468 results about "Spatial image" patented technology

The invention discloses an intelligent fault diagnosis method fusing state monitoring and a multi-modal large model, and the method specifically comprises the steps: synchronously collecting time sequence data and a space image through a heterogeneous sensor group and monitoring equipment disposed in power grid equipment, and forming original data; based on the original data, a physical constraint feature vector is generated in combination with an equipment thermodynamic equation and a material deformation rule; performing health index prediction through the lightweight LSTM network based on the physical constraint feature vector; when detecting that the health indexes continuously decrease, clustering an HI time sequence curve by adopting a Gaussian mixture model, judging a degradation stage according to a clustering center distance, and obtaining a stage recognition result; and based on finite element simulation parameters, introducing a reinforcement learning model, optimizing the simulation parameters by taking maintenance cost minimization as a target, and outputting a predictive maintenance work order. According to the invention, intelligent fault diagnosis and accurate maintenance of the power grid equipment are realized, the fault processing efficiency and accuracy are improved, and the power failure loss is reduced.

The invention provides a supporting cable production monitoring method and system for 3D visual detection, and relates to the technical field of image processing and intelligent detection, and the method carries out multi-source fusion processing based on collected cable three-dimensional space image data, and comprises coordinate alignment, point cloud reconstruction and multi-scale feature extraction, and construction of a unified space geometric model. On the basis, the center line of the cable is extracted, coordinates of starting and ending points are calculated, and then geometric evaluation parameters such as the axial deviation rate and the straightness are obtained. The method has the advantages of high precision, high robustness and high universality, and is suitable for real-time detection and quality control of slender components such as cables and hoses in the industrial production process. According to the invention, the technical problems of inaccurate three-dimensional structure extraction, insufficient defect identification, difficult defect cause tracing and untimely early warning response in the prior art can be solved.

The invention discloses a snapshot type hyperspectral imaging industrial online sorting system which comprises a support assembly, an optical imaging assembly and a motion control assembly. The bracket assembly consists of a bottom plate, and an adjustable bracket and a fixed bracket which are fixed on the bottom plate; the optical imaging assembly comprises a lighting unit, an imaging objective lens and a snapshot type hyperspectral camera, and can synchronously obtain space image information of a measured object and spectral information of a continuous wave band in a single exposure process; the motion control assembly realizes automatic transmission of the measured object through the transmission platform; the data processing module is integrated with an image preprocessing unit, a spectral analysis unit and a spectral database, and is used for end-to-end closed-loop control from original hyperspectral data generation to sorting decision making; the system adopts a metasurface light splitting structure to realize real-time decoding, performs material or category identification by using a pre-trained classification model, and finally automatically generates a sorting decision signal according to an identification result to drive a motion control assembly to complete sorting operation.

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 belongs to the technical field of image processing, and particularly relates to a cable shielding layer weaving density detection system based on image analysis, which comprises an image correction module, a frequency domain analysis module, a self-adaptive filtering module and a density defect detection module, obtaining the maximum peak point of the centralized complex frequency spectrum; constructing a band elimination filter according to the maximum peak point, filtering the centralized complex frequency spectrum through the band elimination filter to obtain a filtered complex frequency spectrum, executing inverse Fourier transform to obtain a filtered space image, and binarizing the filtered space image through a threshold segmentation algorithm to obtain a pore mask; the porosity is obtained according to the ratio of the non-pore pixel points to the total number of the pixel points; and judging the weaving defect of the shielding layer according to the porosity. According to the method, the strong periodic signals of the weaving textures are automatically identified and filtered in the frequency domain, so that non-periodic defects such as pores are effectively highlighted, the technical problem that periodic textures cover defect signals is solved, and the accuracy of defect detection is improved.

The invention relates to the field of intelligent city planning, and discloses a street space quality intelligent evaluation and image generation method and system based on deep learning, and the method specifically comprises the following steps: movably collecting a street space image, and recording the geographic position information; performing perspective correction and multi-view image segmentation on the acquired street image data, and performing spatial matching with geographical location information to obtain a fused image database; and performing semantic segmentation on the image in the fused image database based on a deep learning model, calculating objective and subjective visual perception indexes and facility function indexes of the image, and generating a street space quality evaluation result. The method solves the problems that in the prior art, evaluation dimensions are limited, and an automatic response generation mechanism is lacked, and has the advantages of being intelligent, efficient and comprehensive in subjective and objective evaluation.

The invention provides an underwater multi-color space image enhancement method based on depth information guidance, which is characterized in that a model of the method is based on a training model framework capable of utilizing physical priori knowledge and multi-color information, and comprises a depth information generation module, a multi-color space feature fusion module and a depth enhancement module, the relation between a depth image and an underwater scene is enhanced through attention estimation, scene reconstruction training and fusion of multi-color information, so that insensitivity of a single RGB color space to brightness and saturation image attributes is made up; the feature representation capability is improved, and the scene adaptability of the model is enhanced.

The invention provides a three-dimensional target marking method and device based on a point cloud data-assisted two-dimensional image, and the method comprises the steps: fusing precise three-dimensional point cloud information obtained by a laser radar and two-dimensional image data collected by a camera based on a point cloud data and image data cooperation three-dimensional marking method; and a dynamic high-precision three-dimensional target marking system is constructed. Specifically, a space-image relationship is established through three-dimensional point cloud information and a two-dimensional image plane, and three-dimensional information of a target is mapped into a two-dimensional image, so that geometric and semantic information labeling is carried out on the target in the two-dimensional image, information loss of two-dimensional visual data in dimensions such as depth, attitude and space structure is made up, and the accuracy of the three-dimensional information labeling is improved. And meanwhile, when the three-dimensional point cloud is unmeasurable, a three-dimensional target labeling mode is dynamically adjusted in combination with two-dimensional image labeling information. According to the method, through dynamic high-precision three-dimensional target labeling, the obtained image-label can be used for training and reasoning of a three-dimensional target detection network, and the method has a wide application prospect.

The invention relates to the related field of image processing and computer vision, in particular to a space target image intelligent identification method, which optimizes a series of training strategies, including learning rate dynamic adjustment (such as attenuation and preheating), adaptive optimization algorithm and regularization technology (such as Dropout and data enhancement). And the accuracy, generalization ability and convergence speed of the model are obviously improved. In addition, through a model compression and reasoning optimization technology, efficient reasoning in a resource-constrained environment is realized, and the real-time performance of space image recognition is ensured. The flexible deployment strategy of the model enables the model to adapt to various platforms, including a cloud, a local server and edge equipment, and has good expansibility and practicability. The visualized recognition result is presented, so that the intuition of the recognition result is further improved, and powerful support is provided for subsequent analysis and decision making. The method has wide application prospect and practical value in space image recognition and other related fields.

The application provides a camera module and an electronic device. The camera module comprises a lens, an SMA motor, a substrate and an image sensor. The SMA motor comprises a carrier, a seat and an SMA driving assembly. The lens is fixed to the carrier. The SMA driving assembly connects the carrier and the seat. The SMA driving assembly is used to drive the carrier to move relative to the seat. The shell of the SMA motor comprises a top plate and a bottom plate arranged oppositely. The bottom plate comprises a first part and four second parts. The four second parts are arranged at the outer circumferential side of the first part at intervals. The distance between the second part and the top plate is greater than the distance between the first part and the top plate. The four corners of the substrate are provided with recessed avoiding spaces. The first part is fixed to the substrate. The second part is at least partially located in the avoiding space. The image sensor is fixed to the middle part of the substrate and electrically connected to the substrate. The image sensor is arranged to face the lens. The above-mentioned camera module can have a smaller module shoulder height while ensuring the shooting quality.

The invention discloses a multi-mode feedback control method and system for a femtosecond laser stone crusher, and relates to the technical field of medical instruments. The method comprises the following steps: constructing spectral component analysis, collecting spectral signals, and executing target chemical component identification; ultrasonic position detection: acquiring an ultrasonic echo signal through a transducer, and calculating a spatial distance; performing vision-assisted positioning, acquiring image data through an endoscope, and generating space image information; according to the spectrum identification result, the distance parameter and the space image information, multi-source data synchronization processing is completed; generating a laser parameter control instruction according to the fusion result; and executing a real-time feedback regulation and control process, obtaining feedback information, and completing control parameter updating and closed-loop response. Through fusion of multi-modal information such as spectrum identification, ultrasonic distance measurement and visual navigation, real-time identification of stone types, intelligent matching of laser parameters and accurate control of spatial positioning are realized, and the accuracy, safety and intuition of lithotripsy operation are remarkably improved.

The invention relates to a washing control method and device, dish washing machine equipment, computer equipment and a medium, and the method comprises the steps that space images of at least two to-be-cleaned areas are obtained, and different to-be-cleaned areas are located on different placement layers; identifying whether the space image comprises a target object or not; when the space image comprises a target object and the smudginess degree of the target object is greater than or equal to a preset degree threshold value, determining a to-be-cleaned area corresponding to the space image as a cleaning area; and a cleaning assembly is controlled to clean the cleaning area. The images of the placement layers of the dish-washing machine equipment are collected, the conditions of the placement objects on the placement layers are automatically recognized, the placement layers needing to be cleaned are automatically divided, the cleaning assembly is controlled to clean the areas needing to be cleaned, layered cleaning control over the dish-washing machine equipment can be automatically achieved, cleaning is efficiently completed, and meanwhile the cleaning efficiency is improved. And hydroelectric resources can be effectively saved.

The invention provides a system and a method for detecting geometric parameters of an optical fiber with a longitudinal periodic structure. The system comprises an optical fiber clamp used for fixing a test part of the optical fiber to be detected in optical fiber refractive index matching oil in a space image imaging device; the light source is used for emitting test light to the collecting lens through the optical fiber bundle, and the test light is focused into a focused light spot through the collecting lens and then is sequentially emitted to the space image imaging device and the detection device; the space image imaging device is used for moving along the axis direction of the to-be-tested optical fiber based on a preset moving speed after the test light passes through a test part in the optical fiber refractive index matching oil so as to form an optical imaging signal corresponding to the test part; and the detection device is used for acquiring geometric parameters of the periodic structure in the to-be-detected optical fiber according to the optical imaging signal. According to the invention, the detection device can accurately obtain the periodic structure geometric parameters of the to-be-detected optical fiber, and the detection precision and reliability are improved.

The invention provides a tunnel convergence deformation data acquisition system and method, and relates to the technical field of optical metrology, laser point cloud data of reflection mark points on the inner wall of a tunnel is acquired, local modeling is performed on the laser point cloud data to obtain a local point cloud subset, and then nonlinear fitting is performed on the local point cloud subset to obtain a local deformation descriptor; determining a registration error according to the local deformation descriptor and the space image information of the inner wall of the tunnel, and performing iterative elimination reconstruction on the laser point cloud data according to the registration error to obtain a local deformation matching model; determining a deformation characteristic reference of the inner wall of the tunnel through local reflection data obtained by performing local laser scanning on the reflection mark points of the inner wall of the tunnel; the local deformation matching model determines a deviation abnormal value of the tunnel inner wall based on the deformation feature reference, convergence deformation data of the tunnel inner wall are obtained through screening of the deviation abnormal value, nonlinear local tiny deformation detection can be achieved, and the sensing capacity of the irregular tunnel inner wall is improved.

Systems and methods for fast reconstruction of motion-resolved magnetic resonance images using space-time-coil convolutional networks are disclosed. The system can receive a plurality of k-space data sets. The system can detect a motion signal therefrom. The system can classify the k-space data sets according to states of the motion signals. The system can resolve the k-space data set to Euclidean space images. The system can resolve the Euclidean space images to a combined Euclidian space image. For example, the system can use a convolutional network that exploits spatial, temporal and coil correlations without k-space data consistency to minimize computation time.

The invention discloses a multi-view target image fusion method, device and equipment and a readable storage medium, and the method comprises the steps: carrying out the spatial position coding of the azimuth angle, pitch angle and distance of each image relative to a shooting position, and splicing the obtained spatial position code of each image with a corresponding image block embedding vector; forming a spatial image block embedding sequence by using all the spatial image block embedding vectors, and adding a learnable classification mark at the foremost end of the spatial image block embedding sequence to obtain a new spatial image block embedding sequence; inputting the new space image block embedding sequence into a Transform model, extracting global information in all space image block embedding vectors based on a proxy attention mechanism to update learnable classification marks, and obtaining a fused classification mark; and performing category prediction on the target through a multi-layer perceptron by using the fused classification mark. According to the invention, the target identification accuracy of the model can be improved.

The invention relates to the technical field of artificial intelligence image generation, in particular to a visual task generation method based on domain Token. Comprising the steps of obtaining field feature information of a target field and generating or determining at least one field lexical element; initializing an initial representation of an image to be generated; in an autoregression generation process, according to an image lexical element sequence corresponding to a previously generated image part and the at least one field lexical element, utilizing an autoregression model to predict a next image lexical element of the current position; repeating the prediction step until an image lexical element sequence representing the complete image is generated; and generating a final pixel space image by decoding based on the image lexical element sequence representing the complete image. According to the method, by introducing and fusing the field lexical elements, the field specific attributes of the generated image can be more accurately controlled, the generation fidelity and consistency of the image in the specific field are remarkably improved, and the controllability of the field style, element and structure of the generated content is improved.

Apparatuses and methods for using Raman Resonance Spectroscopy to evaluate metabolic and oxygenation status of the eye are disclosed herein. In some embodiments, metabolic mapping of the eye may be performed by aligning a Raman spectrum and a recorded spatial image of the eye.

It is possible to achieve both a high-resolution real-space image used in, for example, a video see-through type of AR device or MR device, and reduced system load. By an image acquisition unit, a first image captured at a first angle of view and a second image captured at a second angle of view narrower than the first angle of view within the first angle of view are acquired. By an image generation unit, a display image is generated by synthesizing an image of a high-resolution region based on the second image and an image of a peripheral region around the high-resolution region based on the first image. For example, based on gaze information of a user, the movement of an imaging direction of an image capturing unit for obtaining the second image is controlled, and the movement of a position of the high-resolution region is also controlled.

The invention provides a face in-vivo detection method and system based on a double-flow convolutional neural network, and the method comprises the steps: converting an original face feature image into two different color space images after preprocessing the face feature image, and constructing a training set through employing the preprocessed face feature image; constructing a human face in-vivo detection FAS model by using a double-flow convolutional neural network model framework, designing a double-flow convolutional layer, extracting image features in parallel by using two different color spaces, and classifying the double features; using the constructed training set to train a face in-vivo detection FAS model to obtain an optimal face in-vivo detection FAS model; and finally, calling the optimal human face in-vivo detection FAS model to carry out classification detection on the human face feature image data. According to the face in-vivo detection FAS model provided by the invention, the features in two color spaces are comprehensively considered, the classification credibility is increased, and extremely high accuracy is obtained on complex data set and cross-data set detection.

A display system includes a processor and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the processor to function as: a position-orientation acquisition unit that acquires a position and orientation of the image pickup apparatus based on a first frame of the real space image, a generation unit that generates a first frame of the virtual space image on the basis of the position and orientation of the image pickup apparatus based on the first frame of the real space image, a first image combining unit that combines a frame different from the first frame of the real space image with the first frame of the virtual space image, and a second image combining unit that combines the first frame of the real space image with the first frame of the virtual space image.

To display a display image of an interior space including interior equipment that matches a user's image by a simple operation.SOLUTION: An interior space simulation device 1 comprises: an acquisition unit 12 for acquiring atmosphere information of an interior space input by a user terminal 200; an extraction unit 13 for extracting a plurality of images of interior spaces stored in association with the acquired atmosphere information of interior spaces from a storage unit 11; a selection unit 14 for selecting a prescribed number of images of interior spaces from among the plurality of extracted images of interior spaces; and a transmission unit 15 for transmitting at least one of the prescribed number of selected images of interior spaces to the user terminal 20. If an image similar to an image of any interior space constructed by an entity in the past can be retrieved from among the plurality of images of interior spaces through image recognition, the selection unit 14 selects the retrieved image of the interior space as the prescribed number of images of interior spaces.SELECTED DRAWING: Figure 1

In virtual display in a virtual space, a virtual display system and method are provided that improve the reality of the venue and enhance the user's sense of immersion. 【Solution means】A virtual display system that displays an image of a virtual space on goggles 301 worn by a user based on data sent from a server 100. The server prepares, as image data for virtual display, a venue image representing a virtual space that is the venue for virtual display and a booth image representing an exhibitor's booth as high-resolution still images, respectively. Also, information-providing images such as a promotional video to be displayed to the user at the booth are prepared as high-resolution videos. Separately from these images, an object video representing a movable object moving within the virtual space, for example, a video of people walking back and forth in the venue, is prepared as a low-resolution video. By transmitting and superimposing these data on the user terminal 300 for display, the reality of the virtual display, such as people walking back and forth, is improved.

The application belongs to the technical field of image processing, and particularly relates to a cable shielding layer weaving density detection system based on image analysis, which comprises an image correction module, a frequency domain analysis module, an adaptive filtering module and a density defect detection module; a maximum peak point of a centralized complex frequency spectrum is obtained; a band-stop filter is constructed according to the maximum peak point, and the centralized complex frequency spectrum is filtered through the band-stop filter to obtain a filtered complex frequency spectrum and perform inverse Fourier transform to obtain a filtered spatial image, and the filtered spatial image is binarized through a threshold segmentation algorithm to obtain a pore mask; a porosity is obtained according to the ratio of non-pore pixel points to the total number of pixel points; and the shielding layer weaving defect is judged according to the porosity. The application automatically identifies and filters the strong periodicity signal of the weaving texture in the frequency domain, effectively highlights the non-periodic defects such as pores, solves the technical problem that the periodic texture covers the defect signal, and improves the accuracy of defect detection.

The invention relates to a method (60) for detecting defects (58) in a photolithography mask (14), the method comprising: i. capturing an aerial image (54) of the photolithography mask (14); ii. obtaining an underlying design (64) of the photolithography mask (14); iii. generating a plausible design (62) of the captured aerial image (54) by solving an optimization problem that minimizes the deviation of a simulated aerial image (72) of the plausible design (62) from the captured aerial image (54); and iv. detecting defects (58) in the photolithography mask (14) by comparing the underlying design (64) with the plausible design (62). The invention also relates to a corresponding system for detecting defects.

A hyperspectral imaging device includes an optical channel arranged to focus light at a first image plane. A spectrometer includes a slit formed at the first image plane to allow a slit-shaped portion of the light pass through. A dispersive element receives light from the slit and spectrally disperses it along a direction perpendicular to a width of the slit. A focusing lens focuses the spectrally dispersed light at a second image plane such that the spectral dispersion is imaged along a first axis thereof, and a spatial image of the slit width is imaged along a second axis for detection by a sensor. A sliding lens group between the optical channel and the first image plane moves to direct the incident light, scanning the entire image over the slit such that multiple frames acquired by the sensor each correspond to a horizontal line of the image.

The invention relates to a mobile terminal motion sensing game interaction method and device, equipment and a medium, and belongs to the field of motion sensing control. The method comprises the steps that a real-time real space image is captured, in combination with an IMU unit, space posture sensing parameters are obtained, and the user posture state is obtained, and the user posture state comprises the user space position and the user real-time dynamic state; obtaining an operation stability index based on the IMU unit, constructing an operation stability evaluation model, and obtaining a sensitivity adjustment parameter through the operation stability index; and generating a control instruction based on the user pose state and the sensitivity adjustment parameter and feeding back the control instruction to the game terminal. According to the invention, immersive experience of the FPS game is realized and is not limited by peripherals and space sites, so that the game experience cost of the user is greatly reduced.

The invention discloses an unmanned aerial vehicle positioning method and system based on a total station measurement network and visual collaboration. The method comprises the following steps: determining a space reference of the total station based on a ground control point; determining the spatial position of the unmanned aerial vehicle by using the total station after determining the spatial reference; capturing a space image corresponding to the unmanned aerial vehicle by using a camera; and projecting a positioning mark corresponding to the unmanned aerial vehicle on the captured space image based on the determined space position of the unmanned aerial vehicle. Therefore, efficient labeling, excellent consistency, cross-device / cross-camera unified output, precision verifiability, traceability, flexible deployment and excellent expandability can be realized.

Computer-implemented methods and systems for providing an image acquisition information of a medical image are provided. The methods and systems implement a plurality of steps. One step is directed to receive the medical image. Another step is directed to transform the medical image (or data of the medical image) into a frequency domain to obtain a k-space image. Another step is directed to determine the image acquisition information by applying a trained function to the k-space image (or to data of the k-space image). Another step is directed to provide the image acquisition information.

Provided are an augmented reality device for providing an augmented reality service for controlling an object in a real world space, and an operating method for the same. The method may include recognizing a first plane comprising a wall and a second plane comprising a floor from a spatial image based on a photograph of the real world space; generating a three-dimensional (3D) model of the real world space by extending the wall and extending the floor along the respective planes and performing 3D in-painting on an area of the extended wall and the extended floor that is hidden by an obstructive object; segmenting an object selected by a user input from the spatial image based on two-dimensional (2D) segmentation; and segmenting the object on the spatial image from the real world space based on a 3D model or 3D position information of the object using 3D segmentation.