11 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.

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.

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 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 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 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.

The application belongs to the technical field of new energy big data and remote sensing image application, and aims at the technical problems of low positioning accuracy of wind turbine space position and inability to accurately extract key physical parameters, and proposes a wind turbine physical parameter extraction and inversion method using satellite high-resolution images. The improved FAST R-CNN model is used for two-stage detection of wind turbines and bases on the data set, and the SAM3 large model is used for zero sample shadow segmentation. Combined with the skeleton thinning algorithm, six feature points including the three blade tip points, impeller center point, engine cabin end point and base are automatically extracted, realizing the automatic extraction and inversion of the spatial position, hub height, blade parameters and model type of the wind turbine, and providing technical support for the fine management and power prediction of the wind power plant.