476 results about "Image stabilization" patented technology

The invention relates to the technical field of image steady state adjustment, and provides a self-adaptive image stabilization and dynamic horizontal reference calibration method and device, equipment and a medium. Time domain alignment and motion parameter interpolation processing are carried out on original sensor data to obtain a synchronized motion parameter data stream, and multi-sensor data fusion filtering is carried out on the synchronized motion parameter data stream to obtain equipment three-dimensional attitude parameters. The method comprises the following steps: performing motion mapping on an original image frame according to equipment three-dimensional attitude parameters to obtain an image displacement compensation matrix, performing feature tracking and pixel resampling on the original image frame according to the image displacement compensation matrix to obtain a preliminary stable image set, and performing horizon detection and rotation compensation on the preliminary stable image set to obtain a horizontal reference alignment image set; and performing time sequence weighted fusion on the horizontal reference alignment image set to obtain a steady-state video data stream. Through multi-sensor fusion, high-precision mapping, image adaptive calibration and weighted fusion, the precision of motion jitter suppression and horizontal calibration is improved.

The invention belongs to the technical field of multi-camera cooperative imaging, and discloses a multi-camera cooperative anti-shake control system and method. The method comprises the following steps: generating a global hardware trigger signal by using an FPGA (Field Programmable Gate Array), synchronizing IMU and multi-camera acquisition, and combining motion parameters to obtain a space-time aligned multi-view image; obtaining a global jitter component through feature extraction, motion vector field generation, depth map analysis and the like; fusing the data with IMU data to generate a trajectory, and inputting the trajectory into LSTM to obtain future compensation amount; and cutting based on deep layered transformation to obtain an EIS optimized frame, dynamically electing a main camera for super-resolution reconstruction, and outputting a final anti-shake video stream. Through multi-source information fusion, layered precise compensation and dynamic optimization, the accuracy and stability of motion estimation are remarkably improved, the jitter influence of the finally output video stream is effectively weakened, and the reliability and visual coherence of the image stabilization effect in a complex scene are ensured.

The invention provides a plastic packaging barrel online defect detection method and system based on machine vision and deep learning. According to the method, visible light and thermal image data, aligned in time, of the surface of the plastic packaging barrel are collected, the dynamic range of a thermal image is expanded to enhance the identification degree, then highlight interference is compensated through the mapping relation between a thermal image stable area and a visible light reflection area, and surface reflection suppression is achieved; superposing the processed dual-mode data to generate a multi-mode fusion image, dynamically adjusting the temperature reference value of the fusion image based on the thermal conductivity of the material and the environment temperature of the production line, and positioning an abnormal temperature region; and finally, extracting topological contours and temperature diffusion characteristics of the regions, and inputting a deep learning model to judge material structure attributes and spatial positions of the defects so as to finish online detection. According to the method, thermal and visual data are fused to enhance the perception capability on fine structure defects, and the precision and robustness of online detection of the plastic packaging barrel in a complex illumination environment are remarkably improved.

The invention discloses an optical image stabilizer anti-shake detection method and related equipment, and relates to the technical field of optical anti-shake, and the method comprises the steps: responding to a detection request, and transmitting a virtual vibration wave signal to a target optical image stabilizer; determining an image dot virtual displacement curve according to a Hall signal value of a lens module corresponding to the target optical image stabilizer; generating an image dot theoretical displacement curve according to preset optical parameters and the virtual vibration wave signal; and determining an anti-shake effect quantized value of the target optical image stabilizer according to the image dot virtual displacement curve and the image dot theoretical displacement curve. Through combination of the virtual vibration wave signal, the Hall signal value and the theoretical displacement curve, the anti-shake effect of the optical image stabilizer can be accurately evaluated, dependence on a vibration table and image data is reduced, and therefore more efficient, economical, stable and accurate detection of the anti-shake effect of the optical image stabilizer is achieved.

The invention discloses a fuzzy video real-time jitter removing method and system, and the method comprises the steps: distributing feature points through multi-scale FAST detection, lightweight MLP detection and dynamic weight, combining a MobileNet-FPN network and the lightweight MLP dynamic weight to extract the robust features of the feature points, modeling the global matching relation of the feature points of two adjacent frames through Transform, and carrying out the real-time jitter removing of a fuzzy video. And a Bayesian adaptive RANSAC algorithm is adopted to realize high-efficiency mismatching pair elimination, and finally an affine transformation matrix is solved and reverse mapping is performed to compensate jitter. According to the method, while the real-time performance of the mobile terminal is ensured, the image stabilization precision in a violent shaking scene is remarkably improved.

The invention belongs to the field of tunnel wall surface deformation monitoring, and particularly relates to a tunnel wall surface deformation monitoring method based on computer image recognition, which comprises the following steps: acquiring expandable data and accessing the expandable data to a subsystem; image stabilization operation is carried out on the edge side, and a standardized preprocessing subsystem is constructed to process data; constructing a multi-modal fusion architecture of a structural topological graph and a space-time diagram neural network; constructing a hierarchical alarm judgment mechanism of an uncertainty-driven risk score and a sectionalized adaptive threshold, and linking the BIM and work order circulation to form a closed loop; according to the invention, millimeter-level displacement resolution can be realized, false alarm and missing alarm can be obviously reduced, and long-term online traceable tunnel wall surface deformation monitoring and graded early warning closed loop can be supported.

The invention discloses an image stabilization method and system based on inertial measurement data, and the method comprises the steps: obtaining video frame motion optical flow data in real time through a video collection device, obtaining video optical flow motion information through image algorithm processing, and recording and transmitting motion inertia data of a camera through an IMU (Inertial Measurement Unit); the two types of data are preprocessed, and then time axis alignment is completed; accurate video data motion information is obtained through bidirectional correction; kalman filtering is introduced for forward compensation, and a motion model is established to solve a rotation translation matrix; dividing the image into local pixel spaces, calculating a transformation matrix of each region, and obtaining a radiation transformation matrix by adopting neighborhood weighting; and finally, triangular region filling is realized through an OpenGL graphic rendering library, and a stable image is output. According to the method, IMU data and visual information are creatively fused, the real-time performance and accuracy of video image stabilization are remarkably improved through multi-level motion compensation and local optimization, and the method is particularly suitable for meeting the requirement for high-quality image stabilization in a motion scene.

The invention discloses an image super-resolution edge reconstruction method based on morphology and coverage rate perception. The method comprises the following steps: dividing an image into an edge region and a non-edge region based on depth and brightness information; anti-aliasing edge detail recovery is realized through coverage rate perceived depth mode classification and a table look-up filter; generating direction features by using the brightness gradient and keeping details through a table look-up filter; and combining the reconstruction results of the current frame and the historical frame to ensure the image stability in a dynamic scene. The invention also provides an image super-resolution edge reconstruction system. According to the method provided by the invention, the quality of an object edge and a newly appearing pixel region can be remarkably improved, sawtooth artifacts are effectively inhibited, and relatively high time stability is kept in a dynamic scene, so that the requirements of real-time rendering and visual enhancement application are met.

The invention relates to the technical field of image stabilization, in particular to a GMSL camera system design method supporting anti-shake, which comprises the following steps: acquiring a YUV image through image acquisition, extracting an edge through a Canny algorithm and generating trajectory data, tracking pixel displacement to calculate an angle and an amplitude, marking as a stable area if a threshold condition is met, generating a stable area coordinate, and calculating the image according to the stable area coordinate. The IMU collects acceleration and angular velocity data, synchronizes the acceleration and angular velocity data with an image frame, calculates acceleration change, detects an edge direction angle, calculates a vector included angle to generate cutting offset, adjusts the position of a cutting frame, performs bilinear interpolation reduction, and outputs a stable image frame. According to the invention, the jitter compensation precision is improved, the delay and loss are reduced, and the image stability in the vibration environment is enhanced by extracting the image edge track, tracking the pixel displacement path, matching the IMU with the image timestamp, calculating the acceleration and the edge direction offset, dynamically adjusting the position of the cutting frame and performing interpolation reduction.

The invention provides a real-time image stabilization method and system for intelligent image processing, and relates to the technical field of image stabilization. The method comprises the following steps: synchronously obtaining continuous image frames under strong glare interference, and identifying a texture blurred region; for the region, calculating a texture complexity distribution diagram by combining the local structure variation of the adjacent frames, and screening candidate regions according to the texture complexity distribution diagram; polarization filtering processing is applied to the candidate area, the filtering angle is dynamically adjusted to be matched with the polarization direction of incident light, and a polarization filtering image is generated; extracting a candidate region motion vector field based on the gradient continuity feature of the image, and performing spatial superposition on the candidate region motion vector field and the texture complexity distribution map to form a motion vector set carrying texture weight factors; and according to the texture weight factor, carrying out hierarchical clustering to separate a background vector group and a foreground abnormal group, only selecting a geometric center value of the background group to execute inter-frame motion compensation, and outputting a stable image sequence. According to the invention, the stability and quality of images collected by the unmanned intelligent turntable in a strong glare dynamic scene are improved.

A lens driving device includes a carrier; and an image stabilization unit including a lens holder for a lens barrel, and a support frame having a quadrangular frame structure including four corner regions and supporting the lens holder. The lens holder is disposed in the carrier. The image stabilization unit is configured to move the lens holder in a direction perpendicular to an optical axis direction. The support frame includes a first sub-frame including a connection-type molded portion connecting three corner regions of the quadrangular frame structure, and an island-type molded portion separated from the connection-type molded portion and disposed in a fourth corner region of the quadrangular frame structure, and a second sub-frame made of a material stronger than a material of the first and connecting the four corner regions of the quadrangular frame structure and being combined with the connection-type molded portion and the island-type molded portion.

The invention provides a vehicle-mounted instrument image anti-shake acquisition system and assembly based on a magnetic control camera. The system comprises S1, a vibration sensing module; s2, a vibration identification module; s3, a vehicle operation sensing module; s4, magnetically controlling an anti-shake control module; s5, an image acquisition module; and S6, an image anti-shake module. The assembly comprises a magnetic field generating device and a suspension magnetic suspension camera, the magnetic field generating device comprises a miniature electromagnetic coil and an integral frame, and the suspension magnetic suspension camera comprises a camera body and a suspension module. According to the invention, the problems of serious image acquisition jitter, inaccurate identification and the like of detection equipment in the driving process of the motor vehicle are solved, and the image stability and the identification precision are remarkably improved.

The invention provides an endoscope image stabilization control method, which comprises the following steps of: acquiring an original dithering image sequence and inertial data of an endoscope, fusing the original dithering image sequence and the inertial data, acquiring an initial mixed motion field, performing operation semantic segmentation on the original dithering image sequence, and acquiring a collaborative attention map in combination with a physical motion mechanism. Obtaining a space-time adaptive filtering kernel through the collaborative attention map, filtering the initial mixed motion field according to the space-time adaptive filtering kernel, obtaining a stable motion field, carrying out image deformation and interpolation synthesis processing on the stable motion field, and obtaining a stable image sequence; through the integrated technical scheme of operation semantic segmentation, dynamic image stabilization optimization and accurate jitter suppression, the problem of interference of endoscope jitter on the neurosurgery operation visual field is solved.

The invention belongs to the technical field of video monitoring and image recognition, and particularly relates to a video monitoring transmission delay detection method and system based on image recognition, and the method comprises the steps: extracting image stable texture features through SIFT to generate a 128-dimensional descriptor, capturing an inter-frame motion trend through a Lucas-Kanade algorithm to generate a time feature, and carrying out the detection of the transmission delay of the video monitoring through the Lucas-Kanade algorithm. Finally, dynamic weighted fusion is carried out through an attention mechanism, and a space-time joint feature vector is generated; then, a dynamic template containing spatial-temporal characteristics and a local clock is generated at a sending end, cross-end matching is carried out at a receiving end by using an FLANN algorithm, the influence of network jitter and clock skew is eliminated through a double-calibration mechanism of basic time delay calculation, clock skew calibration and jitter compensation, and finally time delay after calibration is output; based on this, the method has the advantages of avoiding the interference of network jitter on the delay detection precision and reducing the delay standard exceeding false alarm condition caused by instantaneous deviation through the design of double-calibration delay calculation and cross-end feature accurate matching.

This disclosure provides systems, methods, and devices for image processing that support improved image quality. In a first aspect, a method of image processing includes determining a scene condition for an image sensor of an image capture device; receiving motion data regarding movement of the image capture device; configuring the image sensor of the image capture device with a first image sensor configuration determined based on the motion data and the scene condition; receiving image data from the image sensor captured with the first image sensor configuration; and determining a video sequence by processing the image data based on the motion data and the scene condition. Other aspects and features are also claimed and described.

An optical image stabilization apparatus includes a first position detector and a second position detector configured to detect a position of a movable member relative to a base member in directions of first and second detection axes that are not orthogonal, a first driving unit and a second driving unit configured to drive the movable member relative to the base member in directions of first and second drive axes. The first or second detection axis is different from the first and second drive axes. An intersection of the first and second drive axes is closer to a center of gravity of a movable unit including an element fixed to the movable member among an optical element, the movable member, and the first and second driving units, than an intersection of the first and second detection axes.

A small-sized image pickup apparatus which has space for locating a portion capable of applying image stabilization to an image pickup unit and is capable of capturing high-quality images by rapidly cooling an image sensor in the image pickup unit. The image pickup apparatus includes a housing, an image pickup unit disposed to divide an inner space of the housing into a first space and a second space, an electronic component, a first duct, and a second duct, where the second space is in front of the first space. The electronic component is in the first space. The first duct is in the first space, and includes a first heat exchanger that exchanges heat with the electronic component and a first flow path. The second duct is in the second space, and includes a second heat exchanger that exchanges heat with the image pickup unit, and a second flow path.

An electronic device is provided that includes a first camera with a first field of view configured to capture a first image, a second camera with a second field of view configured to capture a second image, and control circuitry configured to output stereoscopic content based on the first and second images. The control circuitry can include image signal processors configured to process the first and second images, additional processors for performing stereo rectification and image stabilization on the first and second images, and a compression block for combining images output from the additional processors.

The invention discloses an airborne camera anti-shake control method and system, and relates to the field of camera anti-shake control, and the method comprises the steps: building a hysteretic deformation tensor field, generating a visual hysteretic residual tensor through differential operation and lagging feature analysis, taking the visual hysteretic residual tensor as observation input, and carrying out the state estimation through a LuGre dynamic friction model. Calculating a micro bristle deformation state and an equivalent friction torque value of a blocking holder, performing visual compensation analysis based on the equivalent friction torque value of the blocking holder, judging whether the system is in a static friction zero-crossing critical region or not based on a micro bristle deformation estimated value, generating a reverse feed-forward compensation torque instruction according to the generalized all-source anti-interference torque, and determining whether the system is in a static friction zero-crossing critical region or not. The integral term of the controller is dynamically reset, vector synthesis is carried out on a reverse feed-forward compensation torque instruction and a basic instruction of a main image stabilization control loop, final driving voltage is generated and applied to a pan-tilt motor, and stepped picture lagging and jumping caused by instant release of energy in a long-focus view field are restrained.

The invention provides a monitoring camera image stabilization method and device, and the method comprises the steps: collecting the vibration data of a monitoring camera, extracting vibration characteristic parameters through time-frequency analysis, and generating environment vibration related data; according to the environment vibration associated data, calculating a weight distribution proportion of the monitoring camera between mechanical anti-shake and electronic anti-shake to obtain a cooperative work strategy; predicting a vibration track according to the vibration characteristic parameters, and compensating the vibration track in advance through mechanical anti-shake; and calculating the residual jitter amount after compensation in advance according to the cooperative work strategy, and carrying out electronic anti-jitter based on the residual jitter amount to realize stable output of images of the monitoring camera. By analyzing the characteristics of different vibration sources, the dynamic cooperative work of mechanical anti-shake and electronic anti-shake is realized, the compensation conflict between the two systems is eliminated, and the stability of monitoring camera images in a complex environment is effectively improved.

The invention provides an intelligent image stabilization method and system for an unmanned intelligent turntable. According to the method, an interference library is updated by acquiring electromagnetic interference data, and a signal-to-noise ratio is monitored to generate notch filtering parameters. Based on the parameters, a wave trap is adjusted, non-linear compensation and frequency domain equalization are synchronously triggered, image key frame abrupt change signals are identified at the same time, compensation intensity is adjusted, and closed-loop suppression is formed. In a closed loop, an inner loop extracts high-frequency jitter, an outer loop fuses interference prediction to generate primary parameters, and a cross-domain suppression instruction is output after motion analysis. And instruction-driven anti-interference coding: processing rotation suppression by an attitude coding scheme, processing electromagnetic suppression by a hierarchical error correction protocol, and performing closed-loop verification through link feedback. A verification result is fed back to update the interference library and the compensation intensity, cooperative control of electromagnetic interference and mechanical jitter is achieved, and a stable image is output. By constructing a dynamic closed-loop suppression mechanism, electromagnetic interference and mechanical jitter of the rotary table are cooperatively suppressed, and stable image output of the unmanned intelligent rotary table is realized.

The invention relates to the technical field of image stabilization, in particular to an electronic anti-shake method and system, and the method comprises the following steps: obtaining an angular velocity through a gyroscope, obtaining an angular displacement vector through integration, outputting inter-frame motion transformation parameters through time alignment, segmenting an image, calculating optical flow features, and outputting regional distortion feature distribution. The method comprises the following steps: performing spatial transformation to compare direction mark abnormity to generate a full-image compensation parameter mapping table, performing region transformation based on mapping to generate an anti-shake compensation image frame, performing prediction track Kalman filtering to determine a cutting boundary, and performing dynamic cutting to output a stable image sequence. Local distortion is accurately corrected by combining optical flow feature region calculation and abnormal direction comparison, self-adaptive compensation is achieved through nonlinear reverse mapping and linear translation grading processing, boundary control and view keeping are ensured through motion trail prediction and dynamic cutting, and vibration blurring and offset are remarkably reduced.

An electronic device is provided. The electronic device includes a camera module. The camera module includes a camera housing, a lens assembly including at least one lens aligned along an optical axis, a focus adjustment (AF) driver configured to move the lens assembly in a direction of the optical axis, an optical image stabilization (OIS) driver configured to move the lens assembly in at least one direction intersecting the optical axis, a frame disposed in the camera housing and at least partially surrounding at least one of the AF driver or the OIS driver, and a damper including one end portion fixed to the frame or the camera housing and another end having a shape elongated toward the camera housing and configured to be bent in one direction based on the damper contacting with the camera housing.

The invention discloses a three-spot welding dynamic imaging stabilization detection method based on motion compensation modeling, and relates to the technical field of photovoltaic energy monitoring, and the method comprises the following steps: obtaining an acoustic vibration signal, a picture time marking signal and a jig lifting displacement signal of the whole jacking process of a compressor shell, carrying out the time synchronization and feature fusion of the obtained signals, and carrying out the feature fusion of the obtained signals; and generating a resonance distribution band for constructing a dynamic reference model for subsequent time sequence analysis. According to the invention, through multi-source signal synchronous modeling and light machine closed-loop regulation and control, millisecond-level consistency of a jacking action and an imaging process is realized. Exposure and vibration phases are accurately controlled through staggered anchor points, a drift sketch, a baseline ring and an alignment key, pixel drift and brightness fluctuation are remarkably reduced, the detection false alarm rate and the detection omission rate are reduced by 73% and 67% respectively, and high precision and high stability of three-spot welding dynamic detection are achieved.

A method for improved image stabilization may include shifting image data from a memory device integrated with a display device, where the image data represents motion of the display device and corresponds with a time of capture of the image data; analyzing the image data via a processor to determine a stabilization correction to apply to the image data, analyzing including, determining the stabilization correction to correct for a displacement of at least a portion of the image data; applying the determined stabilization correction to the image data stored in the memory device to achieve stabilized image data; and outputting the stabilized image data from the display device.

To provide highly reliable lens image stabilization units and image-stabilized telescopes. [Solution] The lens vibration isolation unit comprises a position limiting cover and a lens vibration isolation structure mounted inside the position limiting cover. The position limiting cover comprises a bottom cover 20 and an end cover 10 connected to the bottom cover, and both the bottom cover and the end cover are provided with through holes corresponding to the position of the vibration isolation lens in the lens vibration isolation structure. The lens vibration isolation structure comprises a main control circuit board 45 and a movable unit 41 to which a vibration isolation lens 47 is attached. The main control circuit board is fixedly connected to the bottom cover and is provided with through holes corresponding to the vibration isolation lens. The movable unit is connected to the bottom cover via a tension spring 30 so as to separate the movable unit from the main control circuit board and so as to allow the movable unit to move relative to the main control circuit board. The vibration-isolating telescope has the advantages of high vibration isolation accuracy, compact size, and excellent cost performance, as it is equipped with a lens vibration isolation unit.

This application relates to a video processing method, apparatus, system, and computer-readable storage medium. The method includes: sequentially acquiring video images frame by frame using a photosensitive unit, and sequentially determining whether a target object in n consecutive video images is located within the image core region, where n is any integer greater than 1; if the target object is located within the image core region in the n consecutive video images, obtaining n initial positions of the target object relative to the center point of the photosensitive unit in the n consecutive video images; performing image stabilization processing based on the n initial positions to obtain image stabilization parameters corresponding to the Nth video image in the n consecutive video images, and sending the image stabilization parameters to a video display end for image stabilization processing based on the received image stabilization parameters corresponding to each frame of video images, where N is a positive integer less than or equal to n. This can reduce video image jitter caused by video acquisition terminal jitter and improve the viewing experience for video viewers.

This application discloses a miniature gimbal, camera module, and electronic device, including a first bracket, a second bracket, a third bracket, a platform, a first driving component, a second driving component, and a third driving component. The second bracket is located inside the first bracket and is rotatably connected to the first bracket about a first axis. The third bracket is located inside the second bracket and is rotatably connected to the second bracket about a second axis. The platform is located inside the third bracket and is rotatably connected to the third bracket about a third axis. The first driving component drives the second bracket to rotate relative to the first bracket. The second driving component drives the third bracket to rotate relative to the second bracket. The third driving component drives the platform to rotate relative to the third bracket. In this application, the miniature gimbal adopts a nested bracket design and is equipped with three independently decoupled rotating driving components, so that the miniature gimbal can achieve three-axis rotation without crosstalk, and can achieve a larger angle of rotation when performing image stabilization.

The invention provides an electronic image stabilization control method, a program product, electronic equipment and a storage medium, and the method comprises the steps: converting a current frame image based on a homography matrix corresponding to the current frame image, and obtaining a first image region; determining whether a preset cutting area in the current frame image is completely located in the first image area or not; in response to the fact that the preset cutting area is not completely located in the first image area, adjusting the homography matrix; and carrying out conversion again based on the adjusted homography matrix until the preset cutting area is completely located in the first image area, and carrying out cutting based on the preset cutting area to obtain a stable image corresponding to the current frame image.