256 results about "Image stitching" patented technology

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.

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.

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 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 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.

: 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.

This invention discloses a cloud-edge-device collaborative intelligent panoramic perception and target tracking system, including an image processing layer comprising an NPU acceleration module and an image stitching module. The NPU acceleration module is used to extract multi-scale defect features from the panoramic video data using a lightweight convolutional neural network and output feature vectors. This invention achieves real-time edge processing of multiple video streams from the data acquisition layer via the NPU acceleration module and the key-value binding-based image stitching module at the image processing layer. This enables precise alignment and seamless fusion of images from multiple cameras, effectively solving the problems of poor stitching quality caused by large image distortion and asynchronous data frames in existing technologies. Furthermore, the system utilizes YOLO11m as the detection engine and an incremental learning interface at the server layer to perform high-precision target recognition and continuous cross-lens tracking of the panoramic image stream, allowing the system to dynamically expand its recognition capabilities and achieve low-latency intelligent perception.

The invention provides an image splicing method, device and system, the image splicing method is applied to an acquisition card, and the acquisition card corresponds to at least one sub-camera in a multi-camera system. Distributing a corresponding storage space for the images collected by the sub-camera, so that the storage address fields of the same pixel rows of the adjacent images collected by the sub-camera are continuous; the image splicing method comprises the following steps: acquiring image data acquired by the sub-camera; and writing the image data into a storage address field corresponding to the sub-camera. Through the technical scheme of the invention, the image transmission and splicing efficiency can be improved.

The application provides a pinhole image splicing true value acquisition and splicing method based on a heterogeneous camera combination. The acquisition method first symmetrically installs two pinhole cameras on a support, and installs an fisheye camera between the two pinhole cameras. Based on a double spherical camera model, the three cameras are calibrated to obtain the internal parameters and external parameters of the three cameras. The left eye pinhole view, the right eye pinhole view and the middle eye fisheye view of the target scene are simultaneously acquired by using the three cameras. The middle eye fisheye view is subjected to equirectangular projection. According to the internal parameters and external parameters of the three cameras, the left eye pinhole view and the right eye pinhole view are projected to the equirectangular projection view plane respectively, multi-camera coordinate system one is completed, and the splicing true value is obtained. The application has the core advantages of the hardware structure design and the heterogeneous camera image registration algorithm, can stably acquire images without seams and time sequence consistency, and provides strong support for the true value reference of the precision verification and model training of subsequent panoramic video splicing.

The application provides a panoramic system brightness adjusting method, which comprises the following steps: acquiring images of each camera; determining overlapping areas of the images of each camera; selecting a first image as a reference image of a panoramic image and a second image as a to-be-stitched image in the overlapping areas; acquiring an initial homography matrix between the reference image and the to-be-stitched image; correcting the initial homography matrix to obtain an optimized homography matrix; stitching the reference image and the to-be-stitched image through a bilinear interpolation algorithm according to the optimized homography matrix to obtain a panoramic stitched image; and judging whether the brightness uniformity of the panoramic stitched image meets a preset value; if yes, the panoramic image stitching is completed; otherwise, the brightness of the panoramic stitched image is adjusted. The application realizes the brightness uniformity of the panoramic stitched image and improves the imaging quality.

The application provides a panoramic image splicing system and method for weak light enhancement and color temperature correction. The system mainly comprises a multi-thread control module for overall controlling the execution sequence of each module; a video reading and image correction module responsible for reading four camera images and performing image correction operations; a parameter initialization module for processing images, performing key point detection and matching, and calculating the rotation matrix between images and estimating camera parameters; an image projection module for projecting each image onto a cylindrical surface according to the rotation matrix and camera parameters; an optimal seam line finding module for calculating the optimal seam line of each overlapping area; an image fusion module for fusing images according to the optimal seam line and a multi-band fusion method to obtain a panoramic image; and a panoramic image display module responsible for displaying the panoramic image. The system can realize efficient and accurate panoramic image splicing and effectively handle weak light and color temperature problems to improve image perception.

The embodiment of the invention discloses an image splicing method, device and equipment for a cigarette combustion cone, a medium and a product. The method comprises the following steps: acquiring to-be-processed images of the cigarette combustion cone under at least two shooting angles, and preprocessing each to-be-processed image to obtain a corresponding to-be-used image; according to the cigarette center line and the image retention ratio of each to-be-used image, determining an image retention area of each to-be-used image; and according to the cone top and the bottom edge of the cigarette combustion cone in each image reservation area, sequentially splicing all the image reservation areas to obtain a combustion cone panoramic image corresponding to the cigarette combustion cone. The problem that the panoramic form of the cigarette combustion cone cannot be obtained based on single-face shooting at present is solved, and the effect of obtaining the accurate panoramic form of the cigarette combustion cone by reconstructing the panoramic image of the cigarette combustion cone is achieved.

The application provides a penicillin bottle image splicing method based on cylindrical correction and weighted fusion, and relates to the field of image processing. The penicillin bottle image splicing method based on cylindrical correction and weighted fusion comprises the following steps: collecting a cylindrical label image; respectively performing distortion correction on the cylindrical label image from horizontal and vertical directions to obtain an approximately planar label image; roughly estimating an image overlapping area, then performing image registration on the estimated overlapping area; performing feature extraction on the overlapping area image, performing coarse feature matching, removing mis-matching points, and finally realizing feature matching of the image according to the sorting of the ratio of the Euclidean distance of the nearest neighbor and the second nearest neighbor of the feature points; and performing image fusion on the image after feature matching. The method solves the problem of the traditional fade-in and fade-out fusion algorithm, which adopts linear weighted fusion, and the splicing line after image fusion is obvious, and ghosting phenomenon is prone to occur.

The application discloses a multi-degree-of-freedom photoelastic model adjusting device and a panoramic force chain network construction analysis method based on image splicing, and the multi-degree-of-freedom photoelastic model adjusting device comprises a bearing platform, a transverse guide rail, a liftable longitudinal guide rail, a loading frame and an optical assembly, wherein the optical assembly comprises a camera, a polarizer, a polarizing mirror and an LED light source, and is all installed on the longitudinal guide rail which can be precisely moved, and the optical path height is consistent. The application realizes the horizontal and vertical multi-degree-of-freedom precise adjustment of the light source, the camera, the polarizing mirror and the polarizer through the movable guide rail, and overcomes the defects that the large-size polarizing mirror and the polarizer must be used in the analysis of the large-size model in the prior art. A plurality of photoelastic fringe images are shot, and a customized splicing algorithm is used to realize panoramic synthesis of the stress fringe images, so that the imaging quality is ensured, the equipment cost and the technical complexity are significantly reduced, and the high-resolution and full-field stress fringe collection of the large-size photoelastic model is realized.

The invention discloses a cotton field disease and pest control pesticide spraying amount prediction system based on an unmanned aerial vehicle multispectral remote sensing image, and belongs to the field of cotton field disease and pest control pesticide spraying amount prediction, and the system comprises a data acquisition module, an image alignment module, a panoramic spectral image generation module, and a disease and pest recognition and pesticide spraying amount prediction module. The data acquisition module controls the unmanned aerial vehicle to acquire a cotton field multispectral remote sensing image, records an image space-time position through a GPS and an IMU, and collects image processing modes in different historical weathers; the image alignment module aligns the image with the shooting time, divides small areas of the cotton field and associates real-time weather; the panoramic spectral image generation module screens high-quality images and splices the high-quality images into a cotton field panoramic image; the disease and insect pest recognition module recognizes disease and insect pests through deep learning, quantifies the stress degree and generates a variable pesticide application prescription map; the system can improve image quality and processing efficiency, realizes accurate pesticide spraying amount prediction, reduces pesticide waste, and effectively solves the problem of low pesticide application accuracy in traditional cotton field pest and disease control.

A method of displaying a trailer of a vehicle includes: capturing a tractor image and a trailer image from a tractor camera and a trailer camera, respectively; identifying a trigger event relating to a loss of a view of at least a portion of the trailer in the tractor image; splicing the tractor image and the trailer image together; and in response to a trigger event, displaying a trailer image using the stitched tractor and trailer images to maintain a view in which at least a portion of the trailer is present.

The application discloses a kind of construction methods of crop disease and insect pest monitoring model, comprising the following steps:1) unmanned aerial vehicle multi-view multispectral image data acquisition is carried out to crop canopy;2) the unmanned aerial vehicle multi-view multispectral image data collected is respectively preprocessed, including image stitching, geometric correction, radiation correction and canopy extraction;3) random forest algorithm is used to extract crop area;4) the crop area extracted in step 3) is based on the band sensitive to crop disease and insect pest, and the different generation combination is used to calculate the spectral index sensitive to disease and insect pest;5) random forest algorithm is used, and the importance of each spectral index of different observation angles in step 4) in disease and insect pest monitoring is evaluated using average drop gini coefficient;6) forward selection algorithm is used to determine the optimal spectral index combination of different observation angles;7) random forest algorithm is used to construct crop disease and insect pest monitoring model.

According to the microscope time sequence scanning image splicing method based on global position optimization, relative displacement is calculated through a phase correlation method, global position optimization is carried out in a spatial dimension, and a global position parameter with the minimum error is obtained. And then aligning the image at each moment to the global optimal position of the first frame by using a feature point-based time sequence alignment method to realize the minimization of time sequence jitter. The method can eliminate accumulative errors, improve splicing precision and reduce artifacts in dynamic analysis, and is suitable for the field of microscope image processing and splicing.

The application discloses a kind of based on track keeping's unmanned aerial vehicle thermal infrared image splicing method and system, it is related to image splicing technical field, including steps: constructing image set;Obtain the matching feature point of any pair of to-be-spliced unmanned aerial vehicle's thermal infrared image respectively, and the re-projection error of matching feature point is generated alignment item by the similar transformation matrix of to-be-spliced thermal infrared image;The actual distance between the center of reference image and the thermal infrared image of any unmanned aerial vehicle is calculated, and the track trajectory protection item is obtained between the center point of similar transformation matrix and reference image by pixel distance;Alignment item and track trajectory protection item are weighted and summed to construct global optimization objective function, and global optimization objective function is converted into linear least square model with similar transformation constraint to solve, and generate spliced thermal infrared panoramic image.The application minimizes the cumulative error of splicing process, while ensuring the integrity of global structure.

Embodiments of the present application provide an image processing method and device, computer equipment, storage medium and program product, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving. The method comprises: obtaining a target image and an initial foreground mask image corresponding to the target image; the target image contains a target object, and the initial foreground mask image is obtained by performing segmentation processing on the target object in the target image; performing image stitching processing on the target image and the initial foreground mask image to obtain a stitched image; performing feature learning on the stitched image to obtain a reference foreground mask image corresponding to the target image; performing optimization processing on the reference foreground mask image to obtain a target foreground mask image corresponding to the target image; a target foreground region contained in the target foreground mask image is used to indicate a region of the target object in the target image; and the mask image corresponding to the image can be accurately determined.

The invention is suitable for the technical field of image processing, and provides a microsphere image splicing method and device, terminal equipment and a computer program product, and the method comprises the steps: carrying out the superposition of channel images collected at the same position of a microsphere in each channel of a specified round, and obtaining a microsphere small image corresponding to each position; the two microsphere small graphs at any adjacent positions have an overlapping region with a set proportion; on the basis of a preset sequence and the overlapping areas, splicing the microsphere small images in sequence to obtain a complete image corresponding to a specified round; after each time of splicing is completed, recording the reference position of the spliced small image in the new canvas after each time of splicing is completed; and on the basis of the reference position of each microsphere small image in the complete image, splicing the channel images of different positions of each channel of each round to obtain a composite image of each channel of each round. According to the invention, high-precision and high-efficiency alignment of cross-round and multi-channel panoramic images can be realized, and error propagation can be effectively inhibited.

The invention relates to a full-field-of-view security and protection method based on an FPGA platform and a millimeter-wave radar. The full-field-of-view security and protection method comprises the steps of collecting video data of a monitoring area; splicing the multi-channel video data into a panoramic monitoring image by adopting an image splicing algorithm; performing character recognition on the panoramic monitoring image to obtain a recognition result; if people cannot be recognized due to the limitation of environmental conditions or people are detected and whether the people carry dangerous goods cannot be judged, the millimeter wave radar module is controlled through the holder to align at the area where the people are located to carry out data acquisition and processing, and a radar four-dimensional imaging picture is formed; and judging whether the detected person carries a metal article reaching a preset volume threshold value or not by combining an identification result of the panoramic monitoring image and the radar four-dimensional imaging picture. The system has the beneficial effects that by fusing two sensing modes of vision and millimeter wave radar, the defect that the performance of a traditional security system is sharply reduced under severe visible light conditions such as rain and fog, sand and dust, strong light, night and the like is overcome.

This invention belongs to the field of image processing technology, specifically relating to an image stitching method for a low-altitude unmanned aerial vehicle (UAV) monitoring network. The method includes: acquiring a reference image and an image to be stitched; extracting matching point pairs between the two images; determining the static confidence level of the matching point pairs based on their disparity changes; extracting the static matching point pairs and performing multiple linear transformations to obtain multiple static projection matrices; selecting the optimal static projection matrix for image transformation; and extracting dynamic targets within the overlapping area. When generating the stitched image, the gray values ​​of the regions identified as dynamic targets in the reference image are replaced with the gray values ​​of the same regions in the image to be stitched, thus completing the image stitching. This invention, through a dynamic-static separation strategy, effectively avoids the contamination of geometric transformation calculations by dynamic targets, significantly improving stitching accuracy and visual quality.

This invention belongs to the field of image generation, specifically relating to a method and system for generating 360° images of subway vehicles based on image stitching. The method includes: acquiring source images collected along the subway vehicle; obtaining effective matching point pairs through feature extraction matching and spatial topological similarity filtering; selecting the camera pair with the strongest geometric constraints as a benchmark; using incremental triangulation to recover the camera pose and 3D point cloud; in global bundle adjustment, optimization is performed by combining reprojection error and linear regularization terms based on the geometric principal axes of principal component analysis, with the regularization term weights adjusted according to the average distance from the point cloud to the principal axes; after optimization, the source images are projected onto a cylindrical canvas, and the optimal image gradient is selected based on gradient information entropy to construct a gradient field; a seamless 360° panoramic image is generated by solving the Poisson equation. This invention can effectively eliminate mismatches, suppress 3D reconstruction offset, and generate high-quality seamless panoramic images.

The embodiment of the invention discloses a fisheye image splicing method, computer equipment and a computer readable storage medium. The method comprises the following steps: acquiring an acquired image and a corresponding correction parameter; performing distortion removal processing on the acquired image according to the correction parameter to obtain a corrected image; determining a splicing seam between the adjacent corrected images; and performing fusion processing on the corrected image according to the splicing seam to obtain a panoramic image. Therefore, correction can be carried out by using the position look-up table of the collected images, splicing of the images collected by the multiple fisheye cameras is realized, and image distortion caused by the fisheye cameras and parallax is eliminated. The splicing seam is determined through the image features, the original problem of searching the splicing seam is converted into the shortest path problem, and the processing efficiency is improved. According to the invention, the problem that multiple fisheye videos cannot be spliced in the prior art is solved, and the image quality of the panoramic image obtained by splicing is improved at the same time.

This application discloses an image stitching method, apparatus, electronic device, and storage medium. The method may include: acquiring a first image and a second image captured simultaneously by a first camera and a second camera, respectively, wherein the first camera and the second camera are different cameras in a multi-camera device, and the first image and the second image have an overlapping area; determining a target object in the overlapping area; determining a target feature point filtering threshold for the target object based on the target object's feature information, wherein the feature information indicates the importance of the target object, and the importance of the target object is negatively correlated with the target feature point filtering threshold; and stitching the first image and the second image together based on the feature points determined by the target feature point filtering threshold. Implementing this application embodiment can improve the accuracy of image stitching.