7 results about "Contour segment" patented technology

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 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.

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 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.

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.