19 results about "Morphological filtering" patented technology

The invention belongs to the technical field of computer vision and artificial intelligence, and discloses a handwritten mathematical formula primitive feature enhancement method based on a self-adaptive symbol strategy, which comprises the following steps of: 1, dynamically scaling primitive scale matching: realizing undistorted scaling by keeping the aspect ratio of an original image, only fixing the height and dynamically calculating the width to obtain a primitive scale matching result; adaptive interpolation is carried out; step 2, pixel disturbance of the morphological filtering chain: isolated noise points are gradually eliminated through the multi-stage morphological filtering chain, broken strokes are repaired, and large-area background interference is removed; and the optimal structure elements are adaptively selected for different symbol types. According to the method, dynamic scaling of geometric constraints is combined with intelligent morphological filtering, so that the core problems of symbol deformation, noise interference, multi-source data difference and the like in handwritten mathematical formula recognition are solved, and the accuracy of a recognition system is remarkably improved. And an efficient and reliable preprocessing scheme is provided for education AI, intelligent correction and other scenes.

This application relates to the field of marine geophysical exploration technology and provides a method and apparatus for suppressing wave-induced electromagnetic noise. The method comprises: obtaining an optimal structural element; obtaining the results of a multiscale open-close operation and a multiscale close-open operation; performing a weighted linear combination of the multiscale generalized morphological open-close operation and the multiscale generalized morphological close-open operation, iteratively updating the weighting coefficients, and obtaining the entire segment of noise-suppressed marine magnetotelluric data; and evaluating the noise suppression effect. The method of the application improves multiscale adaptive generalized morphological filtering, significantly improving the filtering accuracy of marine magnetotelluric data, and significantly improving the quality of the magnetotelluric data after noise suppression.

This application relates to a SAR ship detection method and apparatus that incorporates spatiotemporal context information. The method includes: performing sub-view processing on a SAR ship image to obtain SAR sub-views corresponding to different synthetic aperture times; constructing a spatiotemporal context covariance matrix based on the SAR sub-views; performing a similarity test on the spatiotemporal context covariance matrix to obtain a similar sample count feature; utilizing the similar sample count feature to enhance the SAR ship image to be detected to obtain an enhanced SAR ship image; and performing ship detection on the enhanced SAR ship image using an adaptive threshold processing method and morphological filtering to obtain a ship detection result. This method can improve ship detection performance.

The application discloses a kind of floating platform reciprocating compressor fault diagnosis method and device, including for the vibration signal to be treated decomposition obtains IMF component;By index, some orders of IMF containing obvious impact characteristics are screened out;The screened IMF component is filtered respectively, and non-impact component is filtered out;The IMF component after adaptive variable scale morphological filtering is reconstructed to obtain noise reduction signal;Amplify the mutation component in noise reduction signal;Solve the envelope of mutation component, and utilize filter to carry out smooth filtering to envelope line;Peak value detection is carried out to extract the phase feature of impact component in signal;The phase feature of impact is acquired.Diagnosis device includes: acquisition module, processing module, extraction module and diagnosis module, establishes reciprocating compressor fault feature knowledge base, and carries out fault diagnosis according to the impact feature of vibration signal captured by extraction module.And support and guarantee are provided for the predictive maintenance of future offshore platform reciprocating compressor.

The present invention discloses an adaptive Raman spectroscopy baseline correction method, device and medium based on Gaussian smoothing and morphological filtering in the technical field of spectral signal. The method includes performing Gaussian smoothing processing on the Raman spectroscopy signal to obtain a smoothed signal; performing morphological filtering on the smoothed signal to preliminarily estimate the baseline; performing Gaussian smoothing processing on the preliminarily estimated baseline to obtain a smoothed baseline; subtracting the smoothed baseline from the Raman spectroscopy signal to obtain a corrected spectroscopy signal; calculating the total area of the corrected spectroscopy signal, and determining whether the relative change in the total area between adjacent iterations is less than a preset threshold. If the convergence condition is satisfied, the finally corrected spectroscopy signal and the baseline estimation result are output; otherwise, the iterative process is repeated. The present invention significantly improves the accuracy and efficiency of baseline correction, and solves the problems of traditional methods being sensitive to parameter selection, low calculation efficiency, and insufficient feature retention when dealing with complex backgrounds.

The present invention discloses a method and system for extracting regions of interest based on contrast boxes and generalized morphological filtering, aiming to solve the problem in the prior art that the extraction of regions of interest is easily interfered by noise and reverberation. The method comprises preprocessing signal data through beamforming and matched filtering, performing gain processing using a contrast box sliding window, and then extracting the region of interest through generalized morphological operations. By setting appropriate contrast box protection areas and transition areas, and combining generalized morphological operations, the local contrast is effectively enhanced and the background is estimated, thereby achieving accurate extraction of targets with complex backgrounds and blurred boundaries. The method has wide applicability and strong anti-interference ability. The present invention makes full use of the morphological features of the region of interest, and by enhancing local contrast and background estimation, can effectively handle complex backgrounds and blurred target boundaries. It is particularly suitable for the field of hydroacoustics, can accurately extract regions of interest, and has wide applicability and good application prospects.

The application provides a vesicle segmentation method and system based on a cryo-EM tomography image, and is applied to the technical field of intelligent processing and analysis of biomedical images.The application carries out preprocessing on the cryo-EM tomography image through deconvolution and missing wedge recovery, combines parallel inference of a double-path pre-training segmentation model, and then carries out multi-stage optimization processing such as fusion, ellipsoid fitting and morphological filtering, so that the accuracy and morphological expression ability of vesicle segmentation are effectively improved, and the technical problems of insufficient vesicle segmentation precision and missing morphological parameters of the cryo-EM tomography image are solved.

This invention provides a thyristor-controlled surge arrester and its control method. By constructing a dual-channel voltage processing algorithm based on morphological filtering and adaptive Kalman filtering, it achieves rapid and reliable judgment of power frequency overvoltage. The controllable surge arrester provided by this invention is installed at the phase-to-phase position of the protected transmission line and includes a nonlinear voltage limiting branch, a main protection circuit, an energy extraction and voltage division module, and a control and detection module. The nonlinear voltage limiting branch includes a first varistor and a first parallel capacitor connected in parallel with it. The main protection circuit consists of a positive thyristor conduction branch and a negative thyristor conduction branch. The two conduction branches are connected in antiparallel and in series with the nonlinear voltage limiting branch to achieve bidirectional controlled conduction of the positive and negative half-cycles of the power frequency overvoltage at both ends of the controllable part of the thyristor-controlled surge arrester. Electrically isolated thyristor gate triggering control is achieved through a pulse transformer and an isolation triggering circuit.

The application discloses a photoacoustic microscopic image correction and restoration method and device based on random subsampling and morphological filtering, and the method comprises the following steps. O Performing distortion estimation, estimating the maximum amplitude by solving the Euclidean distance of the blood vessel center line and edge with morphological characteristics, and obtaining a morphological filtering parameter d; collecting K relatively stable photoacoustic microscopic signals, and performing equal-interval sampling respectively to serve as a positive sample set I D ; fitting the image information of the positive sample I D with a multi-Gaussian distribution, simulating jitter, and serving as a negative sample set I d ; constructing a PADC network model based on random subsampling and morphological filtering, wherein the PADC network model comprises a PADC encoder structure, a PADC decoder structure and a skip layer; training the constructed PADC network model to obtain a trained PADC network model; and correcting and restoring the photoacoustic microscopic image to be processed by using the trained PADC network model. The application can effectively correct and restore the system motion artifacts caused by NURD in the maximum value image.

The invention relates to the technical field of artificial intelligence, in particular to a method for dynamically monitoring the construction process of a floor support plate, which comprises the following steps of: acquiring stress data of the whole construction period of the floor support plate, and constructing a training data set with a construction stage category label; performing adaptive multi-scale morphological filtering processing on the stress data in the training data set; on the basis of a predefined discrete structural element scale set, processing the stress data by adopting two composite operations of performing closing operation after morphological opening operation and performing opening operation after the closing operation; constructing a construction monitoring model and finishing model training by using the training data set so as to dynamically monitor the construction process; wherein the construction monitoring model takes a deep convolutional neural network with adaptive deep convolution and cross-layer feature bridging as a trunk feature extractor, and determines the classification probability of a construction stage through an attention classification layer based on external feature guidance and a weighted loss function of mutation perception.

The present invention discloses a method for generating a digital elevation model based on iterative morphological filtering, comprising the following steps: 1) image segmentation; 2) morphological grayscale filtering; 3) iterative binarization; 4) connected domain labeling; 5) threshold filtering; 6) surface interpolation; and 7) merging. The present invention integrates morphological grayscale filtering with iterative threshold segmentation techniques, combines a segmentation optimization strategy with a dynamic connected domain screening mechanism, and effectively addresses the issues of traditional algorithms such as window size sensitivity, poor terrain adaptability, and the need for multiple parameter settings. This method significantly improves the automated processing efficiency and terrain restoration accuracy of generating a digital elevation model (DEM) from a digital surface model (DSM) in complex terrain.

The application provides a morphological filtering image loss optimization method and device of an optoelectronic tracking system, and the method comprises the following steps: acquiring a basic morphological operation sequence formed by a morphological filtering algorithm adopted by the optoelectronic tracking system; determining a first pixel number required to be added and a second pixel number required to be deleted corresponding to each basic morphological operation based on the number of structure elements corresponding to each basic morphological operation; and performing optimization processing on each basic morphological operation, so that the optimized basic morphological operation performs the following operations: adding a corresponding first pixel number of pixels before and after a to-be-processed image sequence to obtain a reconstructed image sequence; performing the basic morphological operation on the reconstructed image sequence to obtain an operation result sequence; and deleting a corresponding second pixel number of pixels before and after the operation result sequence to obtain an output image sequence. According to the scheme, pixel loss can be effectively avoided, and the performance of the optoelectronic tracking system is improved.

The invention provides a morphological method and device for removing noise of a ship and a medium, and belongs to the technical field of seismic exploration. The method comprises the following steps: step 100, inputting seismic shot gather data; step 200, determining a parallel minimum granularity unit by adopting an SPARK parallel framework, and forming a target set of morphological filtering calculation; step 300, constructing structural elements of morphological filtering, and then predicting noise; step 400, performing boundary noise process treatment; and step 500, separating interference noise of the large ship to obtain de-noised seismic shot gather data. According to the method, two-dimensional mathematical morphology filtering and boundary processing of bidirectional structure elements are combined for denoising calculation, interference noise can be accurately predicted, denoising is accurate, parallel calculation is adopted, the calculation amount can be greatly reduced, the calculation efficiency is greatly improved, and the calculation cost is saved.

The invention provides a rotor three-dimensional morphological filtering method based on unequal interval sampling, and belongs to the technical field of rotor measurement. In order to solve the problems that traditional three-dimensional morphological filtering can only process data in one direction once, and data fusion easily causes model error expansion, the method comprises the following steps: carrying out identification analysis on a geometric structure of a rotor; the number of target points and adjacent sampling points is set for area division, and the weight of the sampling points of each area is distributed; carrying out multi-scale unequal interval sampling on the rotor; carrying out superposition processing on the sampled data, and fitting a model; performing shape detection on the surface of the rotor; constructing a multi-scale morphological probe according to the structural characteristics of each region of the shaft diameter; constructing a morphological pyramid of the whole rotor, fusing and processing the collected data, and completing axial-radial bidirectional filtering at one time; and sequentially performing morphological operation on a subsequent layer of the morphological pyramid until all data are processed by the multi-scale morphological probe to obtain a rotor three-dimensional model.

The invention discloses a detection, segmentation and identification method for an underwater acoustic communication signal, and belongs to the technical field of signal processing. A Gaussian mixture model is constructed, historical data or simulation data are utilized to train and generate a Gaussian mixture prediction model, and Kullback-Leibler divergence is obtained to be used for judging whether underwater acoustic communication signals exist in the obtained underwater acoustic signals or not; short-time fractional order Fourier transform is utilized to obtain short-time fractional order time-frequency features of different underwater sound data; a self-adaptive morphological filtering method is designed to carry out morphological filtering on the obtained short-time fractional order time-frequency characteristics of the underwater acoustic data, morphological detection is carried out by using a Hough transform method, and underwater acoustic communication signals are segmented; extracting short-time fractional order time-frequency features, a cyclic spectrum contour map and square power spectrum features; and a multi-scale fusion multi-head self-attention mechanism is designed, and a recognition model is generated by using historical data training, so that recognition of the underwater acoustic communication signal modulation mode is realized. According to the method, the underwater acoustic communication signal detection capability under the low signal-to-noise ratio is improved, and efficient detection, segmentation and identification are realized.

The present invention discloses a robust Heydemann orthogonal signal processing method combined with morphological filtering, comprising step S1: performing morphological filtering preprocessing on two sampled signals to remove outliers; step S2: fitting an ellipse to the filtered signals and calculating the ellipse parameters; and step S3: calculating the DC offset and amplitude-phase errors in the signals based on the ellipse parameters obtained in step S2, and correcting the original signals. This method removes outliers from the sampled signals, improves the signal-to-noise ratio of the signal to be corrected, and effectively addresses the problem of impact jitter affecting signal correction accuracy. Even when the signals are severely interfered with, a stable orthogonal signal can still be obtained, thereby improving the robustness of the Heydemann correction.

The present invention provides a method for detecting surface defects of plate and strip steel based on morphological quotient operation; the method comprises: an image denoising and image background extraction algorithm based on multi-scale morphological filtering; performing quotient operation on a noise-free image and a background image to obtain a saliency map, and extracting defects in uniformly illuminated areas; performing morphological reconstruction using the saliency map and the noise-free image to extract a background image of the reconstructed image; performing quotient operation on the reconstructed image and its background image to obtain a saliency map, and extracting defects in unevenly illuminated areas; performing mean-weighted fusion on the saliency map of the original image and the saliency map of the reconstructed image to obtain a final saliency map, and performing threshold segmentation to extract defect areas in the original image. The present invention provides a method for detecting surface defects of plate and strip steel based on morphological quotient operation, which can improve the speed and accuracy of plate and strip steel defect detection and meet the production needs of online detection of plate and strip steel surface quality.

The application aims to provide a rolling bearing fault diagnosis method based on morphological product envelope spectrum, and belongs to the field of bearing fault diagnosis. Different order median filters are used to carry out noise reduction processing on the vibration signal; then, the minimum amplitude of the waveform between adjacent local minimum points in the noise-reduced signal is set to zero to construct an adaptive enhanced time-varying structure element. A morphological gradient operator is used to carry out morphological filtering on the original signal in combination with the constructed adaptive enhanced time-varying structure element, and the envelope spectrum of the filtered signal is calculated. Meanwhile, an improved characteristic frequency intensity coefficient is proposed to adaptively select the optimal order of the median filter, and then the envelope spectrum corresponding to the morphological operator is obtained. The application can effectively suppress the interference of background noise by constructing the morphological product envelope spectrum, and the improved characteristic frequency intensity coefficient can effectively represent the information richness of bearing faults.

This invention discloses a method for outlier detection in multi-beam data based on adaptive progressive morphological filtering. The method employs a closed-open-open combined average morphological operator for filtering, extracting a local terrain slope tolerance parameter. Based on this parameter, the elevation threshold is adaptively and dynamically adjusted during iterative morphological filtering. Through multi-level filtering windows and iterative calculations, the morphological reference plane gradually approximates the actual seabed until the iteration termination condition is met. Then, the terrain slope is extracted and a global judgment threshold is calculated. The depth deviation between the actual measured depth and the reference elevation is compared based on spatial location, thereby achieving accurate removal of outliers from the original discrete point cloud. By establishing a local dynamic adjustment and global decision mechanism for the filtering threshold, the method effectively avoids the filtering and under-filtering defects caused by fixed parameters, improving denoising accuracy while ensuring high fidelity of the actual seabed micro-topography.