25 results about "Thinning algorithm" patented technology

The application is suitable for the technical field of image processing, and provides a battery glue line skeleton extraction method based on an improved ZS thinning algorithm, which comprises the following steps: preprocessing a collected battery glue line image to obtain a binary image; performing improved ZS thinning on the binary image, dividing the image into odd and even subdomains for batch processing, and introducing a constraint condition to iteratively delete redundant pixels to obtain a preliminary skeleton; using a T-shaped 4-neighborhood deletion template to remove T-shaped redundant pixels and realize complete single-pixelization; through 8-chain code tracking, identifying and removing burr branches caused by glue overflow and uneven glue coating, while protecting nodes to obtain a final glue line skeleton. The application solves the problems of skeleton redundancy, over-thinning and burr in existing thinning algorithms, realizes high-precision, single-pixel and burr-free glue line skeleton extraction, and can meet the online detection requirements of battery assembly lines, and has good industrial applicability.

The application discloses a segmental straightening method and terminal equipment based on computer vision. The method comprises the following steps: installing a camera sensor at a position between a rack and a straightening roll in a horizontal direction; performing joint calibration of all cameras to facilitate determination of relative positions of two-dimensional information; recording two-dimensional image information of a workpiece to be straightened and the straightening roll by the camera, and simultaneously performing model training preparation; performing semantic segmentation processing on the workpiece by an image recognition hub, and obtaining a bending curve by a distance transformation method or a skeleton thinning algorithm; according to bending information of the workpiece, performing discrete curvature calculation on the workpiece by a point taking method or a spline curve fitting method, and then performing segmental processing on the workpiece according to a point detection method and a curvature threshold method; and according to material thickness, yield strength and other parameters, determining optimal roll spacing and a press-down amount of a current segment, and performing real-time full-automatic closed-loop control on a steel straightening machine by real-time control on a press-down system and a variable roll spacing system of the straightening machine.

The application provides a scoliosis detection device, system and computer readable storage medium, the scoliosis detection device comprises a processor, the processor is configured to implement the following steps: acquiring a full body image of a user performing a preset action by using an image acquisition device, the preset action comprising a standing action; adopting a thinning algorithm to perform thinning line extraction on the full body image of the standing action to obtain a thinning line of a first type of preset joint of the user, the first type of preset joint comprising a spine joint, a shoulder joint and a hip joint; based on the thinning line of the first type of preset joint, obtaining posture information of the user, and calculating the similarity between the posture information of the user and standard posture information; when the similarity is less than a preset similarity threshold, generating a prompt information and sending it to a user device, the prompt information is used to indicate that the user has scoliosis. The application does not need manual screening, the accuracy of detection is higher, and can meet the large amount of scoliosis screening work.

The invention provides a plane calibration method for cross-structured light, which is used for solving the technical problem that when the cross-structured light is used as a light source for shooting, laser stripes contained in a shot image belong to two laser planes, so that a matching error is generated when straight line fitting is carried out in a laser plane calibration process. According to the plane calibration method for the cross-structured light, the laser line image is divided into the laser stripe and the background, then the laser stripe center line is extracted from each divided laser line image through the image refinement algorithm, and accurate extraction of the laser stripe center line is achieved; and then a classification criterion is constructed based on a principal component analysis method of K nearest neighbor and normal vector consistency, so that whether the laser point on the center line of the laser stripe belongs to the first laser plane or the second laser plane can be quickly and accurately judged, and the problem of point cloud attribution ambiguity of the biplanar laser line is successfully solved. And accurate solving and calibration of cross laser plane parameters are realized.

The application provides a cross structured light plane calibration method, which is used to solve the technical problem that when cross structured light is used as a light source for shooting, the laser stripe contained in the shot image belongs to two laser planes, which causes matching error in the process of laser plane calibration. The cross structured light plane calibration method of the application first divides the laser line image into two parts of laser stripe and background, then extracts the laser stripe center line on each segmented laser line image by using an image thinning algorithm, so that the accurate extraction of the laser stripe center line is realized; and then based on the principal component analysis method of K nearest neighbors and the normal vector consistency, a classification criterion is constructed, which can quickly and accurately determine whether the laser point on the laser stripe center line belongs to the first laser plane or the second laser plane, successfully solves the point cloud belonging ambiguity problem of the double-plane laser line, and realizes the accurate solution and calibration of the cross laser plane parameters.

This invention discloses a machine vision-based method for counting half-smooth tongue sole fry, comprising: acquiring half-smooth tongue sole fry images and binarizing them; acquiring all connected component parameters of the binarized image and constructing corresponding connected component images; processing the connected component images using a skeleton thinning algorithm to obtain fry skeleton images; classifying the pixels in the fry skeleton images; calculating the number of half-smooth tongue sole fry in the fry skeleton images using a crosspoint counting method; obtaining the average standard area of ​​the fry; applying a compensation algorithm to connected component images exceeding a set ratio coefficient; and summing the fry counts in all compensated connected component images to obtain the total number of fry. This invention uses crosspoint counting and a compensation algorithm to obtain the number of fry. The judgment method is simple and fast, non-contact with the fry, and enables automatic detection by machines instead of manual labor; it is applicable to all complex situations such as low or high adhesion and overlap of fry, and has the advantages of fast calculation speed, good detection stability, and high counting accuracy.

The invention discloses a pathological section diagnosis area marking and archiving method, which comprises the following steps: acquiring multi-temporal pathological section image data of a target tissue area, the multi-temporal pathological section image data comprising section images of the target tissue area collected at different time points; based on the multi-temporal pathological section image data, constructing a cable pipeline topology network in the target organization area through an image registration algorithm and a topology refinement algorithm; for the pathological section image data of each time phase, identifying an abnormal diagnosis area in the pathological section image data through an image identification algorithm; calculating geometric topological relation data between the spatial position of the abnormal diagnosis area identified in each time phase and the nearest branch node in the cable pipeline topological network; and based on the geometric topological relation data, generating fault source coordinate data in one-to-one correspondence with the abnormal diagnosis areas, and storing the fault source coordinate data into a diagnosis area coordinate database.

This invention provides a geological disaster monitoring method and system based on UAV vision and target collaboration, belonging to the field of disaster monitoring technology. The method includes: acquiring geological images at different times; performing terrain modeling based on the geological images and target locations to obtain a digital surface model; identifying vegetated and bare areas based on the geological images; constructing a Delaunay triangulation based on targets in the vegetated areas to calculate vegetation displacement; calculating bare land displacement based on the digital surface model; fusing vegetation and bare land displacements using thin-plate spline functions to obtain global displacement information; detecting cracks using an improved Canny-Zernike operator based on the digital surface model and identifying crack skeleton lines using a morphological thinning algorithm; and modeling displacement gradient tensors based on crack skeleton lines and global displacement information to construct a crack opening distribution map and obtain monitoring results. This invention creatively combines physical noise reduction, intelligent fusion, and precise analysis to achieve high-precision positioning in harsh environments.

This application discloses a method and a main control chip for improving the accuracy of straight lines in a map. The main control chip includes a binarization unit, an image thinning unit, and a line detection unit. The robot pre-constructs a map by collecting environmental information. The method includes: Step 1, binarizing the map to obtain a binary image; then performing Step 2; Step 2, extracting a skeleton image from the binary image using an image thinning algorithm; then performing Step 3; Step 3, extracting edge detection lines from the skeleton image using a line detection algorithm, denoising the extracted edge detection lines, and then fitting the denoised edge detection lines with straight lines to obtain fitted line segments.

The invention discloses an intelligent marine route extraction method based on multi-resolution grid density. The method comprises the steps of preprocessing AIS data and converting the AIS data into a continuous track segment set; abrupt coordinate change caused by the daily change line is eliminated through a coordinate system processing mechanism; generating a coarse grid by using an improved super-sampling rasterization algorithm, and constructing a multi-resolution density field in combination with high-density region identification and recursive multi-resolution refinement; enhancing density field features through adaptive power law transformation, multi-scale Gaussian decomposition and adaptive morphological processing; extracting a grid skeleton of the enhanced density field by using a GPU parallel Zhangsuen refinement algorithm; a simplified vector path is obtained through intelligent path tracking, coordinate system conversion and DouglasPeucker adaptive simplification, a path topological structure is constructed, and finally a continuous and accurate marine route network is generated. According to the method, the high-precision air route can be efficiently and automatically extracted, and the accuracy and the calculation efficiency of air route identification are remarkably improved.

The invention discloses an expressway-oriented sensing equipment state prediction and life evaluation system, which comprises a multi-source sensing data acquisition module, a sensing equipment state prediction module, a service life evaluation module and a service life evaluation module, wherein the multi-source sensing data acquisition module is used for acquiring multi-source sensing data; the data preprocessing module is used for generating standardized multi-source sensing data; the equipment space marking module is used for forming equipment space distribution; the road section area division module is used for constructing a cross check structure; the equipment credibility scoring module is used for generating a credibility score; the visual degradation feature extraction module is used for generating visual degradation features; the health index calculation module is used for generating a health index; the prediction and evaluation module is used for calculating a residual life interval; and the evaluation result output module is used for outputting a prediction result. According to the method, the improved Zhang-Suen refinement algorithm and the multi-dimensional degradation hierarchical expression structure are combined, so that accurate state evaluation and life prediction of the highway sensing equipment are realized.

This application relates to a method, apparatus, equipment, and medium for extracting three-dimensional phenotypic parameters from plant leaves. The method includes: using Poisson surface reconstruction technology to perform geometric domain smoothing on the pose-standardized point cloud of plant leaves; fusing the local point density and principal component curvature features of the plant leaf point cloud; combining the color texture information mapped from the plant's RGB image; and enhancing the vein signal through nonlinear power function transformation to construct candidate vein data. The candidate vein data is then binarized using the Otsu dynamic threshold segmentation algorithm to extract the target vein region of the target plant leaf. The vein topology skeleton within the target vein region is extracted using the Zhang-Suen thinning algorithm. Based on the vein topology skeleton, the leaf length and width of the target plant leaf are calculated, and the vein density per unit area of ​​the target plant leaf is determined according to the leaf area and the total length of the vein branches. This application allows for phenotypic parameter extraction without leaf harvesting, avoiding measurement errors caused by water loss and curling of leaves after detachment.

The present application relates to a kind of circular pointer type instrument pointer fitting and instrument reading identification method, belong to image recognition field.The present application simultaneously divides the pixel area of scale value and pointer in instrument panel using semantic segmentation method;Using the method of image classification to identify scale value, determine the rotation center of pointer;The skeleton thinning algorithm and least square method are used to the pointer pixel area generated by segmentation to fit the straight line equation of pointer, determine the direction of pointer;Using multiple scale values weighted calculation pointer reading.The present application can automatically fit the straight line equation of pointer, consider multiple scale values to calculate instrument reading, it is advantageous to improve the precision of pointer instrument reading identification.

The application discloses an OCTA-based image processing method, comprising the following steps: acquiring an OCTA angiogram; pre-processing the OCTA angiogram; performing image segmentation on the pre-processed OCTA angiogram; extracting a blood vessel skeleton from the image segmented OCTA angiogram; and performing parameter measurement based on the extraction result. The OCTA-based image processing method can accurately obtain the skeleton and boundary of the blood vessel by performing a thinning algorithm and branch point detection on the binary image, and can split the blood vessel tree into single-section branch blood vessels, so that the measurement process of each branch blood vessel is simplified and unified, and the efficiency and accuracy of the measurement are ensured.

The application relates to a paper electrocardiogram digitization method and device, which comprises the following steps: pre-processing an electronic image of a paper electrocardiogram containing twelve lead regions to obtain an electrocardiogram image; separating each lead region of the electrocardiogram image; based on an eight-neighborhood sparse outlier removal algorithm and a pre-stored refinement algorithm, refining the electrocardiogram image of each lead region to obtain an electrocardiogram waveform curve of each lead region; and connecting the electrocardiogram waveform curves of each lead region in the lead dimension to obtain a digitization result of the paper electrocardiogram. The application converts the paper electrocardiogram produced continuously into an electronic electrocardiogram in a manner of digitizing the effective information of the electrocardiogram signal of the paper electrocardiogram, solves the problem of insufficient electronic electrocardiogram volume, and promotes the development of the automatic electrocardiogram analysis field.

The invention relates to the technical field of palm vein safety identification, and discloses a high-safety scene-oriented non-inductive identity verification and closed-loop management method and system.The high-safety scene-oriented non-inductive identity verification and closed-loop management method comprises the following steps: acquiring a palm vein image of a user through near-infrared imaging equipment; a Frangi blood vessel enhancement filter and a morphological refinement algorithm are utilized to extract a blood vessel skeleton of each part, and an individual vein topological map including bifurcation point coordinates, blood vessel curvature and a relative topological connection relation is constructed based on the blood vessel skeleton. According to the method, a user does not need active cooperation, pause and specific gestures, identity verification is automatically completed in the natural operation process, service flow is embedded in the verification process, operation is verification, the working efficiency is remarkably improved, identity inference is still conducted through forearm or upper arm veins, and palm recognition with arms is achieved by means of a graph neural network cross-region mapping model.

The application discloses a composite material reinforcing body length calculation method and device based on image processing, and the method comprises the following steps: obtaining a composite material organization image, processing the composite material organization image to obtain a reinforcing body image with a single composite material reinforcing body, processing the reinforcing body outer contour of the reinforcing body image by adopting a skeleton thinning algorithm to obtain a first reinforcing body skeleton, performing point-by-point detection based on the first reinforcing body skeleton, and removing redundant points to obtain a more accurate second reinforcing body skeleton. The front moving method is adopted to extract the reinforcing body axis in the second reinforcing body skeleton, and the longest one in the reinforcing body axis is found as a reinforcing body main axis for calculating the reinforcing body length. The method is simple, the calculation amount is small, the reinforcing body main axis obtained can better reflect the main part of the reinforcing body length, and the shortest distance between the reinforcing body main axis two end points and the reinforcing body outer contour makes the calculation of the reinforcing body length more accurate.

The invention belongs to the technical field of metal materials, and discloses a metal structure wear grade identification method and related equipment, which improve the microscopic wear image quality through image preprocessing, obtain accurate and effective edge information in combination with edge detection and a morphological refinement algorithm, lay a reliable foundation for subsequent identification, and improve the identification efficiency. And experienced technicians do not need to participate in visual observation, so that the influence of personal experience difference on a judgment result is avoided, and the objectivity and consistency of an identification result are remarkably improved. Meanwhile, wear level characteristic parameters are extracted in a targeted mode, a recognition model containing edge characteristics and wear characteristics is adopted, multi-dimensional characteristics are fully fused, the algorithm is matched for precise processing of images, the limitation of the precision of a traditional measurement tool and the technical level of operators is broken through, high-precision wear related data can be obtained, and the precision of the measurement tool is improved. And the recognition pertinence and reliability can be improved, and the accuracy of wear grade recognition is guaranteed.

The application relates to the technical field of palm vein security identification, and discloses a high-security-scene-oriented non-sensing identity verification and closed-loop management method and system, wherein the high-security-scene-oriented non-sensing identity verification and closed-loop management method comprises the following steps: collecting a user palm vein image through a near-infrared imaging device, extracting a blood vessel skeleton of each part by using a Frangi blood vessel enhancement filter and a morphological thinning algorithm, and constructing an individual vein topological atlas including bifurcation point coordinates, blood vessel curvatures and relative topological connection relationships based on the blood vessel skeleton. The user does not need to actively cooperate, does not need to pause and does not need a specific gesture, and the identity verification is automatically completed in a natural operation process, the verification process is embedded in a business flow, operation is verification, work efficiency is significantly improved, and identity inference is still performed through a forearm or upper arm vein, and the palm is identified by means of a graph neural network cross-region mapping model.

The invention provides a DSM construction method considering topographic features, and the method comprises the following steps: selecting a collection region with representative topographic region feature information, carrying out the point cloud data collection and preprocessing, and carrying out the initial division of a point cloud based on an elevation threshold value; thinning the ground point candidate set obtained through primary division by adopting a point cloud data thinning algorithm considering topographic features; combining the non-ground point candidate set and the thinned ground point candidate set, filtering the combined point cloud by adopting a progressive TIN encryption filtering algorithm, and segmenting ground points and non-ground points; building point clouds are segmented from non-ground points based on the elevation texture information, building contours are extracted and subjected to geometric regularization processing, and the building point clouds are optimized based on the building contours subjected to the regularization processing; and constructing a DSM based on the ground points obtained by filtering and non-ground points including the optimized building point cloud, and performing multi-resolution organization by adopting a detail level model technology to realize rapid reconstruction display of the DSM.

This invention discloses a method for generating nonlinear frequency modulation (FM) signals based on a thinning algorithm, comprising the following steps: S1, designing a nonlinear frequency modulation function to obtain a discretized FM function curve; S2, constructing a piecewise linear frequency modulation function based on the Douglas-Pock thinning algorithm, such that the piecewise linear frequency modulation function approximates the ideal nonlinear FM function with a given approximation error; S3, calculating the pulse compression coefficient and frequency control word of the corresponding piecewise linear FM signal based on the approximation result of the nonlinear FM function, and compressing and storing the frequency control word data; S4, generating the piecewise linear FM signal based on DDS according to the frequency control word in the storage space. This invention employs the above-mentioned method for generating nonlinear FM signals based on a thinning algorithm to achieve a smaller approximation error in the FM curve and a better pulse compression effect.

The invention discloses a sweet potato seedling stem length estimation method based on deep learning and application, belongs to the technical field of agricultural automation, and aims to solve the problem that continuous stems cannot be accurately extracted by a traditional image segmentation and template matching method due to the fact that sweet potato stems are often shielded by leaves or naturally bent. The stem length estimation method comprises the following steps: S1, data acquisition and labeling; s2, model training; s3, main stem reconstruction; s4, calculating the length of the main stem; wherein the operation of the main stem reconstruction in the step S3 is as follows: S3.1, carrying out binaryzation on the fine mask subjected to semantic segmentation in the step S2.2, and then generating a skeleton by using a Zhang-Suen refinement algorithm; and S3.2, extracting skeleton intersection points, segmenting the skeleton intersection points into discrete line segments, combining PCA principal direction analysis and curvature constraint, and then dynamically searching and repairing a main stem. The method supports shielding (blade shielding middle section), bending, low-density cluster and other complex scenes, and the robustness is remarkably improved; experimental test results show that the processing time of a single image is 0.53 seconds, and the field real-time requirement is met.

The invention discloses an open type soft pen calligraphy character three-fork skeleton precise segmentation method based on position classification, and relates to the technical field of calligraphy digital processing, and the method comprises the steps: carrying out the binary preprocessing of a soft pen calligraphy image, obtaining a Chinese character skeleton through a Zhang-Suen refinement algorithm, and defining a three-fork angular point and a three-fork skeleton; dividing the multi-structure Chinese character into a single structure, and classifying according to the number and position distribution of three-fork skeleton points in the single structure; and finally, for a single structure of one, two or more than three trifurcate skeleton points, combining parameters such as skeleton path length, tangent value and the like to formulate a differential segmentation and retention rule. The method adapts to the stroke width change characteristics of soft pen calligraphy, solves the problems of stroke splitting and skeleton reconnection in a traditional method, assists the robot in track adjustment, realizes smooth stroke transition, and improves the copying precision.

The application discloses a kind of multimodal dance teaching interaction methods, including the dance action video stream of target object acquisition.First, video key point is processed using subpixel interpolation and median filter, and IMU data is compensated for drift using Kalman filter, effectively eliminating sensor noise and occlusion interference, achieving high-precision three-dimensional pose reconstruction;Using dynamic time warping (DTW) algorithm and limiting search path slope, the problem of non-linear alignment of action speed and music beat is solved, and the action deviation calculation is more consistent with the laws of human kinematics by using the weighted scoring formula containing space, time and audio dimensions;Through the construction of user historical feature matrix for cluster analysis, the scoring tolerance and teaching difficulty can be dynamically adjusted, personalized teaching is realized, and comprehensive and in-depth dance guidance is provided for users.