454 results about "Image stitching" patented technology

The invention provides a heavy truck battery compartment guiding method and system based on visual perception. The method and system are used for automatic battery replacement operation in a complex industrial environment. According to the system, a multi-camera fusion visual perception platform is constructed, a plurality of industrial cameras arranged on the ground or ceiling of a battery swap station are used for collecting local images of different visual angles of a battery compartment, and a complete visual field image is generated through feature matching and image splicing. A battery compartment is coarsely positioned by adopting a YOLO series model, a bounding box region is extracted, pixel-level contour segmentation is realized by introducing SAM, and the complex background and multi-interference environment recognition capability is enhanced. And after segmentation, calculating a minimum enclosing rectangle of the battery compartment, obtaining a center coordinate and a deviation angle, and transmitting a pose parameter to an upper computer control system. According to the method, the defects of the laser radar are avoided, image processing, the deep neural network and multi-view information are fused, the recognition precision and stability are improved, the battery replacement efficiency and the unmanned level of the electric heavy truck can be remarkably improved, and reliable support is provided for green traffic.

The invention discloses a tunnel lining crack identification method and system based on panoramic space image splicing, and relates to the technical field of tunnel visual identification. The method comprises the following steps: acquiring a tunnel lining image array, and performing local splicing on tunnel lining images by using a splicing model based on cylindrical surface projection to obtain a local spliced image; fusing and splicing the local spliced images by using the global image space model to obtain a panoramic spliced data graph; and abnormal region detection is carried out on the panoramic splicing data graph according to the spatial local difference, and a tunnel lining crack identification result is obtained. According to the method, the lining panoramic space model based on image two-stage fusion is used for splicing, so that the visual coherence and naturalness of a global spliced image are improved.

The invention relates to the technical field of virtual reality, in particular to an indoor structure reconstruction method based on a panoramic image scene understanding algorithm, and the method comprises the steps: S11, obtaining a plurality of equidistant columnar projection panoramic images of a current indoor scene through a panoramic camera or a panoramic image splicing algorithm; s12, performing semantic segmentation on the collected panoramic image by using SAM, deducing indoor ceiling, floor and wall areas of the panoramic image on the basis of a semantic segmentation result, and generating a multi-channel semantic graph; and S13, inputting the acquired RGB panoramic images and the multi-channel semantic map into a pre-trained panoramic image depth estimation model to obtain a depth map corresponding to each panoramic image. The method is used for automatically generating an indoor structure model, the scheme comprises the core steps of semantic segmentation and layout reasoning, depth estimation and point cloud construction, structure optimization and indoor model reconstruction and the like, and a complete indoor panoramic image scene understanding scheme is formed.

A method and system for constructing a three-dimensional (3D) aerial survey of a city street scene include obtaining a plurality of video frames from a calibrated multi-camera setup covering a 360-degree view mounted on a moving vehicle. The plurality of video frames is split into a plurality of 3D parts containing a subset of the plurality of video frames and preprocessing the subset of the plurality of video frames of each part of the plurality of parts to obtain a calculated information. Further, constructing, by the processing circuitry, a 3D representation of each part of the plurality of parts based on the calculated information to obtain a plurality of local 3D reconstructed scene intervals. The method includes stitching and filtering, by the processing circuitry, the plurality of local 3D reconstructed scene intervals to construct the 3D city street scene.

The invention relates to the field of visual measurement of parts, in particular to a non-contact micropore form and roughness measurement method and system. The method comprises the following steps: carrying out initial contour scanning on a precision part, carrying out part detection base point analysis, and extracting an optimal coordinate base point; performing full-coverage scanning planning and panoramic image splicing based on the optimal coordinate base point to obtain a panoramic fusion image; geometric structure point depth identification is carried out on the panoramic fusion image, three-dimensional point cloud modeling is carried out, and a part CAD digital model is constructed; carrying out micropore shape key size calculation based on a part CAD (Computer Aided Design) digital model, carrying out geometric comparison calculation, and extracting an error value of each measurement point; and performing deviation visual mapping and comprehensive evaluation according to the error value of each measurement point, and outputting a comprehensive evaluation report. According to the invention, the precision part detection efficiency and precision are improved, and the production quality control and later problem traceability of the precision part are enhanced.

The invention discloses an unmanned aerial vehicle image seamless rapid splicing method based on multi-view geometry, and particularly relates to the technical field of unmanned aerial vehicle image splicing, and the method comprises the steps: extracting feature points of video frames through a deep learning model, and carrying out the inter-frame matching, and obtaining a matching point set; based on the matching point set, solving the three-dimensional coordinates of the 3D map points, determining the initial pose of the key frame and initializing the global map, matching the feature points of the current frame with the 3D map points in the global map, and solving the camera pose of the current frame; a new key frame is selected according to the feature coverage rate, a local optimization window is constructed for 3D map points jointly observed by the newly added key frame and the associated key frame, error correction is carried out on key frame poses and 3D map point coordinates in the window through local light beam adjustment optimization, and a global map is updated; and based on the optimized global 3D map point fitting reference surface, projecting the key frame image to the fitting reference surface, generating a panoramic image by adopting a multi-scale pyramid fusion method, and outputting a final image spliced image.

The invention discloses an infrared satellite data processing system suitable for infrared small target detection, and relates to the technical field of remote sensing satellite data processing and infrared image recognition, and the system comprises an image splicing module which is used for arranging L0-level original infrared images according to a shooting time sequence, and identifying overlapped region feature points of adjacent image particles through an SIFT algorithm, eliminating radiation distortion of an optical lens, and generating a seamlessly spliced comprehensive image by adopting a multi-scale fusion technology. According to the infrared satellite data processing system suitable for infrared small target detection, the quality and consistency of infrared satellite images are remarkably improved through a standardized data processing flow, the identifiability of target signals is optimized from a data source, the false alarm rate under the conditions of a complex background and a low signal-to-noise ratio is effectively reduced, and the detection accuracy is improved. And high-quality input is provided for a subsequent detection algorithm, so that the accuracy and reliability of infrared small target detection are improved.

The present invention relates to a compaction monitoring device and method that integrates 3D scanning and image perception. The device comprises a sensing component comprised of a 3D road surface texture scanning module, a camera, a vibration damping module, and a locator; a data analysis component, which performs image positioning, image stitching, time synchronization, and calculation of a compaction index based on texture features; and a control strategy component, which controls the number of compaction attempts based on the surface distribution of the compaction index. Compared to existing technologies, this invention introduces a new information source and evaluation basis for road compaction, enabling dynamic, real-time monitoring and feedback control of compaction levels, improving the quality of road construction projects and enabling compaction monitoring based on 3D scanning and image perception.

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 relates to a photovoltaic land slope stability partition evaluation method, which comprises the following steps that: an unmanned aerial vehicle flies in an oblique photography manner according to a path planning algorithm, and acquires an image and point cloud data of a slope region; correcting the collected images, including distortion removal, noise processing, image splicing, denoising, filtering and point cloud splicing of the point cloud data; creating a real three-dimensional terrain model by combining the texture information of the image and the height data of the point cloud, and extracting terrain height information from the point cloud data to generate a digital elevation model; performing feature extraction on the three-dimensional terrain model, and analyzing a stability index of the slope; establishing a slope stability evaluation model and performing zoning evaluation, performing stability zoning evaluation according to the feature data and the clustering result, and optimizing a zoning standard; and visualizing a slope stability partition result, generating a stability partition map and a report, establishing a dynamic monitoring system, and regularly using the unmanned aerial vehicle to repeatedly fly to obtain updated slope data.

The invention relates to a precision agriculture monitoring system and method based on multispectral imaging. The system and method are applied to real-time monitoring of crop physiological parameters and variable fertilization decision making. The system comprises an unmanned aerial vehicle imaging module, an edge computing unit and a cloud analysis server. The unmanned aerial vehicle module is provided with a multispectral filter wheel, a three-axis holder and an RTK positioning device and is used for acquiring a high-resolution crop image; the edge calculation unit integrates a radiation correction module, an image splicing module and a canopy segmentation module to realize on-site preprocessing; the cloud server runs a deep learning model and a feature fusion mechanism, outputs estimation of parameters such as nitrogen, chlorophyll and moisture, and generates a high-resolution fertilization prescription map. In the aspect of the method, dynamic monitoring of the nitrogen content of crops is realized through route planning, data synchronization, radiation normalization, multi-source feature fusion and time sequence prediction. The system supports online updating and ground verification of the model, has high precision, low delay and large-area operation capability, and is suitable for intelligent agriculture and precise fertilization scenes.

The invention discloses a cultural relic exhibition hall AI intelligent shooting system based on binocular vision, and relates to the technical field of cultural relic digitization and interaction, and the system comprises a binocular vision image collection module which is used for shooting and storing a multi-view high-definition image of a cultural relic; the AI image splicing fusion module preprocesses the image and generates a panorama; the cultural relic three-dimensional reconstruction module constructs a three-dimensional model with fine textures; real-time fusion of the intelligent shooting module fusion model and a visitor image is carried out to generate an interactive picture; the interactive output and management module provides related functions and manages data; by integrating binocular vision image acquisition, AI image splicing and fusion, cultural relic three-dimensional reconstruction and real-time fusion intelligent shooting technology modules, intelligent upgrading of cultural relic display and visitor interaction is achieved, the system adopts a binocular camera shooting mechanism triggered by multiple strategies, timing and induction triggering modes are combined, and the intelligent upgrading of cultural relic display and visitor interaction is achieved. The method can flexibly adapt to the demands of different exhibition scenes, guarantees the high efficiency of cultural relic image collection, and avoids the waste of resources.

The invention discloses a method for realizing intelligent sag measurement of a power transmission line by using a binocular depth camera, which comprises the following steps of: firstly, fixing the binocular camera on a rotary holder at the central position of two towers to complete camera calibration and epipolar correction; then, controlling the holder to rotate according to a fixed stepping angle, collecting a binocular image sequence covering the whole section of lead, and preprocessing the binocular image sequence; performing feature matching and image splicing by using an SIFT algorithm based on the left eye image sequence to generate a panorama and establish a panorama-local mapping relationship; thirdly, detecting an insulator and a spacer target in the panorama based on a Mask-RCNN model, accurately positioning key point coordinates of the insulator and the spacer target, and mapping the key point coordinates to an original local image; in the corresponding left and right local images, a semi-global matching (SGM) algorithm is adopted to calculate parallax and generate depth information, and then three-dimensional coordinates of a target point are obtained through conversion; and finally, performing catenary fitting according to the ordered three-dimensional point set, introducing a temperature and windage yaw dynamic correction model, and accurately calculating a sag value. According to the invention, non-contact, automatic and high-precision sag measurement is realized, the method is suitable for routing inspection of complex terrains and large-span power transmission lines, and the operation safety and efficiency are remarkably improved. The invention also provides a system, equipment and a medium for realizing the method.

Provided in the present application are an image stitching method for an X-ray imaging system, an X-ray imaging method, and X-ray imaging systems. The X-ray imaging system includes an X-ray source, and the image stitching method includes dividing an imaging region of a subject under examination into a first region and a second region, the first region and the second region having an overlapping portion; acquiring a first quantity of X-ray images of the subject under examination by rotating the X-ray source in the first region; acquiring a second quantity of X-ray images of the subject under examination by translating the X-ray source in the second region; and performing image stitching on the first quantity of X-ray images and the second quantity of X-ray images to acquire a medical image of the subject under examination.

The invention relates to the technical field of panoramic images, and discloses a self-correcting panoramic image splicing method for a vehicle around view system, which comprises the following steps: acquiring dynamic data of a vehicle to obtain an environment characteristic dynamic state, establishing a space-time incidence matrix according to the environment characteristic dynamic state, adjusting a fuzzy kernel estimation parameter, and performing accurate estimation and multi-frame super-resolution reconstruction of motion blur; fusing dynamic data, defining a vehicle attitude feature matrix, dynamically correcting vehicle attitude and camera external parameters, unifying cross-camera colors, performing ground constraint, constructing a multi-objective optimization framework, and balancing splicing quality and real-time performance; through monocular depth estimation and geometric constraint, the perspective difference of a close-range object is optimized, and through an edge retention loss function, the depth precision at the boundary of the object is enhanced; monocular depth estimation is optimized through binocular parallax constraint; constructing a multi-scale feature fusion network, and recovering image details; a factor graph model is constructed to integrate historical data, and accumulative errors of long-time-sequence splicing are eliminated.

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 relates to a navigation mark type and health state detection method based on improved YOLOv9, and belongs to the technical field of computer vision and navigation mark inspection. According to the method, in order to solve the problem of insufficient navigation mark data sets, a shape-damaged navigation mark data set is generated by using a CGAN technology, a navigation mark data set containing stains is generated through expansion by using a Canny algorithm, and a skew navigation mark data set is increased by using an affine transformation algorithm; in addition, traditional data enhancement methods such as geometric transformation and image splicing are introduced to simulate the imaging effects of the navigation mark at various angles and positions, so that the diversity of the image is improved. And the improved YOLOv9 model is utilized to improve the recognition accuracy of the small-size navigation mark. According to the method, the high-efficiency performance is maintained, meanwhile, the detection capability on fine and complex features is greatly improved, and accurate recognition on the navigation mark under different conditions is ensured.

The invention relates to the technical field of industrial visual inspection and intelligent manufacturing, and discloses a complex tooth surface structure-oriented bevel gear surface video defect detection method, which comprises a video data acquisition and preprocessing step, a video time sequence modeling branch construction step, a super-image space expression branch construction step and a double-branch fusion prediction step. And a reasoning and detection output step. According to the invention, for the bevel gear tooth surface with complex curvature, strong light reflection and tiny defect characteristics, a two-way detection architecture in which a video time sequence modeling branch and a super-image space expression branch are fused is constructed; cross-frame dynamic defect features are captured by using a video transformer network based on a sliding window, and local space texture perception is enhanced through super-image stitching and a pre-training network, so that stable and accurate identification of micro defects and cross-frame evolution defects is realized under the background of complex tooth surface reflection and structure interference; and the method has relatively high detection robustness and comprehensive performance.

A vision-based tracking control method for a quadruped robot includes receiving unilateral images captured by multiple cameras pointing different directions and utilizes an image stitching algorithm to synthesize the unilateral images into a panoramic image; based on the panoramic image, determining first and second position coordinates of the moving target and environmental obstacles; and formulating or modifying a navigation path for tracking the moving target based on the first and second position coordinates. The method significantly improves the perception ability, navigation accuracy and robustness of the quadruped robot in dynamic environments, thereby achieving more intelligent and flexible control.

The invention discloses an image splicing method and device and a storage medium. The method comprises the steps of fusing paired or grouped images to be spliced into a fused image through a splicing model; the splicing model comprises a splicing network, a correlation analysis network and a fusion network which are connected in sequence; the deep semantic features and the shallow detail features of the to-be-spliced images are extracted through the splicing network, the correlation analysis network can more accurately judge the overlapping relation and the spatial position between the images by mining the context correlation information between the images, and the registration deviation is greatly reduced in combination with the dynamic determination of the size of the minimum bounding rectangle. In the fusion network coding stage, the feature expression capability is enhanced by reducing the size of a feature map, and in the decoding stage, fine fusion of deep and shallow layer features is realized by recovering the size. The three networks cooperate to effectively solve the problems of high calculation complexity, low registration precision, poor splicing quality and the like of a traditional method, and the application requirements of mobile equipment and complex scenes are met.

The invention relates to a panoramic radar image stitching method and device for fitting an optical image and computer equipment. The method comprises the following steps: acquiring multiple groups of synchronously acquired optical images and radar images; acquiring position information of a target object in the radar image, and acquiring a centroid coordinate of the target object in the optical image; the center-of-mass coordinates and the position information form cross-modal feature point pairs; based on the multiple groups of cross-modal feature point pairs, establishing an affine transformation model from the radar coordinate system to the optical coordinate system, calculating unknown parameters in the affine transformation model, and substituting solution results of the unknown parameters into the affine transformation model to obtain an affine transformation matrix; based on the affine transformation matrix, mapping each pixel point in the radar image to an optical coordinate system to obtain a converted radar image; and splicing the multiple frames of converted radar images to obtain a radar panoramic image. By adopting the method, the accuracy and reliability of deformation detection can be improved.

The invention discloses pavement crack detection equipment based on double spectrums, and the equipment comprises an equipment design module which comprises a camera module, a supporting structure, an inclination angle monitoring module, an image processing unit and a mobile device; the dual-spectrum fusion detection module comprises a thermal diffusion enhancement dual-spectrum multi-scale feature fusion image preprocessing module, noise reduction and multi-scale feature fusion are carried out on images collected by the infrared thermal imaging camera and the visible light camera, and a detection result and category and position information are output through an unsupervised enhancement BiSeNet hybrid wavelet transform network to complete detection; and the pavement quality evaluation module is used for realizing pavement crack detection through image splicing and BiSeNet network segmentation, realizing pavement quality evaluation through crack distribution diagram generation and area proportion calculation, and realizing detection result display through visual labeling. According to the invention, the detection efficiency can be greatly improved, the maintenance cost can be reduced, and powerful support can be provided for timely maintenance of the road.

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 discloses a solid tire quality detection method based on infrared and deep learning, and relates to the technical field of tire quality detection, and the method comprises the following steps: in the high-speed operation process of a solid tire, collecting a current infrared image, and extracting a high-gradient thermal texture reference point based on a phase correlation operator; and based on the extracted hot texture reference point, mapping a reference point track in a previous frame of image to the current image through adaptive optical flow tracking, and generating a hot texture original displacement vector field. According to the method, real inter-frame displacement identification is realized through hot texture reference point extraction and optical flow tracking, high-frequency disturbance is suppressed in combination with frequency domain filtering, image position reference is unified through weighted fusion and standardized offset mapping, and meanwhile, low-quality frame input is effectively judged and controlled by introducing continuous verification and dynamic weight regulation. The consistency and robustness of image splicing are integrally improved, the defect recognition error is remarkably reduced, and the detection stability and accuracy of the deep learning model in the industrial environment are guaranteed.

The invention discloses a non-contact measurement system and method for full-field deformation of a fuselage in an airplane crash test, and belongs to the technical field of airplane structure strength testing, and the method comprises the steps: making a high-quality speckle pattern on the surface of the fuselage, and laying cooperation mark points; a binocular camera flexible self-calibration method is used for completing calibration of the stereo measurement system; unification of global coordinates of multiple systems is assisted through unmanned aerial vehicle photogrammetry; a synchronous controller is adopted to trigger multiple sets of systems to synchronously collect images in the falling and collision process; obtaining the motion trail and speed of the key measuring point based on a mark point positioning tracking and stereoscopic vision principle; acquiring a full-field three-dimensional displacement field and a strain field based on a digital image correlation method guided by a control point and a stereoscopic vision principle; and deformation visualization representation is realized through image splicing and data fusion. According to the invention, non-contact, high-precision and full-field dynamic measurement of the three-dimensional deformation field in the falling and collision process of the whole large aircraft is realized, and technical support is provided for analysis and evaluation of falling adaptability of the aircraft structure and verification of anti-falling and anti-collision design.

The invention provides an image splicing method and device based on a pod, electronic equipment and a storage medium, and relates to the technical field of image processing. The method comprises the following steps: sending a control instruction to a stabilizing and pointing unit; when return information sent by the stabilizing and pointing unit is received, acquiring N paths of video data of the pod, and determining a plurality of to-be-spliced images and a reference image from the video data; performing feature processing on the reference image and each to-be-spliced image by using the FPGA to generate a first feature descriptor and a second feature descriptor, and performing feature matching on the reference image and each to-be-spliced image according to the first feature descriptor and the second feature descriptor to obtain a feature matching point pair set; according to the attitude angle information, the SOC chip is utilized to perform estimation transformation on each feature matching point pair in the feature matching point pair set, and multi-path splicing processing is performed on the reference image and each to-be-spliced image based on the transformation matrix set to obtain the target spliced image, so that the image splicing accuracy is improved.

The present invention provides an end-to-end panoramic image stitching method, an electronic device, and a storage medium. The panoramic image stitching method comprises the following steps: acquiring pictures captured by multiple cameras of a vehicle; processing the multiple pictures to obtain camera data; and inputting the camera data, preset parameter data and weight data into a trained panoramic image stitching model to generate a panoramic image, wherein the parameter data is a coordinate mapping relationship between the pictures and the panoramic image, and the weight data is weights of the pictures in the panoramic image. The method can obtain a panoramic stitched view in an end-to-end manner by directly inputting camera data, parameter data and weight data into a stitching model, without intermediate transformations and brute-force matching. The method involves few model parameters, requires less inference time and less GPU computing power, achieves relatively high real-time performance, and is suitable for embedded platforms.

: A system (SF) and related method for facilitating obtaining sub-images (mj) of a region of interest, ROI, (R) for combining into a target image (M) of the ROI (R). The ROI (R) may be situatable in an examination region (ER) of an X-ray imaging apparatus (IA). The system may receive, at an input interface (IN), input data including data (d) indicative of the ROI. The system computes, prior to X-ray exposure, based on the input data, a plurality of sub-fields-of-view, wherein the plurality of sub-fields-of- view in combination are capable to cover the ROI.

The invention relates to the technical field of visual inspection of photovoltaic modules, in particular to a line scanning solar module image self-adaptive splicing method based on a battery piece grid structure. The method comprises the following steps: synchronizing sub-images of the solar module and corresponding cell grid parameters, and extracting key points of each sub-image based on the cell grid parameters; determining a splicing mode of the sub-images, and calculating a position posture of each sub-image based on the key points and the splicing mode; determining the placement position of each sub-image based on the position attitude; selecting different splicing effective areas for each sub-image, and generating a standard splicing image and an extended splicing image based on the placement positions and the splicing effective areas; mapping the cell grid parameters to a standard spliced image and an extended spliced image to obtain a complete spliced image; according to the invention, the adaptive splicing of the solar module image is realized, the splicing precision of the image is improved, and the splicing precision is ensured to meet the technical requirements of photovoltaic module defect detection.