275 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.

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 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 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.

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 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 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 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 near-eye display device and an image calibration method, and the near-eye display device comprises a projection module which generates projection light of a projection image; the spectroscope is used for transmitting at least part of the projection light rays in a calibration mode and reflecting at least part of the projection light rays for watching in a watching mode; the image generation module is used for converting at least part of transmitted projection light into a re-imaging image in a calibration mode; and the controller is used for acquiring an image calibration parameter based on the reimaging image and a reference image corresponding to the projection image in a calibration mode, calibrating the reimaging image based on the image calibration parameter, and updating the projection image by using the calibrated reimaging image. And when the difference between the re-imaging image and the reference image is smaller than or equal to a difference threshold value, switching to a viewing mode. The near-to-eye display device can be dynamically calibrated in real time on the spot.

The invention discloses a rock-soil deformation measurement method and remote monitoring system based on computer vision, and the deformation measurement method comprises the steps: construction of a target data set, model training, image calibration and monitoring point selection, target matching and search parameter determination, integer pixel search, sub-pixel search, real coordinate conversion, and displacement calculation. The advantages of deep learning rapid positioning and DIC accurate searching are fused, the problems that a traditional DIC method loses efficacy in a severe environment and instantaneous large deformation represented by surface collapse is difficult to track are solved, and monitoring continuity under the temporary shielding condition is kept; the remote monitoring system is composed of an image acquisition module, an image transmission module and a deformation calculation and visual display module, online monitoring and management of rock-soil structure deformation are realized through deformation calculation software and a visual management platform, the cost and deployment difficulty of deformation monitoring are reduced, the accuracy and efficiency of deformation calculation are improved, and the system is suitable for popularization and application. The universality is high, and engineering popularization is easy.

The invention discloses a semi-supervised non-contact neonatal jaundice home intelligent early warning method based on image calibration, and the method comprises the steps: building a camera response function database, and building a color constancy depth model and a skin region segmentation network; designing a strong and weak enhancement strategy by using a large amount of label-free home data, constructing a time and context comparison learning module, and performing self-supervised training on a feature encoder; a small amount of labeled hospital data and a large amount of unlabeled family data are combined, and semi-supervised fine tuning is realized through pseudo label generation and supervised comparative learning; image sequences continuously uploaded by a user are input into the model, multi-day prediction of the bilirubin level is achieved, prediction uncertainty is quantified in combination with a Bayesian method, the risk boundary is dynamically adjusted, and personalized early warning is provided. According to the method, a user does not need to use a physical colorimetric card, color measurement errors caused by model differences of mobile equipment and variability of household illumination are inhibited from a data source, and the accuracy and robustness of subsequent jaundice assessment are improved; through a training framework combining self-supervised pre-training and semi-supervised fine tuning, the understanding ability and generalization performance of the model for the sequential characteristics of jaundice are improved.

The invention provides a geometric recalibration method and device based on a star group time sequence image and electronic equipment, and relates to the technical field of satellite data processing.The geometric recalibration method based on the star group time sequence image comprises the steps that the long-period included angle variable quantity between any two star sensors is counted according to time sequence observation vectors of the star sensors, and the time sequence observation vectors of the star sensors are calculated according to the long-period included angle variable quantity; decomposing the variable quantity of the included angle into a three-axis attitude change angle; performing aberration compensation according to the original data of the star sensor, and determining a three-axis attitude correction value; determining a three-axis optimized attitude angle based on the three-axis attitude change angle and the three-axis attitude correction value of the long-period change of the included angle; and a re-calibration model is determined according to the three-axis optimization attitude angle, and the re-calibration model is solved to obtain an optimal calibration model for image calibration, so that the technical problem of space reference change of the satellite group long-time sequence image in the prior art is solved.

The invention discloses an image processing system and method suitable for a turbid water area, and belongs to the technical field of image processing. The system comprises an underwater camera component for collecting original image data of a turbid water area in real time and an embedded image processing unit. The embedded image processing unit comprises a preprocessing module used for carrying out noise suppression and image calibration processing on original image data, and a physical parameter estimation module used for estimating environment background light intensity of a current water area, a water body attenuation coefficient and a distance map of an object in a scene and calculating initial transmissivity. The scattering correction module is used for removing back scattering and preliminarily compensating a color channel based on a physical imaging model in combination with physical parameters, and the deep learning enhancement module is used for improving image local contrast, adjusting brightness and finely correcting colors by adopting a lightweight deep convolutional neural network. According to the image processing system and method suitable for the turbid water area, the image definition and color of the turbid water area can be improved, the real-time performance is high, and the system and method are suitable for different water area environments.

According to the image calibration and splicing method based on sub-pixel reconstruction and elliptic coefficient weighting, a super-resolution reconstruction module is introduced before image array splicing, the splicing precision is improved through sub-pixel-level image registration, and the splicing precision better than that of a single pixel unit can be achieved. Aiming at the problems of edge dislocation and stiff transition existing in multi-camera array system view field splicing, the invention provides a weighted splicing algorithm based on an elliptic coefficient, and the algorithm constructs an elliptic gradient weight model, realizes smooth transition of an image boundary region, and remarkably improves the overall visual effect of a panoramic image.

The invention discloses an image multi-target detection system and method based on a channel attention mechanism, and relates to the technical field of neural network image processing. The system comprises an image processing module, an image calibration module, a bounding box screening module and a multi-target detection module, wherein the image processing module performs automatic image enhancement on an original image based on image enhancement parameters obtained based on historical image data and contrast credibility parameters, and then performs feature extraction to obtain an original feature map of each channel; the image calibration module dynamically corrects the weight ratio of each channel based on the detection target parameter, and calibrates the original feature map of each channel according to the weight ratio; a bounding box screening module performs classification regression processing on the calibrated feature map to obtain each potential target, and performs confidence evaluation and similarity evaluation on each potential target based on a confidence score, a target feature vector and a target position vector to obtain each final multi-target; and the multi-target detection module performs multi-target detection based on each final multi-target.

The invention relates to the technical field of medical data processing, in particular to an inspection report multi-modal generation system which comprises a structure extraction module, an image calibration module, a physical sign association module, a time sequence revision module and a number verification module. According to the method, a continuous structure area in an image is constructed and recognized through a gray scale direction path, the continuity and boundary definition of a mask layer are improved in combination with an edge gray scale trend, an offset point set is constructed through direction jump differences, fine registration between images of different modes is achieved, and multi-sign records are subjected to time sequence cross comparison through change inversion points, so that the accuracy of registration is improved. The method comprises the following steps: establishing a rhythm corresponding relation, enhancing the accuracy of time sequence information expression, performing time projection on unpaired inflection points depending on a direction stable section, supplementing data rhythm discontinuity, keeping the consistency of a sign data time axis, and combining field difference position comparison with integrity judgment, thereby realizing the guarantee of sorting specification and output consistency of multi-source equipment records.

The invention provides an infrared visible light image data fusion method. Infrared visible light automatic registration is realized through a cross-modal image registration technology; after registration of an infrared image and a visible light image, image fusion is realized by using a cross-modal registration-oriented image fusion method so as to realize intelligent identification of typical heating hidden dangers of a power transmission line. An infrared-visible light image calibration fusion technology research, an identification technology research of common heating parts under a limited sample condition, an infrared thermal hidden danger identification technology research under a dual-light fusion condition, and a related standard research of unmanned aerial vehicle infrared-visible light inspection data fusion analysis are developed. Research on contents such as development of an infrared-visible light inspection data fusion analysis algorithm module of the unmanned aerial vehicle and the like. The research result can be applied to the fields of defect identification and analysis of the power transmission line, solves the problems of large workload and low efficiency of unmanned aerial vehicle infrared inspection data analysis, and greatly promotes the application of the big data technology in the power transmission line.

The invention discloses a fusion calibration method for semiconductor measurement equipment, and the method comprises the steps: S1, executing the calibration of an optical navigator, so as to establish a first conversion relation between a CCD camera image coordinate system and a workpiece table coordinate system; s2, executing SEM image calibration to establish a second conversion relation between an SEM image coordinate system and a workpiece table coordinate system; s3, based on the first conversion matrix generated in S1 and the second conversion matrix generated in S2, realizing fusion calibration of a CCD camera image coordinate system, an SEM image coordinate system and a workpiece table coordinate system; wherein fusion calibration is used in semiconductor wafer measurement, initial positioning is carried out through a large view field of a CCD camera so as to distinguish repeated patterns, fine positioning is carried out through high resolution of an SEM image, and nm-level precision is achieved. The method has the advantages of remarkably improving the precision, stability and efficiency of semiconductor measurement equipment and the like.