2260 results about "Projection image" patented technology

The invention relates to the technical field of quality monitoring, and discloses a diamond high-strength micro-powder quality detection method and system based on artificial intelligence. The method comprises the steps of obtaining a two-dimensional projection image sequence of diamond micro-powder particles, calculating a projection matrix based on camera calibration parameters and geometric constraints, obtaining a multi-view image data set of the particles, establishing a pixel-level corresponding relation, extracting three-dimensional space coordinates of the surfaces of the particles, and reconstructing dense point cloud data of the particles. Establishing a local coordinate system based on the dense point cloud data, determining attitude parameters of particles in a three-dimensional space, if the attitude parameters deviate from a normal range, performing attitude compensation processing to obtain standardized point cloud data, and performing three-dimensional grid model construction on the standardized point cloud data; and calculating geometrical characteristic parameters of the particles based on the three-dimensional grid model, performing defect detection on the surfaces of the particles, and generating a crystal integrity evaluation report of the particles. The quality detection accuracy of the diamond high-strength micro-powder particles is improved.

The invention relates to the technical field of image recognition, in particular to a circuit board micropore copper plating quality inspection method based on image recognition. The method comprises the following steps: setting an annular polarized light source array; performing dynamic depth-of-field fusion shooting on the circuit board micropore based on the annular polarized light source array to obtain a two-dimensional projection drawing of the circuit board micropore; performing sub-pixel edge enhancement on the circuit board micropore two-dimensional projection drawing to generate a circuit board micropore enhanced projection drawing; and segmenting the interest boundary of the circuit board micropore enhanced projection drawing to obtain the hole wall region-of-interest boundary. Advanced image recognition, deformation analysis and self-learning technologies are introduced, efficient, accurate and automatic circuit board micropore copper plating quality intelligent inspection is achieved, and the defects of a traditional method in the aspects of detection precision, efficiency and comprehensive evaluation capacity are overcome.

The invention relates to the technical field of human body health assessment, in particular to a health assessment method and system based on a 3D human body posture image model. The method comprises the following steps: acquiring human body annular scanning data; extracting a dynamic posture sequence of a vertical position, a forward bending position and a lateral bending position of the human body annular scanning data, and performing phase shift fringe projection on the human body annular scanning data according to the dynamic posture sequence to obtain human body three-dimensional point cloud data; a sagittal plane, a coronal plane and a cross section of the human body three-dimensional point cloud data are analyzed for orthogonal projection, and a human body multi-angle projection image group is generated; and identifying skeleton contour features of the human body multi-angle projection image group so as to establish a dynamic marking system of the anatomical mark points. Through high-precision dynamic acquisition and multi-dimensional space analysis, precision, standardization and individuation of 3D human body posture health assessment are realized, and the accuracy and comprehensiveness of human body posture health assessment are improved.

The invention relates to the technical field of projection display, and discloses a projection curtain light field display gain method and system used under ambient light. According to the method, environment light data, projection curtain data and original output signals of projection equipment are collected in real time, and a dynamic light field distribution model is established after fusion processing. And based on the dynamic light field distribution model, adopting an adaptive genetic algorithm to optimize a compensation weight, generating a light field compensation parameter set, performing reverse compensation processing of brightness gain, contrast and chromaticity offset on an original output signal, and generating an enhanced projection signal. The system comprises a multi-source data acquisition module, a light field feature extraction module, a dynamic compensation calculation module, a signal enhancement processing module and a closed-loop feedback control module, ensures that the projection image keeps an optimal display effect under different ambient light conditions, and remarkably improves the watching experience of audiences.

The invention relates to a three-dimensional point cloud registration method and system based on a two-dimensional visual large model. A source point cloud and a target point cloud are decoupled into two-dimensional projection representation; constructing a structure consistency restoration domain, restoring geometric structure fracture and semantic deficiency in the projection image, and generating a dense and continuous restoration image; inputting the repaired image into a pre-trained visual geometry large model, carrying out cross-modal feature matching and pose resolving, and synchronously outputting a pixel-level matching confidence map; and inversely mapping a two-dimensional pose calculation result to a three-dimensional space to complete coarse registration, constructing a high-credibility anchor point set in the three-dimensional space by using a confidence map, and guiding a point cloud fine registration algorithm to converge to global optimum. According to the method, the registration large model for natural image training can be seamlessly migrated to the point cloud data, and retraining is not needed; in a weak texture and partially overlapped point cloud scene, a robust rough registration initial value can still be provided; the convergence speed and the anti-noise performance of fine registration are remarkably improved, and adaptive improvement from coarse to fine is achieved.

The invention relates to a skeleton posture prediction method and system, computer equipment and a storage medium. The method comprises the steps that preoperative three-dimensional image data and intra-operative projection data of a target skeleton are acquired; obtaining an initial attitude matrix of the target skeleton according to the three-dimensional image data; obtaining preoperative projection data of the target skeleton according to the initial attitude matrix and the preoperative three-dimensional image data; performing style migration on the preoperative projection data to obtain intra-operative simulation projection data; and obtaining a target attitude matrix of the target skeleton according to the intraoperative simulation projection data and the intraoperative projection data. According to the method, the image style migration is performed on the preoperative projection data to obtain the intraoperative simulation projection data, so that the intraoperative simulation projection data is closer to the real intraoperative projection image to improve the registration precision, prediction is performed in combination with the actually acquired intraoperative projection data, the precision and robustness of bone pose prediction are improved, the iteration process is simplified, and the accuracy and robustness of bone pose prediction are improved. And the bone posture prediction efficiency is greatly improved.

The invention relates to the field of X-ray image processing, and discloses an X-ray image reconstruction method based on direction perception tensor modeling. The method comprises the following steps: acquiring a plurality of X-ray projection images with different incident angles, and establishing a projection direction mapping matrix in combination with tissue direction distribution; constructing a high-order direction perception tensor field based on the mapping matrix and the structure prior information, wherein the high-order direction perception tensor field is used for describing the dominant structure direction and anisotropic response characteristics of each image position; a direction enhancement response diagram is generated through tensor-guided gradient calculation, and dynamic enhancement of local edges is achieved; then structure response intensity is extracted to construct a structure sensitive function graph, and the structure sensitive function graph serves as a weighting factor in image reconstruction; based on the weighted graph and the tensor field, an image reconstruction objective function containing direction consistency constraint is constructed, joint optimization is executed, a regularization item is dynamically updated, and high-fidelity reconstruction of the image under the low-dose condition is achieved. According to the method, the image detail keeping and noise suppression capabilities are improved, and the method has relatively high adaptability and robustness.

The invention belongs to the technical field of medical images, and relates to a surgical navigation-oriented multi-dimensional medical image adaptive registration method, which comprises the following steps: acquiring a 3D CT image, performing feature extraction, and performing voxel-by-voxel addition on the 3D CT image and an original 3D CT image to obtain a 3D image to be projected; obtaining current pose estimation and target pose estimation; inputting the 3D image, the current pose estimation and the current pose estimation into a ProST projector to obtain a current projection image and a target projection image; inputting the current projection image and the target projection image into a double-path encoder-decoder, and capturing a global corresponding relation between features by adopting a cross-modal attention module to generate final features; fusing the final features, and inputting the fused final features into a total differential regression iteration model to obtain a registered medical image; the regression module provided by the invention provides a more robust initial pose for the optimization framework, and the probability that the network falls into local minimum during gradient descent optimization is greatly reduced.

The invention discloses a wide-angle camera distorted image correction method and device based on track visual detection. The method comprises the following steps: acquiring a track distorted image; the projection imaging intersection point between the sleeper and the steel rail is adopted to form a mark point; solving the distortion center of the camera by combining a distortion model according to the mapping relation between the three-dimensional world coordinate and the projection coordinate of the three-dimensional world coordinate in the distorted image; solving distortion parameters of a camera by combining a Levenberg-Marquardt algorithm according to the fact that blanking points formed by parallel steel rails in the image must be subjected to collinear constraint; re-projection correction is carried out on the mark points participating in calculation; screening out bad mark points and removing the bad mark points; the distortion center and the distortion parameters are calculated again until all the mark points meet the 3 sigma criterion; and according to the optimal distortion center and the distortion parameters, track image correction is carried out through a distortion model. According to the invention, high-efficiency and accurate distortion correction can be carried out on line without the participation of a special cooperative calibration object.

The invention belongs to the technical field of medical image data processing, and particularly relates to a cardiac coronary plaque simulation method and system based on a digital phantom, and the method comprises the step of generating reconstructed simulation CT projection images with different halo artifact degrees. The method solves the problems that the effectiveness of an artifact removal method cannot be verified and evaluated due to the fact that the algorithm training effect is not generalized enough, and has the beneficial technical effects that the effectiveness of the artifact removal method is fully verified and evaluated, and the generalization of a deep learning halo artifact removal algorithm is improved.

The invention relates to the technical field of printed circuit board copper embedding, and discloses a method and device for controlling the copper embedding quality of a printed circuit board, computer equipment and a storage medium. The method comprises the following steps: acquiring a projection image of a copper nail grabbed by a mechanical arm and a hole site on a printed circuit board; converting the projection image into a three-dimensional image; extracting information in the three-dimensional image to obtain the diameter of the copper nail and the diameter of the hole site; calculating a difference value between the diameter of the copper nail and the diameter of the hole site to obtain an interference value; judging whether the interference value exceeds a preset threshold value or not; and if the interference value does not exceed the preset threshold value, controlling the mechanical arm to embed the copper nail into the hole site of the printed circuit board so as to complete the copper embedding operation. According to the method, high-precision quantitative detection of the diameter of the copper nail and the diameter of the hole site is achieved, the difference value of the two diameters is calculated in real time, whether the interference magnitude of copper embedding operation is within the design range or not can be accurately judged, the copper embedding yield is increased, and the rework and scrap cost caused by copper embedding defects is reduced.

A method includes generating, using at least one processing device, a ground truth optical flow map for displacement of pixels within a reference image based on a motion model. The motion model determines 3D coordinates of pixels within the reference image based on estimated depths of the pixels within the reference image. The method also includes performing, using the at least one processing device, 3D to 2D reprojection of the pixels within the reference image based on the motion model to generate a reprojected image view corresponding to a shifted camera perspective. The method further includes generating, using the at least one processing device, an occlusion mask for the reference image. The occlusion mask corresponds to occluded pixels within the reprojected image view. In addition, the method includes performing, using the at least one processing device, occlusion region inpainting of the occluded pixels to generate an inpainted reprojected image view.

The invention relates to the technical field of projection display, and discloses a multi-projection picture splicing method and system based on geometric correction. The method comprises the following steps: acquiring initial parameters and original picture data of the multi-projection equipment, wherein the original data contains an overlapped region image and is acquired according to a preset direction; geometric correction is carried out on the original image, geometric distortion feature points are extracted, and a mapping relation matrix is generated; dividing projection boundaries based on the matrix, and adjusting parameters to form a correction parameter set; performing spatial registration on the picture data according to the parameter set to generate multi-channel data; and carrying out fusion processing on the multi-channel data overlapping region, eliminating light intensity difference and color deviation, and generating a continuous splicing picture. The system comprises a data acquisition module, a geometric correction module, a parameter adjustment module, a space registration module and a fusion processing module. Through high-precision geometric correction, adaptive fusion and dynamic adjustment, the precision and visual effect of multi-projection image splicing are improved, and the method is suitable for large-size display scenes and has the advantages of being high in environmental adaptability, high in automation degree and the like.

In various examples, self-supervised learning may be used to pre-train an encoder network of a masked prediction model to reconstruct masked regions of an input representation of 3D detections such as LiDAR point cloud(s). Spatial and / or temporal masking may be applied to a projected representation of 3D detections (e.g., a two-dimensional (2D) projection image), and the masked prediction model (e.g., a masked auto-encoder or joint-embedding predictive architecture) may be used to reconstruct a representation of the masked regions (e.g., reflection characteristic(s) stored in corresponding pixels or cells of the projected representation, a latent representation of the reflection characteristic(s)) during iterations of self-supervised learning. As such, the pre-trained encoder network of the masked prediction model may be used as a foundation model and fine-tuned with a task-specific output head or its pre-trained weights may be used to initialize a task-specific model.

The invention discloses a building outer wall falling risk detection method and system based on deep learning, and the method comprises the steps: obtaining an original surface image, extracting vertical face geometric features, constructing a homography matrix based on vanishing points, carrying out the geometric correction, and reconstructing an orthographic projection image; performing enhancement processing on the orthographic projection image, extracting an effective detection area and intercepting a detection image; inputting the detection image into a deep learning segmentation model into which edge weight constraint is introduced, and performing semantic segmentation, binaryzation and optimization to obtain a falling region; a mapping relation is established according to the actual physical size of the building outer wall, and pixel information of the falling area is converted into multi-dimensional parameters such as the actual physical area, the elevation, the width and the height; and combining the defect intensity input quantification risk assessment model to calculate a comprehensive risk index, determining a risk level and outputting a result. Automatic identification and quantitative evaluation can be realized, distortion and background interference are eliminated, accurate conversion from pixels to a multi-dimensional physical space is realized, and a scientific basis is provided for safety investigation.

The invention provides a panoramic image processing method and device suitable for an unmanned aerial vehicle and a panoramic unmanned aerial vehicle. The method comprises the following steps: acquiring multi-view images in real time through a multi-camera array of an unmanned aerial vehicle, acquiring pose data by using an inertial sensor, converting each view image into a first projection image and a second projection image, and performing dynamic target detection and recognition on the second projection image to obtain a dynamic target, geometric scene features and target distribution. Differentiated processing areas are divided, specifically, a high-precision algorithm is adopted for the first processing area, a low-precision simplified algorithm is adopted for the second processing area, and computing power focusing and processing capacity optimization are achieved. In the splicing stage, a dynamic target historical trajectory optimization splicing algorithm is combined, and processing strategies are adapted to different areas, so that the quality of the key areas is guaranteed, and the process of the non-key areas is simplified to reduce the calculation load. According to the scheme, the problem of real-time panoramic splicing under the condition that unmanned aerial vehicle hardware resources are limited is effectively solved, and the processing real-time performance and efficiency are remarkably improved.

The invention discloses a micro-sensing trapezoidal method, device and equipment based on Aruco recognition and a medium, and relates to the field of computer vision. The method comprises the following steps: S1, projecting an Aruco grid and collecting an image, and extracting marked angular points to construct a position set; s2, calculating a trapezoid tension factor based on the trapezoid area and the opposite side distance, and quantifying local deformation; s3, fusing multi-labeled spatial parallax and tension information, constructing a continuous tension equilibrium domain, and generating a final mapping position through gradient correction basic inverse projection mapping and boundary disturbance compensation; and S4, outputting an inverse perspective matrix based on a fusion result, and estimating a microscopic pose offset parameter for fine adjustment of the projector. And through tension factor and spatial parallax modeling, adaptive correction of a distortion region is realized, the edge consistency and overall symmetry of the image are improved, and the stability and precision of the projected image are enhanced.

A handling apparatus includes a controller and a picking tool for a target object. The controller calculates surface information about a target object by using a first learning model for estimating the surface information from a feature map. The feature map represents a feature of an input image including the target object. The controller identifies surfaces in the input image from the surface information, and transforms the input image into projection images, each being seen from above a point on each of the surfaces in a normal vector direction. The controller calculates, for each projection image, a grasp posture for gripping the target object by using a second learning model. The controller transforms the grasp posture into a grasp posture in a first coordinate system. The controller calculates a final posture of the picking tool by projecting the grasp posture in the first coordinate system onto the input image.

The present invention provides an intelligent monitoring method for the coverage area of submerged plants. While obtaining the projection image of the submerged plants, the present invention obtains the turbidity data corresponding to the projection image; and based on the turbidity data, different image stretching methods are used to stretch the projection image to enhance the contrast of the projection image and obtain an enhanced image. Then, edge detection and optimization are performed on the enhanced image to obtain an edge-optimized image. Finally, the coverage area of the submerged plants is obtained according to the edge-optimized image. Since in the process of monitoring the coverage area of submerged plants in the present invention, based on turbidity, the contrast before edge detection is enhanced by the image stretching method, the clarity of the captured image of the submerged plants is improved, and thus the accuracy of detecting the coverage area of the submerged plants is improved.

The invention relates to an optical distortion test system and method. According to the method, a light source assembly is used for outputting projection light; the target assembly is fixed in front of the projection light output end of the light source assembly. The to-be-tested assembly is located on the side, away from the light source assembly, of the target assembly and connected with the adjusting assembly. The adjusting assembly comprises a pitching adjusting sub-assembly, a horizontal adjusting sub-assembly, a height adjusting sub-assembly and an inclined sub-assembly, the pitching adjusting sub-assembly is used for ensuring that the to-be-detected assembly is perpendicular to the projection optical axis, and the horizontal adjusting sub-assembly and the height adjusting sub-assembly are used for ensuring that the optical center of the to-be-detected assembly is coaxial with the projection optical axis and the lens center of the detection assembly; the inclined sub-assembly is used for adjusting a space angle between an optical central axis of the to-be-detected assembly and a projection optical axis of the light source assembly so as to detect edge distortion of the to-be-detected curved surface element; the detection assembly is located on the side, away from the to-be-detected assembly, of the adjusting assembly and used for shooting a projection image of the target assembly which generates distortion after being acted by the to-be-detected assembly.

In a creation method of a trained model, a reconstructed image (60) obtained by reconstructing three-dimensional X-ray image data (80) is generated. A projection image (61) is generated from a three-dimensional model of an image element (50) by a simulation. The projection image is superimposed on the reconstructed image to generate a superimposed image (67). A trained model (40) is created by performing machine learning using the superimposed image, and the reconstructed image or the projection image.

The invention provides a component identification method and system based on a three-dimensional point cloud, and relates to the field of industrial detection. The method comprises the steps of determining a main geometric region of a geometric component based on first point cloud data; processing the first point cloud data of the main geometric region in a layered and partitioned manner to obtain second point cloud data corresponding to different structure hierarchies; projecting the second point cloud data to a two-dimensional plane, and determining a two-dimensional projection image; determining geometric feature information based on the two-dimensional projection image; and determining a three-dimensional geometric model based on the geometric feature information. The system comprises an area module, a layering and partitioning module, a projection module, a sensing network platform, a feature information module and a modeling module. According to the method, the three-dimensional geometric model of the component can be stably and efficiently determined, the recognition accuracy and efficiency are improved, and the actual requirements of industrial production detection are met.

A projector includes a first light source, a light modulator that modulates visible light output from the first light source to form a projection image, a first relay optical system that forms the projection image at a first position, an enlarging optical system, an invisible image generator that forms an invisible image made of invisible light, and a light combiner that is disposed in the optical path between the enlarging optical system and the light modulator and combines the visible light and the invisible light with each other into combined light. The invisible image is formed at a second position conjugate with the position where the projection image is formed. The enlarging optical system forms an image at the first position and projects the combined light to display the projection image and the invisible image on a single projection surface.

The invention discloses a plane CT geometric calibration method, system, storage medium and device, and the method comprises the following steps: obtaining a plane CT to scan a calibration model body, so as to obtain a projection image of the calibration model body; the calibration die body comprises a body and a plurality of pairs of calibration small balls arranged on the body, and the plurality of pairs of calibration small balls are configured to be of a two-layer structure; wherein a sphere center connecting line of each pair of calibration small balls is perpendicular to a detector receiving plane of the plane CT; processing the obtained projection image to obtain projection coordinates of each calibration small ball; pairing the calibration balls based on the projection coordinates of each calibration ball, and determining a projection coordinate connecting line of each pair of calibration balls; determining vertical point coordinates of a radiation source focus in the plane CT in the receiving plane of the detector based on each projection coordinate connecting line; and adjusting the position of the radiation source or the detector to enable the vertical point of the radiation source to coincide with the plane center point of the detector, thereby completing calibration. The method is easy to operate, the plane CT geometric calibration precision can be effectively improved, and the calibration workload is reduced.

The invention relates to the technical field of optical communication, in particular to an automobile headlamp communication system and method based on image frame interpolation, comprising a transmitting end and a receiving end, a vehicle-mounted central control system of the transmitting end is used for receiving input to-be-transmitted information, and an ambient light detection module evaluates an external illumination condition in response to the input of the to-be-transmitted information; an image gray value and frame insertion frequency are set based on the illumination intensity, the image coding module codes information to be transmitted based on the set image gray value to generate a projection image frame, and the projection module inserts the projection image frame into a normal illumination frame sequence of a vehicle lamp based on the frame insertion frequency and projects the projection image frame to an external environment; the image acquisition module of the receiving end is used for acquiring a projection image frame, the image decoding module preprocesses the projection image frame and then decodes the projection image frame, and the information to be transmitted is restored and sent to the vehicle-mounted central control system. According to the invention, vehicle lamp communication at a certain distance in a traffic environment can be realized on the premise of ensuring normal vehicle lamp illumination.

The present invention provides a vehicle projector device installed inside a vehicle, a vehicle cabin system comprising same, and a method for adjusting the position of a projection image of a projecting module installed inside the vehicle, the vehicle projector device comprising: an armrest having a top cover; and the projecting module that is installed in the armrest to be rotatable and enables adjustment of a projection area to project an image toward the ceiling and rear of the interior of the vehicle.

Supported by artificial intelligence, an object is classified in an X-ray projection image. A 3D representation as well as a localization of the classified object can be determined by matching a model of the classified object to a visualization of the classified object in the X-ray image.

An adjustment image of a projected image is captured by a disparity image sensor. A first defocus factor in generated response to comparing the adjustment image with a reference image driven onto a display projector assembly the generated the projected image. A second defocus factor is generated in response to an alignment of a first intensity profile of the adjustment image and a second intensity profile of the adjustment image. A focusing lens of the display projector assembly is adjusted in response to at least one of the first defocus factor and the second defocus factor.

The invention relates to a reflective glass for a reflective display system for reflecting a projection image into the eye region of a user, the flat reflective glass being made of a transparent material in which an angle-selective optical element is embedded, the optical element extends in the reflecting glass over the entire surface area of the reflecting glass, and the angle-selective optical element deflects at least a part of the projection light which carries the projection image and is coupled into the reflecting glass via the inner surface at an angle, so that the projection image is reflected on the outer surface of the reflecting glass. The portion of the coupled projection light does not reach into the eye region of the user.

The invention provides a method for eliminating metal artifacts in a cone beam CT (computed tomography) projection domain, which comprises the following steps of: converting a current frame projection image IC into a binarization image IL and an edge detection image IG, marking connected domains in the IL and the IG, and deleting non-metal artifact area connected domains, so that binarization and edge detection results can be mutually verified; the accuracy of metal artifact area detection is improved; obtaining an extended bounding rectangle Ri, ext of each connected domain in the IM, and effectively eliminating metal artifacts according to the extended bounding rectangles Ri, ext; by segmenting the metal artifact area in the projection domain image, the resolution of the image is protected, and the artifact elimination effect is improved.