325 results about "Body images" patented technology

The invention discloses a hydraulic engineering dam body crack detection method and system based on machine vision, and relates to the technical field of computer vision. A high-definition camera is used for shooting a dam body image, obtaining a sample data set, extracting feature parameters of different noise types, and constructing a feature database; filtering the current dam body image to obtain a first dam body image, enhancing the crack gray scale difference of the first dam body image, obtaining a second dam body image, segmenting the second dam body image, screening candidate cracks in the crack image, and identifying real cracks according to the edge features of the candidate cracks. According to the method, a feature database is constructed, a targeted dam body image processing flow is combined, a high-definition camera collection and automatic processing flow is used, filtering parameters are dynamically adjusted by constructing the feature database, gray level enhancement and precise segmentation are combined, real cracks are precisely recognized through edge feature analysis and comparison, and quantitative parameters are output; and a reliable basis is provided for dam body safety assessment.

The invention relates to the field of train informatization, in particular to a train running state evaluation system based on data analysis. The train braking stress diffusion abnormal tendency value is determined by setting the braking information responding to the train, calling the train body image of the corresponding braking time period, extracting the train shaking characteristics and combining the discrete difference of the loads of all the carriages in the braking time period, and then the data time period type is marked. And the data in the time period is classified, uploaded and stored according to different marks, so that the real-time bandwidth requirement is reduced. According to the invention, the inter-wheel temperature difference characteristic and the in-wheel temperature difference characteristic of each wheel are considered and extracted, the wheel end abnormal risk characterization value is calculated and compared with the early warning threshold value, and the wheel end data is analyzed in a targeted manner, so that the data processing efficiency of a large amount of train data is improved, the real-time communication bandwidth demand is reduced, and the identification accuracy is improved.

The invention provides an auxiliary rehabilitation teaching system and method based on somatosensory interaction, and the method comprises the steps: determining an initial motion track of a target user during somatosensory interaction, capturing a body image of the target user during somatosensory interaction through a depth camera, determining skeleton points with the positions changed in the body image, and obtaining the skeleton points with the positions changed in the body image; performing drift compensation on the initial movement track based on the dynamic drift features of all skeleton points to obtain an actual interaction movement track when the target user performs somatosensory interaction; based on a standard rehabilitation action matched with the rehabilitation training action when the target user performs somatosensory interaction, performing deviation recognition on the interaction motion track to obtain a posture deviation degree between the rehabilitation training action and the standard rehabilitation action; and generating a feedback adjustment instruction of the target user in the somatosensory interaction process based on the posture deviation degree. By adopting the scheme of the invention, the drift error of inertial sensing can be corrected through the depth camera in the somatosensory interaction process so as to improve the motion capture precision of the auxiliary rehabilitation teaching system.

The invention discloses a driver fatigue state detection system based on computer vision processing. The system comprises a facial feature extraction unit which selects a high-definition camera to capture a driver facial image; the upper body feature monitoring unit collects upper body image data through a high-definition camera to accurately extract the action frequency of the upper body; the hand-held steering wheel characteristic monitoring unit is used for sensing pressure applied by hands of a driver by arranging a grip strength sensor on a steering wheel through a protective sleeve; the data processing unit receives data information collected by the facial feature extraction unit, the upper body feature monitoring unit and the handheld steering wheel feature monitoring unit for feature fusion; the fatigue state judgment unit judges the fatigue state of the driver according to a preset fatigue judgment rule; the face blinking frequency is combined with multi-dimensional information such as the upper body action frequency and the grip strength, the state of a driver can be reflected from different angles, richer and more comprehensive data support is provided for fatigue judgment, and the fatigue state can be judged more accurately.

The invention discloses a fish tank dynamic interaction display device based on position detection and an interaction implementation method. Belongs to the technical field of intelligent aquarium equipment and digital interaction and collects fish body images in real time, a control screen supports touch and voice interaction, and a background display screen dynamically updates display content according to the position of a fish body. The control processing hardware module integrates a microprocessor, a real-time digital graphic processing chip and an artificial intelligence processing unit, and image correction, multi-fish body detection tracking, coordinate mapping and dynamic background rendering are achieved. The method comprises the steps of image acquisition, geometric correction, position detection, coordinate mapping, dynamic rendering, cross-device linkage and the like, and supports gesture interaction, AI background generation and multi-fish tank linkage functions. Through combination of real-time position detection and a dynamic display technology, immersive interactive experience of fish moving and scene following is constructed, the problem that a traditional fish tank is insufficient in interactivity is solved, and the fish tank is suitable for families, commercial display and other scenes.

The invention discloses a defect detection method and device based on a dynamic dual-threshold template, and a storage medium, and aims to improve the defect detection precision of an image shot by a display screen. Collecting a plurality of batches of defect-free sample images of the target model display screen; counting gray extreme value boundary data of each pixel point on the plurality of batches of defect-free sample images; and generating a lower limit standard template and an upper limit standard template according to the gray extreme value boundary data. And obtaining a regional difference amplification coefficient and a compensation offset. And generating a dynamic detection threshold template for the lower limit standard template and the upper limit standard template through the regional difference amplification coefficient and the compensation offset. And obtaining a to-be-tested screen body image of the target model display screen. And carrying out pixel-level difference on the to-be-detected screen body image and the dynamic detection threshold template to generate a defect mask image. And performing defect detection on the display screen through the defect mask image to generate a first defect detection result.

The invention relates to the technical field of image style migration, in particular to a portrait-based controllable style migration and image art enhancement method and system, and the method comprises the steps: carrying out the preprocessing of an obtained content image, enhancing the contrast and definition of the image, and obtaining a preprocessed image; based on a preset image segmentation model, pixel-level semantic segmentation is carried out on the preprocessed image, and a figure main body image is output; obtaining style information, based on a preset style generation model, performing style migration on the character main body image according to the style information, and generating a stylized character image; obtaining a target style image, and fusing the figure image and the target style image based on a preset ComfyUI workflow to obtain a final processing image; the image processing method and the image processing device have the advantages that on the premise of high customization flexibility, the quality of the image after style migration is improved, and the coordination between the portrait main body and the background is improved.

The invention discloses a vehicle body type distinguishing method and device based on an intelligent camera and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring a vehicle body image; segmenting a vehicle body area in each vehicle body image to obtain vehicle body features, and establishing a multi-dimensional feature vector; if it is determined that the similarity between the multi-dimensional feature vector and the target image feature is greater than a preset similarity threshold, determining a target vehicle body type corresponding to the to-be-identified vehicle body as a vehicle body type corresponding to the target image feature; determining a plurality of derived types corresponding to the target vehicle body type and corresponding image feature subsets; performing secondary segmentation on the vehicle body image according to the image feature subset to obtain corresponding local features; matching the local feature with each image feature subset to obtain a target derived category; and according to the target vehicle body type and the target derived type, adjusting production parameters corresponding to the to-be-identified vehicle body. By implementing the technical scheme provided by the invention, the accuracy of vehicle body type identification on the production line is improved.

The invention discloses a large model-based large yellow croaker growth stage feeding amount evaluation method and system, and belongs to the field of aquaculture, and the method comprises the steps: collecting underwater images of a fish pond in a plurality of shooting directions at the same time, and recognizing and segmenting a fish body image corresponding to each entity fish in each underwater image; determining the distance between an entity fish corresponding to the fish body image and a camera for collecting the fish body image, and extracting fish body appearance features of the fish body image; randomly selecting a fish body image from each shooting direction to form a fish body image association combination, and screening a second fish body image association combination from all possible fish body image association combinations according to the distance and fish body appearance features; and constructing three-dimensional point cloud data of the entity fishes according to the second fish body image association combination, fitting three-dimensional body shape parameters of the entity fishes through the three-dimensional point cloud data, and determining the final feeding amount of the fish school according to the three-dimensional body shape parameters of the entity fishes. According to the invention, the problem of low accuracy of the real-time feeding amount of the fish school can be solved.

The invention relates to a motion function data acquisition method and system based on human-computer interaction. The motion function analysis method is applied to a motion function analysis device and comprises the steps that in response to an initial position instruction of an abnormal object, initial motion analysis is conducted based on historical treatment data of the abnormal object, and initial motion data is presented; when the corresponding initial body image is detected, pose analysis is executed, and a body condition labeling box is displayed to a labeling person. After annotation confirmation is received, carrying out movement analysis in combination with annotation data and historical treatment data, and outputting action change data; and if the current body image corresponding to the current body image is detected, taking the current body image as a new initial image, and repeating the pose analysis and labeling process. And until an annotation stop instruction is received, the system summarizes each annotation and historical treatment data to carry out object function analysis, and motion function data of the abnormal object is generated. By adopting the method, the accuracy of understanding the current abnormal information of the abnormal personnel can be effectively improved.

The invention discloses a glass bottle defect detection method, which belongs to the technical field of defect detection, and comprises the following steps: labeling defect areas for all images and adding corresponding defect labels to obtain a first preprocessed image with the defect areas and the defect labels; respectively adopting corresponding pre-training models for a first pre-processed image in the bottle body image library, a first pre-processed image in the bottle opening image library and a first pre-processed image in the bottle bottom image library, taking the first pre-processed images as input, and outputting a predicted defect area and a predicted defect label, incremental learning is carried out on the corresponding pre-training models, and detection models corresponding to the bottle body, the bottle opening and the bottle bottom are obtained respectively; and respectively inputting the newly obtained images into the corresponding detection models to obtain corresponding defect labels, defect areas and confidence coefficients. The glass bottle defect detection method solves the problem that at present, different parts need to be detected at different times, and rapid detection of the glass bottle is difficult to achieve.

The invention discloses a commodity marketing picture and video generation method and device, equipment and a medium. The method comprises the following steps: receiving an input commodity image and description information provided by a user; carrying out preprocessing and main body segmentation on the commodity image to obtain a commodity main body image; based on the commodity main body image and the user description information, commodity content understanding is carried out through a multi-modal model, a structured commodity semantic tag is generated, and the commodity semantic tag comprises the category, the visual feature and the key attribute of the commodity; and on the basis of the commodity semantic label, creative content generation and automatic typesetting processing are carried out through a multi-modal model, and a commodity marketing image containing a background, an advertisement copywriting and decoration elements is generated. According to the method, the tedious process needing multiple stages, multiple tools and repeated manual intervention is integrated into a highly-automatic end-to-end process, the manufacturing efficiency of commodity marketing materials is improved, meanwhile, the requirement for professional skills of a user is lowered, and the consistency of the visual context, style and brand is guaranteed.

A detection and identification system includes a display portion, an image-taking portion, and a protective clothing detection portion. The image-taking portion captures a full-body image of a person wearing protective clothing. The display portion displays the full-body image in real time. The protective clothing detection portion divides the full-body image into plural to-be-identified regions according to the joints of the human body, uses an anomaly detection method or semantic segmentation algorithm to determine whether each to-be-identified region meets detection criteria, and marks the to-be-identified regions in such a way that each to-be-identified region meeting, or failing to meet, the detection criteria is displayed by the display portion as marked with a first mark or a second mark respectively. The first and second marks are different-colored blocks or frames. The system allows the current condition of the protective clothing to be rapidly known so that appropriate handling measures can be taken.

The invention discloses a financial user identity recognition method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence and biological recognition or other related fields, and the method comprises the steps that a first image and a second image of a target financial user are obtained, the first image is a user whole body image collected by a target teller machine, and the second image is a user whole body image collected by a target teller machine; the second image is a certificate image uploaded by the target financial user through a target teller machine; positioning a face region of the target financial user in the first image by adopting a target detection algorithm, and extracting a face feature vector in the face region; performing text recognition processing on the second image to obtain an identity information text of the target financial user; and performing associated identity recognition based on the facial feature vector and the identity information text to obtain a recognition result, and returning the recognition result to the target teller machine for financial service processing. Through the method and the device, the technical problem of low user identity recognition accuracy of a financial institution in related technologies is solved.

A system is provided.SOLUTION: A system, comprising: means for inputting height data; means for uploading a whole body image; means for selecting product data; means for transmitting the height data and the whole body image to a server; means for generating a list of available products and transmitting the list to a terminal; means for transmitting data of a selected product to the server; means for synthesizing an image of the product with the whole body image at an appropriate size and position to generate a fitting image; and means for transmitting the generated fitting image to the terminal.SELECTED DRAWING: Figure 1

Described are systems and methods to determine one or more regional body composition values for one or more regions of a body based on a processing of one or more two-dimensional images that include a representation of the body. Regional body composition values may include any of a fat tissue mass, a lean muscle mass, a bone mineral density, a skeletal muscle mass, etc., which may be determined for any one or more regions of the body, such as the right arm, left arm, right leg, left leg, trunk, android, gynoid, etc.

The invention discloses a vehicle seat adjusting device and method, electronic equipment and a storage medium, and relates to the field of vehicle seat control, and the device comprises an image collection module which is used for collecting a whole body image of a person in a vehicle; the visual algorithm processing module is used for receiving the whole-body image and judging the height of a person in the vehicle through a visual algorithm, and the visual algorithm comprises the steps that the whole-body image is preprocessed; recognizing a human body region in the image through a human body detection algorithm, wherein the human body detection algorithm is a convolutional neural network model based on deep learning; the visual algorithm processing module is used for extracting feature points in a human body area, the ergonomic data storage module stores an optimal seat angle database corresponding to different heights, and the seat adjusting control module is used for calling the corresponding seat angle in the database according to height data output by the visual algorithm processing module and adjusting the seat angle according to the height data. And the electric adjusting mechanism is controlled to execute an adjusting action.

The invention discloses a defect extraction method and device for a display screen image and a storage medium. The defect extraction method and device are used for reducing the situation that the defect detection precision is reduced due to shadows. Obtaining a screen body image, and determining a target area; performing image segmentation precision analysis on the screen body image; correcting the screen body image; four dynamic array coordinate arrays are generated for the target area, shadow removal processing is carried out according to the four dynamic array coordinate arrays, a shadow-removed screen body image is generated, and the four dynamic array coordinate arrays are the end row and column arrays of the single segmented image area to be divided; carrying out interpolation calculation on pixel points of the corner area of the screen body image subjected to shadow removal; constructing an adaptive spatial filtering kernel matrix, and performing convolution enhancement operation on the adaptive spatial filtering kernel matrix and the shadow-removed screen body image; carrying out threshold value clamping control processing on the screen body image without the shadow, and processing and integrating a defect area through gray scale morphology; and performing defect feature extraction and analysis on the screen body image subjected to shadow removal.

The embodiment of the invention provides a wallpaper setting method, terminal equipment and a storage medium, and relates to the field of terminal equipment. The method comprises the following steps: displaying a wallpaper preview interface in response to a click operation on a synthetic wallpaper control; in response to a click operation on the wallpaper selection control, displaying a first option and a second option; determining a first image in response to a selection operation on the first option; performing main body extraction on the first image to obtain a target main body image, and displaying the target main body image on the wallpaper preview interface; determining a second image in response to a selection operation on the second option; determining a superposition area in the second image based on the target main body image; generating a target image according to the target main body image and the overlapping area, and displaying the target image; and in response to a click operation on the wallpaper application control, setting the target image as wallpaper. In the wallpaper generation process, the number of times of man-machine interaction is increased, and the sense of participation of the user is improved.

The invention provides an intelligent inspection method for harbor container body damage. The method comprises the steps of S1, judging whether a container transport vehicle exists in a designated position of the view of each camera or not, and if yes, turning to the step S2; if not, returning to the step S1; s2, controlling each camera to zoom the focal length to shoot the container transport vehicle in different directions so as to obtain container body images of different surfaces of the container body; s3, identifying each box body image to obtain box number information, and transmitting each box body image to an identification server for box body damage identification to obtain a corresponding damage identification result; and S4, the container number information and the damage identification result are linked with a tallying platform, and a worker at the gate is prompted to carry out manual intervention or release. The beneficial effects of the invention are that the system can achieve the automatic and intelligent container defect detection, and improves the defect detection efficiency and accuracy.

The invention discloses a method and system for recognizing the sleeping posture of a user by an intelligent pillow, and relates to the technical field of sleeping posture recognition methods, and the method comprises the steps: determining an image of the head of the user according to the division of a current sleeping image of the user; the head sleeping posture coefficient of the head of the user to the intelligent pillow is determined according to the image of the head of the user and the spatial positions and the regional forms of the multiple sub-regions, and the accuracy of the head sleeping posture coefficient is improved. Therefore, the image of the body is determined according to the division of the current sleep image of the user, and the sleeping posture coefficient of the upper half part of the body and the sleeping posture coefficient of the lower half part of the body are determined based on the recognition of the image of the body; in the intelligent pillow, the current sleeping posture of the user is determined based on the sleeping posture coefficient of the head, the sleeping posture coefficient of the upper half part of the body and the sleeping posture coefficient of the lower half part of the body, the accuracy of the current sleeping posture of the user is guaranteed, the intelligent pillow and cameras on the peripheral sides are fully utilized, and cooperative control over the intelligent pillow and the cameras on the peripheral sides is achieved.

This invention discloses a method and system for controlling submarine cable laying trajectory based on plow body state perception. The method includes: acquiring real-time state images of the plow body in the seabed operating environment to generate a plow body attitude distribution image; extracting feature point sets of the dynamic region of the plow body based on a preset plow body feature localization method; obtaining distribution information from the feature point set to the stable attitude region and correcting the feature point set; and comparing the plow body trajectory region by partitioning the corrected feature point set to obtain trajectory optimization information. The system includes plow body image processing, feature localization, feature correction, and partition comparison modules to generate stable or dynamic adjustment commands, achieving precise control of the plow body trajectory. This invention effectively optimizes the submarine cable laying trajectory by real-time perception of the plow body state, improving operational accuracy and stability.

The invention provides an image processing method, vehicle-mounted equipment and a storage medium. The method comprises the following steps: acquiring an upper vehicle body image and a lower vehicle body image of an external vehicle; acquiring space coordinates of a plurality of vertexes of the target view plane; projecting each space coordinate to a coordinate system of the upper vehicle body image and a coordinate system of the lower vehicle body image to obtain a first projection coordinate and a second projection coordinate corresponding to each space coordinate; generating a first conversion matrix or a second conversion matrix according to the first projection coordinate and the second projection coordinate corresponding to each space coordinate; converting the upper vehicle body image according to the first conversion matrix to obtain a first conversion image, or converting the lower vehicle body image according to the second conversion matrix to obtain a second conversion image; and generating a complete vehicle body image of the external vehicle according to the first conversion image and the lower vehicle body image, or the second conversion image and the upper vehicle body image. According to the invention, a complete vehicle body image can be generated, so that a detection result and a vehicle tracking effect are ensured.

The application relates to a kind of body image matching network assisted internal three-dimensional deformation field measurement method, belong to deformation measurement field.The application implementation method is: in reference body image, define calculation region and calculation voxel point;Using three-dimensional body image feature extraction network, key three-dimensional features are extracted simultaneously.Using three-dimensional feature matching network, key three-dimensional features are matched.From matched three-dimensional feature point pair, the feature point pair in the preset three-dimensional neighborhood range around each calculation voxel point is extracted, and the three-dimensional deformation initial value of the calculation voxel point is calculated when more than four groups of feature point pairs are judged;Less than 4 groups are directly assigned using the deformation initial value of other successfully calculated points with the spatial position of the calculation voxel point nearest to the interpolation or, as the three-dimensional deformation initial value of the point.Using three-dimensional reverse combination Gauss-Newton nonlinear iterative optimization method, high-precision internal three-dimensional deformation field measurement value is calculated, that is, internal three-dimensional deformation field measurement is realized.

The invention relates to the technical field of smart home and visual identification, in particular to an intelligent dressing mirror system based on non-inductive interaction and a clothes collecting method, and the intelligent dressing mirror system comprises a dressing mirror body which is used for displaying a whole-body mirror image picture of a user; the intelligent acquisition communication module is mounted on the dressing mirror body and is used for sensing a human body and acquiring an original image including a whole-body image of a user; and the cloud server communicates with the intelligent acquisition communication module and is used for analyzing and processing the acquired whole body image of the user and pushing a result to a mobile terminal of the user. Through the system architecture of hardware collection, cloud computing and mobile phone terminal interaction, the problems that an existing intelligent mirror is high in cost and poor in privacy, and traditional APP clothes input is tedious are solved.

A three-dimensional (3D) digital image of an individual patient marked with target therapeutic locations on a skin surface of the patient is used for locating those treatment locations on a patient's skin for fascial manipulation and other treatments. The 3D image may be obtained by merging an unmarked 3D digital patient model image converted from a 2D optical image with a “generic” musculoskeletal digital model having optimized target therapeutic locations distributed over a skin surface thereof. The generic musculoskeletal digital model may be obtained from a library of such images.

The invention provides a coaxial telecentric imaging tinplate can defect identification method and system, and relates to the technical field of defect identification, the system is composed of a coaxial telecentric camera assembly, a polarization multispectral light source assembly and an image processing and control unit, and can body images with constant magnification are obtained through a telecentric lens and coaxial illumination; a switchable cross-polarization visible light and near-infrared light source is used for synchronously collecting multi-modal images, and separation and difference are carried out on different polarization and wave band images to obtain a specular reflection component image, a diffuse reflection component image and a multi-spectral difference image. The image is divided into a character area, a pattern area and a bottom color area according to the format of the can body, comprehensive judgment is conducted through character comparison, a lightweight neural network and defect area connectivity analysis, automatic recognition of defects such as scratches, through printing and smudginess is achieved, and the accuracy and stability of appearance detection of the tin can on a high-speed production line can be improved.

The invention discloses a super-endurance multifunctional display device, system and application. The system comprises an image acquisition module, a weight data acquisition module, a processing module, a display module and a power supply module. The processing module calculates health index parameters based on the body image data and the weight data, calls an AI model to construct a 3D human body model, and generates reminding information when indexes are abnormal; meanwhile, responding to a scene selection instruction, recommending virtual clothes and ornaments from the electronic wardrobe, and displaying a fitting effect in a virtual scene; and multi-user interaction is supported, and other user terminals can be accessed for synchronous display and real-time discussion. The power supply module adopts at least two independently detachable battery units and an automatic switching circuit, monitors the electric quantity and automatically switches. According to the invention, precise health management reminding, immersive fitting experience, social interaction promotion and super-long battery life are realized.

The invention relates to the technical field of vehicles, in particular to a vehicle control system and a vehicle. The control system comprises an image acquisition module, a vehicle-mounted computing platform and a central domain controller, based on the control system, a body image of a vehicle target object is acquired, based on a built-in image processing module, the body image is recognized, and the height and the leg length of the target object are obtained; after a mapping relation model of the height, the leg length and the pedal height is called to determine the pedal height corresponding to the height and the leg length, a pedal control instruction is generated based on the pedal height and sent to a driving mechanism of a target pedal. According to the method and the device, the target pedal is automatically adjusted and unfolded to the matched height, so that personalized adaptation to passengers is realized.

The invention provides a visual field depth expanding method based on sparse scanning of a light field microscope, which comprises the following steps of: performing sparse scanning on a sample in X, Y and Z axial directions by utilizing a micro-lens array light field imaging system, enabling the overlapping rate between adjacent visual fields to be lower than a preset value, and acquiring multi-visual-field two-dimensional original light field data; performing pixel rearrangement and deconvolution three-dimensional reconstruction on the two-dimensional original light field image of each view to obtain a reconstructed three-dimensional body of each view; calculating the theoretical overlapping region width in the XYZ axial direction according to the sparse scanning step length, and carrying out consistency calibration on the overlapping region in the XYZ axial direction of the adjacent visual fields; and carrying out recursive fusion on the calibrated reconstructed three-dimensional body along the X, Y and Z axial directions to obtain a full-view-field and full-depth-of-view three-dimensional body image. According to the invention, not only can a larger imaging depth range be provided, but also the image definition at different depth levels can be ensured, and the inherent depth-of-field limitation of a traditional optical system is overcome.