24 results about "Image motion" patented technology

This invention discloses a license plate recognition method and system for a parking lot patrol robot based on dynamic visual compensation, belonging to the field of data processing technology. The method includes: predicting the transient stationary point of chassis vibration based on motion posture data sequence to trigger license plate image acquisition; calculating motion blur vectors by combining angular velocity data and imaging intrinsic parameters to generate a spatial variation degradation kernel; using this kernel to perform non-uniform deblurring on the license plate candidate region, extracting and fusing the restored texture features and original topological features, and outputting the license plate recognition result and confidence level; calculating visual degradation parameters based on the blur vector length and confidence level, triggering deceleration and initiating hysteresis hold-up period control when the parameter exceeds a threshold. This invention solves the technical problems of non-uniform image motion blur caused by vibration and rotation in dynamic inspection and frequent control oscillations caused by single feedback, effectively improving the accuracy and operational stability of the robot's license plate recognition.

The application discloses a two-axis two-frame roll-pitch configuration photoelectric detection equipment control system and method, and belongs to the field of photoelectric detection equipment. The system comprises a power supply, an image controller, a servo controller, an outer frame, an outer frame roll motor, a first code disc, an outer frame slip ring, an inner frame, an inner frame pitch motor, a second code disc, a first gyroscope, a second gyroscope and a camera. An angle instruction is sent from a display control console to the servo controller and the image controller. The servo controller performs angle conversion, position loop control, roll rotation direction judgment and speed loop control, and outputs a signal to drive the motor. The code disc measures real-time angle information of the motor and sends the information to the servo controller. The gyroscope measures real-time angular velocity information of the camera and sends the information to the servo controller. The image controller receives a roll angle to perform electronic image stabilization, outputs an image to the display control console, and sends an image deviation to the servo controller when tracking a target. The image motion direction is consistent with the azimuth and pitch direction in the base coordinate system, and the human-computer interaction comfort is improved.

The present application relates to the field of optical remote sensing, and more particularly to a space camera off-track image motion test and compensation ground test device and test method thereof, the method comprising: fixing a TDICMOS camera on a three-dimensional turntable and pointing its optical axis to a drum target; determining a push-scan direction image motion speed according to the line frequency and pixel size of the TDICMOS camera; determining an image motion speed perpendicular to the push-scan direction based on a preset angle between the push-scan direction image motion speed and the push-scan direction of the detector; using the object-image relationship to inverse the target motion speed of the drum target; controlling the rotation of the drum target and driving the three-dimensional turntable to perform a pitch compensation motion to eliminate image motion mismatch; and acquiring off-track scanning images in a dynamic process. The present application uses a drum rotation to simulate the motion of a target, is not limited by the refresh frequency of a display screen, can effectively match the test requirements of a high line frequency TDICMOS camera, and realizes ground verification of the off-track scanning image motion compensation effect.

The present application relates to the technical field of artificial intelligence, and more particularly to an AI interaction system for ornithological scientific research, which comprises a collection unit, a trigger determination unit, a path determination unit, a dominant determination unit, a prompt generation unit and an adjustment unit. The present application constructs a multi-level behavior determination process through joint analysis of bird song spectrum, image motion characteristics, flight trajectory and environmental factors, and through statistical analysis of the time distribution and spatial distribution of these behavior indicators within a preset period, and correlation analysis with environmental factors such as temperature, humidity, wind speed and illumination, the influence of environmental changes on bird activity frequency and spatial aggregation degree can be identified, so that the acoustic trigger threshold can be dynamically adjusted, so that the system can continuously maintain the sensitive recognition ability of bird activity with the change of the habitat environment, and then realize high-reliable behavior recognition and interaction prompt for ornithological scientific research.

The application relates to the technical field of image acquisition and processing, in particular to a skin fine texture acquisition method and system, wherein four light sources L1 to L4 are uniformly and sequentially arranged around the center line of a camera lens, each light source has at least three channels C1 to C3 and emits light rays to the same skin area to be acquired; a positive direction image and a negative direction image are acquired; images in the same coordinate axis direction are subjected to difference value operation to obtain gradient images in three directions; the gradient image gray values in the three directions are normalized to obtain normal line values in three channels; the normal line values in the three channels are converted to be respectively loaded into a normal line map three channel and output the normal line map; the positive direction image light source lighting mode comprises L1 and L2 lighting C1 and C2, the negative direction image light source lighting mode comprises L3 and L4 lighting C1 and C2, and C3 of the four light sources is all lighted in the positive direction image or the negative direction image, so that the image motion blur probability is reduced.

A vehicular vision system includes a camera that captures image data. The vehicular vision system, responsive to processing by an image processor of image data captured by the camera, detects a plurality of objects present within the field of view of the camera. The vehicular vision system, responsive to detecting the objects, generates a plurality of intra-hypotheses. The vehicular vision system, responsive to generating the plurality of intra-hypotheses, generates a plurality of inter-hypothesis, with each inter-hypothesis (i) based on at least one of the intra-hypotheses and (ii) representing a respective detected object different from each other inter-hypothesis. The vehicular vision system, responsive to generating the plurality of inter-hypothesis tracks the detected object. The vehicular vision system, responsive to tracking the object, controls a driver assistance system of the vehicle.

The application provides a single-frame image motion deblurring method and device based on direction perception and diffusion refinement, wherein the method comprises the following steps: acquiring a single-frame blurred image, and estimating spatial motion blur parameters of the single-frame blurred image to obtain a blur direction, a blur length and a corresponding confidence degree of each pixel in the single-frame blurred image; performing direction regularization deconvolution on the single-frame blurred image based on the blur direction, the blur length and the confidence degree to obtain a coarse restoration image; inputting the coarse restoration image and the blur direction and the blur length into a pre-trained conditional latent space diffusion model to perform refinement processing to obtain a refined restoration image; and performing frequency domain angular consistency constraint on the refined restoration image to output a final restoration image. Through the estimation of the spatial motion blur parameters, the combination of the direction regularization deconvolution and the conditional diffusion refinement, and the introduction of the frequency domain angular constraint, the directionality artifacts are effectively inhibited, and the restoration quality is improved.

The RGB image acquisition unit (30) acquires an RGB image of the object. The ranging image acquisition unit (32) acquires a ranging image of the object along the same optical axis. The RGB image motion detection unit (40) detects movement in the RGB image for each pixel by taking the difference between the current frame and the previous frame. The ranging image motion detection unit (42) detects movement in the ranging image for each pixel by taking the difference between the current frame and the previous frame. The interference determination unit (50) determines whether there is infrared interference during the acquisition of the ranging image for each pixel based on whether there is movement in the RGB image and whether there is movement in the ranging image.

The application provides a high-precision generalized dynamic image motion compensation method, device, equipment and storage medium, six homogeneous coordinate transformation matrices between a geographic coordinate system and an image plane coordinate system are sequentially multiplied to form a total transformation matrix, and a multi-stage series kinematics mapping of a ground point to an image plane point is completely expressed in a single mathematical framework. A homogeneous position vector of the image plane point obtained by the total transformation matrix is directly derived with respect to time, so that each motion source and its cross-coupling effect are naturally included in an image motion velocity vector expression in an analytical form, and a truncation error caused by component separation and superposition is avoided. Accurate image motion velocity vector values are obtained by substituting real-time parameters into the expression, and then a deflection angle correction amount and a TDI charge transfer matching rate are solved to perform compensation.

This invention discloses a sequential image fusion enhancement method based on three-axis slide table displacement sensing, belonging to the field of machine vision technology. The method includes the following steps: S1, constructing discretized state and output equations to complete the three-axis slide table motion modeling, and establishing the correlation between motion parameters and image blur kernel and pixel position offset; S2, using the inverse function of the camera response function combined with Taylor linearization, performing exposure normalization processing on multiple frames of observed images to obtain scene illumination estimates with a unified radiance scale; S3, obtaining multi-dimensional fusion weights for the image by setting a fusion weight calculation mechanism that correlates the quality features of the fused image with the slide table position; S4, completing the fusion of multiple frames of images through a weighted fusion model to obtain a high-quality single-frame fused image. Using the above method, the problems of image motion blur and uneven multi-frame imaging quality caused by three-axis slide table motion are effectively solved, achieving accurate fusion and deblurring enhancement of sequential images.

The application discloses a kind of based on motion compensation time domain filtering method for image, comprising: using autoregressive moving average model to the obtained gyroscope error is modeled, the change rule of data is used to estimate model parameter, and gyroscope error model is established;Using the gyroscope data of removing error obtained by gyroscope error model, the rotation matrix of camera is calculated, and the rotation image is compensated in reverse using rotation matrix, and the de-rotation image is obtained.Through kalman filtering to image motion vector sequence, image random jitter is obtained, and the de-rotation image is compensated according to random jitter, and the stable image and the subjective motion vector of image are obtained;Using the motion target detection algorithm in difference map based on large map coordinate system to detect target in stable image.The application has high detection sensitivity, and can detect target and its trajectory quickly through a small amount of frame track correlation.

This application provides an image motion compensation method, apparatus, and electronic device. The method, applied to an electronic device, includes: drawing a first nonlinear motion trajectory based on the frame order and motion position of the previous N frames; determining the motion position of a predicted frame image with frame order N+1 on the first nonlinear motion trajectory based on the image frame rate of the electronic device; and determining a motion vector from the Nth frame image to the N+1th frame image based on the image information of the Nth frame image, the image information of the N+1th frame image, the motion position of the Nth frame image, and the motion position of the predicted frame image, provided that the image information of the predicted frame image after moving a first distance remains consistent with the image information of the N+1th frame image. This narrows the search range of the motion vector from the Nth frame image to the N+1th frame image, improves search efficiency, and enhances the rendering performance of sliding screens.

The application discloses an image registration method and device, a medical image motion correction method and system, equipment and a medium. The image registration method comprises the following steps: acquiring medical image data of a plurality of time points containing a target object; determining a motion artifact degree of the medical image data, and determining a plurality of frames of candidate image data according to a balanced position of the target object in the medical image data; selecting medical image data with the lowest motion artifact degree from the plurality of frames of candidate image data as registration reference image data; and performing image registration on the medical image data by using the registration reference image data. According to the two dimensions of the motion artifact degree and the balanced position, the application automatically selects the registration reference image, can avoid selecting an image with poor image quality as the registration reference image, can reduce the registration difficulty and cost, and can improve the quality and efficiency of image registration, and further proposes a quality control scheme for medical image motion correction.

The application relates to the technical field of image processing, and discloses an image dynamic and static area distinguishing method and device. The method comprises the following steps: performing feature extraction on at least one of a current image frame and a previous image frame in a time sequence change dimension, a spatial structure dimension and a motion dimension to obtain a local edge gradient feature map, an interframe difference feature map and a direction vector feature map; fusing the local edge gradient feature map, the interframe difference feature map and the direction vector feature map to obtain a cooperative feature map comprising a plurality of cooperative feature values; generating a dynamic judgment threshold based on the cooperative feature map, and comparing the plurality of cooperative feature values with the dynamic judgment threshold to obtain a three-value mask graph comprising a motion area, a static area and a transition area. The above method can significantly improve the dynamic and static area distinguishing accuracy and spatiotemporal consistency under complex illumination, low signal-to-noise ratio, camera jitter and a small motion scene.

The invention discloses a method for identifying the amount of motion of an image and electronic equipment, and relates to the technical field of terminals. The first image and the second image are sequentially compared according to pixel units such as a row or a column, the same pixel units in the first image and the second image are obtained, and the motion amount of the second image relative to the first image is obtained according to the same pixel units. When the pixel units are compared in sequence, after the pixel units are subjected to one-way hash coding, hash values corresponding to the pixel units are compared in sequence, and if the hash values are the same, the pixel units are determined to be the same pixel units. In this way, rapid and accurate comparison can be achieved, the calculated amount is remarkably reduced under the condition that accuracy is guaranteed, and the efficiency of recognizing the exercise amount is improved.

The application discloses a line-scan imaging cooperative control method and device under high-speed continuous relative motion, and belongs to the technical field of machine vision and image acquisition. The method acquires the relative motion speed in real time during the imaging process by presetting the axial space sampling interval threshold and the single-row space image motion threshold, cooperatively controls the trigger row frequency and the single-row exposure integration time, makes the axial space sampling interval and the single-row space image motion satisfy the constraint condition, and applies the consistency constraint to avoid exposure overlap. The device comprises a speed acquisition module, a parameter setting module, a trigger row frequency control module, an exposure integration time control module, a constraint control module and an imaging execution module. The application guarantees the space sampling sufficiency along the relative motion direction and the single-row imaging definition under the premise of not reducing the operation efficiency, effectively suppresses the missing scan and the motion blur, the control logic is intuitive and clear, the applicability is strong, and the engineering implementation is facilitated.

The present application relates to the technical field of digital image processing, and discloses a double-frame image motion blur removal method based on joint control of definition and motion, which acquires two time-adjacent images under the same scene, constructs definition distribution map and motion direction map after pretreatment, and obtains overall definition evaluation value based on direction consistency weighted statistics, so as to determine the image to be restored and the auxiliary reference image; further constructs joint confidence information of definition and motion, performs inter-frame motion estimation with blur perception, and divides adaptive blur area and non-blur area in combination with the definition distribution map and the motion estimation result; the main motion direction and the main motion amplitude are extracted in the adaptive blur area to construct the motion blur kernel, and the joint optimization objective function of the image to be restored and the motion blur kernel is established, the image to be restored and the motion blur kernel are updated through alternating iteration, and the final deblurring result image is output.

The application discloses a kind of wind power blade surface defect rapid detection methods, comprising the following steps: A1, wind power blade surface defect image acquisition: for wind turbine microcosmic inspection mode, four rotor unmanned aerial vehicle is used to the image acquisition of wind turbine blade surface, under the premise of fully considering unmanned aerial vehicle obstacle avoidance function, when unmanned aerial vehicle detects wind turbine blade, the distance between the two is generally maintained between 1 meter to 2 meters.The wind power blade surface defect rapid detection method solves the image motion blurring phenomenon generated when the unmanned aerial vehicle takes a photo of the wind power blade, reduces the influence of the image preprocessing caused by the deceptive targets such as stains, bird droppings and other deceptive targets on the wind power blade, and improves the clarity and fidelity of the scratch edge after image threshold segmentation.

This invention discloses a real-time correction method and system for motion artifacts in PET-CT brain metabolic images based on a large language model, belonging to the field of medical image processing technology. It acquires sequential images at a fixed frame rate, extracts key CT anatomical points and PET metabolic hotspot features; calculates the multimodal feature matching degree between the current frame and the reference frame based on a large language model, and identifies translational, rotational, or locally deformed motion frames; uses ICP registration for rigid motion and rigid-elastic hybrid registration for local deformation; calculates the Dice similarity coefficient, grayscale variance ratio, and artifact persistence index for quality assessment; and updates the identification threshold and registration parameters in a closed loop based on historical correction data. This invention achieves automatic real-time identification and hierarchical correction of single-frame motion, integrates multimodal features to avoid metabolic information loss, and has parameter iterative optimization capabilities, significantly improving correction accuracy and clinical examination efficiency.

The application provides a dynamic hand gesture recognition method and device based on motion compensation, and belongs to the technical field of human-computer interaction. The method aims to solve the problem of image blur caused by camera motion in a dynamic scene, which further causes the decline of gesture recognition accuracy. The method comprises the following steps: acquiring image data and motion data within an exposure time synchronously collected by a device worn on a user's limbs; determining a motion feature vector representing image motion blur according to the motion data; inputting the image and its corresponding motion feature vector into a multi-modal neural network model; in the feature extraction process, the model fuses the image features extracted from the image and the motion feature vector to compensate for the degradation of the image features caused by motion blur using the motion feature vector; and finally outputs hand gesture information based on the fused features.

This invention discloses a method and apparatus for detecting and warning of abnormal audio and video events in video glasses, belonging to the field of audio and video detection technology. The method and apparatus include: S1, collecting multi-source data from the video glasses, performing preprocessing, feature parsing and extraction, storing the data, and constructing an abnormal event database; S2, constructing a baseline and analyzing external disturbances using image motion features and action nearest neighbor vectors; S3, conducting audio-visual-inertial co-correlation and anomaly credibility assessment based on multimodal temporal synchronization data; and S4, performing early warning decision calculations based on anomaly handling sequence features. This solves the problem of false alarms and missed alarms caused by the inability to distinguish between everyday head movements, running voluntary movements, and external anomalies such as falls and collisions due to similar features in existing video glasses.

This invention relates to the field of airborne imaging technology, and more particularly to a dual-actuator cooperative command planning method for image shift compensation. Based on the image shift model of an airborne optical imaging system, the imaging parameter constraints of the airborne optical imaging system are converted into compensation parameter constraints for image shift compensation. Based on the compensation parameter constraints, compensation planning is performed for forward image shift and scanning image shift, corresponding to the total image shift compensation commands for forward and scanning image shifts. The main actuator and auxiliary actuator jointly perform image shift compensation on the airborne optical imaging system, and based on the motion saturation of the two actuators, the two total image shift compensation commands are allocated to the two actuators. This invention establishes a cooperative command planning method from imaging parameters to image shift compensation commands, and then allocates commands based on dual-actuator capability constraints. It fully utilizes the performance of active optics devices and is of great significance for improving the active control capabilities of airborne airborne optical imaging, such as image shift compensation.

The application relates to the technical field of digital image processing, and discloses a double-frame image motion blur removal method based on joint control of definition and motion, which acquires two time-adjacent frames of images under the same scene, constructs a definition distribution graph and a motion direction graph after pretreatment, and obtains an overall definition evaluation value based on direction consistency weighted statistics, so as to determine a to-be-restored blurred image and an auxiliary reference image; further, joint confidence information of definition and motion is constructed, inter-frame motion estimation of blur perception is carried out, and adaptive blur areas and non-blur areas are divided in combination with the definition distribution graph and the motion estimation result; a main motion direction and a main motion amplitude are extracted in the adaptive blur area to construct a motion blur kernel, a joint optimization objective function of the to-be-restored clear image and the motion blur kernel is established, the to-be-restored clear image and the motion blur kernel are updated through alternating iteration, and a final deblurring result image is output.

The application discloses a dynamic focus target detection method and system for an automatic driving vehicle, relates to the technical field of automatic driving, and discloses a dynamic focus target detection method and system for an automatic driving vehicle, which obtains vehicle images and speed data, generates an image motion vector field based on motion analysis, performs dynamic region priority division in combination with vehicle speed, outputs dynamic detection frequency planning data, generates a to-be-processed region mask by using an adaptive sparse decision module, selectively crops an image input target detection neural network, and finally maps coordinates to output results, so that intelligent allocation of computing resources is realized, computing resources can be efficiently allocated, processing delay can be reduced, and the accuracy and real-time performance of key target detection can be improved.