690 results about "Perspective transformation" patented technology

The invention discloses a self-adaptive three-dimensional scene reconstruction method and system based on a single panorama, and belongs to the field of computer vision processing. The method comprises the following steps: firstly, generating a depth map through an indoor scene panorama and constructing an initial three-dimensional grid; then generating a multi-view image and a shielding mask thereof based on view conversion, forming a training sample pair for fine tuning of the diffusion completion model, and injecting scene prior information for the model; then extracting a grid boundary contour and calculating a central axis, and adaptively constructing a camera pose set; after the integrity of the grid is optimized through iteration completion, the grid is converted into a 3D Gaussian sputtering field, and Gaussian point parameters are optimized through multi-view data; in the optimization process, an up-sampling strategy of rendering error feedback and edge Gaussian points is adopted, and finally a scene model with complete geometric textures is output. According to the method, a high-quality three-dimensional scene is reconstructed from a single panorama through a structure self-adaptive completion and Gaussian refining technology, and the method is particularly suitable for immersive roaming reconstruction of indoor scenes.

The invention discloses a control method for an underwater cleaning robot, and the scheme can comprise the steps: S1, collecting an environment image of a to-be-cleaned region through a global camera, and carrying out the distortion correction and perspective transformation preprocessing, and obtaining a preprocessed image; s2, generating a static environment map according to the preprocessed image, wherein the static environment map comprises obstacles and dirt sub-regions; s3, adopting a multi-scale path planning strategy: firstly, dividing a map by using a first-scale grid, determining a cleaning end point, and planning an access sequence based on an A * algorithm; setting the first dirt sub-region as a target, and planning a path to a boundary turning point of the first dirt sub-region; dividing a map by using a second scale grid, and planning a path from a turning point to a cleaning end point; and updating the operation starting point and removing the processed area, and circulating until the operation path sequence is generated. And S4, the underwater cleaning robot completes cleaning operation on all the dirt sub-areas according to the planned path.

The embodiment of the invention provides a GIS (Geographic Information System)-based metropolitan area safety video monitoring method and system. The method is applied to the technical field of image processing and comprises the following steps: acquiring a video picture of a coverage area in real time through a camera; performing real-time analysis on the video picture by using a target detection algorithm, and identifying a target in the video picture; converting the position of the target in the video picture into an actual geographic coordinate based on coordinate system conversion; continuously tracking the target in different camera coverage areas through the geographic coordinates; based on perspective transformation, converting the video image into an aerial view angle, and splicing aerial views to form a panoramic view; and visualizing the geographic coordinates of the target in the aerial view. In this way, the efficiency and accuracy of the city monitoring system can be improved, and therefore the requirement for city safety monitoring can be better met.

The invention discloses a method for a mowing robot to move along a lawn boundary based on a local grid map, and relates to the field of mowing robot edge navigation movement, and the method comprises the steps: recognizing a target region and an obstacle region through a semantic segmentation algorithm, constructing a dynamically updated local grid map through the combination of improved inverse perspective transformation and depth point cloud information, and carrying out the navigation of the target region and the obstacle region; no physical boundary dependence is realized, the deployment cost is reduced, and the real-time processing efficiency of acquired images can be improved; according to the local grid map, the edge navigation deflection angle is calculated through lawn boundary feature extraction in combination with the position of the robot, precise navigation of the robot along the lawn boundary is achieved, rapid response of dynamic obstacles is supported, and the edge movement precision and operation efficiency of the mowing robot are remarkably improved. The problems that an existing mowing robot is low in edge movement precision and poor in operation efficiency due to the fact that an edge track cannot be decided in real time and calculation efficiency cannot be considered at the same time are solved.

The invention provides an evidence obtaining method and system based on image processing, and the method comprises the following steps: S1, generating a pixel-level depth-of-field distribution diagram of an input image through a multi-scale encoder-decoder network, employing an edge perception optimization layer in a decoding stage, and improving the depth-of-field boundary precision through minimizing a local gradient consistency loss function; s2, performing depth-of-field rationality verification based on an optical imaging physical model, and triggering a first-level tampering alarm by calculating a defocusing fuzzy radius and a gradient direction of a selected region when a difference between the defocusing gradient directions of a target region and a background region exceeds a preset threshold value; and S3, dynamically positioning a key pixel region, identifying a depth-of-field mutation boundary by using an edge detector, calculating by combining local texture complexity, screening a pixel set of which the entropy value is higher than a threshold value and which is located at the mutation boundary, correlating metadata to verify the rationality of the physical size and the spatial position of an object, and eliminating false detection caused by perspective transformation.

The invention discloses a heading equipment cutting head position calibration method based on image acquisition, which comprises the following steps: S1, acquiring image data and preprocessing the image data; s2, extracting cutting head feature points, and constructing a two-dimensional feature point set; s3, calculating a three-dimensional coordinate by using perspective transformation, and generating a point cloud set; s4, performing rigid registration on the point cloud set and a standard structure model of the tunneling equipment, and iteratively solving a rotation matrix and a translation vector to obtain pose parameters; s5, simulating change tracks of the feature points in continuous frames, constructing a time consistency constraint, and optimizing pose parameters; s6, the optimized three-dimensional coordinates are converted to a reference coordinate system, space alignment is completed, and a position calibration result is generated; and S7, outputting a calibration result for control instruction generation and path planning. According to the invention, high-precision and non-contact three-dimensional position calibration of the cutting head of the tunneling equipment is realized, and operation automation and control precision are improved.

The invention relates to the technical field of information, and discloses a parking lot panoramic safety monitoring method and system, and the method comprises the steps: obtaining a real-time video stream of a parking lot, and carrying out the denoising preprocessing of each frame of image, and obtaining a clear image; adjusting the brightness and the contrast ratio of the clear image by adopting a self-adaptive illumination compensation algorithm to obtain an illumination compensation image; according to the angle and distance change of the vehicle, correcting the vehicle image visual angle in the enhanced image by adopting a perspective transformation algorithm to obtain a perspective transformation image; identifying a vehicle position and a bounding box in the perspective transformation image by adopting a vehicle detection model based on deep learning, and determining a specific position of the vehicle in the image; and in the vehicle dense area, a multi-target tracking algorithm is combined with the moving tracks and the feature information of the vehicles, the shielding relation between the vehicles is judged, and the positions of the shielded vehicles are determined. The method can realize panoramic safety monitoring of the parking lot.

The invention discloses an inclined pointer instrument accurate reading identification method based on a cascade model. The problem that a traditional method is low in reading accuracy under the scenes of complex backgrounds, inclined shooting and the like is mainly solved. The method comprises the following steps: constructing a cascade model: positioning an instrument area through an instrument detection model, cutting the instrument area, analyzing scale line and pointer features through an instrument feature extraction model, and extracting a dial center, a main scale line and a pointer position in combination with key point detection and a semantic segmentation technology; inclination correction optimization: calculating a perspective transformation matrix according to the main scale line endpoint coordinates, performing rotation correction on the inclination instrument image, and eliminating a visual angle inclination error; and angle method reading calculation: based on the corrected image, realizing accurate reading by combining the angle relation between the pointer and the adjacent scale lines with OCR identification scale values. According to the method, the recognition accuracy and robustness in a complex scene are remarkably improved, computing resources are reduced, and the recognition precision of instrument reading is improved.

The invention discloses a coal mine belt deviation real-time lightweight detection device and a coal mine belt deviation real-time lightweight detection method based on image sub-pixels, firstly, the device captures video streams of belt operation in real time through an image acquisition device, analyzes the video streams in real time by means of edge computing nodes, and monitors the running state of a belt in real time to determine the deviation of the belt; once the belt starts to work, image distortion caused by a shooting angle or environment is immediately corrected through perspective transformation. Secondly, automatically selecting a high-contrast reference strip through an image preprocessing method, and accurately extracting a region near the belt edge as a minimum region of interest, namely a belt edge region; then, a lightweight sub-pixel convolutional neural network is used to carry out deep analysis on the areas, and a high-quality super-resolution image is generated, so that the accuracy of edge detection is further improved. And finally, accurately identifying and positioning the edge position of the belt by introducing a bidirectional edge tracking method with an abnormal detection function, thereby realizing real-time and accurate detection on the deviation condition of the belt.

The invention relates to a monocular vision tower span measurement method based on RTK correction, and belongs to the technical field of space distance measurement. Comprising the following steps: acquiring ambient light intensity and quality in real time based on an environment where a power transmission and distribution tower is located, and obtaining ambient light adaptation parameters by analyzing ambient light data and adjusting ISO sensitivity and shutter speed of a camera. According to the method, real-time environment light data analysis and camera parameter automatic adjustment are introduced in the monocular vision tower span measurement process, the image quality is effectively improved, tower recognition is more accurate, background interference is reduced, the geographic position and the shooting angle of a shooting point are corrected through the RTK technology, and the measurement accuracy is improved. And perspective transformation correction is carried out on the image in cooperation with a perspective projection theory, and the accuracy of distance measurement data is improved to centimeter level.

Three-dimensional Gaussian splatting mechanisms that initialize a set of 3D Gaussian distributions, un-project pixels from two-dimensional (2D) planes to 3D space by applying queries to the 3D Gaussians at expected un-projected ray depth positions, and splat the 3D Gaussian distributions on the 2D planes based on the expected un-projected ray depth positions.

The invention discloses an appearance detection multi-camera image splicing method and system and a related device, which are used for improving the overall quality and accuracy of image splicing in a multi-camera vision field non-overlapping scene. The method comprises the following steps: respectively calibrating a main camera and an auxiliary camera through a calibration board in combination with a weighted error minimization model; determining a pixel plane transformation matrix from the auxiliary camera to the main camera; transforming an initial image shot by the auxiliary camera to a pixel plane of the main camera according to the pixel plane transformation matrix; projecting the vision fields of all the cameras into a world coordinate system, and judging whether the projection positions of the vision fields are overlapped or not; if yes, feature points are extracted from the to-be-spliced image, the feature points are screened through a distance threshold value and a quality threshold value, and a feature point pair set is obtained; and calculating a perspective transformation matrix between the to-be-spliced images based on the feature point pair set, and splicing and fusing the to-be-spliced images according to the perspective transformation matrix and the vision field projection position.

The invention discloses a multi-view construction personnel tracking method and system based on attention perception. The method comprises the following steps: giving synchronous images from S cameras, and inputting the synchronous images into an encoder for feature extraction to obtain a multi-view feature map; transforming the multi-view feature map into a unified aerial view space by using perspective projection, and aggregating features after projection transformation of all views by using a convolutional layer; inputting the aggregated aerial view features into a decoder for decoding; a cross attention module is introduced, bird's-eye view features of a current frame and an adjacent frame are processed through 3D position coding, instance tokens are extracted as query, keys and values, an affinity matrix is generated through CNN coding similarity, features are propagated through matrix multiplication, and the bird's-eye view features of the current frame are updated. According to the method, the multi-view feature map is projected to the aerial view to realize early fusion, and a cross-frame attention mechanism is introduced, so that the problem of appearance feature distortion caused by perspective transformation is solved.

The invention provides a core photograph automatic correction and cutting method based on YOLOv8-seg and perspective transformation, and belongs to the technical field of image processing, and the method comprises the steps: S1, collecting a core box image; s2, polygonal point sequence labeling; s3, obtaining an optimal segmentation model; and S4, cutting. Aiming at the problems of much manual intervention, low efficiency and poor adaptability in the existing core photograph processing, the invention provides a set of full-automatic end-to-end solution without preprocessing, realizes rapid and stable correction and cutting of the core photograph in a complex scene, relieves the mechanical labor burden of geological personnel, focuses on the core exploration work, and improves the core exploration efficiency. And the practical application requirements of large-scale geological exploration projects are met.

The embodiment of the invention discloses a video generation method and device, electronic equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: generating a rough three-dimensional world of a target scene formed by a three-dimensional Gaussian ball set, and automatically searching a multi-angle offset view angle at the same coordinate position as a new view angle. According to the method, a multi-view-angle combined repairing mechanism is realized, geometric and semantic consistency of image data among different view angles is ensured, consistency of scene structures, textures and semantic information at different observation angles is realized, and a continuous, coherent and high-quality three-dimensional world is constructed. According to the method, the problem of multi-view inconsistency in a traditional method is solved, the new view image quality under large view conversion is improved, the image quality problems of floating objects, artifacts, structural distortion and the like in the image are eliminated, the generated image is more stable and real, the spatial continuity is improved, and the immersion and exploration experience of a user are enhanced.

The invention provides a core photograph processing method based on perspective transformation and a graphical user interface. The core photograph processing method comprises the following steps: S1, collecting a high-definition core photograph; s2, establishing a graphical user interface; s3, defining and designing a user-defined function for selecting the core photos, and acquiring file paths of all the core photos to be processed in batches by using the function; s4, defining and designing a user-defined function to obtain four angular points of the core picture selected in the S3, performing perspective transformation, and storing the four angular points; s5, creating a'batch selection photo 'button and an'interactive perspective transformation' button, and binding the buttons with the custom functions in S3 and S4; and S6, performing packaging on the steps S2 to S5 by using Anacoda, and creating an exe executable file. According to the method, on the premise that the core box does not need to be preprocessed, a method for rapidly and accurately correcting deformation and cutting a large number of core photos is provided for geologists based on the graphical user interface.

The invention relates to the technical field of scene matching navigation, and provides a multi-mode scene matching navigation positioning method and device for a self-adaptive variable-structure unmanned aerial vehicle. According to the method, geographic coordinates corresponding to all pixel points in an aerial image are determined according to pose information in the aerial image of the unmanned aerial vehicle, and the geographic position of the unmanned aerial vehicle with errors is corrected based on difference information between the pixel coordinates of the central point of the aerial image of the unmanned aerial vehicle and the geographic position corresponding to the center of a camera. Based on the corrected geographic position of the unmanned aerial vehicle, determining a reference image pixel coordinate corresponding to the angular point pixel coordinate of the aerial image, and obtaining a simulated aerial image under the view angle of the unmanned aerial vehicle through perspective transformation so as to determine a homography transformation matrix; according to the method, the satellite reference image pixel coordinates of the interest point in the aerial image are determined based on the homography transformation matrix and the perspective transformation matrix, and finally the longitude and latitude of the interest point are determined, so that the limitation of the traditional method in view angle difference compensation, computing resource constraint and cross-modal processing is solved, and the universality, robustness and positioning accuracy of the system are improved.

The invention provides an indoor human body positioning and track generation method and device, equipment and a medium, and the method comprises the steps: obtaining target Bluetooth data and position data with timestamps, achieving the data fusion through a data fusion algorithm, and obtaining a first moving track point set; based on a preset data acquisition period and timestamp information of each track point of the first moving track point set, when the track points are missing, detecting by using a computer vision algorithm and determining a corresponding target by using a tracking detection algorithm based on video data acquired by monitoring equipment, and obtaining an image sequence containing the target; determining an actual physical coordinate of a target in each image based on camera calibration and perspective transformation, obtaining an image positioning result and a second moving track point set, and aligning with a timestamp of the first moving track point set and realizing data fusion to obtain a third moving track point; and according to the map information, matching each track point of the third moving track point set to a grid map to form a target track map.

The invention discloses an automatic cattle checking method and system based on two-dimensional panoramic vision, and belongs to the technical field of computer vision and intelligent breeding, and the method comprises the following steps: reasonably arranging a plurality of fixed cameras in a cattle farm area, obtaining the internal reference and distortion coefficient of each camera through employing a camera calibration technology, and obtaining the internal reference and distortion coefficient of each camera; performing real-time distortion correction on the collected video frames; on the basis of side-by-side splicing or homography matrix perspective transformation, all paths of corrected images are fused into a complete two-dimensional panoramic image, and a view blind area of a single camera is eliminated; calling a lightweight target detection model on the panorama, and extracting bounding boxes and confidence coefficients of all cattle at one time; sorting according to the confidence from high to low, performing IOU non-maximum suppression de-duplication on the detection frame, and ensuring that the same cattle only counts once in an overlapping region; and the whole process is completed through the edge computing node. According to the invention, efficient, real-time and accurate on-site cattle checking of a large-scale cattle farm can be realized.

The invention discloses a display screen fault detection method, system and device and a storage medium, and the method comprises the steps: obtaining a monitoring video stream of a display screen, and obtaining a display screen monitoring image set according to the monitoring video stream; performing perspective transformation on the display screen monitoring image set to obtain a display screen correction image set; performing feature extraction on the display screen correction image set to obtain a display screen feature image set; detecting the display screen feature image set by using a pre-trained fault detection model to obtain fault types corresponding to the display screen feature images in the display screen feature image set one by one; and when the fault types of all the display screen feature images meet a preset condition, determining that the display screen has a fault, and outputting a target fault type corresponding to the display screen. According to the invention, real-time intelligent fault detection of the display screen can be realized, the accuracy is high, various types of display screen faults can be detected at the same time, full-automatic intelligent detection alarm is realized, manual inspection by operators on duty is not needed, and the operation and maintenance efficiency is improved.

The invention discloses a multi-camera synchronous electronic image stabilization method and device based on virtual camera imaging, and the method comprises the steps: obtaining and splicing images captured by all cameras in a multi-camera cooperative imaging system, and constructing a virtual camera image; calculating the translation offset of the virtual camera according to the perspective transformation matrix between the adjacent cameras, and calculating the internal reference of the virtual camera; converting the pixel coordinate system into a to-be-stabilized virtual camera coordinate system according to the internal reference of the virtual camera; converting the compensation amount to a virtual camera coordinate system to be stabilized; calculating an image stabilization rotation matrix for converting the coordinate system of the virtual camera to be stabilized into the coordinate system of the stable virtual camera; and converting the to-be-stabilized image from the stable virtual camera coordinate system to the pixel coordinate system according to the image stabilization rotation matrix and the internal reference of the virtual camera to obtain a stabilized image. The method can be applied to multi-camera synchronous electronic image stabilization in a multi-camera collaborative imaging system, and high-quality anti-shake video real-time output is realized.

The invention discloses a digital watermark registration positioning method based on linear Hough transform, which is applied to positioning and identification of a digital watermark on a digital image, and comprises the following steps: encoding input data, adding random offset, generating basic unit watermark blocks, paving the basic unit watermark blocks, and reserving intervals for a linear detection positioning algorithm. In the extraction algorithm, firstly, preprocessing and a Hough straight line detection algorithm are carried out on a carrier image, detected straight lines are grouped, intersection point information between two groups is calculated, vertex positions of basic unit watermark blocks are positioned by calculating the mutual position relation between intersection points, and then perspective transformation correction is carried out on each basic unit watermark block. And the embedded basic unit watermark block information is obtained. And then extracting coding information from the basic unit watermark block, and sequentially carrying out mask removal, error correction and decoding to recover original embedded information. The invention further discloses a system and application for implementing the method, and the system and the application have wide application value.

The invention provides a suspension bridge main cable wire bulging detection method based on multi-feature fusion, and relates to the field of bridge detection. The method comprises the following steps: detecting the position of a carrier roller by using a deep learning target detection algorithm, constructing a perspective transformation matrix by taking the standard geometric dimension of the carrier roller as a benchmark, converting a squint image into a standard top view, extracting a cable strand area mask so as to construct a width contour vector, carrying out quantitative analysis on drum wire characteristics from six dimensions, and establishing a comprehensive scoring model. Through weighted fusion of multi-dimensional features, intelligent judgment and severity quantitative evaluation of drum wires are realized, the detection efficiency is improved, multi-dimensional feature fusion avoids missing detection of a single feature, good adaptability to a complex field environment is achieved, safety and traceability are improved, manual intervention is reduced through whole-process automatic processing, and the detection efficiency is improved. And the result objectivity is ensured by a multiple judgment mechanism.

The invention discloses a product detection method and device, electronic equipment and a readable storage medium, which are applied to the technical field of image processing, and the method comprises the steps: extracting a plurality of product edge feature points from an image of a circular product, carrying out the fitting of the plurality of product edge feature points to obtain an ellipse, and carrying out the building of a standard circle through the ellipse, then, a perspective transformation matrix is constructed by using an ellipse and a standard circle, perspective transformation is carried out on the multiple product edge feature points and images respectively, non-standard circles presented by qualified circular products in the images due to camera shooting angle or product position inclination are corrected, complete visual angle correction is achieved, and the product quality is improved. And finally, based on the plurality of transformation feature points obtained by perspective transformation and the target image obtained by perspective transformation, carrying out qualification detection on the circular product, so that the over-detection rate can be reduced, and the detection efficiency and precision of the circular product can be improved.

The invention provides a method and a device for mapping image coordinates to desktop coordinates, equipment and a storage medium, which are used for improving the positioning precision of a projection touch system in a real environment. The method comprises the steps of performing distortion correction on original gesture video data according to internal parameters of a camera and a lens distortion coefficient to obtain a corrected image frame sequence, and performing interaction space calibration according to the corrected image frame sequence to obtain a distortionless interaction plane, performing perspective change matrix solving on the distortionless interaction plane according to the target vertex coordinate set to obtain orthogonal mapping data, and when gesture key points are detected in the distortionless interaction plane, performing perspective transformation and normalization processing on gesture coordinates of the gesture key points according to the orthogonal mapping data to generate initial desktop control coordinates; and performing display mapping processing on the initial desktop control coordinates according to the physical attribute parameters of the target display to obtain desktop control coordinates.

The invention relates to a calibration plate circle center detection method, device and equipment and a storage medium, in the application, a perspective transformation matrix is determined by creating a virtual standard square, and the perspective transformation matrix is utilized to map an original calibration plate image into a square calibration plate image, so that the calibration plate circle center detection accuracy is improved. The problem of deformation of the calibration plate during oblique shooting can be effectively solved, so that circle center detection is not influenced by view angle inclination; moreover, the contour of each target circle is combined through a clustering algorithm in the square calibration plate image, and the coordinate of the combined center is determined through confidence, so that noise interference can be effectively suppressed, and the precision of circle center detection is improved.

The invention provides an image processing method and device, electronic equipment, a chip and a storage medium, and relates to the field of image processing.The method comprises the steps that a reference image is determined from multiple frames of shot images based on quality scores of the multiple frames of shot images; wherein the multiple frames of shot images are obtained by shooting the same shot object by adopting different shooting view angles; performing shadow correction on the multiple frames of shot images based on shadow areas in the multiple frames of shot images to obtain multiple frames of corrected images; based on the homography matrix of the multiple frames of shot images, aligning the multiple frames of corrected images to the reference image to obtain multiple frames of aligned images; wherein the homography matrix is used for indicating a perspective transformation relation of distortion of the shot image to the first reference image; and performing image synthesis according to the multiple frames of aligned images to obtain a target image. Therefore, the problem of shadow shielding caused by illumination can be eliminated, and the imaging effect is improved. In addition, assistance of depth-of-field information and multi-exposure is not needed, and the complexity of image processing can be reduced.

The invention discloses a computer vision-based railway tool online and offline checking method, which comprises the following steps of: acquiring online and offline and warehouse tool images of a high-speed railway work section, cutting a target area through an area focusing algorithm to eliminate interference, and combining enhancement technologies such as perspective transformation and multi-transformation splicing with a generation method based on SAM and a diffusion model. Constructing a diversity training data set; constructing a text vision multi-modal rotating target detection model, and guiding the model to pay attention to key categories by enhancing feature extraction and fusing text information and visual features of a job schedule; detecting parameters are adjusted by adopting a self-adaptive threshold optimization algorithm, a few-sample detection technology is combined, and after category sensing scale filtering, outlier frame suppression and cross-category non-maximum suppression processing are performed, a result is compared with an operation plan, and a result is output; and based on a sample cutting and screening mechanism driven by false detection and missing detection, high-value samples are mined and supplemented to a training set. The method has the advantage that the safety and efficiency of railway tool management are improved.

The invention discloses a vehicle target detection tracking and trajectory data extraction method based on deep learning, and relates to the technical field of unmanned aerial vehicle aerial photography. The method comprises the following steps: carrying out stable frame processing on an unmanned aerial vehicle video, extracting feature points and feature vectors through an SURF algorithm, matching and screening reliable matching pairs through an FLANN algorithm, calculating a homography matrix through an RANSAC algorithm when a condition is met, carrying out perspective transformation to eliminate jitter, and outputting a stable video sequence; vehicle target detection: introducing an AIFI module to construct an improved YOLOv5OBB model, and outputting vehicle rotation bounding box parameters and categories after training; vehicle tracking and trajectory extraction are carried out, cross-frame tracking is realized based on a DeepSORT model, original trajectory data are preprocessed, and the speed, the acceleration, the additional lane number and the ID of an adjacent vehicle are calculated. According to the method, the problems of video jitter and insufficient detection precision are effectively solved, and the accuracy and continuity of track data extraction in the highway scene are improved.

The invention relates to the technical field of power transmission lines, and particularly discloses a power transmission line icing early warning method and system based on an image technology, and the method comprises the steps: obtaining a front view, a 45-degree upward view and a 45-degree top view of a power transmission line; performing perspective transformation of a foresight angle on the 45-degree upward view and the 45-degree top view, and splicing the 45-degree upward view and the 45-degree top view with the foresight view to obtain a corrected foresight view; threshold image segmentation and image feature extraction are carried out on the corrected front view, the icing thickness and icing shape of the power transmission line and the angle between the power transmission line and the horizontal plane are determined, and a thickness early warning score, a shape early warning score and an angle early warning score are obtained; and obtaining an icing score, and judging whether to give an early warning prompt or not according to the icing score. According to the method, the icing thickness, the icing shape and the angle between the power transmission line and the horizontal plane are obtained by using the pictures at different angles, the early warning score is obtained, whether icing is serious or not is judged according to the early warning score, early warning can be given out in time, the detection accuracy is high, and online monitoring is achieved.