22 results about "Phase correlation" patented technology

This invention relates to the field of prefabricated building installation accuracy control technology, specifically disclosing an intelligent calibration system for prefabricated building installation accuracy that integrates point cloud data and BIM. The system collects on-site point clouds and acquires design geometric information; after distance attenuation compensation for the point cloud reflection intensity, it generates on-site and design projection intensity maps along the normal direction of the component installation plane, and obtains the in-plane pre-translation amount through phase correlation calculation; using this pre-translation amount as the prior center, it constructs a spatial transformation objective function containing an exponentially growing dynamic penalty coefficient, and solves the final spatial transformation parameters through weighted centroid closed-loop inversion iteration; it calculates the signed vertical distance along the normal of the aligned point cloud and removes outliers to form a deviation field, outputting translation or rotation fine-tuning amounts according to the median deviation of the joint sub-region; this invention solves the in-plane sliding problem in the registration of flat components, improving the accuracy of installation deviation calculation and calibration reliability.

The application provides an infrastructure surface crack feature enhancement method, medium and system, and belongs to the technical field of crack detection.The application obtains a corrected three-dimensional depth image by starting a line structured light sensing device and an inertial navigation device to scan an infrastructure surface, synchronously triggers a high-speed camera to collect a corresponding two-dimensional gray image by using an incremental encoder, establishes a stereo calibration model, and combines a sub-pixel level phase correlation algorithm to realize pixel level accurate alignment of the two-dimensional gray image and the three-dimensional depth image, extracts crack contour features and crack center lines, superimposes and fuses the crack contour features and the crack center lines to the three-dimensional depth image to generate a crack feature enhancement image, and inputs a multi-scale crack recognition model to recognize and classify, so that the technical problem that two-dimensional image texture features and three-dimensional depth data are difficult to realize pixel level accurate fusion, resulting in poor infrastructure surface crack feature enhancement effect, is solved.

This invention discloses a method and system for synchronous monitoring of bridge structural displacement based on wireless intelligent vision, belonging to the field of bridge health monitoring technology. The method involves acquiring images of the bridge monitoring area and performing format standardization processing; synchronizing the clock and frame acquisition timing of multiple monitoring nodes, achieving microsecond-level synchronization through linear drift compensation, hardware-triggered synchronization, and frame buffering technology; calculating sub-pixel displacement data using either target-independent or improved marker tracking modes, the former based on frequency domain phase correlation analysis, and the latter using a constrained attitude decomposition algorithm to improve accuracy; performing localized visual calculations on the displacement data and outputting displacement time-series data; and wirelessly transmitting the data to achieve real-time visualization and data interaction with downstream systems. The system includes modules for image acquisition, node synchronization, displacement calculation, local calculation, wireless transmission, and data interaction. This invention achieves non-contact, high-precision displacement monitoring, improves multi-node synchronization and data real-time performance, and is adaptable to various inspection scenarios.

The application discloses an interferometric SAR synchronization method of radar inter-satellite link combined with Ka-band link cross correction, and aims at the problems of interrupting normal SAR imaging or existing initial phase winding in the existing synchronization link method, and proposes a cross correction scheme of X-band radar inter-satellite link combined with Ka-band high-precision synchronization link. The system adopts a common reference source to ensure the phase correlation, and different synchronization time sequences are designed, that is, the X-band link is synchronized at a low frequency to eliminate the initial phase winding, and the Ka-band link is synchronized at a high frequency same as the SAR pulse repetition frequency (PRF) to realize high-precision phase measurement. During ground processing, the initial phase error of the Ka-band compensation function is corrected by using the X-band synchronization data, so that a high-precision phase synchronization compensation function is obtained, and the echo of the secondary satellite is compensated. The application solves the problem of initial phase winding under the premise of not interrupting the normal SAR imaging time sequence, and significantly improves the phase synchronization precision, image quality and absolute height measurement reliability of the dual-satellite interferometric SAR system.

The application provides an anti-interference pipeline angle deviation detection method and device, and belongs to the technical field of underground pipeline detection. The method comprises the following steps: acquiring electromagnetic field X, Y and Z axis induction signals and corresponding sampling time information; extracting axis amplitude and phase parameters based on signal sequences, calculating amplitude correlation coefficient, phase correlation factor and amplitude stability evaluation parameters; obtaining an initial angle deviation reference value through XY axis amplitude parameters, correcting the amplitude correlation coefficient and weighting and fusing the stability parameters to obtain a final angle deviation reference value; obtaining a precise phase angle difference by combining XY axis phase parameters and the phase correlation factor; calculating the confidence degree based on the Z axis amplitude parameters to determine the effectiveness, and if the effectiveness is valid, the direction is determined according to the quadrant division rule, and if the effectiveness is invalid, the above process is repeated. The method integrates the three-axis signal characteristics, anti-interference is realized through multiple rounds of correction and effectiveness verification, the directional ambiguity is solved, and the detection accuracy and stability are improved.

This invention provides a method, medium, and system for enhancing the features of cracks on infrastructure surfaces, belonging to the field of crack detection technology. The invention uses a structured light sensor and an inertial navigation device to scan the infrastructure surface and acquire a corrected three-dimensional depth image. An incremental encoder synchronously triggers a high-speed camera to acquire the corresponding two-dimensional grayscale image. A stereo calibration model is established, and a sub-pixel-level phase correlation algorithm is used to achieve pixel-level precise alignment between the two-dimensional grayscale image and the three-dimensional depth image. Crack contour features and crack centerlines are extracted and superimposed and fused into the three-dimensional depth image to generate an enhanced crack feature image. This image is then input into a multi-scale crack recognition model for identification and classification. This invention solves the technical problem of poor enhancement effect of crack features on infrastructure surfaces due to the difficulty in achieving pixel-level precise fusion of two-dimensional image texture features and three-dimensional depth data.

This invention discloses an escalator stop detection method and terminal device based on multimodal displacement detection, belonging to the field of escalator stop detection technology. It can solve the problems of high false alarms and false negatives in escalator stop detection under scenarios such as crowd obstruction, complex lighting, and unclear step texture. The method includes: S1, acquiring a sequence of step images and a sequence of handrail images from the real-time video stream of the escalator; S2, calculating the displacement between every two adjacent frames of step images in the step image sequence, obtaining multiple sub-pixel displacements of the steps and the phase correlation peak of the current frame step, and determining the step confidence level; S3, calculating the displacement vector of each effective corner point in the handrail image sequence between the current frame handrail image and the previous frame handrail image, and determining the handrail confidence level; S4, determining a comprehensive confidence level based on the step confidence level and the handrail confidence level, and generating an escalator stop alarm signal based on the comprehensive confidence level. This invention is used for escalator stop detection.

This invention relates to the field of digital image processing technology, and in particular to a cross-scale image feature field registration method, comprising: extracting the target object shadow regions of a reference image and a floating image respectively, generating a reference topological field and a floating topological field through morphological thinning processing; calculating the sub-image isomorphism similarity between the two to identify matching anchor point pairs, and determining a local target region in the reference image; within the region, mapping the scale scaling and rotation differences between the images to linear displacement in the polar coordinate system through logarithmic polar coordinate transformation; subsequently performing one-dimensional cross-correlation calculation along the polar radial axis, detecting the phase correlation peak offset to obtain the scale scaling coefficient; using this as a reference for initial projection, establishing a composite optimization function that fuses the homography matrix energy term and the dense light flow field energy term; finally, dividing the floating image into a control grid, using an iterative solver to drive node displacement compensation, and completing non-rigid registration.

This invention discloses a method, medium, and system for visual measurement of structural displacement based on dual reference templates. The method includes: acquiring a first frame image and dividing it into multiple first frame image blocks, and generating a long-term reference template and a short-term reference template based on the first frame image blocks; acquiring a current monitoring frame and dividing it into multiple current monitoring image blocks; extracting image features and calculating manual feature scores and prior scores based on the image features; performing phase correlation matching on each current monitoring image to obtain a first phase displacement and a second phase displacement; calculating a reliability index; determining whether the reliability difference value is greater than a preset difference threshold based on the reliability index; if not, performing reliability-weighted fusion to obtain the final measurement result; it can effectively measure structural displacement by combining dual reference templates, ensuring the reliability of the measurement results; at the same time, it divides the target area into blocks to improve the referenceability of the final measurement results.

The application discloses a kind of based on joint error correction's motor target array ISAR three-dimensional imaging method, belong to radar imaging technical field.The method includes: the envelope alignment of target echo data received by each antenna element, initial phase correction and azimuth FFT transformation, obtain multi-channel ISAR two-dimensional image;Complex motor target's space variation wave path difference model and unmanned aerial vehicle radar platform's array system error model are constructed;Multi-channel ISAR two-dimensional image is initially roughly registered using maximum correlation coefficient criterion;Multi-criterion cost function is constructed by fusing image domain similarity constraint and signal domain phase correlation constraint;And joint optimization is carried out to model error parameter;Phase compensation is carried out to multi-channel ISAR two-dimensional image using optimized error parameter, and the image after compensation is carried out DOA estimation and three-dimensional reconstruction, obtains array ISAR three-dimensional image.The method has the advantages of high precision, strong robustness and high degree of automation.

This invention discloses a micrometer-level dynamic displacement detection method for bridge structures based on eye tracking and spatial anchoring. The method establishes a digital twin coordinate system by aligning the bridge's BIM model with the physical structure; it locks onto the detection target using eye tracking; spatial anchor points are created at the target location; an extended Kalman filter is used to fuse IMU data for jitter compensation; and high-frequency image sequences are acquired. An adaptive multi-level filter is designed to separate interferences such as temperature drift and wind vibration; a phase correlation method combined with optical flow is used to achieve sub-pixel displacement calculation, obtaining micrometer-level displacement time histories; spectral analysis and standard comparison are performed; and the diagnostic results are overlaid and displayed in augmented reality; an inspection path is generated, and a digital report is automatically output. This invention enables instantaneous measurement of dynamic displacement in key bridge components, improving the measurement accuracy of mobile AR devices to the micrometer level, effectively solving the problems of handheld jitter and environmental interference, and providing an efficient and intuitive solution for early damage identification and preventative maintenance of bridges.

The present application belongs to the technical field of visual guidance robot positioning, and particularly relates to a robot positioning method based on gradient weighting correction under multi-view. The present application firstly obtains the camera internal parameter matrix of each vision unit and the three-dimensional space coordinates of target features through calibrating the image of a calibration board in a common field of view; then establishes the matrix conversion relationship and inverse solution equation between the three-dimensional space and the two-dimensional imaging plane, and gradually obtains the external parameter matrix of each auxiliary camera relative to the main camera under the same world coordinate system; then constructs a gradient weighting correction algorithm using the gradient amplitude and phase correlation between the image pairs, filters out the error caused by the too large camera offset angle, and is used for correcting the conversion matrix between the multi-view vision units; finally, the data is converted to the robot base coordinate system through a hand-eye calibration algorithm, and the robot precise positioning based on gradient weighting correction under multi-view is realized. The present application increases the stability and robustness of the multi-view visual guidance robot positioning.

The application provides a multi-color LED illumination-based co-localization analysis multi-channel image automatic registration method and system, relates to the image processing technical field, and obtains the driving current parameters corresponding to each illumination channel and the structural jitter parameters of the acquisition device in the face image acquisition process, and the correlation is the face acquisition state parameter; according to the face acquisition state parameter, a preset model is used to analyze the chromatic dispersion displacement component and the structural offset component; the two are nonlinearly fitted to determine the estimated registration deviation; the position fluctuation interval is determined according to the fluctuation amplitude, and the local search area is delimited in the phase correlation diagram; the sub-pixel offset coordinates are positioned and extracted in the local search area; the sub-pixel offset coordinates are determined as the final registration offset, high-precision automatic registration of multi-channel images can be realized, and the reliability and efficiency of co-localization analysis are significantly improved.

Embodiments herein include an automated vehicle performing localization functions using particle scoring and particle filters. The automated vehicle performs a phase correlation operation that transforms image data of a sensed map and pre-stored base map from a spatial to frequency domain and combines the transformed maps to generate image data of a correlation map. Estimated location information of particles are compared against sensed data or other data in sensed sub-maps or the correlation map. The automated vehicle may apply an image-convolution scoring map by combining image data of the sensed and base maps in the spatial domain. The autonomy system may calculate entropies for the correlation map and image-convolution scoring map and combines these maps based upon the respective entropies.

The application discloses a kind of phase correlation FDA radar quantitative transmit pattern design method, the application realizes the quantitative design of the gain of the transmit pattern in multiple discontinuous regions of interest in observation space, improves the design freedom of FDA radar.Meanwhile, the application does not constrain the baseband waveform of phase correlation FDA radar, and no longer depends on the linear frequency modulation waveform to realize the design of pattern.In addition, the technology is based on phase correlation FDA radar, and compared with traditional MIMO radar, it does not depend on complex multi-dimensional coded waveform optimization design, and the computational complexity is low.The application can be widely applied to the related application of all-digital array radar, such as air search, space monitoring.

This invention relates to the field of optical precision inspection, and particularly to a sub-aperture stitching inspection method based on a frequency-domain and spatial-domain collaborative strategy. The method includes: acquiring discrete phase data of the sub-apertures; constructing a continuous physical field model; performing coarse alignment of adjacent sub-apertures using frequency-domain phase correlation technology to obtain integer pixel displacements between adjacent sub-apertures; performing sub-pixel fine alignment using a numerical gradient method based on the continuous physical field model and a normalized cross-correlation function with an embedded geometric error culling operator; constructing a global robust energy functional for global optimization; solving for the zero-curvature pose under a floating reference, and then performing Gaussian gradient weighted fusion and adaptive orthogonal base surface reconstruction to obtain the full-aperture surface shape of the large-aperture optical element. This invention solves the problems of strong initial value dependence, displacement-tilt degeneracy, cumulative error warping, and sensitivity to outliers in traditional sub-aperture stitching inspection methods, achieving ultra-high precision and high robustness in the sub-aperture stitching inspection of large-aperture optical elements.

The application discloses a kind of space positioning systems based on steady-state visual evoked potential.The stimulation module in the system utilizes the spatial coding strategy of four flicker arrays, the SSVEP signal induced is amplified and collected after signal pretreatment is carried out by electroencephalogram signal collection module, then the amplitude, phase, correlation coefficient of each stimulation frequency component and the ratio of the correlation coefficient corresponding to each coding stimulation frequency or phase are used as characteristic information to decode spatial information to determine the coordinates of visual fixation, finally the coordinate information is converted into instruction and given to controlled operation module, to realize visual feedback.The application can effectively solve the problem that the area of divided region and the number of target in each partition are limited in existing spatial coding, and the edge information of each partition cannot be distinguished, realizes the BCI of low visual load and accurate positioning in screen, and provides the possibility for realizing high-integration embedded BCI system.

The application provides a phase analysis-based optical interference fringe displacement prediction method and system, and belongs to the cross technical field of image processing and optical interference measurement. The method comprises the following steps: obtaining two optical interference fringe images to be detected, i.e., a reference fringe image and a target fringe image, wherein the target fringe image is an image obtained by translating the reference fringe image; pre-processing the obtained fringe images, eliminating redundant information and interference, and strengthening the fringe phase features; converting the fringe images from a spatial domain to a frequency domain through phase correlation calculation, extracting pure phase information related to displacement, and inversely transforming back to the spatial domain to obtain a phase correlation matrix; and completing fringe displacement detection based on the phase correlation matrix. The application solves the common problems of the prior art, such as complicated process, large amount of calculation, weak anti-interference and insufficient precision, and significantly improves the real-time performance, stability and sensitivity of methane concentration monitoring.