4108 results about "3d image" patented technology

The invention discloses a TSV technology-based silicon wafer image defect identification method and system, and the method comprises the steps: synchronously collecting three-dimensional images according to the depth structure characteristics of a TSV silicon wafer, mapping the three-dimensional images of different modes to a unified space coordinate system, and obtaining a three-dimensional fusion image; according to the three-dimensional fusion image, a feature extraction model based on a three-dimensional convolutional neural network is adopted, TSV hole wall morphology, depth deviation and material uniformity features are extracted, and an enhanced multi-dimensional feature tensor is obtained; according to the multi-dimensional feature tensor, modeling in combination with the spatial topological relation of the TSV structure to obtain a spatial topological distribution diagram of the defects; according to the space topology distribution diagram of the defects, the relevance between defect causes and process links is analyzed, a defect cause report and process optimization suggestions are generated, and an interpretable defect diagnosis result is obtained. According to the embodiment of the invention, a comprehensive and accurate silicon wafer image defect identification and process optimization scheme can be provided, and the reliability of a TSV manufacturing process is improved.

The invention discloses a pipe online defect detection method and system, and relates to the technical field of image detection. The detection method comprises the following steps: placing a to-be-detected pipe in a dark box environment, irradiating the to-be-detected pipe in a rotating state through a light source, displaying a pipe projection on a projection surface, and setting a detection line at the upper end of the projection surface; comparing the detection line with a set reference line in real time, and marking a suspected warping area according to the local offset; performing three-dimensional image reconstruction on the suspected warping area to generate a simulation three-dimensional point cloud model; the method is technically characterized in that preliminary judgment passes through a grading strategy of'rapid screening-precise reinspection ', and the detection speed and precision are balanced; by means of the optical path principle and threshold value comparison, positioning operation of the whole-surface suspected warping area can be rapidly completed, only data of a local area (suspected warping area operation) is analyzed, the hardware cost and energy consumption are greatly reduced, and the high-speed online detection requirement is met.

The invention relates to the field of image recognition, in particular to a wind power construction intelligent safety management method and system based on intelligent AI monitoring. The method comprises the following steps: obtaining an omnibearing real-time image flow of a wind power construction area, carrying out super-resolution deep convolution optimization and operator three-dimensional image segmentation, and extracting an operator three-dimensional image frame; three-dimensional point cloud modeling of the construction area is carried out based on the image flow, real-time image frame position positioning rendering is carried out according to a three-dimensional image frame, and a real-time twinborn model of the construction area is constructed; performing operation dynamic behavior analysis and behavior deviation degree quantitative analysis based on a twin model to obtain the behavior deviation degree of the operator; and according to the behavior deviation degree, carrying out early prediction analysis on illegal behaviors, making an adaptive risk early warning decision, and constructing an operation behavior risk early warning strategy. According to the invention, through real-time operation behavior identification and environmental risk analysis, the intelligence and safety level of wind power construction are improved.

The invention discloses a multi-angle particle therapy system without a rotating rack and a using method thereof, and relates to the technical field of particle therapy equipment, and the treatment system comprises an accelerator, an irradiation system, a control system, a patient supporting system and an imaging system. The patient supporting system comprises a containing and fixing device, a two-dimensional translation system, a rotating system and a multi-degree-of-freedom mechanical positioning system, the containing and fixing device is connected with the two-dimensional translation system, the two-dimensional translation system is connected with the rotating system, and the two-dimensional translation system controls the relative position of a patient and a rotating center; the rotating system rotates a patient to an appointed angle of a treatment plan or cooperates with the imaging system to obtain a three-dimensional image of the patient, and the irradiation system irradiates a tumor target area; the use method comprises the following steps: generating a treatment plan by reconstructing a three-dimensional CT image, and completing irradiation at different angles according to the treatment plan. According to the treatment system, multi-angle irradiation on a patient can be realized under the condition that a rotating rack is not used, and the manufacturing period and cost of the particle treatment system can be reduced.

Presented herein are systems and methods for the automated determination of a prostate cancer staging score (e.g., a PRIMARY score) for a subject. In certain embodiments, the systems and methods employ a machine learning model (e.g., one or more convolutional neural networks, CNNs) to analyze three-dimensional (3D) images obtained via both a functional imaging modality and an anatomical imaging modality. In addition to identifying regions of PSMA binding agent uptake (hotspots), the techniques described herein are able to accurately and automatically associate specific prostate zones to each hotspot and use this information in the determination of the staging score.

An in-situ fretting corrosion fatigue testing machine based on synchrotron radiation diffraction and three-dimensional (3D) imaging includes an axial fatigue loading system, a fretting loading system, and a corrosion environment control system, where the axial fatigue loading system includes a driving device, a load control device, and a load sensing device; the load sensing device is configured to measure an axial force and a normal force in real time; the driving device is configured to drive the load control device, thereby achieving axial displacement of the load control device; the load control device is configured to carry out axial fatigue loading of a specimen; and the fretting loading system includes a fretting wear device. The testing machine achieves real-time 3D imaging characterization of wear spot and crack morphology of a material in a fretting corrosion environment, as well as characterization of a residual stress evolution law.

The invention discloses a self-adaptive gravity center adjustment method and system for a transfer robot, and relates to the technical field of robot control, and the method comprises the steps: respectively collecting the three-dimensional information and contact force distribution information of an article and the contact force information between the robot and the article through a sensor, integrating the collected information to obtain a multi-modal data set, and carrying out the preprocessing of the multi-modal data set; utilizing a deep learning algorithm to extract visual feature vectors from the three-dimensional image information, and extracting tactile feature vectors from the contact force distribution information and the contact force information; fusing the extracted visual feature vector and the extracted tactile feature vector to obtain a multi-modal feature set; constructing a motion state model based on a deep learning algorithm, inputting the motion state model by using the historical multi-modal feature set, and outputting a control strategy; a control algorithm and a control strategy are optimized by using real-time feedback information; the invention provides a self-adaptive gravity center adjustment method by collecting multi-modal sensor data and combining a deep learning algorithm to perform feature extraction and fusion.

The invention relates to the technical field of three-dimensional image reconstruction, in particular to a VR-based three-dimensional reconstruction method and system for textile culture heritage, and the method comprises the steps: obtaining a multi-view image collection sequence of the textile culture heritage, carrying out the geometric topological feature extraction of the multi-view image collection sequence, generating a three-dimensional point cloud geometric model, and carrying out the reconstruction of the three-dimensional point cloud geometric model. Performing multi-resolution texture feature mapping processing on the three-dimensional point cloud geometric model to generate an initial three-dimensional model fusing geometric topological features and multi-resolution texture features; performing dynamic geometric optimization processing on the initial three-dimensional model based on preset VR display parameters to generate a target three-dimensional model after surface continuity correction; and performing dynamic matching processing on the target three-dimensional model and a preset VR interaction algorithm to generate a VR visual model with a multi-dimensional interaction attribute, and transmitting the VR visual model to a VR display terminal to perform three-dimensional space rendering, so that the three-dimensional reconstruction and interaction intelligence degree of the textile culture heritage can be improved in combination with a VR technology.

The invention discloses a quality detection system and method for a glue injection laser contour, and belongs to the technical field of quality detection, and the method comprises the steps: obtaining a reflection point cloud signal of a glue injection finished product, constructing a point cloud data stream, setting an image reconstruction method, constructing a glue layer three-dimensional model, synchronously generating a pseudo-color grey-scale map, and achieving the visual representation of the surface texture of a glue layer. A three-layer feature extractor is constructed, a quality primary judgment method is set, features of different scales are fused in a cross-layer mode, the problem of missing detection of complex defects in traditional single-feature detection is solved, basic defects are automatically recognized, and a quality primary judgment result is output; and performing defect judgment on the glue-injected finished product which is unqualified in primary judgment, setting a defect fine judgment method, performing voxel-level segmentation on the three-dimensional image, calculating defect characteristics, and judging whether the defects affect the use performance of the product or not so as to generate a fine judgment result, so that accurate positioning of complex defects is realized, and the defect type identification accuracy is improved.

The invention discloses a device and a method for intelligently investigating types and quantity of fishes. The device comprises a self-adaptive sonar detection module, a three-dimensional image acquisition module, an image preprocessing module, a fish detection module, a main body segmentation module and an identification and classification module. The sonar module is integrated with a three-frequency-band transducer, can dynamically switch frequency according to fish school depth, and realizes target tracking counting and quantity estimation in combination with an algorithm; the image acquisition module constructs a fish school three-dimensional image model by combining a depth camera with a light attenuation compensation algorithm; the preprocessing module fuses acoustic and optical features and expands a data set; the detection and segmentation module is used for accurately positioning fishes and removing impurities; the identification and classification module realizes type identification based on transfer learning and supports incremental learning of new fingerlings. According to the method, through cooperation of multiple modules, the problems of insufficient detection precision, poor image quality and the like in traditional investigation are solved, efficient and accurate investigation of fish species and quantity is realized, and technical support is provided for fishery resource management and ecological protection.

The invention discloses an immersive robot teleoperation method and system, and belongs to the technical field of robot teleoperation. An existing teleoperation scheme lacks an effective and timely feedback mechanism, is poor in operation intuition and low in control precision, and is difficult to compete with complex and fine operation tasks. According to the immersive robot teleoperation method, by constructing the first person mapping model, the interaction data acquisition model, the teleoperation processing model, the execution perception model and the immersive visual angle simulation model, real-time mapping can be performed on posture actions of an operator, and a real-time response three-dimensional image capable of being displayed in VR equipment is generated; an effective and timely immersive feedback mechanism from a first person perspective is formed, an operator can execute a task as like being personally on the scene, and the immersion, intuition and naturalness of interaction are improved, so that the control capability and the task execution effect can be remarkably improved, the operation efficiency and precision are improved, and then the operator can competent for complex and fine operation tasks.

Dual-energy imaging of a recording region is provided by a recording arrangement with an X-ray tube assembly and an X-ray detector for receiving X-rays of an X-ray field emitted by the X-ray tube assembly in cone beam geometry. The field has a central beam, and the recording arrangement is rotated around the recording region for recording projection data of different directions of projection for two different X-ray spectra. For each X-ray spectrum, a three-dimensional image dataset of the recording region is reconstructed from the respective projection data. The projection data of the two X-ray spectra is recorded during the rotation that covers at least 360°. For each X-ray spectrum, an associated portion of the X-ray field is fixed over the rotation, and a corresponding, associated, fixed portion of the X-ray detector is used.

The invention belongs to the field of image generation, particularly relates to a three-dimensional image generation method based on spherical reflection cavity parameter optimization, and aims to solve the problems of low imaging precision and poor adaptability caused by lack of a collaborative optimization mechanism in the prior art. The method comprises the following steps: acquiring optical characteristics of the inner wall of a cavity to generate a reflection path offset comparison table, measuring deformation deviation of the cavity to construct a geometric compensation mapping relation, and monitoring environmental disturbance in real time and converting the environmental disturbance into a noise intensity coefficient; inputting the target three-dimensional image into a pre-compensation processor, synchronously executing optical path compensation, geometric distortion correction and environmental noise suppression, and outputting a pre-corrected image to projection equipment; capturing an actual projection through an image sensor, extracting difference data with the pre-corrected image, and decomposing the difference data into a system error component and an environment interference component; and feeding back the updated parameters to the processor to regenerate a final three-dimensional image. According to the invention, multi-error-source cooperative correction and dynamic optimization are realized, and the imaging precision and adaptability are significantly improved.

The invention relates to an intaglio roller surface defect detection method and device and a storage medium. The method comprises the following steps that a to-be-detected intaglio roller is obtained; the gravure plate roller is driven to rotate, multi-layer scanning is conducted in the surface height direction of the gravure plate roller in the rotating process of the gravure plate roller, and a three-dimensional image of the surface of the gravure plate roller is obtained; and carrying out ink cell identification in the three-dimensional image, and obtaining net shape and ink cell depth information according to the identified ink cell so as to carry out defect point detection. Compared with the prior art, the method has the advantages that the printing roller does not need to be subjected to trial printing, defect detection is directly carried out on the surface of the printing roller, cost waste caused by trial printing is avoided, comprehensive and accurate defect detection on the surface of the printing roller is achieved, and the defect detection efficiency is improved.

The invention relates to the field of 3D rendering, in particular to an intelligent scenic area three-dimensional image rendering method, which introduces a differentiable discrete decision into 3D fusion, supports end-to-end learning of a k value, performs discrete-continuous optimization based on an activation function, predicts an optimal k value of each voxel, introduces feature adaptive fusion based on dynamic neighborhood bidirectional retrieval, and realizes the 3D image rendering of the scenic area. The alignment of the color image and the point cloud is enhanced, the false detection rate of a small target is reduced, the detail reconstruction capability of a large target is improved, and the comprehensive rendering capability of a scenic spot is improved; according to the method, a lightweight grid is adopted to express a scenic spot subject, residual Gaussian is introduced to supplement high-frequency detail features, the number of Gaussian is reduced, rendering efficiency and capability are improved, textures are generated based on initial rendering back projection, fuzzy view angle dependence is avoided, hierarchical clustering and contour extraction from bottom to top are adopted on the basis, and the method is more efficient and efficient. The point cloud vertical structure change is dynamically detected, the point cloud is complemented, the accurate contour is extracted, the number of grid vertexes is reduced, and the rendering integrity is improved.

The invention provides a control system and method for an oral surgery robot, and relates to the field of intelligent control, and the method comprises the steps: firstly obtaining thin-layer CT scanning data covering neck and throat regions, constructing a throat three-dimensional model, then collecting a surgery view three-dimensional image through a 3D endoscope, and carrying out the 3D image collection; performing semantic-level dynamic registration based on visual features on the three-dimensional model of the throat, determining pose information of the oral surgical robot, outputting a next target pose point of the oral surgical robot in combination with the pose information and a pre-operative planned surgical resection path, and finally determining the target pose point of the oral surgical robot on the basis of the target pose point. And generating a joint control instruction of the oral surgical robot. Therefore, the navigation preparation time in the operation is shortened, the high consistency of the motion track of the mechanical arm and the focus resection path is ensured, and the track deviation risk caused by registration deviation of a traditional system can be fundamentally solved.

The invention relates to the technical field of image processing, in particular to a three-dimensional image reconstruction method utilizing depth information, which comprises the following steps of: acquiring the depth information of a target scene, generating a depth map based on the depth information of the target scene, and acquiring the value of each pixel point in the depth map corresponding to the depth value of the pixel point from a camera in a real scene; in the target scene depth information acquisition stage, a target scene space model is acquired according to a target scene boundary coordinate, effective three-dimensional scene model modeling service is finely brought to a depth map through a 3D Gaussian Splitting scene rapid modeling technology, and in the method execution stage, the depth information of the target scene is acquired through the 3D Gaussian Splitting scene rapid modeling technology. The depth information sampling point density is designed by considering the complexity degree of the target scene space, the modeling precision of the three-dimensional scene model is effectively improved, and the precision of the three-dimensional scene model constructed by the method is improved more comprehensively by carrying out denoising processing on the depth map in advance and smoothing processing after the three-dimensional scene model is constructed.

The invention discloses a visual detection system for longitudinal tearing of a conveying belt, relates to the technical field of image recognition, and optimizes the problems of insufficient anti-interference capability, detection precision, false alarm rate and insufficient system integration and expansibility of the visual detection system for the conveying belt. Dust concentration, muddy water attachment and illumination conditions are monitored in real time, and a window structure and a cleaning device are dynamically adjusted by using a logical judgment algorithm, so that environmental interference is effectively reduced, image acquisition quality is improved, and definition of 3D image data is ensured; a multi-detection mechanism and a secondary confirmation strategy are introduced, a deep learning model is utilized to fuse historical data to construct a time sequence model, a tear prediction result is optimized through an attention mechanism, a tear risk assessment index Tlzs is finally generated, the detection precision is improved, and the false alarm rate is reduced. TCP / IP, Modbus Tcp and webSocket protocols are supported, data formats are converted in a unified mode and displayed visually, and centralized management of multiple devices is achieved.

Embodiments include example systems, methods, and computer-accessible mediums for analysis of anatomical images for assessment of stenosis and disc degeneration. In some embodiments, systems, devices, and methods described herein include selecting a region of interest (ROI) in a three-dimensional (3D) volume of image data of a plurality of vertebra of a spine, identifying one or more anatomical parts in the ROI, determining one or more parameters of the one or more anatomical parts, and assessing a severity of a spinal deformity based on the one or more parameters.

The invention discloses a cigarette appearance quality detection method based on three-dimensional and multispectral fusion, and the method specifically comprises the steps: obtaining a panoramic image, a three-dimensional image and a multispectral image of a to-be-detected cigarette; expanding the cylindrical surface of the cigarette into a two-dimensional characteristic spectrum based on the three-dimensional image, and obtaining the optical characteristics of the appearance of the cigarette based on multispectral imaging; in combination with the two-dimensional characteristic spectrum and optical characteristics, performing coarse classification on defects existing in the panoramic image by using a dynamic defect weighted classification strategy to form a cigarette appearance defect distribution spectrum; according to the cigarette appearance defect distribution map, the panoramic image and the corresponding three-dimensional image and / or multi-spectral image are respectively sent into a defect detection model aiming at a specific type to carry out defect fine identification, and finally the final defect type of the cigarette appearance is determined according to the output result of the multi-type defect detection model. According to the method, through feature space reconstruction, a special detection mechanism is set, the algorithm model is used for driving, and high-precision detection of the main appearance defects of the cigarettes 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 discloses an automobile tire defect automatic detection device and system, and belongs to the field of automobile tire processing, through highly integrated modular design, the automobile tire defect automatic detection device comprises a multifunctional image recognition module, a depth measurement and 3D imaging module, an internal structure and air tightness detection module and an analysis and decision module, comprehensive detection of the surface, the geometric structure, the internal structure and the air tightness of the tire is realized, and efficient, accurate and intelligent tire defect detection is realized through cooperative work of each module and equipment.

1. The name of the product under this design: Earhook Bluetooth Headset (YF28). 2. Purpose of this design product: used for communication and audio transmission. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: 3D image of component 1.

An imaging system can include a cone beam tomosynthesis imaging system configured to create a 3D image of a patient anatomy upon an initiation input. The system can also include at least one memory device that has instructions that, when executed by at least one processor, cause the tomosynthesis imaging system to execute multiple actions including obtain the 3D image from the tomosynthesis imaging system; obtain a prior 3D image of the patient anatomy; and register the 3D image with the prior 3D image to produce a composite 3D image. The navigation system can further include an interface system which accepts the initiation input to obtain the 3D image and renders at least a portion of the composite 3D image for review by a supervisor.

Systems and methods for detecting and contouring structures of interest in a 3D image are provided. In an embodiment, a method includes detecting structures of interest from a multi-channel input comprising at least one 3D image and generating a corresponding segmentation map using a first neural network; extracting a plurality of cropped images from the at least one 3D image, each cropped image corresponding to a subregion of the at least one 3D image containing at least one of the detected structures; and estimating contours of the detected structures in the plurality of cropped images and generating corresponding shape representations of the estimated contours using a second neural network. A corresponding system and non-transitory computer-readable medium are also provided.

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 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 platform for architectural drawing generation and approval which allows for easy generation of 3D architectural images from text descriptions, question and answer templates, and / or sample images for user or designer review and approval, and conversion of those 3D architectural images to 2D architectural drawings for permitting and construction. In an embodiment, the system and method involve generating structured requirements via a question and answer structured template, generating 3D images from a combination of the structured requirements and sample images provided by a user, and generating 2D architectural drawings from the 3D architectural images. In an embodiment, the 2D architectural drawings can be submitted for automated code compliance checking via one or more architectural modeling engines.

The invention relates to the technical field of image processing, and provides an indoor three-dimensional image intelligent rendering method based on image processing. Comprising the following steps of indoor multi-view image acquisition, image preprocessing, intelligent analysis of indoor scene elements, construction of an indoor three-dimensional initial model with attributes, intelligent generation of rendering parameters, adaptive LOD real-time rendering and intelligent interaction optimization. According to the intelligent interaction optimization system, through deep fusion of natural language processing, user preference learning and real-time rendering technologies, a set of efficient, visual and personalized virtual scene rendering interaction process is constructed. According to the method, the problems that traditional graphic software is complex in operation, high in learning cost and low in debugging efficiency are solved, and the user satisfaction and creation efficiency are remarkably improved through an intelligent recommendation and rapid iteration mechanism.

The invention relates to the technical field of 3D image rendering, in particular to a commodity three-dimensional model real-time rendering system for an e-commerce platform, and the system comprises a model geometric weight generation module which carries out voxelization processing on an input commodity three-dimensional model, retrieves the geometric curvature change rate of each voxel, the position relative to a model contour and a preset region identifier, and generates a model geometric weight; calculating voxel structure saliency measurement, and establishing a geometric importance weight map. According to the method, the input commodity three-dimensional model is subjected to voxelization processing, the geometric curvature change rate of the surface of the model and the position relation of the geometric curvature change rate relative to the contour of the model are obtained, the significance measurement index is constructed by integrating the region identification, and the importance degrees of different regions are distinguished; therefore, rendering resources can be concentrated in a more critical visual feature area of the commodity model, the detail expression effect is improved, meanwhile, the resource overhead of unnecessary areas is reduced, and the resource utilization efficiency is improved.