658 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 invention belongs to the technical field of telescope manufacturing, and discloses a 20 * 42 telescope system which is characterized in that an objective first lens, an objective second lens, a focusing lens, a semi-pentaprism, a roof prism, a rhombic prism, an eyepiece first lens, an eyepiece second lens, an eyepiece third lens and an eyepiece fourth lens are sequentially arranged in the optical axis direction from the object side to the image side. The visual field of the whole machine is 3.25 degrees, the exit pupil diameter is 2.1 mm, the exit pupil distance is 35 mm, the nearest focusing distance is 8 m, and the image stabilization range is + / -5 degrees.

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 discloses a real-time electronic image stabilization system for a flapping-wing flying robot, which effectively solves the problems of image dithering and blurring of a flapping-wing flying robot in a complex flying environment by combining flying attitude monitoring and a real-time image stabilization algorithm. The system comprises an image acquisition module, an electronic image stabilization module, a flight attitude monitoring module and a control system, the image acquisition module acquires image data in real time, and the electronic image stabilization module performs real-time stabilization processing on an image based on attitude change of an aircraft. The flight attitude monitoring module collects attitude data of the aircraft through a three-axis gyroscope, an accelerometer and a magnetometer, and calculates an accurate flight attitude matrix through a sensor fusion algorithm. The control system dynamically adjusts parameters of the electronic image stabilization module according to the flight attitude data to ensure image stability. Compared with the prior art, the method has high real-time performance and response speed, image stability parameters can be adjusted in real time in the flight process, and the image quality is remarkably improved.

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 aircraft automatic balancing and image stabilizing system based on sensor feedback, and belongs to the technical field of aircraft balance control. The aircraft automatic balancing and image stabilizing system is based on sensor feedback data, measures the angular velocity and acceleration of an aircraft, estimates the attitude of the aircraft in real time, and predicts the future attitude of the aircraft; according to attitude estimation and prediction results, adjusting a control surface of the aircraft in real time, capturing images continuously shot by the aircraft in real time, analyzing whether the continuously shot images shake or not, when shaking occurs, analyzing attitude information and camera settings of the aircraft, and if the shaking occurs, keeping the current camera settings, adjusting the attitude of the aircraft, and if the attitude of the aircraft is a stable attitude, adjusting camera setting; in a complex flight environment, the attitude and image setting of the aircraft can be automatically adjusted, and the stability and image quality of the aircraft in the complex environment are 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 utility model discloses a binocular inverted image prism image stabilization module forming linkage of a parallelogram mechanism, which comprises a mounting frame, an X-axis rotating frame, a left prism assembly, a right prism assembly, a left Y pivot shaft, a right Y pivot shaft, an X pivot shaft, a connecting rod, an X-axis driving mechanism and a Y-axis driving mechanism, the X-axis rotating frame is nested in the mounting frame and is rotatably connected with the left side and the right side of the mounting frame through X pivoting shafts on the two sides; the left prism assembly is nested in the X-axis rotating frame and is rotatably connected with the upper end and the lower end of the X-axis rotating frame through a left Y pivot shaft; the right prism assembly is nested in the X-axis rotating frame and is rotatably connected with the upper end and the lower end of the X-axis rotating frame through a right Y pivot shaft; the connecting rod, the left prism assembly and the right prism assembly form a parallelogram mechanism to be linked; the structure design is ingenious and greatly simplified, the production cost is reduced, the structure is more compact, the control is simple, and the imaging quality is more stable.

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 a vehicle track extraction method and device based on a rotation detection frame and a storage medium, and belongs to the technical field of vehicle track recognition, and the method comprises the steps: obtaining a road vehicle image, and classifying the road vehicle image, and obtaining a training set; training a pre-constructed rotating target detection model by using the training set to obtain a trained rotating target detection model; acquiring a traffic flow video acquired by the unmanned aerial vehicle, and performing image stabilization processing on the traffic flow video; the trained rotating target detection model and a target tracking algorithm are used to process the traffic flow video after image stabilization processing to obtain vehicle trajectory data, and the vehicle trajectory data comprise vehicle image coordinates; converting the vehicle image coordinates into vehicle geographic coordinates through a homography matrix; and smoothing the vehicle trajectory time sequence data containing the vehicle geographic coordinates to obtain the vehicle trajectory curve, thereby solving the problem of low vehicle trajectory data extraction precision in the prior art.

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.

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

This application relates to the field of electronic device technologies, and provides a camera module and an electronic device, to reduce a volume of the camera module while improving image stabilization performance of the camera module. The camera module includes an optical lens, a module circuit board, a photosensitive chip, and an actuator. The module circuit board is disposed on a light exit side of the optical lens and includes a fastening part, a moving part, and an elastic part. The moving part is elastically connected to the fastening part through the elastic part. The photosensitive chip is disposed on a side that is of the moving part and that faces the optical lens. The actuator includes a fastened clamping jaw, a movable clamping jaw, and a wire. The actuator drive the moving part to move relative to the fastening part when the length of the wire changes.

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 embodiment of the invention provides an image stabilization method and device for a single-frame image of a video, and relates to the technical field of data processing, and the method specifically comprises the steps: decoding a to-be-processed video, and obtaining a plurality of continuous single-frame images in real time; generating a target image sequence based on a preset threshold number of single-frame images; for each two adjacent frames of single-frame images in the target image sequence, respectively extracting corresponding feature points, so as to obtain a first homography matrix corresponding to the two adjacent frames of single-frame images based on the feature points; generating a first homography matrix sequence based on the plurality of first homography matrixes, and performing Gaussian filtering processing on the first homography matrix sequence to obtain a target homography matrix; and based on the target homography matrix, performing transmission transformation on a middle single-frame image at the middle frame position of the target image sequence, and generating a target image stabilization image corresponding to the middle single-frame image. According to the method and the device, the quality of the generated stabilized image can be improved while the efficiency of obtaining the stabilized image is improved.

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.

An imaging apparatus includes: an image sensor that captures a subject image formed via an optical system to generate image data; an optical image stabilizer including at least one of a first image stabilizer moving a correction lens, and a second image stabilizer moving the image sensor; a third image stabilizer that adjusts an area from which an image is cropped; and a controller that controls image stabilization by the image stabilizers, wherein the controller sets a shake correction amount of the optical image stabilizer; and sets a shake correction amount of the third image stabilizer, based on an error amount indicating a difference between the shake correction amount set to the optical image stabilizer and a displacement of the correction lens or the image sensor moved by the optical image stabilizer, and the third image stabilizer performs image stabilization based on the set shake correction amount.

The invention relates to the technical field of motor manufacturing, in particular to a propulsion motor rotor winding method and system. The method comprises the following steps: acquiring a frequency spectrum image of a winding grayscale image, and selecting and screening high-frequency information by a central circle to obtain a high-frequency image; determining a motion stability factor according to the position of the winding probe, and determining an image stability factor through edge detection and image recognition; screening to obtain a stable frame image; performing gradient analysis on the stable frame image and the high-frequency image, determining a first histogram and a second histogram, and determining similar parameters of the first histogram and the second histogram according to the gradient distribution structure difference of the first histogram and the second histogram; and screening according to the similar parameters to obtain an optimal radius, converting the high-frequency image under the optimal radius into a spatial domain to obtain a deblurred image, carrying out winding detection on the deblurred image, and determining a winding grayscale image with abnormal winding. According to the invention, the accuracy of rotor winding detection in the propulsion motor manufacturing process can be improved.

A zoom optics structure for implementation in a laser-based rangefinding instrument provides a magnified image of a target. The structure disclosed can also serve to magnify a reticle or other information on an in-sight display in conjunction with the magnified target image. The zoom optics structure disclosed is also amenable to rangefinding instruments incorporating ballistics interfaces and those having image stabilization.