15 results about "Contour segment" patented technology

The invention relates to a robot drawing method, device and equipment and a storage medium, and is applied to the field of robot control. Contour extraction processing and skeleton extraction processing are carried out on the original image, a contour image is generated, the contour image comprises a plurality of contour segments, and each contour segment comprises a plurality of contour points; a Douglas-Peucker algorithm is adopted to simplify the number of contour points of each contour segment in the contour image, and a contour optimization image is generated; converting the image coordinate system of the contour optimization image into an actual coordinate system of preset paper according to the size of the preset paper; according to a contour screening threshold value, screening an optimized contour section in the contour optimization image, and according to the optimized contour section, generating a contour secondary optimization image; and controlling the robot to finish drawing in the actual coordinate system according to the outline secondary optimization image and preset drawing parameters. The method has the technical effects that the drawing precision is guaranteed while the drawing efficiency of the robot is improved.

The invention relates to the technical field of medical image processing, in particular to an acupuncture guide system based on image registration. According to the method, the height parameter field of the human body surface three-dimensional model is established and the contour line density distribution is extracted, so that hierarchical division and density aggregation identification of morphological characteristics of a target area can be realized, and local geometric characteristic identification is carried out by carrying out tangential analysis on direction changes of continuous contour line segments and combining Gaussian curvature. According to the method, geometric abnormal point locations of the surface structure can be accurately calibrated, and an area with direction stability and geometric continuity can be discriminated in multi-point data in combination with a space consistency judgment mechanism in the normal direction, so that the space identification process is more robust, and the accuracy of the space identification is improved. Multi-feature re-check judgment of a fitting end point can be realized through density peak value and normal consistency dual screening, the spatial accuracy of a positioning point is guaranteed, and the consistency of structural continuity and visual guidance information can be considered through a path construction mode generated by combining an image registration result and image gradient information.

The application provides a tumor radiotherapy multi-modal image fusion method and system, which extracts an initial target region contour of a tumor and a set of all high metabolic voxels; determines the shortest spatial distance from each voxel in the set of high metabolic voxels to all contour points on the initial target region contour, and then generates a distance statistical histogram; identifies a far-end distance point cluster that is significantly separated from a main distribution cluster, separates a corresponding spatial outlier voxel cluster from the set of high metabolic voxels; on the initial target region contour, determines continuous contour points closest to the spatial outlier voxel cluster as a to-be-corrected contour segment; determines a displacement vector of each point on the to-be-corrected contour segment to the spatial outlier voxel cluster, adjusts the spatial position of the to-be-corrected contour segment according to the displacement vector, and obtains an optimized target region contour of the tumor. The scheme of the application can avoid definition distortion of the target region contour caused by main noise interference.

The invention relates to the technical field of contour recognition, in particular to a fast contour recognition method under a complex background, and the method comprises the steps: carrying out the contour recognition training under the complex background through employing a sample image, and collecting contour attribute data, so as to determine a plurality of first clear contour segments; determining a standard contour frame based on the performance parameters of the plurality of first clear contour segments; collecting contour attribute data of the image of the target detection area, and determining a plurality of second clear contour segments so as to determine a plurality of contour matching segments; determining whether to trigger quick matching or not based on the proportion of the contour matching section; determining the adjustment amount of the contour recognition optimization parameter based on the plurality of second clear contour segments; and processing the image of the target detection area by using the adjusted contour recognition optimization parameters, and obtaining a plurality of second clear contour segments again to determine whether to trigger rapid matching. According to the invention, the efficiency and accuracy of rapid contour recognition under a complex background are improved.

The invention relates to the technical field of image processing, in particular to an aluminum alloy pipe compression molding defect classification method. The method comprises the steps of obtaining a front surface image of a to-be-detected aluminum alloy shell obtained by performing extrusion treatment on an aluminum alloy pipe, and obtaining a first outer contour of the front surface image; determining a mass center of an outer contour pixel point of the first outer contour, and respectively determining central moments of different outer contour segments of the first outer contour relative to the mass center of the first outer contour; constructing a first feature sequence according to the central moments of different outer contour segments of the first outer contour, and obtaining a second feature sequence of the standard aluminum alloy shell; performing shift matching on the first feature sequence and the second feature sequence, and determining a contour defect value according to a DTW distance of a shift matching result; and classifying shape defects according to the contour defect values. By means of the technical scheme, classification of shape defects of the aluminum alloy shell made of the aluminum alloy pipe can be achieved.

The present application relates to the technical field of contour recognition, and particularly relates to a fast contour recognition method in a complex background, contour recognition training in the complex background is performed using sample images, contour attribute data is collected to determine a plurality of first clear contour segments; a standard contour frame is determined based on performance parameters of the plurality of first clear contour segments; contour attribute data of an image of a target detection region is collected, a plurality of second clear contour segments are determined to determine a plurality of contour matching segments; whether to trigger fast matching is determined based on a proportion of the contour matching segments; an adjustment amount of contour recognition optimization parameters is determined based on the plurality of second clear contour segments; the image of the target detection region is processed using the adjusted contour recognition optimization parameters, the plurality of second clear contour segments are reacquired to determine whether to trigger fast matching. The present application improves the efficiency and accuracy of fast contour recognition in a complex background.

Embodiments of the present application provide a bolt size measurement method and device, electronic equipment and storage medium. The method comprises calibrating a camera for shooting a bolt; acquiring an image of the bolt shot by the camera, and identifying a thread edge contour area of the bolt from the image; performing feature extraction on the thread edge contour area to obtain a thread contour of the bolt; segmenting the thread contour by using an improved adaptive DP algorithm to obtain a plurality of contour segments; fitting the contour segments by using a Hough transform to obtain a smooth thread contour; detecting an angular point of the curvature corresponding to the smooth thread contour based on an optimized FRPD algorithm; and fitting the angular point by using a least square method transformation to calculate the size of a major diameter and a minor diameter of the thread of the bolt. Based on this, the bolt size measurement method of the embodiments of the present application has high measurement accuracy, accuracy and real-time performance, and can be used for detecting the size of bolt parts in the field of mechanical equipment manufacturing.

The invention provides a graph modeling method and device, a storage medium and computer equipment, and the method comprises the steps: carrying out the feature coding of each contour segment corresponding to a contour curve in a photoetching layout through a first neural network, and obtaining a segment structure feature vector corresponding to each contour segment; obtaining each arc length position parameter corresponding to the contour section; the arc length position parameter is used for indicating the corresponding arc length percentage of each sampling point in the contour section in the contour section; generating a sampling position vector corresponding to each sampling point by using a second neural network according to the arc length position parameter; determining a target coordinate corresponding to each sampling point in the contour segment by using a third neural network according to the segment structure feature vector and each sampling position vector; and according to each target coordinate corresponding to each contour section, determining a modeled curve corresponding to the contour curve.

This invention discloses a method for extracting human contour boundaries in complex scenes based on deep learning, comprising: acquiring the original scene image; processing it using a feature extraction model to obtain a multi-scale feature map, a coarse human contour probability map, and human skeletal information; performing topological analysis based on the feature map and probability map to obtain the contour segments to which limbs belong and occlusion sequence information; performing feature re-aggregation on the concave corner regions in combination with the skeletal information to obtain the concave corner recovery contour segment; inferring the geometric information of the occlusion break endpoints based on the contour segment and obtaining the endpoint geometric constraint parameters; and finally stitching together the above parameters and occlusion sequence information to output a human contour boundary map. This invention overcomes the problems of topological confusion and local geometric blunting under severe occlusion and pose overlap, and achieves human boundary reconstruction with high fidelity.

The embodiment of the invention relates to a measurement method and device and a storage medium. The method provided herein comprises: in an image having a measurement object, determining a reference start point and a reference end point for a first contour segment associated with the measurement object; determining a target path connected between the reference start point and the reference end point based on respective confidence levels of a plurality of pixels located between the reference start point and the reference end point in the image, where a confidence level of a pixel of the plurality of pixels indicates a likelihood of taking the pixel as part of the first contour segment; and determining a measurement result for the measurement object by measuring a second contour segment associated with the measurement object and a first contour segment generated based on the target path.

The application relates to the technical field of wafer defect measurement, and specifically discloses a wafer edge collapse size measurement method and device, a storage medium and computer equipment, the method comprising the following steps: obtaining a wafer image to be detected, detecting an edge collapse region of the wafer image to be detected, outputting an edge collapse defect region, and detecting a wafer region of the wafer image to be detected, and outputting a wafer contour; extracting a local contour segment corresponding to the edge collapse defect region from the wafer contour; determining a reference line based on a straight line where the local contour segment is located, measuring a maximum width in the edge collapse defect region and parallel to the reference line as a defect width along the wafer edge direction, and measuring a maximum depth in the edge collapse defect region and perpendicular to the reference line as a defect depth along the wafer radial direction. The application strictly aligns the measurement reference with the physical definition of manual wafer edge measurement through the local contour segment, aligns the automatic detection result with the rechecking result of the quality inspection personnel, and avoids systematic deviation caused by inconsistent measurement directions.

This application provides a method, apparatus, storage medium, and computer device for calibrating capacitive sensor signals. The method includes acquiring a first distance between a preset calibration position and the processed area of ​​each processed contour segment, and a second distance between the position and the workpiece edge. If the first distance is greater than or equal to a preset safety distance, and the second distance is greater than or equal to the preset safety distance, a real-time calibration mark P is marked at the preset calibration position. Timing is then performed on the nth processed contour segment. It is then determined whether the nth processed contour segment is complete. If so, the timing time T is compared with a preset detection interval B. If T ≥ B, it is determined whether the (n+1)th processed contour segment has a real-time calibration mark P. If the (n+1)th processed contour segment has a real-time calibration mark P, calibration is performed at the preset calibration position of the (n+1)th processed contour segment. The capacitive sensor signal calibration method provided by this application can achieve accurate calibration of capacitive sensor signals.

This application proposes an intelligent extraction and structured transformation method for holographic features of open-pit mine slopes, belonging to the field of intelligent slope feature technology. The method includes: establishing a color-coded parameter mapping model; assigning corresponding color attributes to each layer according to the parameter mapping model to generate a parsable digital slope file; extracting the slope's geometric shape from the digital slope file and calculating the bounding box of the slope region; performing meshing processing on the bounding box of the slope region, converting the data in the meshed bounding box into fixed-size three-dimensional mesh data; identifying the external contour line of the slope using a contour extraction algorithm based on the fixed-size three-dimensional mesh data; calculating the local dip angle of each contour segment based on the coordinates of adjacent points in the discrete surface point set; and performing semantic segmentation along the external contour line of the slope based on the local dip angle of each contour segment. This method solves the problem that slope features are difficult for computers to efficiently identify and use for deep learning.

The application relates to the technical field of image processing, in particular to an aluminum alloy pipe compression molding defect classification method. The method comprises the following steps: obtaining a front surface image of an aluminum alloy shell to be detected obtained by extruding an aluminum alloy pipe, and obtaining a first outer contour of the front surface image; determining the center of mass of outer contour pixels of the first outer contour, and respectively determining the central moments of different outer contour segments of the first outer contour relative to the center of mass of the first outer contour; constructing a first feature sequence according to the central moments of the different outer contour segments of the first outer contour, and obtaining a second feature sequence of a standard aluminum alloy shell; performing shift matching on the first feature sequence and the second feature sequence, and determining an outline defect value according to a DTW distance of a shift matching result; and classifying shape defects according to the outline defect value. Through the above technical scheme, the classification of shape defects of an aluminum alloy shell manufactured from an aluminum alloy pipe can be realized.

This invention relates to a method for collaborative simplification of roads and settlements, belonging to the field of digital mapping technology. The invention first uses Delaunay triangulation to extract the contour segments of adjacent settlements and the corresponding road segments. Then, it performs node matching on the extracted settlement contour segments and their corresponding road segments. Finally, it simplifies roads using constraint points, synchronizing the node selection of roads to the corresponding settlement contours based on the node matching results, thus achieving collaborative simplification. This invention establishes node-level associations between roads and settlements in adjacent areas through node matching, synchronizing the node selection of roads to the adjacent settlement contours, thereby achieving collaborative simplification. Compared to traditional road and settlement simplification methods, this invention effectively maintains the shape similarity and topological consistency between features, significantly reducing topological and shape conflicts.