions, and is helpful to expand the application range of the polarization three-dimensional reconstruction technology.

The application provides a workpiece surface three-dimensional reconstruction method and device, and belongs to the technical field of machine vision. The method comprises the following steps: collecting a test workpiece surface image after a projected fringe pattern and performing phase unwrapping to obtain an absolute phase image of the test workpiece; based on a preset phase height model of each pixel, calculating an initial predicted height and a variance of each pixel in the test workpiece surface image; according to the variance of each pixel in the test workpiece surface image, calculating a height weight coefficient of each pixel; and according to the variance and the height weight coefficient of each pixel in the test workpiece surface image, correcting the initial predicted height of the pixel to obtain a height measurement result of each pixel, so as to realize three-dimensional reconstruction of the test workpiece. The application can effectively reduce the three-dimensional reconstruction error of the complex workpiece surface caused by factors such as imaging system noise, nonlinear error of the projector, phase unwrapping error and the like, and effectively improve the three-dimensional reconstruction precision of the complex workpiece surface.

The present invention discloses a method for three-dimensional reconstruction of surround-view scenes based on implicit representation, including: using a laser to illuminate a relay wall surface, forming a secondary diffuse reflection spot on the relay wall surface, and generating hidden object projections at different angles on the opposite wall by illuminating different positions on the relay wall; estimating the three-dimensional coordinates of the secondary light source by a light source estimation method; establishing a neural shadow field model by the physical relationship that the secondary light source emits light in all directions in a hemispherical space and terminates at the observation relay wall, and using the cumulative transmittance of light to characterize the probability of light propagating to the surface of the relay wall; representing the three-dimensional space parameterization of the neural shadow field model as a continuous MLP function, and using a binary shadow label to supervise the optimization of the cumulative transmittance of light, and finally obtaining the three-dimensional structure of the hidden space by depth integration. The method can accurately reconstruct the shape and contour details of the hidden object.

The invention belongs to the technical field of greenhouse monitoring, and discloses an intelligent greenhouse monitoring system based on deep learning, and the system comprises a data collection module, a data preprocessing module, a main control module, a prediction module, a three-dimensional reconstruction module, a measurement module, and an analysis module. According to the method, a method combining SFM and deep learning MVSNet is adopted, reconstruction of a three-dimensional model of a plant or a crop is taken as a core, and phenotypic characteristics of the plant or the crop are extracted by performing preprocessing such as down-sampling, segmentation and noise reduction on the three-dimensional point cloud of the plant or the crop, so that phenotypic parameters of the plant or the crop are accurately acquired. According to the method, phenotypic parameters of plants or crops can be obtained more accurately and efficiently, reliable data processing method reference is provided for research in the fields of botany, agronomy and the like, the breeding process of the plants or crops is accelerated, the growth environment is optimized, development of agricultural production is promoted, and the production efficiency is improved.

The invention belongs to the related technical field of imaging technology, and discloses a multi-view-angle-based photoacoustic microscopic imaging system, which comprises a two-dimensional scanning module, a view angle selection module, a signal detection module and a three-dimensional reconstruction module, and is characterized in that the two-dimensional scanning module enables a light beam to carry out multiple XY plane two-dimensional scanning on a sample; the visual angle selection module adjusts the visual angle of each two-dimensional scanning to enable the angle of each two-dimensional scanning to be different, the visual angle is the direction in which the light beam enters the sample, and the visual angle of each two-dimensional scanning is perpendicular to the signal detection direction; the signal detection module is located on the side face of the sample and receives ultrasonic signals in the detection direction, the detection direction is parallel to the XY plane, and the ultrasonic signals are ultrasonic signals generated by the sample under light beam excitation; and the three-dimensional reconstruction module performs three-dimensional reconstruction according to the ultrasonic signals at different visual angles to obtain a three-dimensional body structure of the sample. According to the system, the axial resolution of photoacoustic microscopy can be improved in a simpler mode, and scanning and three-dimensional reconstruction can be rapidly completed.

The invention discloses a non-contact strain gauge identification and coordinate accurate positioning method. The method comprises the following steps: acquiring strain gauge image data; carrying out graying processing on the strain gauge image data, and obtaining screened strain gauge contour image data; determining contour data of a target strain gauge; determining an essential matrix of the image acquisition equipment according to the image rotation matrix and the translation vector, identifying the same strain gauge in the contour data of the target strain gauge based on the essential matrix, performing coordinate positioning on the same strain gauge based on binocular vision, and converting the coordinate into a coordinate under the image acquisition equipment. Coordinate information of the strain gauge under the image acquisition equipment is obtained; establishing a conversion relation between the coordinate information and the target coordinate system, and converting the coordinate information into the target coordinate system to obtain a strain gauge identification result under the target coordinate system; and repeating the steps S1-S5 to obtain strain gauge identification results of all structure tests. The accuracy of the position coordinates of the strain gauges can be improved.

The present invention discloses an abdominal aorta stent system, wherein the coated stent comprises a stent body, a contralateral branch and an ipsilateral branch, wherein the contralateral branch and the ipsilateral branch are respectively connected to one end of the stent body; the delivery system comprises an outer sheath tube and a central rod, wherein the outer sheath tube is sleeved outside the central rod, and the delivery system is further provided with a restraining rod; during delivery, the central rod passes through the ipsilateral branch and the stent body, and one end of the restraining rod is located in the contralateral branch; a positioning sensor is used to position the coated stent; at least two positioning sensors are provided, which are respectively located at different openings of the coated stent, and at least one sensor is located at the opening of the contralateral branch, and the positioning sensor is used to detect the opening data of the coated stent. In the abdominal aorta stent system of the present invention, the sensor is separable from the coated stent; the sensor is arranged in a limited space to position the stent opening; and the release degree of the stent is detected in real time.

The invention provides an intelligent plant pruning mechanical arm control method and system, relates to the field of intelligent robot control, and solves the technical problems that an existing plant pruning mechanical arm system seriously depends on a plane vision image, the plant sensing precision is low, and the pruning path planning capability is poor. The method comprises the following steps: collecting multi-modal visual data of a target plant, and processing the visual data based on a three-dimensional reconstruction algorithm to generate a plant three-dimensional model; a target three-dimensional model of a target shape is obtained, difference analysis and trajectory optimization are conducted on the plant three-dimensional model and the target three-dimensional model based on the differentiable simulation technology, and a pruning path of the mechanical arm is generated; and receiving a user instruction, analyzing the user instruction through an intelligent algorithm, mapping the user instruction to the three-dimensional model, and generating and driving a mechanical arm to perform trimming operation along the trimming path.

The invention provides a three-dimensional reconstruction and positioning method for a weak texture object based on binocular vision, and the method comprises the steps: processing an obtained image of an object according to a camera distortion parameter in combination with an image distortion removing method, so as to form a distortion-removed image; processing the distorted image through binocular stereo correction to determine a corrected image; performing stereo matching on the left camera correction image and the right camera correction image according to a CRESTereo deep learning network to determine a disparity map; semantic segmentation is carried out on the left camera correction image or the right camera correction image based on a Unet network to obtain semantic information, a depth map is determined according to the optical center distance of the binocular camera, the focal length of the binocular camera and the disparity map, and the semantic information and the depth map are combined to determine a dense point cloud model of the object; and performing point cloud matching on the dense point cloud model and a standard point cloud model of the object to obtain depth information of a complete object point cloud so as to determine three-dimensional reconstruction and positioning of the object.

The present application provides a structured light three-dimensional reconstruction method, device, electronic device and storage medium. In an example of the present application, the structured light three-dimensional reconstruction method includes: acquiring an image of the object to be measured; performing phase solution processing on a first type of image in the image of the object to be measured to obtain a first phase solution result; performing phase solution processing on a second type of image in the image of the object to be measured to obtain a second phase solution result; performing unwrapping processing on the first phase solution result based on the second phase solution result to obtain an absolute phase map; performing three-dimensional reconstruction processing based on the absolute phase map. This method can achieve high-precision three-dimensional reconstruction.

The application discloses a deep fracture visual photoacoustic magnetic cooperative in-situ measurement device, which comprises a measurement robot placed in a borehole, a cable lowering device placed near a borehole mouth and an upper computer placed outside the borehole. The measurement robot can realize in-situ measurement of fracture networks at different positions in the borehole and has the function of autonomous travel. The cable lowering device mainly realizes depth position sensing of the measurement robot through a depth editor and realizes data communication between the measurement robot and the upper computer. The application further discloses a deep fracture visual photoacoustic magnetic cooperative in-situ measurement method. The application can realize feature area sensing search, autonomous cruise and rapid acquisition of multi-source data, and in combination with a subsequent data processing method, high-precision in-situ measurement and visualization of deep fracture networks can be realized.

The invention discloses a VOCs fluid three-dimensional reconstruction method and device based on a neural fluid field, and belongs to the technical field of computers. The VOCs fluid three-dimensional reconstruction method based on the neural fluid field comprises the following steps: inputting an obtained sample fluid image corresponding to petrochemical gas in a sample time period in a target space and a sample label corresponding to the sample fluid image into a neural fluid field model to obtain a first fluid image corresponding to the petrochemical gas output by the neural fluid field model; constructing a target loss function based on at least one of the first fluid image, the sample fluid image and the sample label; and training the neural fluid field model based on the target loss function. According to the VOCs fluid three-dimensional reconstruction method based on the neural fluid field, the velocity field and the density field of the VOCs fluid can be recovered from multi-view video data, the method is suitable for processing the VOCs fluid lacking stable visual features, real-time monitoring, three-dimensional reconstruction and other applications can be better supported, and the detection precision is high.

The invention provides a motion image acquisition rotary table, a motion image acquisition device and a control method, the motion image acquisition rotary table is provided with a plurality of position coding hole sites and a whole circle coding hole site, the plurality of position coding hole sites are uniformly arranged, the plurality of position coding hole sites form a circle, the circle is parallel to the plane of the rotary table, and the whole circle coding hole site is parallel to the plane of the rotary table. And the circle center of the circumference is positioned on a rotating shaft of the motion image acquisition turntable. By using the motion image acquisition rotary table, the image acquisition position can accurately correspond to the image data.

The invention belongs to the technical field of three-dimensional reconstruction, and provides a three-dimensional reconstruction method and system for linear structured light dynamic stereoscopic vision. The method comprises the following steps: carrying out stereoscopic vision device push-scan along a preset direction to obtain a plurality of stripe images corresponding to a target; combining the perspective projection imaging model of the left camera with the light plane equation of the line-structured light to obtain a stripe center three-dimensional coordinate of the stripe center of the line-structured light; calculating a relative pose of adjacent positions, and calculating an absolute pose of the camera at each position based on a global optimization algorithm; and finally, unifying the three-dimensional coordinates of the centers of the stripes to a reference coordinate system based on the absolute poses so as to realize three-dimensional reconstruction. The method overcomes the limitation of the static stereoscopic vision measurement range, and is suitable for three-dimensional reconstruction of the surface of a large device.

The invention relates to a binocular stereo matching method based on 3D vision, an endoscope system and a storage medium. The binocular stereo matching method comprises the steps that a binocular imaging system is used for obtaining a first image and a second image of a focus area; the image preprocessing system is used for processing the first image and the second image to improve the quality and adaptability of the images; the binocular stereo matching algorithm system is used for carrying out stereo matching on the first image and the second image to obtain a view difference; the three-dimensional reconstruction system is used for generating a depth map through the view difference, mapping the information of the original image to a three-dimensional grid model for three-dimensional information fusion, and obtaining a three-dimensional model of the constructed image; and the image display system is used for displaying the three-dimensional model of the constructed image. Three-dimensional imaging of a focus area is achieved through binocular imaging, image processing and three-dimensional reconstruction, the accuracy and safety of an operation are improved, the 3D vision technology is combined with a medical endoscope, three-dimensional imaging of a focus is achieved, more comprehensive focus information is provided, and therefore the diagnosis accuracy and the success rate of the operation are improved.

The present invention provides a non-contact coaxiality measurement method and system, the system includes a single-axis drive module, an industrial scanning device, a laser emitting device and a data processing module; the system is used to implement the following steps: obtaining structured light images of a measured part and a reference part; inputting the structured light images into an optimized three-dimensional reconstruction model, and extracting point cloud data of the measured part and the reference part using the optimized three-dimensional reconstruction model; according to the point cloud data of the measured part and the reference part, obtaining the cylindrical curve of the measured part and the cylindrical curve of the reference part, and using the common axis method to calculate the coaxiality of the two cylindrical curves as coaxiality measurement data. The laser scanning measurement form is adopted to realize non-contact measurement, simplify the measurement procedure, save measurement time, and the measurement process is simple and easy to implement.