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132 results about "Thresholding algorithm" patented technology
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Tunnel lining crack recognition method and system based on gradient inter-class threshold algorithm
InactiveCN107862677AEasy to storeEasy to filterImage enhancementImage analysisRailway tunnelPattern recognition
The present invention discloses a tunnel lining crack recognition method and system based on a gradient inter-class threshold algorithm. The method comprises: (1) denoising a tunnel crack image; (2) using a gradient inter-class threshold algorithm to carry out binarization processing on the denoised image, carrying out edge detection on the obtained binarized image, and calibrating the fracture index; and (3) carrying out morphological processing on the binarized image to remove the noise of the crack itself and fill the internal void, and carrying out crack index extraction on the filled image. The system comprises an image enhancement module, an edge detection module, and a crack recognition extraction module that are connected in sequence. The tunnel lining crack recognition method andsystem based on the gradient inter-class threshold algorithm provided by the present invention has a good recognition effect for the tunnel lining crack images with huge processing amount and multi-interference, and is applicable to the automatic detection of the lining of the high-speed railway tunnel skylight period.
Owner:CHINA RAILWAY SIYUAN SURVEY & DESIGN GRP
Spectral Anomaly Detection in Deep Shadows
InactiveUS20110221926A1Image enhancementTelevision system detailsKernel principal component analysisData set
A spectral anomaly detection method includes the steps of segmenting a panchromatic image, obtained from a hyperspectral sensor into cluster data sets. Principal component analysis can be separately performed on each of the cluster data sets to produce a plot of principal components. An anomaly detection algorithm can be applied to an adaptively selected subset of principal components for each of the cluster data sets to produce cluster detection scores. Finally, separate detection thresholding algorithms can be applied to each of the cluster detection scores, and the results of the detection thresholding algorithms can be combined into a single detection plane.
Owner:THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY
SAR (Synthesized Aperture Radar) image target detection method based on zone markers and grey statistics
ActiveCN102622598AAccurate removalReduce false alarm rateImage analysisCharacter and pattern recognitionImaging processingPrior information
The invention discloses an SAR (Synthesized Aperture Radar) image target detection method based on zone markers and grey statistics. An artificial target potential zone thoroughly including all the artificial targets in the original SAR image is detected when independent of prior information such as target shapes, target characteristics and background characteristics and the like by using the structural information of the original SAR image extracted from a Primal Sketch model, the grey information of the original SAR image and the characteristic that the pixels of the SAR artificial target zone are distributed in an alternately dark and bright way are made the best of, a false alarm target zone is effectively removed in combination with an OTSU (maximum between-class variance) image thresholding algorithm, and the false alarm rate of an artificial target detection result is reduced; and the artificial targets are accurately positioned in the target zone, the technical problems of the SAR image target detection with high false alarm rate and low possibility of accurate positioning of the artificial targets in the target zone are solved, and the processing speed is quick. The SAR image target detection method can be applied to the target detection in the field of SAR image processing and computer vision.
Owner:XIDIAN UNIV
Method for quickly implementing ultrasonic imaging on basis of compressive sensing
InactiveCN104306023AImprove rebuild speedReduce computing timeInfrasonic diagnosticsUltrasonic/sonic/infrasonic image/data processingSonificationImage resolution
The invention discloses a method for quickly implementing ultrasonic imaging on basis of compressive sensing and mainly solves the problem that the time of computing iteration time step length by a quick iterative shrinkage / thresholding algorithm under a compressive sensing frame is slow. The method includes the steps of 1, according to a set resolution, discretizing a detection area; 2, subjecting the discretized detection area to wide-band pulse scanning to obtain an echo vector and an observation matrix; 3, establishing an ultrasonic imaging mathematic model according to the echo vector and the observation matrix; 4, determining the iteration step length by acquiring a 2-norm of a sum of module values of each row of elements in the observation matrix; 5, plugging the iteration step length into the quick iterative shrinkage / thresholding algorithm to solve scattering intensity of a reconstructed observation scenario; and 6, arranging module values of the scattering intensity into a two-dimensional matrix so as to obtain a reconstructed ultrasonic image. Compared with the traditional quick iterative shrinkage / thresholding algorithm, the method has the advantages that the time of computing the iteration step length is greatly shortened, timeliness of the ultrasonic image is improved, and the method is applicable to the field of ultrasonic real-time processing.
Owner:XIDIAN UNIV
CT (Computerized Tomography) image metal track prediction and artifact reduction method based on integral cosine
ActiveCN103279929APrecise positioningGood removal effectImage enhancement2D-image generationMetal ArtifactTomography
The invention relates to a CT (Computerized Tomography) image metal track prediction and artifact reduction method based on integral cosine. Aiming at metal area part cutting in a metal artifact reduction algorithm, compared with a common threshold algorithm which uses original sinogram data to reestablish images, then cuts an image domain into metal pixels and finally projects the cut metal pixels onto a sinogram domain to position a metal track, the CT image metal track prediction and artifact reduction method based on integral cosine firstly obtains various projection tracks according to a cosine projection relationship, projections on each track are added and values which are greater than a threshold are regarded as values corresponding to metal, so that the metal track is obtained. The CT image metal track prediction and artifact reduction method based on integral cosine has the advantages that the original images are not required to be reestablished, the time is greatly saved, the accurate positioning of metal areas in images is kept as much as possible and artifacts introduced in the reestablished images are ensured to be as few as possible. According to results, the CT image metal track prediction and artifact reduction method can be used in a metal artifact reduction algorithm of CT medical images and the metal artifact reduction effect of the repaired images is better.
Owner:BEIJING UNIV OF TECH
Bottled liquid impurity and liquid level detection method based on image processing
ActiveCN105334228ARealize adaptive adjustmentReduce conservatismOptically investigating flaws/contaminationMachines/enginesImaging processingSelf adaptive
The invention provides a bottled liquid impurity and liquid level detection method based on image processing. The bottled liquid impurity and liquid level detection method comprises following steps: a, images to be processes are collected and inputted by a camera; b, a memory space used for storing images obtained via each step of treatment is constructed; c, Gaussian filtering is adopted for image grayscale smoothing treatment; d, improved otsu auto-thresholding algorithm is adopted so as to obtain a threshold T1; e, the threshold T1 is subjected to amplification so as to obtain a new threshold T2; f, the threshold T2 is used for binary-morphology treatment of the images obtained via Gaussian filtering; g, detection on impurities and liquid level is carried out, and results are outputted; and h, the memory space is released. The bottled liquid impurity and liquid level detection method is capable of realizing self-adaptive adjustment of thresholds in a certain light range. It is shown by experiment results that the bottled liquid impurity and liquid level detection method is capable of identifying impurities with a diameter larger than 0.5mm, detecting liquid level accurately, giving an alarm on unqualified products, and rejecting unqualified products.
Owner:HARBIN ENG UNIV
BCG signal heart rate calculating method and system based on dynamic second difference threshold
ActiveCN110916636AEffective filteringAdaptableSensorsMeasuring/recording heart/pulse rateJ waveComputation complexity
The invention discloses a BCG signal heart rate calculating method and system based on a dynamic second difference threshold. The method comprises the following steps of performing collecting to obtain BCG signals; according to a preset rule, performing filtering pretreatment on BCG signals to obtain filtered BCG signals; according to a dynamic second difference threshold algorithm, treating the filtered BCG signals, and determining the position of J wave peaks in each signal period to obtain the sequence of J wave peaks; according to the position of the each J wave peak in the sequence of theJ wave peaks, calculating the average length of BCG signal dominant waves; and according to the average length and the sampling rate, calculating the heart rate. The method and the system are high inalgorithm adaptability, and have good noise removing effects on different signals. The method and the system are simple in parameter structure, and low in calculation complexity, the problems that aconventional BCG signal extracting method is long in calculation time and large in delayed time, are solved, and the BCG signal heart rate calculating method and system have high calculation accuracyand are suitable for real-time monitoring of the heart rate.
Owner:OVATION HEALTH SCI & TECH CO LTD
An adaptive threshold algorithm for real-time wavelet de-noising applications
InactiveCN1625842AModulated carrier system with waveletsDigital technique networkTransducerEngineering
The invention discloses a method and system for extracting information from a received signal with the minimum loss due to noise. The system includes: a converter for correlating the received signal with a wavelet function and generating wavelet decomposition coefficients; and a threshold circuit, responsive to the received signal, for applying a predetermined threshold based on the type of signal. The system also includes a filter connected to the transformer and a threshold circuit for altering the wavelet decomposition coefficients produced by the transformer using a threshold applied by the threshold circuit to produce altered wavelet coefficients from which The reduced noise reconstructs the received signal.
Owner:GENERAL INSTR CORP
Systems and methods for training multipath filtering systems
A method for training a neural network to be configured to filter a multipath corrupted signal is provided. The method includes receiving, at the neural network, real or simulated multipath corrupted signal data, and training the neural network on the multipath corrupted signal data using a complex iterated least square thresholding algorithm (CILST) capable of processing both real and complex signals.
Owner:THE BOEING CO
Nonlocal self-similarity and sparse representation-based remote-sensing image denoising method
InactiveCN106157254AReduce complexityImprove denoising effectImage enhancementImage denoisingDictionary learning
The invention provides a nonlocal self-similarity and sparse representation-based remote-sensing image denoising method which comprises a dictionary learning process and an image reconstruction process, wherein the dictionary learning process comprises the step of constructing a group for each image block in an image; each group consists of nonlocal blocks with similar structures and adaptively learns a dictionary; the image reconstruction process comprises the step of calculating a spare coefficient of each group through an iteration shrinkage / thresholding algorithm, and obtaining a denoised image by using the dictionaries of the groups. According to the nonlocal self-similarity-based image denoising method, the nonlocal self-similarity of most images is used, and such structural self-similarity information is added into image denoising, so that a better denoising effect is achieved.
Owner:NANJING UNIV OF SCI & TECH
Method and apparatus for segmenting image into halftone and non-halftone regions
A method of segmenting an image into halftone and non-halftone regions includes: processing a pixel block of a grayscale image using a thresholding algorithm and an intensity threshold to form a binary block, the pixel block including grayscale pixels with intensity values, the binary block including binary pixels with binary values; identifying a pixel group in the binary block, wherein the pixel group includes connected pixels represented by a select binary value, wherein pixels in the pixel group adjacent to pixels of the pixel block represented by another binary value are identified as boundary pixels of the pixel group; and processing the pixel group using a scale invariant feature transform (SIFT) algorithm to extract keypoints from the pixel group to form a keypoint map in conjunction with segmenting the grayscale image into halftone and non-halftone regions. An image processing device for performing the method is also provided.
Owner:XEROX CORP
Bridge moving load identification method based on cascaded dictionaries and sparse regularization
ActiveCN106503730AInnovativeAccurate identificationCharacter and pattern recognitionMobile vehicleElement model
The invention discloses a bridge moving load identification method based on cascaded dictionaries and sparse regularization. The method mainly includes the following steps: 1) arranging a speed measuring device on a bridge to be used for measuring vehicle speed, and arranging a plurality of strain and acceleration sensors on the bridge for actual measurement of bridge response; 2) building a bridge finite element model; 3) adopting cascaded dictionaries formed by a discrete trigonometric function and a discrete rectangular function to expand an unknown moving load; 4) normalizing actual measurement response, and introducing a weighted L1 norm regularization method to build an identification equation; and 5) utilizing a fast iterative shrinkage-thresholding algorithm (FISTA) to solve the equation, and calculating a corresponding time interval signal. The method provided by the invention can accurately identify a bridge moving load, including a slowly-changing integral signal and local impact signal in bridge moving vehicle load signals, has strong noise robustness, and is particularly suitable for field utilization of bridge response to estimate gross vehicle weight.
Owner:JINAN UNIVERSITY
Portrait paper-cut generation method
InactiveCN102609964AImprove noise immunitySteady Portrait Cutout Effect2D-image generationHuman bodyComputer graphics (images)
Owner:湖北莲花山计算机视觉和信息科学研究院
Paddle torsion angle real-time monitoring method based on mark point detection
InactiveCN110879048ARealize real-time monitoringHigh precisionUsing optical meansAlgorithmTorsional angle
The invention discloses a paddle torsion angle real-time monitoring method based on mark point detection. The method comprises the following steps: firstly, separating a foreground from a background by utilizing an Otsu threshold algorithm to obtain a binary image with a connected domain; secondly, matching out circular mark points by adopting a minimum circumcircle method to realize coarse positioning of the circular mark points; thirdly, removing singular points through a circle fitting method to improve the circle center positioning precision of the mark points and achieve fine positioningof the circular mark points; and finally, calculating an included angle between straight lines formed by the circle centers of the mark points obtained twice to obtain a torsion angle. The method hasthe advantages of simplicity in operation, high precision, high speed and no contact, and is particularly suitable for real-time monitoring of the torsion angle of a paddle in a high-speed motion state.
Owner:NANCHANG HANGKONG UNIVERSITY
Autonomous plant growing systems
Owner:YUKA GROW SYST LLC
Image super-resolution reconstruction method based on deep convolution sparse coding
ActiveCN112907449ACompact structureEasy to implementInternal combustion piston enginesGeometric image transformationAlgorithmImage resolution
The invention belongs to the technical field of image super-resolution reconstruction, and discloses an image super-resolution reconstruction method based on deep convolution sparse coding, and the method comprises: embedding a multilayer learning iteration soft threshold algorithm ML-LISTA related to a multilayer convolution sparse coding model ML-CSC into a deep convolution neural network DCNN; adaptively updating all parameters in the ML-LISTA by using the learning ability of the DCNN, and constructing an interpretable end-to-end supervision neural network SRMCSC for image super-resolution reconstruction; and introducing residual learning, extracting residual features by using an ML-LISTA algorithm, combining the residual and an input image to reconstruct a high-resolution image, and then accelerating the training speed and the convergence speed. The SRMCSC network provided by the invention is compact in structure, has good interpretability, can provide a result with visual attraction, and provides a practical solution for super-resolution reconstruction.
Owner:SOUTHWEST UNIV
Steel rail surface defect identification and classification method
PendingCN111242891ASolve the problem of not enoughSolve the problem of blind spotsImage enhancementImage analysisClassification methodsUncrewed vehicle
The invention provides a steel rail surface defect identification and classification method, which is based on unmanned aerial vehicle monitoring image and depth forest model analysis, and comprises the following steps of: firstly, preprocessing an unmanned aerial vehicle monitoring image; secondly, extracting steel rail surface defects based on a proportional reinforcement maximum entropy threshold algorithm; and finally, realizing small sample defect data classification by utilizing a depth forest method. The steel rail surface defect identification and classification method provided by theinvention has the advantages and positive effects that the blind zone problem of a traditional detection mode in the field of steel rail surface defect detection is solved, the improved method for processing the unmanned aerial vehicle image is provided, and a certain promotion effect is achieved on track defect detection by utilizing the unmanned aerial vehicle; and the defect classification method suitable for the small samples is provided, and the problem of insufficient sample data volume at present can be solved on the basis of ensuring the accuracy.
Owner:BEIJING JIAOTONG UNIV
Sign early warning method and system for participant
InactiveCN107644681ADetermining Heart Rate ToleranceImprove accuracyHealth-index calculationPatient-specific dataSudden deathTime dynamics
The invention discloses a sign early warning method and system for a participant. The method comprises the steps that a cloud server acquires the sign parameter historical data and the identificationinformation of the participant in advance, wherein the cloud server comprises a sign safety threshold algorithm model; previously acquired sign parameter historical data of mass participants are usedas basic data, the safety threshold of dynamic sign data corresponding to each participant is acquired through the mode of big data operation; a wearable device acquires the real-time dynamic sign data of the participant during a competition; real-time monitoring data including the real-time dynamic sign data are uploaded to the cloud server; and the cloud server generates the sudden death risk assessment result of the participant according to the safety threshold of the dynamic sign data of the participant and the real-time dynamic sign data.
Owner:医遛健康咨询(上海)有限公司
Non-local neural network myocardial transmembrane potential reconstruction method based on iterative shrinkage threshold algorithm
ActiveCN111513709AReliable theoretical explanationReliable Convergence GuaranteeImage enhancementMedical imagingThresholding algorithmFeature extraction
The invention discloses a non-local neural network myocardial transmembrane potential reconstruction method based on an iterative shrinkage threshold algorithm. Through the fusion of a neural networkand a conventional optimization algorithm, and according to the non-local self-similarity of a transmembrane potential in space-time distribution, the invention designs a non-local feature extractionmodule; and an iterative shrinkage threshold algorithm optimization framework provides reliable theoretical explanation and convergence guarantee for the algorithm, the fusion of the neural network increases the flexibility and generalization performance of the method, and the addition of the non-local feature extraction module improves the performance of the network. Through the finally obtainedspace-time distribution of the myocardial transmembrane potential, the position and boundary of an infarction area during myocardial infarction, a pace-making point during ectopic pace-making and other areas with abnormal electrical activity can be accurately observed through three-dimensional display or waveform display, and the method has important reference significance in clinical diagnosis and treatment.
Owner:ZHEJIANG UNIV
Kalman filtering steel truss bridge structure parameter monitoring method based on adaptive control
PendingCN114036605AService custody workMeet engineering needsGeometric CADDesign optimisation/simulationStructural engineeringMonitoring methods
The invention discloses a Kalman filtering steel truss bridge structure parameter monitoring method based on adaptive control. The method comprises the following steps: firstly, determining mechanical parameters such as mass and rigidity of a steel truss bridge structure; secondly, speed, acceleration, displacement and ground acceleration vibration response data of a truss where the steel truss bridge structure is located are collected; and then tracking the change of the speed, acceleration, displacement and rigidity of the structure by using a Kalman filtering algorithm, performing envelope control by combining a dynamic statistical process algorithm, and automatically alarming when the rigidity generates a change value and exceeds an envelope control line. According to the method, the Kalman filtering algorithm is optimized so that the Kalman filtering algorithm can achieve the change of the predicted rigidity on the steel truss bridge structure, and the actual engineering requirements are met; compared with a traditional single threshold algorithm, the defect of a fixed threshold is overcome, the fixed threshold is optimized into dynamic control, reference is provided for performance evaluation of the steel truss bridge structure, and management and maintenance work of the steel truss bridge structure can be effectively served.
Owner:HOHAI UNIV
Compressed-sensing-based two-dimensional code image illumination equalization method
The invention discloses a compressed-sensing-based restoration method of a two-dimensional code image with non-uniform illumination. The method comprises the following steps that: a same two-dimensional code image is collected to obtain two two-dimensional code images and sparsity analysis is carried out on the two-dimensional code images; Fourier transform is carried out on the two two-dimensional code images to obtain spectrum images X1 and X2, a non-correlation sampling matrix is set according to the Fourier features of the two-dimensional code images, wherein the non-correlation sampling matrix is formed by a cross and a concentric circle and the sampling cross width and concentric circle dimension can be adjusted properly, and spectrum sampling is carried out on the spectrum images X1 and X2 at the Fourier zone so as to obtain a Y1 and a Y2; linear fusion is carried out on the Y1 and Y2 to obtain a new Fourier spectrum Y; and quick soft threshold iteration is carried out on the Fourier spectrum Y by using a fast iterative shrinkage-thresholding algorithm (FISTA) to obtain a Y', Fourier transform is carried out on the Y' to obtain a restored image f, and binarization processing is carried out on the image f and a two-dimensional code image is identified. With the method, equalized illumination can be realized; a processing speed of an image with non-uniform illumination can be accelerated; and an original two-dimensional code image can be restored accurately.
Owner:SUN YAT SEN UNIV +1
High-precision settlement monitoring method and device for SAR data
InactiveCN112034463ASolve the technical problem of low monitoring accuracyHeight/levelling measurementRadio wave reradiation/reflectionPhase correctionEngineering
The invention provides a high-precision settlement monitoring method and device for SAR data, and relates to the technical field of data processing. The method comprises the steps: obtaining to-be-processed SAR data inputted by a user, and enabling the to-be-processed SAR data to be SAR data in a TOPS mode; performing high-precision registration processing on the to-be-processed SAR data to obtaina multi-scene image; determining a pre-selected point of a scatterer of the multi-scene image by utilizing an amplitude deviation threshold algorithm; performing phase correction processing on the pre-selected point to obtain a target preset point, and determining a target scatterer by using the target preset point; and performing phase unwrapping processing and atmosphere and orbit correction processing sequentially on the target scatterer to obtain linear deformation information of the area corresponding to the to-be-processed SAR data. The technical problem that an existing SAR data settlement monitoring method is low in monitoring precision of the linear deformation information of the monitoring area is solved.
Owner:BEIJING AEROSPACE HONGTU INFORMATION TECH
Power plant instrument image detection and identification method and device
PendingCN111723821AClear boundariesAvoid the problem of inaccurate meter readings caused by insufficientCharacter and pattern recognitionTransformation algorithmImage detection
The invention relates to a power plant instrument image detection and recognition method and device, and the method comprises the steps: collecting an original image of a power plant instrument, carrying out the image preprocessing, and extracting an instrument dial region in the original image to form a target image; processing the target image through an improved Canny detection algorithm; carrying out non-maximum suppression on the gradient amplitude; obtaining an upper threshold value and a lower threshold value of the image after non-maximum suppression by adopting a self-adaptive threshold value confirmation algorithm; determining the boundary of the image through a double-threshold algorithm according to the upper threshold and the lower threshold; detecting straight lines and circles in the binary boundary image through a Hough change algorithm; and obtaining the range reading of the instrument according to the straight line and the circle in the binary boundary image through apointer instrument identification method. Compared with the prior art, the instrument image is identified by combining the Canny detection algorithm and the Hough transformation algorithm, and the pointer type power plant instrument is rapidly and accurately identified; meanwhile, the recognition stability is high.
Owner:SHANGHAI UNIVERSITY OF ELECTRIC POWER +1
Bunching SAR clutter suppression and moving target refocusing method based on approximate observation matrix
ActiveCN112731394ASuppress strong clutter informationReduce computational complexityRadio wave reradiation/reflectionComputation complexityImaging processing
The invention discloses a bunching SAR clutter suppression and moving target refocusing method based on an approximate observation matrix, and the method comprises the following steps: 1, building a geometric model of SAR data collection, and obtaining an echo signal; 2, performing PFA imaging processing on the mixed signal, estimating motion parameters of the moving target by adopting an FRFT algorithm, and constructing a dictionary of a radar projection matrix of the moving target; 3, constructing a joint projection matrix of the static target and the moving target to obtain an approximate observation matrix for clutter suppression and moving target separation; and 4, constructing an iterative shrinkage threshold algorithm based on the approximate observation matrix to obtain a clutter suppressed and focused moving target image. According to the invention, clutter suppression and moving target refocusing are realized by using the joint projection matrix of the moving and static targets, and a radar projection matrix and data are prevented from being stacked into a column vector by using an approximate observation matrix method, so that the calculation complexity and the storage memory are reduced.
Owner:NANJING UNIV OF POSTS & TELECOMM
Fire point detection method for Himawari-8 remote sensing data
ActiveCN113095437AAuxiliary early warningAuxiliary prevention and controlCharacter and pattern recognitionNeural architecturesData setEngineering
The invention discloses a fire point detection method of Himawari-8 remote sensing data, and belongs to the technical field of fire point detection of remote sensing data. The method comprises the following steps: preprocessing Himawari-8 satellite remote sensing data to obtain pixels and neighborhoods thereof, and making a data set; building a double-input convolutional neural network model, and inputting the radiation temperature wave band and the reflectivity wave band into the network; training a deep learning model by using the data set, iteratively updating network model parameters according to the change condition of a loss function, and converging to obtain an optimal network model; and applying the obtained model to fire point detection of data in a test set. Compared with a traditional context relative threshold algorithm, the method provided by the invention can automatically carry out fire point judgment, and can effectively improve the accuracy of fire point detection of remote sensing data.
Owner:NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP
Choroidal vessel lumen area recognition method, device and equipment and medium
PendingCN111899247AReduce manual identification costsImprove recognition accuracyImage enhancementImage analysisFeature extractionOphthalmology
The invention relates to the field of artificial intelligence, and provides a choroidal vessel lumen area recognition method, device and equipment and a medium. The method comprises the steps of obtaining a fundus image to be recognized; inputting a fundus segmentation model based on U-Net, and performing choroidal feature extraction and edge segmentation on the fundus image to be recognized through the fundus segmentation model to obtain a fundus segmentation image; recognizing a foveal area in the fundus segmentation image through a fundus foveal recognition model, and intercepting a first fundus choroid image from the fundus segmentation image according to the foveal area; carrying out binarization processing on the first fundus choroidal image through a Niback local threshold algorithmto obtain a first choroidal binary image, and extracting a first lumen area from the first choroidal binary image; and identifying the first lumen region image. According to the invention, the funduschoroidal vessel lumen area in the fundus image can be automatically identified. The invention is suitable for the field of smart medical treatment, and can further promote the construction of smartcities.
Owner:PING AN TECH (SHENZHEN) CO LTD
Intelligent electric meter chip image binarization processing method based on adaptive mixed threshold
PendingCN111986222AEasy to handleImprove processing efficiencyImage enhancementImage analysisEngineeringGrayscale
The invention discloses an intelligent electric meter chip image binarization processing method based on an adaptive mixed threshold. The method comprises the following steps: S1, preprocessing an original image to obtain a grayscale image; s2, calculating a global threshold Tg according to the gray value of the whole gray image; s3, calculating a stroke width corresponding to each pixel point inthe grayscale image, adaptively calculating a window width corresponding to each pixel, and calculating a local threshold Tw of each pixel according to a pixel value in each window; s4, combining theglobal threshold Tg and the local threshold Tw to calculate a mixed threshold T; and S5, performing binarization operation on the grayscale image according to the mixed threshold T to obtain a binarized image. Compared with the prior art, the processing method provided by the invention improves the traditional local threshold method for the problem of non-uniform brightness of the chip image of the intelligent electric meter, and performs weighted addition on the global threshold and the local threshold, thereby solving the problem that the local threshold algorithm does not consider the overall effect of the image.
Owner:STATE GRID NINGXIA ELECTRIC POWER CO LTD MARKETING SERVICE CENT STATE GRID NINGXIA ELECTRIC POWER CO LTD METERING CENT
CT image-based hepatic blood vessel three-dimensional segmentation method
The invention discloses a CT image-based hepatic blood vessel three-dimensional segmentation method. According to the method, adaptive S-type nonlinear gray mapping and isotropic interpolation sampling are adopted; and improved hepatic blood vessel enhancement processing based on Hessian matrix eigenvalue analysis is carried out; blood vessel enhanced response is introduced into a fuzzy affinity function; fuzzy segmentation parameters are initialized by means of an Otsu multi-threshold algorithm; and a complete hepatic blood vessel is obtained through a fuzzy connection segmentation algorithm.With the method adopted, a complete three-dimensional hepatic blood vessel structure can be segmented from a CT image, and segmentation accuracy is significantly improved.
Owner:BEIJING UNIV OF TECH
Wireless sensor node task time slot scheduling method based on matrix completion
ActiveCN111954305AImprove performanceIncrease the number of sleep slotsPower managementNetwork topologiesSingular value thresholdingWireless sensor networking
The invention discloses a wireless sensor node task time slot scheduling method based on matrix completion, and the method comprises the steps: dividing the continuous working time of a node into different task time slots through taking a sampling time slot as a unit based on the time correlation and low-rank characteristics of sampling data of a wireless sensor node in an environment monitoring application; the energy consumption of the node is reduced and the battery life of the node is prolonged by reducing the frequency of executing a sampling task time slot by the node; constructing a sampling matrix of wireless sensor nodes at a coordinator end, reconstructing a node sampling matrix subjected to data reduction by utilizing a singular value threshold algorithm, ensuring that completenode sampling data is provided for a user, and meanwhile, meeting the requirement of low-power-consumption operation of the wireless sensor network nodes; designing a singular value threshold algorithm of dynamic correction amplitude, adjusting the correction amplitude according to the reconstruction recovery precision of the sampling matrix, reducing the iteration frequency of matrix reconstruction, shortening the reconstruction time of the sampling matrix, and improving the algorithm performance.
Owner:UNIV OF ELECTRONIC SCI & TECH OF CHINA
Crack extraction method based on iterative phase consistency and application
ActiveCN108364285ASmall amount of calculationFast extractionImage enhancementImage analysisDenoising algorithmComputer vision
The invention relates to a crack extraction method based on iterative phase consistency. The method comprises the specific steps that (1) a CT image is preprocessed by combining morphological operation and a denoising algorithm; (2) polar coordinate transformation is carried out on the preprocessed image to acquire the image PolarImg; (3) the phase consistency of the image PolarImg is iterativelycalculated in a polar coordinate system, and the image is enhanced; (4) polar coordinate inverse transformation is carried out on the enhanced image; and (5) the method automatically selects a threshold for the enhanced image according to a unimodal thresholding algorithm, and then the enhanced image is split by 1.5 times the threshold to acquire a crack in the image. The method can automaticallydetect the high-precision crack from the CT image of an industrial part, and is not affected by the gray contrast difference of the CT image. In addition, the method has the advantages of small calculation amount and fast extraction speed, and can meet real-time application requirements.
Owner:CAPITAL NORMAL UNIVERSITY
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