570 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 discloses a lingual surface diagnostic information acquisition, diagnosis and analysis method and system, and belongs to the technical field of medical auxiliary diagnos.The method comprises the steps that an acquired lingual surface image is matched with patient information, a symptom associated lingual surface area is determined, the associated lingual surface area is subjected to priority division, and whether the acquired image meets a clear standard or not is judged; the method comprises the steps of constructing an image index evaluation model based on tongue vibration and image texture, performing tongue vibration, texture stability and water vapor fuzzy interference evaluation on an image needing to be processed, constructing a stable frame evaluation model, and importing vibration intensity, texture stability and a water vapor proportion into the stable frame evaluation model to evaluate image area stability. Image registration is carried out on the stable frame set, multi-frame registration and fusion are carried out based on an image stable region, region stability and processing information are recorded, a high-quality image for tongue picture analysis is generated, the image definition of a key diagnosis region is improved, and the accuracy and stability of tongue picture analysis are improved.

The airborne photoelectric confrontation pod comprises a pod body, a U-shaped frame is fixedly arranged at the top of the pod body, side cover plates are arranged on the two sides of the U-shaped frame respectively, a servo control module and an orientation assembly which are used for controlling an image stabilization system are installed in the side cover plates, and the top of the U-shaped frame and an unmanned joint are assembled together through a damping assembly; a front cover for sealing and protecting is arranged at the front end of the cabin body; a power supply module, a power supply system connecting frame and a subsystem connecting frame are sequentially arranged in the cabin body from top to bottom, the power supply module is fixed on the power supply system connecting frame, the power supply system connecting frame is fixedly connected with the subsystem connecting frame, and the subsystem connecting frame is fixedly connected with the inner side of the cabin body. Through control of the upper computer system, stable observation, distance measurement and automatic tracking of ground and low-altitude targets can be realized, and a laser suppression system of the unmanned aerial vehicle is guided to emit strong laser to perform interference blinding and disposal on the unmanned aerial vehicle target.

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.

A motor, camera module and device having a base, an image stabilization bracket, a first image stabilization magnetic piece, a second image stabilization magnetic piece, a first image stabilization coil, a second image stabilization coil, and a guide bracket having an L-shape. The first image stabilization magnetic piece is fastened to a first edge portion of the image stabilization bracket, and the second image stabilization magnetic piece is fastened to a second edge portion of the image stabilization bracket. The image stabilization bracket, and the first and second image stabilization coils are fastened to the base. Three support portions of the guide bracket are all located between the image stabilization bracket and the base, are disposed in a one-to-one correspondence with three corner portions of the image stabilization bracket, and are connected to the base and the image stabilization bracket through support pieces.

The invention relates to the technical field of image analysis, in particular to a method for monitoring the bottom of a battery swap station vehicle based on AI vision, which comprises the following steps: acquiring an image frame to extract bottom gray level distribution, calculating illumination difference to judge an abnormal frame, extracting a gray level jump band, calculating a slope, screening miscellaneous points, identifying a closed contour, and extracting a texture direction and a pitch. And analyzing an offset screening abnormal number, calculating an included angle and a contraction mark mutation pixel, and generating a bottom monitoring result. According to the method, the image stability under the complex illumination condition is enhanced by analyzing the gray level distribution and illumination change in the image frame, the edge response density difference elimination mechanism is combined, the structure overlapping interference is avoided, the closure degree of the closed structure and the texture period are extracted, and the structural integrity recognition is enhanced; texture direction and pitch cross-frame change analysis supports micro structure offset early warning, boundary point included angles are combined with contour shrinkage trends, accurate marking of abnormal areas is achieved, and sensitivity, accuracy and reliability of bottom monitoring are 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 multi-camera synchronous electronic image stabilization method and device based on virtual camera imaging, and the method comprises the steps: obtaining and splicing images captured by all cameras in a multi-camera cooperative imaging system, and constructing a virtual camera image; calculating the translation offset of the virtual camera according to the perspective transformation matrix between the adjacent cameras, and calculating the internal reference of the virtual camera; converting the pixel coordinate system into a to-be-stabilized virtual camera coordinate system according to the internal reference of the virtual camera; converting the compensation amount to a virtual camera coordinate system to be stabilized; calculating an image stabilization rotation matrix for converting the coordinate system of the virtual camera to be stabilized into the coordinate system of the stable virtual camera; and converting the to-be-stabilized image from the stable virtual camera coordinate system to the pixel coordinate system according to the image stabilization rotation matrix and the internal reference of the virtual camera to obtain a stabilized image. The method can be applied to multi-camera synchronous electronic image stabilization in a multi-camera collaborative imaging system, and high-quality anti-shake video real-time output is realized.

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 belongs to the technical field of photoelectric detection, and particularly relates to a super-large field-of-view circumferential scanning imaging system and a control method thereof.The system comprises a rotary table, an orientation fast reflecting mirror, a pitching fast reflecting mirror, an optical mirror set, an imaging assembly, a master control unit and an image processing unit; meanwhile, the invention further provides a super-large field-of-view circumferential scanning imaging control method, in the process that the rotary table rotates to drive the imaging assembly to carry out rapid imaging, image motion of an image in the process that the rotary table rotates at a constant speed is eliminated through the orientation fast reflecting mirror, and the problem that the image quality of an imaging assembly detector is reduced in the dynamic process is solved; through point-to-point pointing movement of the pitching fast reflecting mirror, an ultra-large field-of-view imaging function in the pitching direction is realized. By reasonably controlling the rotary table and scheduling the orientation fast reflecting mirror and the pitching fast reflecting mirror in the light path, accurate pointing of light beams and stable output of images are achieved, and the requirements for the imaging quality, the coverage range and the real-time performance are met.

The invention discloses a vibration table test sample real-time deformation monitoring system based on machine vision. The vibration table test sample real-time deformation monitoring system comprises an active modulation light source module, a multi-camera high-speed acquisition subsystem, a real-time deformation analysis unit, a full-field strain field reconstruction module, a motion compensation fusion module and a vibration synchronous control interface. An active modulation light source is synchronous with vibration, and motion blur is effectively eliminated in cooperation with a narrow pulse width design; the multi-camera orthogonal layout is combined with the vibration isolation base, so that stable acquisition of images is guaranteed; and the high-contrast coding datum point and dynamic tracking module accurately obtains the 6-DOF displacement. The rigid body and the elastic deformation can be accurately separated through a digital image correlation method and motion compensation fusion. High-frequency updating of a full-resolution strain field is achieved through multi-scale feature fusion, and monitoring intuition and safety are improved through an online visualization and early warning module. The system can realize high-precision, real-time and full-field deformation monitoring, meets complex vibration test requirements, and provides reliable data support for material and structure performance evaluation.

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 relates to the technical field of telescope image processing, and particularly provides a telescope electronic image stabilization method and system based on a theoretical guide trajectory, a telescope pointing error is calculated according to encoder pointing data and telescope guide pointing, the jitter offset of a target image is further calculated, a cutting area is calculated according to the jitter offset, and a target image is obtained. And cutting the target image according to the cutting area, and outputting the cut target image to realize image stabilization. The method does not depend on hardware equipment, does not need to extract target features, and is low in technical difficulty, simple and easy to implement and good in image stabilization effect.

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 relates to a multi-mode fusion dynamic image stabilization method, device and equipment for a small view field of an unmanned aerial vehicle. The method comprises the following steps: acquiring a jitter frame sample and gyroscope integral input; constructing a dynamic image stabilization network for respectively extracting inter-frame difference features and feature difference input of the jitter frame samples and fusing the inter-frame difference features and the feature difference input, and performing feature extraction on a fusion result to obtain an optical feature vector; performing feature extraction on the gyroscope integral input to obtain a gyroscope feature vector; splicing the optical feature vector and the gyroscope feature vector to obtain a fusion feature, carrying out linear transformation and nonlinear mapping on the fusion feature, then carrying out feature decomposition to obtain a high-frequency component feature and a low-frequency component feature, and carrying out adaptive weighted fusion to obtain an inter-frame motion compensation parameter; performing motion compensation on the jitter frame sample by using the inter-frame motion compensation parameter to obtain a stable frame; and carrying out image stabilization processing by utilizing the trained dynamic image stabilization network. By adopting the method, the image stability in a small view field scene can be effectively 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.

A motor includes a base, an image stabilization carrier, a focus carrier, an image stabilization drive mechanism, and a focus drive mechanism. The image stabilization carrier is movably connected to the base, the focus carrier is located on an inner side of the image stabilization carrier, the focus carrier is movably connected to the image stabilization carrier, and the focus carrier is configured to mount a lens. The image stabilization drive mechanism is configured to drive the image stabilization carrier and the focus carrier to move in a first direction and / or a second direction relative to the base, and the focus drive mechanism is configured to drive the focus carrier to move in a third direction relative to the image stabilization carrier.

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.

A control apparatus for use in a camera system that includes a first correction member provided on one of an image pickup apparatus and a lens apparatus detachable from the image pickup apparatus, and a second correction member provided on the other of the image pickup apparatus and the lens apparatus includes a memory storing instructions, and a processor configured to execute the instructions to control image stabilization using first control configured to provide image stabilization based on a first correction ratio between image stabilization using the first correction member and image stabilization using the second correction member and to electronically correct a trapezoidal distortion in an image blur, or second control configured to provide image stabilization based on a second correction ratio between image stabilization using the first correction member and image stabilization using the second correction member without electronically correcting the trapezoidal distortion in an image blur.

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 provides a navigation guidance method based on augmented reality. The method comprises the steps of scene construction, scene coordinate establishment, AR spatial position positioning, augmented display making, voice enhancement prompt establishment and landing process enhancement guidance. In addition, the invention also discloses a navigation guidance device based on augmented reality. The navigation guidance device comprises an aviation cabin, an aviation seat, an in-cabin display, a flight rocker, AR glasses, a computer, a visual display and a power supply, the visual field range is enlarged, the image stability is improved, light interference is reduced, enhanced display of a simulated flight route is provided, voice prompt and voice control are added, and the accuracy of virtual landing training is improved by performing enhanced display on a runway contour and an electromagnetic beam.