238 results about "Binocular stereo" patented technology

The invention discloses a double-station robot sorting optimization method and system based on digital twinning and a terminal, double improvement of sorting efficiency and safety is achieved by constructing a digital twinning driven collaborative operation system, and the method comprises the steps that firstly, a laser radar and a polarization camera are used for forming a composite sensing unit; geometric morphology, material reflection characteristics and spatial pose data of a target object are synchronously obtained, and are input into a digital twin engine after time synchronization processing; an engine constructs a virtual sorting scene containing a material attribute database based on a physical rendering technology, sub-millimeter-level space registration is achieved through feature fusion of a binocular stereoscopic vision depth map and geometric parameters, high-precision digital twin stations are generated, a system plans a space-time constraint trajectory of a double-station robot in a virtual environment, and a target object is obtained. And an integrated discrete event simulation engine performs operation time sequence conflict prediction, and when a space overlapping risk is detected, an alternative path containing a dynamic obstacle avoidance strategy is generated through a trajectory re-planning algorithm.

The invention discloses a multi-modal fusion real-time environment monitoring visual robot system, and relates to the technical field of real-time vision. The system comprises a multi-mode sensing module, and is equipped with various sensors such as a binocular stereo camera and a laser radar to collect environment data. The heterogeneous data preprocessing unit cleans and downsamples data such as images and point clouds; the space-time alignment fusion module realizes multi-source data space-time registration and synchronization; the environment semantic understanding engine constructs an environment semantic graph through a multi-branch network in combination with an attention mechanism; the abnormal event detection unit identifies abnormity based on a historical data model; the path planning and decision-making module integrates multiple targets to generate an optimal path; the autonomous movement execution module controls the robot to move and operate; and the cloud cooperative control center supports model updating and remote intervention. According to the invention, through cooperative work of all the modules, full-process intelligentization of environment monitoring data acquisition, processing, analysis and decision making is realized.

The invention provides a macrobrachium rosenbergii quality grading system based on machine vision. The macrobrachium rosenbergii quality grading system based on machine vision comprises a prawn body placing platform used for placing macrobrachium rosenbergii to be tested; the three-dimensional acquisition module comprises a structured light projection device, a binocular stereo camera and a flight time depth sensor; and the three-dimensional reconstruction module is used for constructing the data of the three-dimensional acquisition module into a complete three-dimensional point cloud model through a data fusion algorithm and a point cloud registration algorithm. According to the macrobrachium rosenbergii quality grading system based on machine vision, the overall scheme has robustness and expandability, the system is suitable for various large-scale farms and grading scenes, and the intelligent level of macrobrachium rosenbergii quality control is greatly improved.

The invention relates to a vehicle-mounted road defect detection system and method based on binocular vision and deep fusion, and the system comprises a binocular camera module, a main control platform, a positioning module, a communication module and a power supply control module. The system realizes automatic detection and severity quantitative evaluation of various pavement defects such as cracks, pits and ruts, obtains defect positions in combination with a positioning module, and uploads the defect positions to a cloud platform in real time through a communication module, thereby forming a closed-loop urban road defect information perception and management system. According to the method, the quantitative evaluation capability of the identification accuracy and severity of the road defects is remarkably improved, and automatic identification, accurate positioning and real-time cloud synchronous uploading of the road defects are realized; the method has the advantages of flexible deployment, efficient operation, high adaptability and the like, is particularly suitable for urban road intelligent inspection and maintenance management scenes, and has good engineering application prospects and popularization values.

The invention relates to the technical field of computer vision, and particularly provides a tunnel video stream three-dimensional modeling system based on binocular stereo matching and SLAM (Simultaneous Localization and Mapping), which comprises a multi-modal image acquisition unit, a binocular infrared camera and an RGB (Red, Green and Blue) camera are configured to synchronously acquire an infrared image pair, an RGB image pair and inertial measurement unit data of a tunnel environment, the multi-source data is uploaded to the cloud processing platform in real time through the wireless transmission module; based on a dynamic switching mechanism of environmental perception, performing adaptive fusion pose estimation of a feature point method and a direct method on input multi-modal image data; the stereo matching and dense reconstruction unit is used for calculating a disparity map by adopting an improved self-adaptive window stereo matching algorithm, generating a three-dimensional point cloud in combination with the pose information output by the pose estimation unit, and constructing a global consistency point cloud model of the tunnel scene through a time sequence point cloud registration and splicing algorithm; and a multi-algorithm target detection and semantic fusion unit. The method can meet the requirements of precision and robustness of tunnel reconstruction.

The invention relates to the technical field of computer vision, in particular to a three-dimensional reconstruction method and device based on optical polarization and stereoscopic vision principles. The three-dimensional reconstruction method sequentially comprises the steps of image preprocessing, polarization parameter extraction, binocular stereo matching, disparity map generation and optimization, normal vector correction, depth information fusion and three-dimensional point cloud reconstruction and modeling generation. A polarization normal vector field is constrained and corrected as a'skeleton ', and the azimuth angle pi ambiguity problem which puzzles polarization three-dimensional reconstruction for a long time is solved; high-frequency surface normal details contained in corrected polarization information are used as textures to enhance and fill up depth information loss of binocular vision in weak texture and repeated texture areas, the inherent limitation of a single sensing technology in a three-dimensional reconstruction task is overcome, and the three-dimensional reconstruction of the surface of an object, especially a diffuse reflection object, is realized. And high-precision and high-integrity three-dimensional shape recovery is realized.

The invention discloses a PCB soldering paste printing three-dimensional defect detection system based on multispectral imaging, and relates to the field of machine vision detection, and the system comprises a multispectral image acquisition module, a four-channel industrial camera based on RGB and near infrared, and a tunable LED light source array; acquiring reflection characteristic data under different penetration depths through a wavelength switching mechanism; the motion control trigger module is used for realizing positioning based on an XYZ three-axis objective table driven by a servo motor in cooperation with feedback of an encoder; a pulse width modulation signal is adopted to coordinate the moving speed of a camera shutter and a platform; according to the method, RGB and NIR four-channel imaging is combined with Beer-Lambert law modeling, so that double verification of material component quantitative analysis and three-dimensional shape reconstruction is realized, and limitation of monocular vision is avoided; structured light projection and binocular stereo matching technologies are adopted, cross-frame data alignment is realized in cooperation with an ICP algorithm, and detail defects can be better detected.

The application provides a three-dimensional reconstruction method based on binocular stereo matching, and relates to the technical field of binocular stereo vision. The method combines binocular stereo matching algorithm, triangulation algorithm and surface texture mapping, and can realize surface reconstruction of scene objects in different environments. After stereo calibration is performed on a binocular camera, the internal and external parameters of the binocular camera are obtained, stereo correction is performed, then an image disparity map of the corresponding scene object is generated according to an optimized semi-global stereo matching algorithm, after the disparity information is obtained, the point cloud information converted by the object disparity is triangulated on the surface according to the triangulation algorithm, and finally three-dimensional surface reconstruction of the object is realized through the texture mapping technology. The application can reduce the influence of noise in the disparity map generation process, i.e. the semi-global stereo matching algorithm, improve the accuracy of the disparity information, and complete the three-dimensional surface reconstruction task of the object with little sacrifice of time performance.

The invention discloses a point cloud data enhancement method based on a false point cloud technology, and the method comprises the steps: innovatively designing a binocular depth estimation method for rapidly inspecting a residual structure, and extracting the feature information of three levels through a real-time binocular stereo matching network RealtimeStereo; a rapid feature aggregation module with an attention mechanism aggregates the features to achieve the performance of a high-cost feature extraction network; a residual structure aggregation cost volume is designed, a two-stage depth optimization module is introduced, the two-stage depth optimization module comprises an accelerated expansion depth self-optimization module and a KNN-based point cloud depth correction algorithm, the accelerated expansion depth self-optimization module carries out self-optimization on a depth map, and the KNN-based point cloud depth correction algorithm introduces point cloud information to optimize the depth to generate a false point cloud with higher quality; an auxiliary module is innovatively designed to remove invalid information; and finally, a high-quality enhanced point cloud is generated through a depth projection module and a point cloud merging module, so that the quality and practicability of point cloud data are improved.

The invention discloses a lightweight image recognition method and system for power plant safety, and relates to the field of image recognition, and the method comprises the steps: constructing a multi-scale adaptive perception image anomaly detection model, and recognizing the violation behaviors of power plant operators in power plant real-time video data through the image anomaly detection model; constructing a multi-stage binocular stereo area distribution model to match the feature points in the binocular image of the power equipment, and calculating the safety distance between the power plant operating personnel and the electrified body based on the matching result; and constructing an edge equipment reasoning model of lightweight knowledge distillation in combination with illegal behaviors and safety distances of power plant operating personnel, and monitoring potential safety hazards of the power plant in real time by using the edge equipment reasoning model. According to the method, the teacher model with high expression ability is deployed on the cloud for training, semantic information and structural knowledge are transmitted to the student model on the edge device through the dynamic adaptation strategy, and the recognition ability of the edge model in a computing power limited scene is remarkably improved.

The invention relates to the field of pavement crack detection, in particular to a pavement crack detection device and method based on machine vision, and the device comprises a multi-modal data acquisition module, a lighting unit, a central processing unit, a display module, a storage module, a positioning and communication unit, a power supply module and a supporting vibration reduction structure. The multi-modal data acquisition module comprises a high-definition RGB camera module, a binocular stereoscopic vision module and an infrared thermal imaging module; the detection method comprises the following steps of S01, data acquisition and preprocessing, S02, multi-modal fusion and input preparation, S03, crack identification processing, S04, post-processing and parameter extraction, and S05, result output and storage. The problems that in the prior art, crack detection is poor in adaptability, insufficient in real-time performance, high in false detection and omission ratio, incomplete in quantitative measurement and the like are solved.

The invention provides a binocular stereo matching method and system, and the method comprises the steps: obtaining a left and right stereo image pair captured by a binocular camera, and carrying out the feature extraction and enhancement through a depth separable convolution basic network and an ECANet attention model; carrying out topological structure transformation by using a TopoAug feature enhancement strategy, constructing a topological consistency loss function and carrying out adaptive feature fusion; a large neighborhood search strategy and a hybrid node-destructor model are adopted to construct an initial cost body, and cost aggregation is carried out through capacity routing; and constructing an M uniform loss grid and a grid motion model to carry out parallax estimation, and obtaining a final parallax map through unsupervised consistency optimization. Through the technologies of lightweight network design, topology perception feature enhancement, hybrid node optimization cost body construction, unsupervised consistency optimization and the like, the calculation complexity is reduced while high precision is kept, and the method is particularly suitable for real-time monitoring scenes in resource-constrained environments such as substations and the like.

The invention relates to the field of binocular stereo vision, and discloses a binocular stereo matching method and system based on multi-scale iterative optimization and related equipment. The method comprises the steps of performing semantic structure feature extraction on a corrected left view and a corrected right view through a feature extraction network; determining a cost space pyramid and a probability matrix according to the left view feature map and the right view feature map output by the feature extraction network; extracting a multi-scale context feature of the left view through a context sensing network, and initializing the multi-scale context feature to obtain a hidden state and input of a recursive network; during recursive network iteration, according to the probability matrix, a multi-range search strategy is adopted to index local cost from the cost space pyramid; and inputting the local cost into the recursive network, combining the hidden state obtained by the context features and the input, and carrying out iterative updating on the parallax value to obtain a parallax map, thereby improving the accuracy of parallax calculation.

The invention provides a substation safety construction monitoring and early warning system based on binocular stereoscopic vision, which comprises the following steps: respectively controlling a left camera and a right camera to synchronously shoot a construction site, and positioning the real-time positions of the left camera and the right camera in a three-dimensional space in real time, determining a real-time image distance between the left image and the right image to construct a camera coordinate system, identifying a plurality of monitored objects in the construction site in the camera coordinate system, performing feature extraction on each monitored object, determining a plurality of dynamic objects in the construction site, and respectively constructing an object behavior corresponding to each dynamic object; according to the method, the behavior consequence corresponding to each object behavior is analyzed, the dynamic object of the target corresponding to the danger consequence is screened, danger early warning is carried out on the construction site, the problems of positioning interference, scene adaptation, safety early warning and the like in transformer substation construction can be effectively solved, the construction safety management level is remarkably improved, and the method has extremely high practical application value.

The invention provides a binocular stereoscopic vision system and structured light 3D scanner composite calibration method, and the method employs a digital coding point and checkerboard composite calibration technology. Only four digital coding points and a common checkerboard are needed to realize conversion matrix solution from a coding point coordinate system constructed by the digital coding points to a structured light 3D scanner measurement coordinate system, and high-precision dynamic calibration of a binocular vision system and a structured light scanner is realized. The problem of adaptability of a traditional calibration method in a complex industrial environment is solved, the calibration precision and stability of a composite measurement system are remarkably improved, meanwhile, the calibration method has the advantages of being simple in calibration process, low in system cost and the like, the calibration precision and stability are improved, a brand new technical solution is provided for three-dimensional measurement of an industrial site, and the method is worthy of popularization and application. The method is suitable for a dynamic measurement scene in a complex industrial environment.

This invention discloses a design method for a deep-sea in-situ fine-scale detection framework based on acoustic-optical remote sensing and VR technology. The main steps include: (1) studying the structure of the photon-counting lidar scanning system and the dynamic geometric relationship between the mother ship and the submersible, and constructing a calculation model for the lidar bathymetry point coordinates in the WGS84 spatial rectangular coordinate system; (2) considering the submersible's attitude, and based on the ray-tracking model and the geometric relationship between the mother ship and the submersible, constructing a calculation model for the multibeam bathymetry point coordinates in the WGS84 spatial rectangular coordinate system; (3) fusing the lidar and multibeam bathymetry points to construct a seabed topographic map; (4) proposing a development scheme and detection method for a deep-sea functional imaging spectrometer; and (5) constructing a VR environment for the deep-sea target survey area using a three-dimensional seabed topography model, rendering technology, and binocular stereo imaging technology. Through these steps, deep-sea in-situ fine-scale detection based on acoustic-optical remote sensing technology and the construction of a VR environment for the survey area can be achieved.

This application belongs to the field of computer vision and optical measurement technology, specifically disclosing a point cloud stitching method and apparatus based on monocular pose prior marker matching. The method includes: calculating the pose of multiple markers extracted from left and right camera images, determining the normal vector and three-dimensional coordinates of each marker's circular cross-section in its respective camera coordinate system; transforming the three-dimensional coordinates and corresponding normal vectors of each marker in either the left or right camera image to the other camera coordinate system for marker point registration between the left and right camera images; the circular cross-section is a circular cross-section in three-dimensional space with the origin of the camera coordinate system as its vertex, passing through the elliptical curve where the marker is located; and stitching the three-dimensional point cloud of markers based on the marker point registration results of the left and right camera images. This application can significantly improve the accuracy of binocular stereo marker matching and the system's anti-interference capability in complex industrial scenarios.

The application discloses a kind of environment simulation method and system based on binocular stereo vision measurement, it is related to scene simulation technical field, and its technical solution points are: the method includes by constructing the physical imaging model in left and right optical elements in binocular stereo vision camera, and left and right view is obtained based on the physical imaging model;Determine the disparity map between the left and right view, determine scene depth image based on the disparity map;Three and more scene depth images generated by three and more different binocular stereo vision cameras corresponding to the scene are acquired, and the three and more scene depth images are fused, to construct the three-dimensional simulation model corresponding to the scene based on the depth image after fusion.The application can accurately reflect the depth level and spatial relationship of scene, and the three-dimensional simulation model finally constructed is more realistic, and can strongly support virtual reality, three-dimensional measurement and other applications.

The invention discloses an underwater binocular camera calibration method based on laser assistance, and the method comprises the steps: firstly constructing an underwater stereoscopic vision binocular refraction-removing imaging model according to the Snell's law, and correcting an underwater imaging error; secondly, acquiring a camera internal reference matrix by using a Zhang Zhengyou calibration method; then, a laser range finder is used for projecting laser to the calibration plate to form a light spot, the center pixel coordinate of the light spot is extracted through a gray gravity center method, the three-dimensional coordinate of the light spot is calculated in combination with laser ranging data, and the initial value of an external parameter matrix of the binocular camera is solved; and finally, introducing a Bayesian optimization algorithm, and optimizing the constraint equation by taking minimization of a three-dimensional coordinate calculation error as a target so as to obtain an exact solution of an external parameter matrix of the camera. Through organic combination of a deep learning technology and binocular stereo vision, the parameter calibration precision of the underwater binocular stereo vision camera is improved, a reliable technical guarantee is provided for subsequent underwater concrete structure defect quantification, and the fine monitoring requirement in a complex water environment is met.

The application discloses a welding robot pose calculation method, system, device and medium, the method comprises adopting binocular camera to grab the image of the workpiece to be welded and positioning, the first local image and the second local image grabbed are respectively subjected to welding surface segmentation, and the first local welding surface and the second local welding surface are obtained; the first local welding surface and the second local welding surface are respectively subjected to feature point detection and feature point matching; the sparse three-dimensional point cloud of the local welding surface is subjected to plane fitting, and the fitted welding plane and the normal vector of the fitted welding plane are obtained; the spatial position of the weld starting point in the camera coordinate system is converted to the robot coordinate system for subsequent attitude control. The application positions the weld starting point of the workpiece to be welded by combining binocular stereo vision, obtains the normal vector of the local welding surface according to the positioning, obtains the robot attitude, and effectively realizes the accurate positioning of the weld starting point of the workpiece to be welded.

The application discloses a kind of based on edge feature direction code matching's hydraulic hoist tower structure deformation measurement method, belong to computer vision measurement field, this method includes the following steps: using subpixel edge detection method to the detection area image is handled, obtain subpixel edge line position and subpixel edge direction;Based on subpixel edge direction, using direction code encoding method to the edge direction angle is handled, obtain the edge direction code of discretization, and based on the edge direction code of discretization the edge direction code of left and right camera image is calculated;Based on binocular stereo vision system, using template matching method and parallax principle to the edge direction code of left and right camera image is matched, calculate the spatial three-dimensional coordinates of detection area matching coefficient maximum point;Based on the spatial three-dimensional coordinates change of same detection point before and after structure deformation, obtain the deformation of hydraulic hoist tower structure.

The invention discloses a binocular stereoscopic vision feature point matching method, a binocular stereoscopic vision feature point matching device, a medium and equipment, and belongs to the field of feature point matching. And then applying a template matching algorithm on the left camera image to obtain a matching result of the feature points. The initial depth is calculated based on the actual length of the feature point, the pixel size and the focal length of the binocular camera, redundancy adjustment is carried out in combination with the minimum bounding ball diameter to obtain a depth range, and then the parallax range is calculated. And determining a cut region of interest of the feature points in the right camera image by using the parallax range, performing template matching in the region, and finally determining the three-dimensional coordinates of the feature points by combining the matching result of the left camera and the right camera and the re-projection matrix. The problem that feature points cannot be accurately and efficiently matched in the prior art is effectively solved.

The application provides a mechanical arm grabbing method and system based on cooperation of large field of view and local vision, and relates to the technical field of robot vision recognition. The system comprises an unmanned ship platform, a five-degree-of-freedom mechanical arm, a large field of view vision module, a local vision module and a control module; the large field of view vision module realizes wide range search and tracking of a sea surface target through a spherical camera at a base, guides the unmanned ship to approach, and the local vision module acquires target depth and three-dimensional coordinates by means of binocular stereo cameras of end grippers. The application combines YOLOv8 detection, Kalman filtering and forward dynamics compliant control algorithm, realizes cooperation of the large field of view and the local vision, completes the whole process automation from long-distance target discovery to close-range accurate grabbing, and effectively improves the recognition accuracy and grabbing success rate of the mechanical arm on the sea surface environment on targets such as floating balls and ropes.

The application relates to the technical field of spectral imaging, and discloses a spectral imaging method and system based on hyperspectral low rank and binocular stereo matching, which comprises the following steps: representing a hyperspectral image as based on an SVD algorithm, updating orthogonal spectral bases and coefficients, synthesizing a color image under a CASSI branch perspective by using an initial hyperspectral image, obtaining a disparity between the color image under the CASSI branch perspective and the color image under the RGB camera perspective by using a GwcNet neural network, aligning the color image of the RGB camera to the CASSI branch according to the disparity, forming a new color image, and quickly reconstructing the hyperspectral image by using a low rank algorithm again on the new color image and the original encoded image; the method fully excavates the low rank characteristics of the spectral image, greatly improves the imaging speed, uses the color image to guide the reconstruction of the spectral image, eliminates the image difference possibly caused by the first prism dispersion through twice dispersion, and improves the spectral reconstruction accuracy to a certain extent.

The application discloses a PCB solder paste printing three-dimensional defect detection system based on multispectral imaging, and relates to the field of machine vision detection.The technical scheme points of the application include a multispectral image acquisition module, a four-channel industrial camera based on RGB and near-infrared, and a tunable LED light source array; the reflection characteristic data under different penetration depths are acquired through a wavelength switching mechanism; a motion control trigger module is based on a servo motor driven XYZ three-axis object table, and positioning is realized in cooperation with an encoder feedback; a pulse width modulation signal is adopted to coordinate the camera shutter and the platform moving speed; the application realizes the dual verification of material composition quantitative analysis and three-dimensional topography reconstruction through the combination of the four-channel imaging of RGB and NIR and the Beer-Lambert law modeling, and avoids the limitations of monocular vision; the cross-frame data alignment is realized through the projection of a structured light and a binocular stereo matching technology in cooperation with an ICP algorithm, and the details defects can be better detected.

This invention discloses a portable binocular stereoscopic imaging device based on a single camera, applicable to the field of medical aesthetics. The device comprises an image acquisition component, a supplementary lighting component, and a laser locator. The image acquisition component receives images of the subject reflected from optical paths in two directions, thereby performing 3D modeling. The supplementary lighting component has a mirror angle identical to that of the image acquisition component, ensuring the supplementary lighting angle matches the shooting angle, allowing for uniform illumination of the subject, enhancing lighting, and eliminating shadows. The laser locator allows for adjusting the angle of the laser emitter to set different shooting distances for different subjects. This invention achieves single-camera binocular stereoscopic imaging while not only providing more uniform supplementary lighting but also enabling more convenient adjustment of the shooting distance.

The invention discloses an epipolar alignment method and device for an asymmetric binocular stereoscopic vision system and a storage medium, and the method comprises the steps: carrying out the calibration of two eyes in the asymmetric binocular stereoscopic vision system, and obtaining key parameters; the key parameters comprise internal parameters and external parameters; internal parameters are adjusted, and binocular calibration is carried out again and key parameters are obtained; based on the rotation matrixes in the reacquired external parameters, rotation quantity sharing is adopted to obtain rotation matrixes of the left image and the right image, then directional rotation is carried out on translation vectors in the reacquired external parameters, final rotation matrixes of the left image and the right image are obtained, and perspective transformation matrixes are calculated respectively; performing perspective transformation on the left and right images based on the perspective transformation matrix; and based on the left and right images after perspective transformation, searching a maximum common inscribed regular rectangle by adopting a central epipolar circular scanning method, further cutting the left and right images after perspective transformation, and then matching by adopting one-dimensional parallax. According to the method, the YZ parallax of the asymmetric binocular can be thoroughly eliminated, and more effective pictures can be reserved.

The invention discloses an airport bird identification and tracking method and system based on visual radar fusion, and the method comprises the steps: carrying out the three-dimensional positioning and morphological analysis of an airport airspace target through the cooperative work of a binocular stereo camera and a millimeter-wave radar; a background difference technology is adopted to extract candidate targets, and multi-dimensional descriptors are constructed through visual features such as morphological asymmetry and wing flapping frequency; performing distance and speed verification on a visual identification result by using micro-Doppler features of radar echoes, and determining a bird identification target through fusion error evaluation; an inter-frame image matching and shielding detection technology is implemented to generate a continuous trajectory sequence, and trajectory fluctuation parameters and periodic features are extracted to reflect flight dynamics; according to the method, identification inconsistency parameters are obtained through consistency checking of multi-frame identification results, bird target identification tracking results are output according to quality grading, and reliable information support is provided for airport airspace safety early warning and bird repelling decision making.

This application provides an optical lens, a camera module, and a binocular stereo vision system. The optical lens, used in the binocular stereo vision system, includes multiple lenses, specifically at least eight lenses and a filter. Each lens has a different temperature coefficient of refractive index (dn / dT) to compensate for thermal defocusing when the temperature changes, thereby maintaining the total focal length of the optical lens within a preset range. Here, n is the refractive index of the lens, and T is the temperature. This optical lens achieves a balance of large field of view, high resolution, and clear imaging over a wide temperature range.

The invention discloses a hydraulic lifting tower structure deformation measurement method based on edge feature direction code matching, and belongs to the field of computer vision measurement, and the method comprises the following steps: employing a sub-pixel edge detection method to process a detection region image, and obtaining a sub-pixel edge line position and a sub-pixel edge direction; processing the edge direction angle by adopting a direction code coding method based on the sub-pixel edge direction to obtain a discretized edge direction code, and calculating the edge direction codes of the left and right camera images based on the discretized edge direction code; based on a binocular stereoscopic vision system, matching edge direction codes of left and right camera images by adopting a template matching method and a parallax principle, and calculating a space three-dimensional coordinate of a maximum value point of a matching coefficient in a detection area; and obtaining the deformation amount of the hydraulic lifting tower structure based on the spatial three-dimensional coordinate change of the same detection point before and after the structure deformation.