343 results about "Image calibration" patented technology

The invention provides an interaction method and system applied to painting and calligraphy exhibition, and relates to the technical field of data interaction, and the method comprises the steps: building a user exhibition watching behavior data set through real-time collection based on an exhibit region; traversing the exhibit area to carry out multi-dimensional image calibration, and establishing a coordinate-label mapping network; traversing the coordinate-label mapping network set according to the user exhibition viewing behavior data set to activate an exhibit identification module, identifying a target exhibit number to perform linkage display of painting and calligraphy on a target user, generating display information, starting an exhibit interaction module to perform deep interaction on the target user in combination with the display information, and generating a personalized painting and calligraphy display guide path. The technical problem that in the prior art, due to the lack of real-time perception and accurate recognition of exhibition watching behaviors of users, personalized exhibit linkage and dynamic guide cannot be achieved is solved, and the technical effect that the personalized guide path is generated based on the interests of the users, so that the exhibition watching immersion and interactive experience are improved is achieved.

An electronic device for processing a blood vessel image according to an embodiment may include: an arc-shaped C-arm open toward the isocenter; a radiation source connected to the C-arm and emitting radiation to a target blood vessel located on a table; and a processor for computing a target distance from the radiation source to the target blood vessel, on the basis of a first vertical distance from the isocenter to the table and a second vertical distance from the target blood vessel to the table, and computing a physical distance of the target blood vessel by using the computed target distance, from a blood vessel image obtained using radiation.

The invention relates to the technical field of image calibration, and discloses an ink-jet printer real-time image calibration system and method based on edge calculation, and the method comprises the steps: constructing a composite parameter matrix, completing the no-load error analysis, and generating a compensation matrix and a dynamic weight distribution function; constructing a multi-scale gradient feature pyramid according to the composite parameter matrix, fusing the features of the pyramid to generate a feature correlation thermodynamic diagram, and establishing a model to predict an ink diffusion trajectory after correction; and finally generating a control signal by combining the compensation matrix and the prediction result, and controlling the motion pose of the nozzle. According to the method, the code spraying process is accurately controlled by integrating multiple factors, the precision and quality of code spraying patterns are remarkably improved, the rejection rate is effectively reduced, and the production efficiency is improved.

The invention discloses a key point detection-based fish size estimation system and method in a complex underwater environment. An image acquisition module acquires a calibration plate image and left and right images of a fish; the calibration parameter acquisition module acquires calibration parameters; the distortion correction module performs distortion correction on the left and right images; a depth information calculation module calculates depth information corresponding to the pixel points of the left image; the data set construction module is used for marking a fish body and constructing a fish key point detection data set; the image enhancement module performs image enhancement on the left image; the key point detection model construction module constructs a key point detection model, the model training module trains the key point detection model and identifies a fish target and key points in an image, the key point moving module moves the key points, and the fish size calculation module obtains depth information of the moved key points. And converting the pixel coordinates into world coordinates, and calculating the distance between the key points to obtain the fish size. According to the invention, accurate estimation of the fish size is realized.

The invention belongs to the technical field of space remote sensing surveying and mapping, and particularly relates to a monitoring system and method for a front and rear view visual axis included angle and absolute direction of a surveying and mapping camera. The method comprises the following steps: S1, through side sway of a satellite platform, taking a time for sky imaging calibration as a reference time; s2, calculating a rotation matrix from a front and rear view ground camera measurement coordinate system to a star camera coordinate system at a reference moment; s3, calculating respective thermal deformation matrixes of the star camera coordinate system, the front-view camera measurement coordinate system and the rear-view camera measurement coordinate system; s4, obtaining a real-time rotation matrix from the measurement coordinate system of the front-view camera to the coordinate system of the star camera and a real-time rotation matrix from the measurement coordinate system of the rear-view camera to the coordinate system of the star camera at the measurement moment; and S5, carrying out arc cosine calculation on the two absolute pointing vectors to obtain a visual axis included angle between the front-view camera and the rear-view camera at the measurement moment. According to the invention, while the geometric accuracy of the surveying and mapping camera is ensured, the real-time performance of measurement and the comprehensiveness of subsystem monitoring are realized at the same time.

The invention relates to the field of microscopic imaging, and discloses a miniature microscopic system optical precision improvement and image calibration error optimization method, which comprises the following steps: establishing an optical distortion model and a mechanical disturbance model, and respectively describing a static error and a dynamic error; constructing a joint dynamic error model, and uniformly expressing a coupling relationship between optical distortion and mechanical disturbance; decoupling and separating the joint error through a space-time separation method to obtain a static error component and a dynamic error component; performing iterative optimization on the optical distortion parameter and the mechanical disturbance parameter based on an optimization algorithm to minimize a system calibration error; a real-time sensor is utilized to obtain dynamic disturbance data, and real-time dynamic compensation is performed on an image calibration error in combination with an optimization result, so that a high-precision calibration result is obtained. The method can effectively improve the calibration precision of the microscopic system in a dynamic environment, remarkably improves the imaging quality of the system, and has a wide application prospect.

The invention discloses an image feature calibration method based on motion offset, and relates to the field of track detection image processing. The method comprises the steps of motion image acquisition, initial image calibration, fuzzy feature calibration and calibration image output. Acquiring real-time acceleration data through a train acceleration sensor, and converting the real-time acceleration data into pixel displacement deviation to realize preliminary calibration so as to obtain a reference processing image; based on historical database target features, separating a target body from an environment area, generating an environment point processing curve in combination with motion parameters, and screening a to-be-calibrated pixel set through feature fitting; a fuzzy feature calibration strategy is adopted to calibrate pixels and then fuse the calibrated pixels with a reference image, and the calibration precision is dynamically optimized through curve calibration and effect verification steps. Layered calibration is realized, the detail reduction degree of the moving image is improved, the environmental adaptability is enhanced, the target feature integrity is guaranteed, and the method is suitable for a rail transit image monitoring scene.

The invention provides an attitude measurement camera coordinate system calibration method, apparatus and device, and a storage medium, which can be applied to the technical field of measurement calibration. The method comprises the steps that a calibration plate is constructed, a conversion target seat and at least one reflective mark point are arranged on the calibration plate, the conversion target seat is used for placing a cube-corner prism target ball and a photogrammetry target ball, the cube-corner prism target ball and the photogrammetry target ball are the same in diameter, and the calibration plate is placed at different positions in a view field of an attitude measurement camera; the method comprises the following steps: acquiring three-dimensional coordinates of a cube-corner prism target ball by using a laser tracker, replacing a photogrammetric target ball, shooting an image of a calibration plate by using an attitude measurement camera to obtain the three-dimensional coordinates and a plurality of images of the cube-corner prism target ball in a laser tracker coordinate system, and calculating the three-dimensional coordinates of the cube-corner prism target ball according to the three-dimensional coordinates and the plurality of images of the cube-corner prism target ball in the laser tracker coordinate system. And calibrating a coordinate system of the attitude measurement camera. The extraction precision of the two-dimensional image coordinates of the target spot can be improved, and then the calibration precision of the coordinate system is improved.

The invention is suitable for the technical field of welding defect detection, and provides a welding defect detection method and system, and the method comprises the steps: constructing a region-of-interest extraction model, a permeability meter line model and a welding defect model based on a target detection algorithm; inputting a to-be-detected welding image into the region-of-interest extraction model to obtain a penetration meter region, a welding bead region and a positioning mark region; inputting the permeameter area into the permeameter line model to obtain a visible line detection result, and obtaining image calibration information based on the visible line detection result; the welding bead area is input into the welding defect model, and a defect detection result is obtained; based on the image calibration information and the positioning mark area, the defect detection result is mapped to the physical welding area, welding defects are positioned, automatic detection of welding production is achieved, and then the production quality of welding workpieces is improved.

The invention discloses a satellite-borne inverse synthetic aperture radar motion compensation imaging calibration integration method, equipment and a medium, and relates to the technical field of radar signal processing and radar imaging. The objective of the invention is to solve the problems of inaccurate motion compensation and difficult large-rotation-angle imaging in ISAR imaging. According to the method, a particle swarm optimization algorithm is adopted to optimize motion parameters, optimal motion parameters are obtained, and the motion parameters comprise relative translation motion parameters and relative rotation motion parameters of a target and a radar; and obtaining focusing and calibration imaging results based on the optimal motion parameters and echo data reflected by the target. The influence of the translation compensation effect on rotation parameter estimation is reduced, more accurate parameter estimation and better imaging focusing performance are realized, and the ISAR imaging problem under the condition of violent relative movement in the rendezvous scene is solved.

The invention provides a polyvinyl chloride sheet defect detection method and system based on image recognition, and relates to the technical field of quality detection.The method comprises the steps that a plurality of detection area coordinates are preset in an image acquisition system, and through position mapping and real-time image calibration of the plurality of detection area coordinates, the detection area coordinates are obtained; and aligning the actually shot image with the detection areas of the polyvinyl chloride sheet, and generating a final defect result according to a detection result obtained by identifying each detection area. According to the method and the device, the technical problem that the reliability of an overall quality evaluation result is affected due to the fact that the traditional image detection method is limited in sheet feature extraction capability, the defect recognition accuracy is not high and local anomaly is difficult to position is solved, and the reliability of the overall quality evaluation result is improved by constructing a multi-detection-area mapping mechanism based on a standard geometric template. And in combination with image registration, feature recognition and defect judgment algorithms, the detection precision of sheet defects is improved, so that the recognition accuracy of the quality state of the polyvinyl chloride sheet and the efficiency of the detection process are improved.

The invention discloses an oral cavity three-dimensional scanning system and a control method thereof, electronic equipment and a storage medium, and relates to the technical field of oral cavity three-dimensional scanning. The method comprises the following steps: controlling a projection module to alternately project white light and projection fringes generated based on Debrueine coding on a preset chessboard graph in different time periods towards a target; controlling the target to move, and controlling the imaging module to shoot a plurality of target images towards the target; the target image comprises a coding stripe image collected at the same position and a checkerboard image collected under white light; the multiple checkerboard images are calibrated to obtain imaging calibration parameters of the imaging module, meanwhile, after the multiple coded stripe images are calibrated to obtain projection calibration parameters of the projection module, a system calibration result is determined, and calibration is completed; and performing three-dimensional reconstruction processing based on the system calibration result on the to-be-reconstructed object to obtain a three-dimensional reconstruction result. The calibration efficiency and the calibration accuracy when the oral cavity three-dimensional scanning system is calibrated can be improved.

The invention relates to the technical field of tunnel crack detection, and discloses a tunnel crack image identification method and a tunnel wall uniform image detection system. The method comprises the steps that tunnel images are collected, images belonging to cracks are calibrated to form an image set, and a crack target sample library is constructed; performing target detection identification on the collected tunnel image set, optimizing a target identification method according to an identification result, and outputting multiple tunnel crack disease detection images; extracting crack features from the collected tunnel image set; and based on the multiple tunnel crack disease detection images, performing pixel-level segmentation on the tunnel crack disease to complete tunnel crack identification. According to the invention, the traditional layout is broken, the requirements of closer shooting object distance and depth of field are met, and the detection requirement of smaller width of the welding seam is met; according to the algorithm level, a front image preprocessing part of deep learning training is optimized, especially contrast enhancement, multi-level fusion and the like are added, and the recognition accuracy of a tiny target can be further improved.

The invention discloses an unmanned aerial vehicle image calibration method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the image data of an unmanned aerial vehicle image, and carrying out the analysis of the image data, and obtaining the parameter information of the unmanned aerial vehicle image and the flight attitude information of an unmanned aerial vehicle; wherein the flight attitude information comprises a pitching angle, a rolling angle and a flight height; calculating the initial resolution of the image center point of the unmanned aerial vehicle image according to the parameter information and the flight height, and calculating the initial resolution of the image center point of the unmanned aerial vehicle image according to the initial resolution, the pitching angle, the rolling angle and the offset distance of each pixel point in the unmanned aerial vehicle image relative to the image center point. Calculating the actual resolution of each pixel point in the unmanned aerial vehicle image; and according to the actual resolution, calibrating the resolution of each pixel point in the unmanned aerial vehicle image to obtain a calibrated unmanned aerial vehicle image. According to the invention, the calibration precision of the unmanned aerial vehicle image can be improved.

The invention discloses an unmanned aerial vehicle inspection system and method for an intelligent street lamp based on multi-source video fusion, and relates to the technical field of unmanned aerial vehicle inspection, and the system comprises an inspection data collection module, an inspection image analysis module, an inspection mode switching module and an inspection task dynamic evaluation module. The inspection data acquisition module, the inspection image analysis module, the inspection mode switching module and the inspection task dynamic evaluation module are in communication connection with one another; wherein the inspection data acquisition module is used for performing flight inspection on street lamps in a target inspection area one by one through an unmanned aerial vehicle with a visible light camera, and setting image calibration array points to match the accuracy of inspection image acquisition; the inspection image analysis module is used for processing and analyzing the acquired image data; according to the invention, the problem that the inspection time consumption and the data processing burden are greatly increased in the existing multi-source image fusion processing mode is solved.

The invention relates to the field of track detection, in particular to a vision-based rapid identification method for a target object in a track area, which comprises a target object image sampling step, a fuzzy database construction step, a sampled image calibration step and a target object rapid identification step. The problems of image blurring, multi-source errors and real-time performance under high-speed movement are systematically solved; the beneficial effects of efficiently coping with image blurring and dynamic interference, improving system robustness and detection coverage rate through a multi-camera cooperative calibration mechanism, adapting to a complex operation environment through a dynamic error elimination strategy, and improving detection reliability and safety are achieved.

The invention discloses an unmanned aerial vehicle surveying and mapping method and system based on three-dimensional point cloud data analysis, and relates to the technical field of unmanned aerial vehicle surveying and mapping. Determining the altitude of a key position node, and constructing an initial three-dimensional model; analyzing the laser data, generating a ground point cloud model, and screening an adjustment strategy with a high initial matching degree through proportional adjustment, rotation and translation optimization; and comparing the ground image with the surveying and mapping block features, determining a secondary matching degree, selecting an optimal point cloud model, and outputting data in combination with surveying and mapping marks. According to the method, GIS positioning, node modeling, point cloud optimization and image calibration are creatively fused, the complex terrain surveying and mapping precision is improved, and the method is suitable for the fields of engineering planning and the like.

This application provides a method for determining a wireless signal strength in an area, a computer-readable storage medium, and an electronic device. The method includes: obtaining building diagram information, wherein the building diagram information comprises a position of a target signal source, a target area, size information of one or more obstacles in the target area, type information of the one or more obstacles, and image calibration information; converting the building diagram information into a polar coordinate system; determining an attenuation amount of a target pixel based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system, wherein the propagation path penetrates at least part of the one or more obstacles; and determining a signal strength of the target pixel based on a signal strength of the target signal source and the attenuation amount of the target pixel.

The embodiment of the invention is suitable for the technical field of medical imaging and image calibration, and provides an ultrasonic probe calibration method and system and electronic equipment, and the method comprises the steps: receiving an ultrasonic probe pose sequence and a calibration model pose sequence; receiving an ultrasonic image sequence; performing mark point identification and straight line identification on the ultrasonic image sequence to determine a first noise image and a second noise image in the ultrasonic image sequence; after the second noise image is deleted from the ultrasonic image sequence, time calibration is carried out on the ultrasonic probe, and a rate difference value between an ultrasonic probe displacement signal and an ultrasonic image displacement signal is obtained; and after deleting the first noise image from the ultrasonic image sequence, performing spatial pose calibration on the ultrasonic probe based on the rate difference value to obtain a spatial pose calibration matrix of the ultrasonic probe. By adopting the method, the calibration precision of the ultrasonic probe and the stability of the calibration result can be improved.

The invention discloses a micro-scale mixing effect induced carbonate precipitation rate coefficient calculation method, which comprises the following steps: S1, carrying out a micro-scale mixing effect induced carbonate precipitation visualization experiment to obtain a carbonate precipitation image data set; s2, establishing a carbonate precipitation identification model, wherein the carbonate precipitation identification model sequentially comprises three steps of image calibration, gray scale iteration adjustment and precipitation identification; s3, establishing a carbonate precipitation rate calculation model, wherein the carbonate precipitation rate calculation model sequentially comprises three steps of pixel point statistics, precipitation amount calculation and precipitation rate calculation; and S4, establishing a carbonate precipitation rate coefficient calculation model, wherein the model comprises precipitation rate analysis and precipitation rate coefficient calculation. The calculation of the rate coefficient of the carbonate precipitation induced by the mixing effect under the microscale is realized, and support is provided for understanding the carbonate precipitation mechanism in the karst area and improving the geological storage efficiency of carbon dioxide and the efficiency of calcium carbonate precipitation induced by microorganisms.

The invention discloses a diamond microstructure precision grinding system and method with visual positioning, and the method comprises the following steps: collecting a microscopic visual image, calibrating a visual coordinate system and a machine tool coordinate system, and building a unified positioning coordinate system; extracting composite visual features, constructing an energy field, performing adaptive partitioning, and generating risk partitioning codes; the risk partition codes are input into a double-flow network, grinding signals are input into grinding branches, and parameter tracks are generated; precisely grinding according to a segmented parameter track, reducing the cutting depth and the speed in a high potential energy area, and increasing the speed in a low potential energy area; after grinding, obtaining a three-dimensional shape, performing error analysis and energy spectrum generation, and mapping to risk partition coding; and according to the error energy and the energy field, the grinding priority is judged, and high-priority partitions are selectively ground and remeasured. According to the method, the visual potential energy field is constructed and the improved double-flow neural network is fused, so that accurate positioning, self-adaptive grinding control and high-precision micro-area grinding of the diamond microstructure are realized.

The invention discloses a structured light camera exposure duration prediction method based on RGB information. The method is divided into a camera calibration stage and a camera working stage. In a camera calibration stage, firstly, a two-dimensional color image calibration plate is shot with different exposure durations to obtain a corresponding two-dimensional color image sequence and a three-dimensional point cloud image sequence, and the two-dimensional color image sequence and the three-dimensional point cloud image sequence are used to calibrate a camera response function of RGB three channels of a camera and cut-off exposure of the RGB three-color channels corresponding to complete point cloud information. In the working stage of the camera, a two-dimensional color image sequence of a working scene is firstly shot, and the optimal exposure duration of the three-dimensional point cloud image of the structured light camera is calculated by using the camera data obtained in the calibration stage. The method provided by the invention has good adaptability to complex ambient light, and compared with manual adjustment of exposure duration, the three-dimensional point cloud imaging speed of the structured light camera adopting the method provided by the invention is greatly increased, and the imaging quality is obviously improved.

The invention provides a line-scan digital camera image-based high-precision calibration method, a measurement method and a system, and relates to the field of automatic optical measurement of plates, and the calibration method comprises the following steps: constructing a hardware mechanism for line-scan digital camera image calibration; acquiring a linear array camera image based on a hardware mechanism; performing distortion calibration on each line-scan digital camera based on the line-scan digital camera images so as to obtain reference point X coordinates, X-axis average precision, distortion correction coefficient arrays, working distances, grid numbers, Y longitudinal view offset pixels and Y longitudinal average precision corresponding to different intervals, wherein the reference point X coordinates, the X-axis average precision, the distortion correction coefficient arrays, the working distances, the grid numbers, the Y longitudinal view offset pixels and the Y longitudinal average precision correspond to different intervals; and performing multi-machine joint calibration on the plurality of line-scan digital cameras based on the line-scan digital camera images so as to obtain the proportion of the blind area width corresponding to different intervals to the height difference of the calibration plane. Calibration data are obtained on the basis of high-precision calibration, automatic optical detection is carried out on the thickness of the plate in combination with the calibration data, and the problems that existing plate size measurement is low in efficiency, poor in precision and poor in repeatability are solved.

The invention provides an intelligent image calibration system based on a vehicle-mounted AI, and the system comprises a vehicle-mounted image collection device, and also comprises an image marking subsystem and an image calibration subsystem. The image marking subsystem comprises an image screening module, an image processing module, a feature marking module and a feature construction module; the image calibration subsystem comprises a feature index module, an extraction marking module, a feature comparison module and a parameter correction module; element features are determined from environment image information of a scene point through an image marking subsystem, an element feature model is configured in advance, when a vehicle passes through a scenic spot again, an image calibration subsystem compares reference shooting features with actual shooting features to generate comparison difference information, then image parameters and position parameters at each moment are calibrated, and the scene point is obtained. And the image acquisition unit is configured in an optimal acquisition state, so that the reliability of vehicle image acquisition is improved, and support is provided for functions of intelligent driving, obstacle avoidance and the like.

The invention relates to the technical field of image calibration, in particular to a layered grating image auxiliary calibration system, which comprises a brightness intersection point screening module, a node synchronous correction module, a reference difference extraction module, a spatial offset distribution module and a template link updating module. According to the invention, through directly extracting change characteristics of pixel brightness, deep screening of image structure information, real-time pairing and synchronous compensation of space nodes after acquisition, dynamic capturing and detailed comparison of space states between grid reference points are realized, and a system automatically distributes space errors to each grid point position. The parameter linkage compensation keeps the overall space coordination among lattice points, template data are reconstructed in real time and are subjected to chain mapping, the space data are continuously synchronized in the calibration process, the space parameter correction keeps high adaptability under noise disturbance, and continuous dynamic response can be realized by adapting to a multi-scene environment. And the calibration stability and the data chain integrity under different illumination, shielding and non-ideal conditions are enhanced.

The present application discloses an image processing method, apparatus and system based on artificial intelligence, and a storage medium. The method comprises: acquiring a calibration image of a calibration apparatus, wherein the calibration apparatus comprises a pattern plate with a plurality of patterns; performing feature extraction on the calibration image to obtain a first feature map; inputting the first feature map into a frame regression network to output a plurality of regions of interest corresponding to the calibration apparatus in the first feature map; generating a preset number of candidate frames for each region of interest on the basis of a preset prior frame, the size of each candidate frame being the same as that of the preset prior frame, and the preset number being determined on the basis of the number of the patterns; and inputting all the candidate frames and the first feature map into a center regression network to obtain image center point coordinates of each pattern in the calibrated image. The solution can obtain clear imaging edge information, even if the imaging quality is poor, an accurate candidate region can be obtained, and the detection precision of image recognition is significantly improved.

The invention provides a mixed type purple boundary correction method and system, electronic equipment and a medium. The method comprises the following steps: calculating corresponding purple boundary intensity based on basic information of pixel points in an original image and basic information of corresponding first candidate points; according to the purple edge intensity of each pixel point, determining whether the pixel point is a purple edge pixel point, and if not, skipping the current pixel point; if yes, acquiring an adaptive filtering window of the current purple edge pixel point by using a set image calibration strategy; calculating corresponding candidate compensation colors according to the self-adaptive filtering window and purple boundary intensity of each purple boundary pixel point; and according to the candidate compensation color of each purple edge pixel point, the basic information and the basic information of the corresponding second candidate pixel point, calculating to obtain a corresponding saturation reduction intensity, and according to the saturation reduction intensity of each purple edge pixel point, carrying out saturation reduction processing on the candidate compensation color to obtain a corresponding target compensation color. According to the method and the device, the purple edge can be effectively removed, and meanwhile, the processed image space is naturally transited.

The invention relates to the technical field of computer vision and intelligent monitoring, and particularly discloses a pavement ponding detection method based on image calibration and dynamic region segmentation, which comprises the following steps of: firstly, selecting a reference frame image in a ponding-free or slight ponding state from a road monitoring video, and manually marking a ponding region to generate a reference mask; the method is used as a unified detection reference standard. And then, frame extraction is performed on a to-be-detected video, pixel-level identification is performed on each frame of image by using a pre-trained semantic segmentation model, a water accumulation area of a current frame is automatically extracted, and a current water surface mask is generated. And dynamically judging the diffusion or fading trend of the accumulated water by calculating the difference value between the pixel area of the current frame accumulated water area and the pixel area of the reference mask accumulated water area. According to the method, the defects that a traditional sensor is high in deployment cost and complex in maintenance and an existing visual method is prone to being interfered and cannot be quantitatively changed are overcome, and low-cost, high-adaptability and quantifiable continuous automatic monitoring and early warning on the road surface ponding range is achieved.

The invention discloses a calibration method and system based on multi-scale feature fusion and an adaptive optimization algorithm, and belongs to the technical field of computer vision. The method comprises the following steps: collecting a plurality of images containing calibration modes; detecting and positioning feature points by adopting a multi-scale feature fusion technology, and distributing a confidence score for each feature point; carrying out feature point matching and removing abnormal values by using an improved RANSAC algorithm based on the prior geometrical relationship and confidence score; preliminarily calculating camera parameters; and a nonlinear optimization model fusing confidence weighting and adaptive regularization is constructed, joint optimization is performed on camera parameters, and a high-precision calibration result is output. According to the method, through an optimization mechanism of multi-scale feature fusion and confidence guidance, the problems of unstable feature point detection, abnormal value sensitivity and insufficient precision of a traditional method in a complex environment are effectively solved, and the accuracy, robustness and automation degree of image calibration are remarkably improved.

The invention provides a vehicle-mounted image calibration method and device, equipment and a storage medium. The method comprises the steps that first pose information of cameras located on the two opposite sides of a vehicle body under a world coordinate system is acquired; converting the first pose information into second pose information of the camera in a standard coordinate system; and based on the second pose information, determining a homography transformation matrix of the camera, so as to determine a corresponding rendered image of the camera under the target visual angle based on the homography transformation matrix. Thus, the first pose information of the cameras on the two opposite sides of the vehicle body is converted into the second pose information, it is guaranteed that the view angles of the cameras on the two opposite sides of the vehicle body are symmetric, and the symmetric rendering images under the target view angle are finally obtained. Besides, the first pose information is converted into the second pose information, so that the individual difference of the installation angles of the cameras is ignored in a standard coordinate system, independent wheel visual angle parameter adjustment does not need to be carried out on each camera, and the vehicle-mounted image calibration efficiency can be improved.