274 results about "Multi-image" patented technology

The invention belongs to the technical field of image processing, and discloses a multi-image processing method based on multi-modal entity alignment, which comprises the following steps: acquiring a plurality of images; retrieving rich semantic information of the entity from an external knowledge base; selecting the most representative image for each entity in the multi-image scene by using semantic information; encoding the original input of each mode; performing first-layer fusion between a visual mode and a text mode by using cross-divergent attention, then performing second-layer interaction with a structured mode, and finally aligning an entity representation of an image by using contrast loss; and outputting multiple images fusing the text modality and the visual modality. According to the invention, hierarchical interaction fusion is utilized to enhance multi-modal interaction; enhancing entity text representation by integrating the external attribute value and the context information; and the most representative image is selected by using the semantic text, so that the influence of uncorrelated images is minimized.

The invention belongs to the technical field of Internet of Things information security, and particularly relates to a radio frequency fingerprint identification method based on multi-image feature fusion. According to the method, multiple images are extracted from original IQ data, the limitation of single image features is made up, different basic networks are selected according to different types of image data, the basic networks are optimized, SA-D-ResNet18 and SA-ConvNeXt-T networks are provided, a cross attention mechanism module is introduced between the networks, and image feature information is exchanged. In the final stage of feature extraction, a Concat mode is used to splice and fuse the features of a plurality of images. Therefore, the method can still maintain high recognition accuracy in a more complex environment. According to the invention, a common cross attention mechanism in multiple modes is applied to radio frequency image feature fusion, an image-based classification technology is also applied to the field of radio frequency fingerprint identification, and the radio frequency fingerprint identification method based on multi-image feature fusion is researched.

The invention discloses a water level identification method and device based on image fusion and electronic equipment, and relates to the field of image water level identification or other related fields, and the method comprises the steps: employing a target instance segmentation model to carry out the segmentation processing of a target image in which a water area exists, outputting a global contour segmentation map including the water area and an initial mask map for completing preliminary segmentation of the water area; performing depth estimation on the target image through an improved target depth estimation model to generate a depth map; inputting the initial mask graph, the global contour segmentation graph and the depth graph into a multi-image fusion network model, and outputting a water area segmentation mask graph for complementing the sheltered water area part; extracting a water level line for calibrating the water area mask area in the water area segmentation mask graph; and outputting a water level detection report based on a comparison result of the water level line and the warning line. According to the invention, the technical problem of low water level detection precision caused by object shielding and wrong segmentation of a water area in the prior art is solved.

The invention aims to provide a multi-condition diffusion model-based Shengtuo calligraphy rubbing fusion restoration method, which comprises the following steps of: firstly, acquiring a plurality of Shengtuo calligraphy rubbing images from different sources, preprocessing the images, and constructing a standardized training data set; designing a multi-image feature extraction and alignment module to obtain a fused structural feature tensor; constructing a core network structure of the multi-conditional diffusion model, and supporting guidance of a plurality of conditional vectors; jointly inputting the obtained fusion structure feature tensor and a plurality of condition guide items into a diffusion model to generate a fused and repaired potential image; and finally, restoring the potential image obtained by reconstruction into a final output image through a reverse mapping module. According to the method, the problems of blurring, pen lacking, breakage and non-uniform styles during fusion and restoration of the rubbing image in the prior art are solved.

The invention provides a bridge structure health diagnosis agent construction method based on a thinking chain and a domain tool set. According to the method, a language model with a causal reasoning capability is introduced, and a complete task chain process is constructed by combining target detection, segmentation and geometric analysis models for image processing, so that automation and intelligence from image perception to structure diagnosis are realized. The method supports multi-image input and multi-task cooperative processing, has good generalization ability and interpretability, and can effectively improve the efficiency and accuracy of structural health assessment.

A system to treat a patient comprises a user interface that allows a physician to view an image of tissue to be treated in order to develop a treatment plan to resect tissue with a predefined removal profile. The image may comprise a plurality of images, and the planned treatment is shown on the images. The treatment probe may comprise an anchor, and the image shown on the screen may have a reference image marker shown on the screen corresponding to the anchor. The planned tissue removal profile can be displayed and scaled to the image of the target tissue of an organ such as the prostate, and the physician can adjust the treatment profile based on the scaled images to provide a treatment profile in three dimensions. The images shown on the display may comprise segmented images of the patient with treatment plan overlaid on the images.

The invention relates to the field of computer vision and intelligent transportation, and provides a zero-training vehicle re-identification method based on a visual language large model, which comprises the following steps of: generating a dynamic multi-granularity text, analyzing visual features of a vehicle by using the visual language large model to generate structured hierarchical description, and constructing a hierarchical generation framework. Generating basic semantic tags of vehicle types, colors and visual angles and key detail area descriptions guided by local semantics in a layered manner, and dynamically adjusting description levels according to confidence; adaptive feature fusion: realizing adaptive fusion of visual-text features for rough sorting of vehicle similarity; and performing combined comparison reasoning, dividing the TopN images of the vision-text rough sorting list into N / 2 comparison groups, and performing multi-image conjoint analysis by using a visual language large model to realize fine sorting. According to the method, the multi-level fine-grained text description of the vehicle image is generated, and vehicle re-identification in an open scene is realized without training.

The invention relates to the technical field of chaotic cryptography, image encryption and information security, in particular to a multi-image encryption algorithm based on a hyper-chaotic system and computer-generated holography, which comprises the following steps: S1, generating a pseudo-random sequence for encryption by using the hyper-chaotic system; s2, preprocessing the original image based on computer-generated holography; s3, combining the generated pseudo-random sequence with the preprocessed image to realize image encryption; s4, through decryption operation corresponding to the encryption process, the original image is restored after the correct secret key is input; and S5, the decryption operation comprises inverse transformation and reconstruction operation on the encrypted image. The algorithm comprises an image preprocessing module, a hyperchaotic system module, a compressed sensing coding module, a computer-generated holographic encryption module, a decryption module and a post-processing module, the security of sensitive image data in the transmission and storage process can be ensured, and efficient and reliable guarantee is provided for sensitive image encryption in various fields.

A camera apparatus includes a camera body portion including a prism unit, a lens assembly, and an image sensor unit, a gyro sensor detecting a hand-shake with respect to the camera body portion and outputting gyro sensor information, a driver circuit generating at least one of a prism driving signal for image stabilization of the prism unit and a sensor driving signal for image stabilization of the image sensor unit based on the gyro sensor information, a prism actuator disposed in the camera body portion for driving the prism unit and performing image stabilization on the prism unit in response to the prism driving signal, and a sensor actuator disposed in the camera body portion for driving the image sensor unit and performing image stabilization on the image sensor unit in response to the sensor driving signal.

The invention discloses a visible light infrared multi-source image target fusion detection method and system, and relates to the technical field of image target detection, and the method comprises the steps: carrying out the radiation correction and spatial registration of a multi-source image set, forming an aligned multi-image sequence, carrying out the coordinate calculation and position correlation through employing a PROSAC optimization algorithm, obtaining the position information of a preliminary screening target, and carrying out the recognition of the preliminary screening target; and inputting the position information of the primarily screened target into a dual-channel decoupling model, executing multi-scale context sensing and space-spectrum joint analysis by a visible light channel layer, performing thermal contour extraction and thermal radiation intensity calibration by an infrared channel layer, outputting a target decoupling feature vector, performing manifold mapping on the target decoupling feature vector, and obtaining a multi-source evidence body. According to the invention, through the dual-channel decoupling model and the D-S evidence fusion engine, the discrimination capability of target feature expression is significantly improved, and the accuracy of target detection is enhanced.

Techniques for image generation based on a multi-image set and pose data is described herein. In an example, a computer system generates, by at least using a first machine learning (ML) model, a pose feature based on pose data that indicates a target pose. The computer system generates, by at least using a second ML model, a first appearance feature based on a first image and the pose data. The computer system generates, by at least using the second ML model, a second appearance feature based on a second image and the pose data. The computer system generates a combined appearance feature based on the first appearance feature and the second appearance feature. The computer system generates, by at least using a third ML model, a third image showing an appearance of an element in the target pose based on the pose feature and the combined appearance feature.

Systems and methods for generating augmented reality environments from 2D drawings are provided. The system performs a camera calibration process to determine how a camera transforms images from the real world into a 2D image plane. The system calculates a camera pose and determines an object position and an object orientation relative to a known coordinate system. The system detects and processes a 2D drawing / illustration and generates a 3D model from the 2D drawing / illustration. The system performs a rendering process, wherein the system generates an augmented reality environment which includes the 3D model superimposed on an image of the 2D drawing / illustration. The system can generate the augmented reality environment in real time, allowing the system to provide immediate feedback to the user. The images processed by the system can be from a video, from multiple image photography, etc.

Techniques are described for automated operations to analyze visual data from images acquired in multiple rooms of a building to generate multiple types of building information (e.g., to include a floor plan for the building), such as by simultaneously or otherwise concurrently analyzing groups of three or more images having at least pairwise visual overlap between pairs of those images to determine information that includes global inter-image pose and structural element locations, and for subsequently using the generated building information in one or more further automated manners, with the building information generation further performed in some cases without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room.

The invention relates to a metal workpiece surface image acquisition method and device based on multiple exposure. The acquisition method comprises the following steps: determining total exposure, and determining single exposure time and corresponding weight according to the total exposure; acquiring a surface image of the metal workpiece at each exposure time, and adjusting the surface image by using the corresponding weight; and combining a plurality of adjusted images to obtain a metal workpiece surface reflection-removed image. According to the method, a strategy of multiple times of irregular exposure is adopted, multiple times of short-time exposure is used for replacing one time of long-time exposure, a strong single light reflection area is avoided, light reflection is reduced, meanwhile, more image details are reserved, and the final image quality is improved.

The invention discloses a method for detecting functional components of multiple medicinal and edible substances based on image analysis, which comprises the following steps: acquiring n multispectral images of a target medicinal and edible substance sample, and preprocessing the acquired multispectral images to obtain a standardized multispectral image set; for an image Ii in the standardized multispectral image set, outputting texture features used for representing surface structure distribution and particle arrangement, extracting spectral features reflecting sample color change and chemical component reaction capability, and outputting structural features used for identifying micro-textures, edge contours and color spot distribution; generating a fused composite feature based on a multi-image channel fusion strategy; and classifying the composite features based on a support vector machine and / or a multi-layer perceptron, and outputting a component detection result of the target medicinal and edible substance sample. Through a multispectral image acquisition and analysis technology, a detection method suitable for samples with homology of medicine and food in different types, sources and processing modes is realized.

The invention relates to the technical field of super-resolution reconstruction, and discloses a continuous shooting image super-division method based on discrete wavelet transform fusion, which comprises the following steps of: extracting features of multiple frames of low-resolution pictures, and aligning the pictures by using deformable convolution to obtain aligned low-resolution pictures; decomposing the feature map of the low-resolution picture into low-frequency components and high-frequency components in different directions to obtain preliminary fusion features; separating the preliminary fusion feature channel into a semantic branch and a spatial branch, and obtaining a fused feature map by using complementarily enhanced semantic features and spatial features; and carrying out channel expansion on the fused feature map by using a pixel shuffling algorithm, and carrying out spatial rearrangement on the features after channel expansion to realize efficient and rapid up-sampling. According to the method, the problems of difficulty in alignment of multi-target complex movement and artifacts, detail distortion, blurring and the like of super-resolution of different-scale targets in a traditional method are solved, and the multi-image super-resolution imaging effect is enhanced.

The invention discloses a multi-image-source common exit pupil overlapping display system and method, and belongs to the technical field of optical imaging and display, and the system comprises a multi-image-source module which comprises a plurality of independent image generation sources and is used for providing different types of image information; the image wavefront guiding optical module is arranged behind each path of image source and is used for carrying out collimation, shaping, regulation and control and path guiding on light waves emitted by the multi-image source module and realizing consistent superposition of a plurality of heterogeneous image sources in spatial positions, angles and wavefront parameters at a common exit pupil superposition display surface P; the common exit pupil superposition display surface P is used for carrying out space and time fusion on wavefronts of all image sources to generate a composite image; and the detector module is arranged behind the common exit pupil superposition display surface and is used for receiving the fused composite image wavefront and converting the fused composite image wavefront into image data to be output. According to the system and the method, high-uniformity, high-resolution, high-dynamic-range and multispectral large-depth-of-field fusion imaging can be realized, so that higher requirements of modern simulators, visual systems and multidimensional sensing equipment on imaging quality and system performance are met.

The invention relates to the technical field of computer image processing, and particularly discloses a multi-image intelligent compression splicing method and splicing system capable of configuring the column number, and the splicing method comprises the following steps: 1, achieving the intelligent compression of images through the iteration quality attenuation, and balancing the image quality and storage space; step 2, dynamically calculating an image layout size based on the number of columns configured by a user; 3, keeping the aspect ratio of the image by adopting a cell centering strategy; and 4, realizing multi-image splicing by a dynamic canvas synthesis technology. The method has the advantages that intelligent image compression is achieved, and mass and storage space are balanced; a compression strategy can be dynamically adjusted according to the number of images; maintaining the original aspect ratio of the image; flexible multi-column image arrangement is supported; and splicing parameters can be dynamically configured.

The invention discloses an image processing method based on an adaptive weight multi-image fusion algorithm, which relates to the technical field of image processing and comprises the following specific steps of: extracting a plurality of images; constructing an adaptive weight multi-image fusion algorithm to carry out fusion processing to obtain a fused image; the adaptive weight multi-image fusion algorithm specifically comprises the following steps: inputting an image sequence; convolution processing is carried out; performing position alignment on the image; screening overexposure and underexposure areas of the source image for shielding to obtain a convolution result image; carrying out merging processing to obtain a convolution image; performing normalization processing on the convolution image; and calculating the distance standard deviation from each pixel of the source image to the average gray value, and fusing a new image. According to the method, multiple images can be fused into one image with a soft surface and a luxurious edge, detail information in the multiple images is reserved, the noise of the images is reduced, and the local contrast of different areas in the images is enhanced, so that the quality of the images is improved.

The invention provides an image-based eye lesion grading analysis method and device, a medium, a program product and a terminal, and the method comprises the steps: obtaining one or more eye lesion images, inputting the one or more eye lesion images to a pre-trained first model, and generating a corresponding eye feature vector; for a single image, calculating the similarity between the feature vector and each eye disease category, and outputting a prediction category with the highest similarity; and for a plurality of images, respectively calculating the similarity between the feature vectors and each category, and realizing adaptive weighted integration by using the second model to obtain a final prediction category. Sub-model subdivision and risk level layering are carried out according to prediction categories, and a structured risk layering report is output. The problem that in the prior art, the diagnostic value of multi-image information in complex cases is difficult to effectively evaluate is solved, the accuracy of ultrasound in serious vitreous lesion and intraocular tumor recognition is remarkably improved through a self-adaptive weighted integration mechanism, high-risk patient screening and clinical decision making are supported, and the application scene of ultrasound in ophthalmic diagnosis is expanded.

A method for creating a 3D point cloud map includes acquiring image frames from an image frame sequence of an external environment captured by a target camera of a vehicle. The method further includes processing the image frames using a feature point recognition model to identify a set of feature points in the image frames, along with a corresponding set of descriptors for the feature points. The feature point recognition model is a neural network model trained using a plurality of sample images of a same scene under different lighting intensities. The method further includes creating the 3D point cloud map of the external environment based on the set of descriptors. The method enables the obtained descriptors to include more image information, and further allows for an extraction of more matching feature points from the image when there are changes in lighting or view.

The invention provides an identification card preparation method, identification card printing equipment and a storage medium, and the method comprises the steps: obtaining a plurality of to-be-printed images for preparing a target identification card, the plurality of to-be-printed images being a plurality of first images with the same style but different contents, or a plurality of third sub-images formed by splitting a second image, and then obtaining a plurality of to-be-printed images for preparing the target identification card, the method comprises the following steps: firstly, processing each to-be-printed image to obtain a plurality of target images, then, sending each target image to a corresponding laser printing component, and finally, concurrently controlling each laser printing component to print the corresponding target image on a to-be-printed certificate card to obtain a target certificate card, so that when a plurality of certificate cards need to be printed, the target certificate card is printed on the to-be-printed certificate card. By means of the technical scheme, parallel printing of multiple images corresponding to multiple cards can be achieved through the multiple laser printing components, when a single card needs to be printed on the device, the multiple laser printing components can conduct regional parallel printing on a single image corresponding to the single card, and the card image printing efficiency is improved.

The invention provides a multi-medical image encryption method with tampering localization capability, and aims to solve the problems of security and integrity of digital medical images in transmission and storage, and the core is to provide localized tampering prevention capability. According to the method, firstly, a novel two-dimensional S-type logarithmic chaotic mapping 2D-SLCM is utilized to generate a secret key and a chaotic sequence which are highly related to plaintext content so as to resist differential attacks; then, performing efficient compression on each medical image by adopting a block compressed sensing (BCS) technology to ensure the transmission efficiency; in the encryption stage, data confidentiality is ensured through a multi-layer encryption process including local binary tree traversal scrambling and global random block scrambling; most importantly, an encrypted unique digital watermark is embedded into each image before the images are merged; the dual mechanism not only can detect the tampering behavior, but also can accurately identify which image in the multi-image set is damaged by verifying the watermark extracted from each image, thereby ensuring the reliability of residual data.

Aspects of the subject technology may provide time-synchronized image frames from multiple cameras to various system and / or application processes running on an electronic device. In one or more implementations, a frame identifier may be determined for each image frame from each camera based on a system pulse associated with the capture of the image frame. By generating frame identifiers based for images from multiple cameras based on a centralized source such as the system pulses, subsequent processes can immediately identify images from multiple cameras having the same frame identifier for co-processing of those images.

The invention discloses a gradient-guided panchromatic sharpening method for unlocking spatial textures, which comprises two image processing branches: a guide feature extraction branch for capturing gradient features from gradient amplitudes and generating auxiliary gradient features grads and refined guide gradient features Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr, Gsr and Gsr; gradient features extracted from gradient amplitudes can provide complementary information to promote optimization and improve the overall performance; one branch is a gradient-guided fusion branch, the other branch is a gradient-guided fusion branch, PAN and MSI are combined with extra information of gradient features, and in the fusion branch, a multi-image cross attention module is designed to gradually integrate image features with different spectral bands and resolutions, so that the PAN and MSI fusion process is effectively guided, and the panchromatic sharpening performance is remarkably improved.

The application relates to the fields of information security and image processing, and discloses a multi-image parallel encryption processing method based on an improved chaotic mapping, which comprises the following steps: separating and stacking each color channel of multiple images to be encrypted to construct a three-dimensional pixel matrix; extracting a matrix hash digest to be converted into a sub-key; inputting the sub-key into an improved chaotic mapping model of a historical state variable to iteratively generate a scrambling and diffusion sequence; performing sorting scrambling on the three-dimensional matrix in multiple orthogonal dimension sections by using the sequence; mapping the sequence into a shift step length to perform a cyclic shift and a bitwise XOR linkage diffusion on the pixels; and finally, outputting ciphertext images by segmentation. The application breaks the physical isolation of a single image to realize spatial depth mixing by constructing a three-dimensional matrix and performing cross-dimension scrambling; the chaotic dynamics degradation under limited precision is overcome by means of a historical state delay; and the efficiency of multi-image encryption and the system attack resistance are improved by using a shift and XOR linkage to realize bit-level depth confusion.

This application relates to the field of image detection technology, specifically to a method, device, and system for pedestrian trajectory tracking across cameras. Specifically, it includes: dividing a surveillance image into far-field, mid-field, and near-field regions; analyzing the imaging characteristics of moving pedestrians in different regions to construct regional change coefficients for far-field and near-field regions at different time periods; constructing motion change influence coefficients for each region by analyzing the pixel feature changes of clusters within the surveillance image during pedestrian movement and the grayscale changes of each pixel over time; determining the tracking region in each far-field and near-field region based on the regional change coefficients and motion change influence coefficients; reducing the hard threshold for denoising in the tracking region and mid-field region to retain more image details, thereby performing pedestrian trajectory tracking; avoiding the problem that traditional denoising algorithms use the same denoising parameters for the entire image, which may smooth the pedestrian's features during denoising, affecting the accuracy of pedestrian recognition.

The invention provides a multi-image array splicing method for a large cement prefabricated part, and the method comprises the following steps: 1, collecting an original image of the cement prefabricated part, carrying out the region division of the original image, carrying out the gray adjustment of each region, and obtaining a preprocessed image; 2, searching feature points between every two adjacent images in each row in the images, identifying and extracting key feature points in the images through an SIFT algorithm, matching the key feature points of the adjacent images through a feature point matching algorithm KNN algorithm, and determining a relative position relationship between the key feature points; 3, searching feature points between every two adjacent images in each column, and matching the feature points; and 4, calculating the boundary position of each image in the splicing area, and then splicing. According to the invention, high-precision splicing of the cement prefabricated components is realized, the appearance detection precision of the subsequent cement components can be effectively improved, and the product detection quality is improved.

To provide an information processor, an information processing method and a program for improving the efficiency of the whole tree diagnostic task while accurately acquiring data related with tree diagnosis at a job site.SOLUTION: The information processing apparatus 10 includes a reception unit 113 that receives diagnosis data including a plurality of pieces of image data and a plurality of pieces of sound data related to a tree to be diagnosed from the worker terminal 30 and registers the diagnosis data in a storage unit, a provision unit 110 that provides the diagnosis data to the diagnoser terminal 40, an acquisition unit 114 that acquires a diagnosis result regarding the soundness of the tree from the diagnoser terminal 40, and an output unit 115 that outputs the diagnosis result.SELECTED DRAWING: Figure 2

The invention belongs to the technical field of image processing, and particularly relates to a multi-image sensor image acquisition alignment method and system and a medium, and the alignment method comprises the steps: correcting the coordinate data of an image to be corrected to reduce the spatial deviation of the image to be corrected relative to a reference; the sequence of the corrected image coordinate data is adjusted, and the corrected image coordinate data and the to-be-corrected image coordinate data are made to be the same in sequence according to the mapping relation between the corrected image coordinate data and the address; the corrected image coordinate data is cached to the minimum pixel row, and down-sampling is started to form an aligned image; according to the invention, the correction logic of the correction formula is utilized, and the line number of the image coordinate data occupied in the corresponding originally collected image is obtained through the first line of image coordinate data of the corrected image by utilizing the correction formula in a back-stepping manner, so that the delay time of image correction and output is reduced, the image processing speed is improved, and the real-time performance of image correction is improved.