477 results about "Image splicing" patented technology

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses an image generation method, device and equipment based on theme information and a medium. The method comprises the steps that input information is analyzed to generate theme information and copywriting information, a cue word set is generated, and a figure image set and a background image set are generated; fitting the segmented figure image with the background image to form a head image candidate set, and selecting a head image matching template frame to generate a basic image; decomposing the copywriting to generate a sub-module initial picture set, and adding a gradual change effect to form a sub-module picture set; the adjusted sub-module pictures are obtained based on size adjustment, and a pre-synthesized image is generated through splicing; and identifying the blank area to draw a title text to obtain a final image. Through theme analysis, template matching, image splicing, modular copywriting processing and blank drawing, poster generation efficiency is improved, layout flexibility is enhanced, and visual unification is realized.

The invention discloses a video transmission image stitching data enhancement method based on deep learning, and relates to the field of video image processing. The method comprises the following steps: S1, acquiring and screening images; s2, continuously screening structures and selecting key frames; s3, correcting image distortion; s4, splicing and fusing the images; s5, performing image enhancement output; firstly, a sliding time window mechanism is adopted, multi-dimensional image quality screening is combined, fuzzy, underexposure or severely-shielded inferior frames are accurately removed, and high quality of input key frames is ensured; through intelligent splicing and enhancement of a dynamic adaptive threshold strategy and semantic guidance, the image splicing precision and efficiency of the unmanned aerial vehicle and the multi-view camera in a complex environment are remarkably improved; besides, semantic segmentation guided feature extraction is combined with a multi-band fusion technology, seamless splicing is realized, the quality of an output image is improved, and the reliability of automatic analysis and decision making is remarkably improved.

The invention discloses a global scanning image splicing and defect positioning system for an ultra-large-diameter quartz crucible, and relates to the technical field of quartz crucibles, and the system comprises a scanning control module which constructs a fusion model through multiple sensors, evaluates a risk coefficient, obtains the fusion model, dynamically plans a multi-arm path of a robot based on reinforcement learning, and sends the multi-arm path of the robot; adaptively adjusting the acquisition frequency of the corresponding area based on the risk coefficient, and outputting multi-modal data through a multi-round feedback iteration optimization acquisition process; the image splicing module is used for acquiring multi-modal data for local splicing, and generating a panoramic image in combination with a multi-arm path of the robot; the defect positioning module is used for constructing a quartz crucible model through the panoramic image, detecting defects in a layered manner by utilizing a YOLOv5 model, tracking the defects through extended state Kalman filtering, quantifying the defect volume and the hazard level by combining point cloud semantic segmentation, and performing 3D positioning and evaluation on the defects; the output data is ensured to always meet the subsequent image splicing and defect positioning requirements, and the system stability is guaranteed.

The invention discloses a radiation correction method and system for an airborne hyperspectral imager. The radiation correction method and system are used for improving the radiation correction precision in complex weather. The method comprises the following steps: calculating a theoretical sun position based on unmanned aerial vehicle initial coordinates, ephemeris data and atmospheric parameters; performing course and differential compensation on a solar azimuth angle by combining IMU course and wind speed and direction data, performing refraction correction on an elevation angle, and outputting a high-precision sun position parameter; hyperspectral images and irradiance data are synchronously acquired, quaternion interpolation is combined with IMU data to realize space-time alignment, and attitude disturbance is eliminated; a hemispherical space irradiance model is constructed based on alignment data, cloud layer modes (clear sky, thin cloud and thick cloud) are divided according to atmospheric optical thickness variance, and Lambert body proportion correction, a discrete longitudinal standard method or a deep convolutional spectral network are respectively adopted for radiation correction. The method remarkably improves the correction precision and generalization ability, supports large-area image splicing, and is suitable for quantitative application of geological exploration, environment monitoring and the like.

The invention provides a panoramic image intelligent splicing method based on context semantics. The method comprises the following steps: firstly, obtaining and preprocessing a sequence image; extracting a depth feature map of the image by using a pre-trained depth network; performing semantic-guided feature matching and image alignment based on the feature map; an optimal suture line is generated according to the semantic region boundary, and fusion is carried out by adopting a semantic weighted multi-band fusion algorithm; and finally, detecting and repairing the semantic inconsistent region to ensure the semantic coherence of the panoramic image. According to the method, matching is carried out by using the high-dimensional feature tensor rich in semantic information extracted by the deep neural network, the problem of feature matching ambiguity caused by repeated textures and weak texture regions such as sky or white walls is solved, the semantic information is used as a strong constraint, regions with similar appearances but different semantics can be effectively distinguished, and the accuracy of feature matching is improved. Therefore, correct matching point pairs with consistent semantics are screened out from massive candidates, and the matching accuracy is greatly improved.

The invention relates to the technical field of industrial defect detection, and discloses an aluminum surface micro defect detection system for optimizing an RT-DETR model in combination with an attention mechanism, which comprises an image acquisition module, an image preprocessing module, an improved RT-DETR detection module and a result output module. According to the aluminum surface micro-defect detection system for optimizing the RT-DETR model in combination with the attention mechanism, small target copying is executed through an image preprocessing module to increase micro-defect samples, defects and matching backgrounds are fused through image splicing, illumination is optimized through brightness adjustment, Gaussian filtering noise reduction is conducted, and original defect information is strengthened; an orthogonal attention feature extraction module in the improved RT-DETR detection module strengthens channel features, a multi-scale deformable frequency hierarchical attention coding module processes the features according to high and low frequencies, an ELAHS-FPN feature fusion module fuses the multi-scale features, a super-resolution auxiliary branch improves the feature resolution, a prediction frame is corrected in combination with an Inner-GIoU bounding box loss function, and the detection precision is improved. And weak characteristics such as paint bubbles, scratches and jet flow are effectively extracted.

The invention relates to the technical field of image processing, solves the problems that in the prior art, UV flat plate printing needs multiple cameras to cover the whole printing platform, and the precision is not high, and provides a scanning image processing method and device based on a single camera, equipment and a medium. The method comprises the steps that a camera is controlled to scan a calibration graph in the main scanning direction to obtain a first area image, the first area image is analyzed to correct distortion, target images are obtained, then the camera moves in the auxiliary scanning direction and repeatedly scans to obtain a second area image, distortion correction is conducted as well, and overlapped parts of the two target images are compared to obtain a target image. And longitudinal shooting overlapping parameters are calculated, and adjacent target area images are spliced by using the two groups of longitudinal overlapping parameters through a mapping splicing technology. Scanning of the whole printing platform can be completed through a single camera, hardware configuration is simplified, image splicing is carried out after multiple times of scanning and distortion correction, and the overall printing precision is improved.

The invention relates to the technical field of image processing, in particular to a panoramic image splicing method for a curtain wall building facade. The method comprises the following steps: performing three-dimensional scanning on a curtain wall building facade to obtain entity point cloud data of the facade, and selecting a plurality of discrete points from the entity point cloud data as reference anchor points; shooting a plurality of local images of the curtain wall building facade, and in the shooting process of each local image, recording the spatial correspondence between the image viewing range and the reference anchor point; and according to the spatial correspondence, aligning the image area corresponding to the reference anchor point in each local image to the position of the reference anchor point in the entity point cloud data to form a preliminary spliced image. According to the invention, through an image processing technology, zero-offset binding of the panorama and the BIM is completed through one-time shooting, so that the millimeter-level positioning precision and the inspection efficiency of the curtain wall facade are improved.

The invention provides a multi-camera-based AI glasses FOV extension method and system, and the method comprises the steps: transmitting a synchronization signal to a plurality of cameras, enabling the plurality of cameras to carry out the exposure at the same time, and obtaining a plurality of frames of original images at the same time; pre-processing the multiple frames of original images to obtain pre-processed images; key feature points of the preprocessed image are extracted through a feature point detection algorithm, and feature descriptors are generated; through a feature matching algorithm, feature point matching is carried out on the adjacent preprocessed images by utilizing the feature descriptors, and a local transformation matrix between the adjacent preprocessed images is calculated; based on the local transformation matrix, fusing the adjacent preprocessed images to obtain a fused image of the adjacent preprocessed images; and all the fused images are spliced to obtain a large-view-field-angle image covering the target view angle, so that the method has the advantages of effectively expanding the shooting view angle, eliminating image distortion and improving the image splicing naturalness.

The invention discloses a submarine image splicing method based on suture line optimization, and the method comprises the steps: carrying out the dual-stage feature extraction of a target submarine image based on an improved ResNet50 network, and obtaining a multi-level feature map containing global structure information and local detail features; respectively carrying out global coarse registration and local fine correction on the second feature map and the first feature map based on a deformable convolutional network to obtain a sub-pixel level aligned deformed image; and carrying out cross-scale feature interaction and dynamic mask optimization on the deformed images based on a cross-image self-attention mechanism, dividing suture line weights between the spliced images, and carrying out pixel classification according to the weights to obtain seamless spliced images. According to the method, semantic fusion is guided through deformable convolution modeling elastic deformation and a self-attention mechanism, sub-pixel-level alignment and seamless splicing are achieved, and the problems of geometric dislocation and suture line artifacts caused by refraction distortion, scattering noise and dynamic deformation in large-parallax submarine image splicing are solved.

The invention provides a digital pathological image high-color accurate splicing method and device based on feature point matching. The method comprises the following steps: obtaining a target splicing region in a target splicing image and a to-be-spliced region in a to-be-spliced image based on a scanning sequence of digital pathological images; performing affine transformation on the to-be-spliced region by using the affine transformation matrix to obtain an initial correction region; constructing a global color mapping function, and mapping the initial correction image by using the global color mapping function to obtain a color correction image; and splicing the color correction image and the target splicing image based on the scanning sequence of the pathological images to obtain a digital pathological image splicing result. According to the scheme, only the target splicing area and the to-be-spliced area are subjected to feature point matching, the cumulative distribution function of the effective feature points is calculated according to the RGB channels, and the global color mapping function is constructed and optimized, so that accurate color correction is realized, and the visual integrity and consistency of the spliced image are improved.

The embodiment of the invention belongs to the field of intelligent network connection automobiles, and relates to a vehicle all-round view image splicing method, which comprises the following steps: acquiring a to-be-corrected image; performing checkerboard calibration processing on the to-be-corrected image to obtain a first corrected image; performing overlook transformation processing on the first corrected image to obtain a second corrected image; and performing correction splicing processing on the second correction image to obtain a target correction image. The invention further provides a vehicle all-round view image splicing device, computer equipment and a storage medium. According to the method, the checkerboard calibration processing, the overlook transformation processing and the correction splicing processing are sequentially carried out on the to-be-corrected image, so that the geometric accuracy and the visual coherence of the surround view image can be remarkably improved, splicing traces and blind areas are reduced, a higher-quality and more stable panoramic surround view picture is provided for a driver, and the driving safety is improved.

The invention discloses an improved Faster R-CNN underground drainage blow-off pipeline defect detection model, and particularly relates to the field of target detection, and the method comprises the steps: firstly constructing a defect image data set, extracting a defect-containing image from a pipeline detection image, and dividing the defect-containing image into a training set, a verification set and a test set according to a preset proportion after validity screening and defect category labeling; secondly, improving a detection model, replacing a traditional regional proposal module with an anchor-frame-free detection head, embedding an attention module in a high layer of a backbone network, and introducing a feature pyramid network to generate multi-scale features; then training the model, performing multi-graph splicing type data enhancement on a training set, training by adopting an optimizer and a two-stage loss function, and storing an optimal weight in combination with an early stop strategy; and finally evaluating the model, inputting the test set to obtain a detection result, counting related detection data, calculating a precision index, and comparing the precision index with a preset threshold to judge whether the model reaches the standard. The method is high in detection precision and high in adaptability, and meets the requirement for pipeline defect detection.

The invention relates to the technical field of automotive electronics, in particular to a vehicle panoramic image system based on multi-camera collaboration, which comprises a camera group used for acquiring local images of the surrounding environment of a vehicle in real time; the image processing module is used for receiving the local image and processing the local image in real time to generate a panoramic aerial view surrounding the vehicle; the display control module is used for receiving and outputting the panoramic aerial view to a vehicle-mounted display device for real-time display; the real-time communication connection between the image processing unit and the camera group ensures the real-time processing of image data, the display control module outputs the processed panoramic view to the vehicle-mounted display equipment in real time, and the cooperative work architecture effectively solves the problem of image splicing dislocation caused by camera parameter offset in the prior art. Possible camera installation deviation is compensated through real-time image processing, and continuity and accuracy of panoramic images are guaranteed.

The invention discloses a panoramic image splicing method, system and device, and relates to the technical field of image processing, and the method comprises the steps: collecting images around a vehicle at different visual angles; using the MASK masks to generate overlapping region masks of the different view angle images, and performing local feature detection on the overlapping region masks to generate a transformation matrix; aligning the images of different visual angles according to the transformation matrix; a Canny edge detection operator is fused in splicing seam energy detection, the energy weight of the image edge area of the aligned image is enhanced, and a splicing seam is guided to actively avoid an object with remarkable structural features; b spline interpolation is introduced to optimize an initial splicing seam path; constructing a Laplacian pyramid along Gaussian blur of a splicing seam, and sequentially carrying out gradual fusion to generate a seamless panoramic image; according to the method, the basic function of eliminating the visual blind area is realized, a clear and visual panoramic view can be provided for a driver, and the driving safety is effectively improved.

The application discloses a SIFT image splicing method and system based on multi-feature fusion and adaptive optimization, and comprises the following steps: performing data preprocessing on acquired image data to generate a gray image; constructing a scale space by using a SIFT feature extraction method, detecting local extreme points in the gray image to generate a descriptor, and performing SIFT feature matching optimization; performing false matching elimination by using a nearest neighbor ratio criterion and a matching threshold value, and maintaining the distribution balance of feature points in the gray image by using a uniform sampling method; performing random sample consensus estimation by using an adaptive threshold value in a feature matching point set, eliminating outliers, and calculating a homography matrix to realize image registration; and realizing image splicing in an overlapping area based on a weighted fusion strategy, avoiding the abruptness of a joint transition by combining a smoothing weight, and performing black edge trimming to optimize a splicing result. The application can optimize a traditional SIFT image splicing algorithm, and thus the splicing quality of an image can be improved.

The invention discloses an infrared image registration method and an unsupervised learning image registration model training method, and belongs to the technical field of image processing. Aiming at the characteristics of weak texture and few features of a low-overlapping-rate infrared image, a weak texture feature extractor is firstly designed, and the feature extraction capability of a model on a weak texture image is improved through multi-scale feature fusion; then, by adopting multi-scale receptive field correlation calculation, the discrimination capability of the model on similar features is enhanced; furthermore, by adopting a homography transformation estimation method which is optimized gradually from coarse to fine, the estimation precision of a transformation matrix is improved; and finally, realizing registration and splicing of the infrared images through image transformation and overlapping region fusion processing. According to the method, the registration precision of the low-overlapping-rate infrared image can be effectively improved, and application scenes such as large-scene image splicing can be supported.

The invention relates to the technical field of aviation photoelectric imaging, in particular to a multi-load aviation photoelectric pod timing system control system which comprises a timing system analysis module, a synchronous control module, a communication control module and an information superposition module. The timing system analysis module generates an absolute moment, the synchronization control module provides a multi-source synchronization pulse signal, the communication control module realizes data interaction and generates additional information including the absolute moment, a pose and a system state, and the information superposition module synchronously superposes the additional information to image data. According to the technical scheme, automatic matching of the image and the telemetry data is achieved, the problems of poor synchronization precision and low efficiency caused by manual matching are solved, and the difficulty and workload of rear-end processing such as image splicing and radiation measurement are remarkably reduced.

The invention discloses a transformer substation video fusion monitoring method and system based on 3DGS, and relates to the technical field of three-dimensional modeling. The method comprises the following steps: acquiring a laser radar point cloud and a multi-view camera image of a transformer substation, and constructing a three-dimensional Gaussian splashing model; establishing a mapping relation library based on P source view angle and Q target view angle transformer substation 3DGS samples; based on the library, using a picture splicing boundary confidence degree adjusting pointer and a space coordinate mapping deviation correction pointer to carry out fusion training; and when a user clicks a target device in the model, calling an improved line-of-sight cone analysis algorithm to dynamically screen an optimal camera, receiving a video stream of the optimal camera, and determining a device state recognition result. The technical problem of poor accuracy of image splicing and equipment positioning caused by multi-view and view range limitation in substation equipment monitoring is solved, and the technical effect of improving the monitoring precision and efficiency of substation equipment by dynamically screening the optimal camera and equipment state recognition of space coordinates is achieved.

The invention relates to the technical field of pathological section image splicing, and discloses a pathological section association-based pathological image splicing method and device. The method comprises the following steps: acquiring and preprocessing a serialized pathological sub-slice image; calculating a texture flow direction field representing microstructure arrangement of the tissue, and constructing a multi-scale feature descriptor; on the basis of the multi-scale features, the adjacency relation between the sub-slices is quantitatively evaluated by fusing gradient differences, texture distribution KL divergence and a multi-scale correlation degree function of frequency domain mutual information; constructing a global spliced graph model by taking the degree of association as an edge weight, establishing an energy function containing data fidelity and texture smoothness constraints, solving an optimal splicing parameter through iterative optimization, and controlling an iterative process according to convergence criteria of comprehensive splicing stability, residual matching potential and progress; and finally generating a seamless panoramic pathological image. According to the method, biological structure characteristics are utilized, robustness and matching accuracy under complex conditions are improved, and continuity and consistency of splicing results are ensured.

The invention discloses a ship spherical global image splicing method and system based on image processing, and the method comprises the following steps: obtaining multi-camera images which are distributed at the top, the bottom and the annular direction, and executing camera calibration and distortion correction; performing hemispherical projection and cylindrical projection by using a hybrid projection link; feature point extraction and matching are carried out, and an initial registration relation between adjacent view fields is established; executing APAP gridding local registration of projection perception, and generating local homography by applying an anisotropic weight kernel consistent with the region projection direction to obtain a partition alignment result set; carrying out weighted fusion and stitching suppression on the overlapped region to generate a panoramic spliced image; and converting the panoramic spliced image into an interactive three-dimensional panoramic view. According to the method, mixed projection and projection perception APAP algorithms are fused, ship spherical surface global high-precision splicing and three-dimensional immersion display are achieved, and the method has the advantages of being small in distortion, high in precision and high in visibility.

The invention discloses a large-parallax image splicing method and device, equipment and a storage medium, and belongs to the technical field of image processing. The method comprises the following steps: performing feature point matching on a to-be-spliced feature point set and a reference feature point set to obtain a feature matching point pair set; according to the parallax value of each feature matching point pair in the feature matching point pair set, layering the parallax of an overlapping region intersected with the reference image in the to-be-spliced image to obtain a plurality of parallax layers and a matching feature point pair set corresponding to each parallax layer; according to the matching feature points to be spliced in the matching feature point pair set of each parallax layer, determining each geometric feature region by using a region growing method; and according to the global homography matrix and the local homography matrix of each geometric feature region, performing fusion processing on the to-be-spliced image and the reference image to obtain a target spliced image. By using the technical scheme provided by the invention, the accuracy of large parallax scene image splicing can be improved.

The invention discloses a multi-view fisheye camera real-time look-around image splicing method and device, and relates to the technical field of image processing, the method generates a lookup table (LUT) based on calibration parameters, converts a fisheye image distortion removal correction process into a table lookup operation, avoids real-time calculation one by one pixel, significantly reduces the operation overhead, and improves the image quality. And the system can keep low-delay processing under the condition of high-resolution input. According to the method, self-adaptive feathering weight distribution is introduced into a seam band, local energy matching and a multi-band fusion method are combined, and the width and the weight of a splicing area are dynamically adjusted according to scene brightness and contrast difference, so that ghosting and brightness abrupt change at the seam are effectively reduced, and the smoothness of splicing transition is ensured.

The invention provides a panoramic image splicing method and device and electronic equipment, and the method comprises the steps: obtaining a plurality of images and metadata thereof, carrying out the preprocessing of the plurality of images according to the metadata, and obtaining a plurality of preprocessed images; extracting image key points and feature descriptors of the image key points from the plurality of preprocessed images through a SuperPoint neural network model; performing approximate nearest neighbor search matching on the image key points according to the feature descriptors of the image key points to obtain a plurality of initial matching pairs; eliminating matching pairs with spatial consistency smaller than a threshold value from the plurality of initial matching pairs through a random sampling consistency algorithm to obtain final matching pairs; based on the final matching pair, performing global binding adjustment on camera transformation parameters corresponding to the plurality of images through a nonlinear optimization algorithm to obtain alignment parameters, and transforming the plurality of images according to the alignment parameters to obtain a plurality of transformed images; and performing multi-band fusion rendering on the plurality of transformed images to obtain a panoramic image.

The invention relates to the technical field of image synchronization, in particular to a multi-screen collaborative immersive interactive cinema image synchronization method and system.The method comprises the steps that when the system is initialized, a multi-screen projection module completes image splicing and sends real-time splicing parameters to a coordinate mapping calibration module; the coordinate mapping calibration module establishes a basic mapping relation between physical coordinates and virtual coordinates based on the real-time splicing parameters, and the environment sensing module collects environment parameters and transmits the environment parameters to the cooperative control unit. According to the invention, a dynamic mapping algorithm model is constructed, real-time splicing parameters of the multi-screen projection module and light and temperature data collected by the environment sensing module are integrated, and a mapping relation between physical coordinates and virtual coordinates is corrected in real time; the problems of aiming deviation and special effect dislocation caused by the fact that coordinate mapping lacks dynamic adaptation and cannot be adjusted along with changes of splicing parameters in the prior art are effectively solved.

The invention relates to a floating algae detection method, system and device. The method comprises the following steps: preprocessing a multi-vision original image sequence to obtain a multi-vision preprocessed image sequence; performing image splicing on the multi-vision preprocessed image sequence according to the boundary features to obtain a panoramic image; carrying out step-by-step edge identification and labeling on the panoramic image by adopting a multi-operator and region growing method to obtain a labeled image; and performing type identification and counting on the floating algae in the labeled image based on a stacked integrated learning method to obtain floating algae biological information. According to the method, image splicing is performed firstly, then edge recognition is performed, and multi-operator step-by-step edge recognition from low precision to high precision is performed on the panoramic image, so that the detection efficiency can be improved; in addition, the types of the floating algae in the annotated image are identified and counted based on the stacked integrated learning method, and the identification accuracy is higher than that of an existing single model.

The invention discloses an SIFT image splicing method and system based on multi-feature fusion and adaptive optimization. The method comprises the steps of performing data preprocessing on acquired image data to generate a grayscale image; constructing a scale space by using an SIFT feature extraction method, detecting a local extreme point in the grayscale image to generate a descriptor, and performing SIFT feature matching optimization; carrying out mismatching elimination through a neighbor ratio criterion and a matching threshold value, and maintaining the distribution balance of feature points in the grayscale image in a uniform sampling mode; random sampling consistency estimation is carried out in the feature matching point set by using an adaptive threshold value, outer points are eliminated, a homography matrix is solved, and image registration is realized; and image splicing is realized in the overlapped region based on a weighted fusion strategy, joint transition abrupt is avoided in combination with a smooth weight, and black edge cutting is performed to optimize a splicing result. According to the method, a traditional SIFT image splicing algorithm can be optimized, so that the image splicing quality can be improved.

The invention provides an image processing method and device, equipment, a storage medium and a program product, and relates to the technical field of intelligent cabins. The method comprises the following steps: acquiring a plurality of environment images acquired by a plurality of image acquisition devices arranged on a vehicle from different visual angles at target time, wherein the plurality of environment images have a common-view area; determining actual plane parameters of an actual ground plane of the vehicle at the target time based on geometric features of the common-view area in the plurality of environment images; correcting a preset external parameter of the image acquisition device according to the actual plane parameter to obtain a target external parameter; and converting and splicing the plurality of environment images based on the target external parameters to obtain a panoramic image. According to the method, the spatial parameters of the actual ground plane where the vehicle is located can be automatically determined by using the geometric features of the common-view areas in the plurality of environment images, and the external parameters of the image acquisition device are corrected accordingly, so that the accuracy and consistency of panoramic image splicing are improved, and image dislocation caused by vehicle attitude change is avoided.

The application discloses a kind of compound eye camera image fusion methods, comprising: the global camera image is interpolated and enlarged, and the global camera image after amplification is obtained;The global camera image after amplification is divided into regions, obtain multiple local areas, and the coordinate range of each local area is obtained;Multiple sub-camera images and corresponding local area are extracted and matched with image features, and the final matching point pair is obtained;Registration is carried out based on the homography matrix formed by the final matching point pair each sub-camera image and corresponding local area, and the restoration image composed of all registered sub-camera images is obtained;The restoration image is color corrected based on the fusion algorithm of gradient fitting, to fuse the restoration image into the global camera image after amplification, and the final fusion image is obtained.The application solves the problems of traditional multi-image splicing algorithm splicing process cumbersome, image picture stretch distortion, photo brightness and chroma inconsistency.

The application provides an image recognition-based online detection method and system for surface defects of ultra-wide and thick plates, and relates to the technical field of image recognition. The method comprises the following steps: synchronously collecting surface images and process state parameters containing final rolling temperature, rolling force distribution, laminar cooling intensity and real-time speed, firstly completing image splicing according to the final rolling temperature and the rolling force distribution to obtain a topological image; then separating a texture channel image by feature decoupling with the laminar cooling intensity as a constraint; subsequently extracting edge features of the texture channel image by Hough transformation, and introducing the rolling force distribution and the real-time speed as constraints for curve fitting to generate topological structure features; finally dynamically adjusting a kernel function by a support vector machine, and analyzing the topological structure features and a preset feature library to obtain a defect detection result. The application can effectively improve the accuracy and adaptability of defect detection under complex working conditions through deep fusion and dynamic guidance of process parameters.