46 results about "Contour set" patented technology

The present application provides a model printing method based on a 3D printing device, an electronic device, and a storage medium. The method comprises: acquiring shape parameters of a model to be printed and, on the basis of the shape parameters, acquiring a contour set of the model to be printed; receiving a separation line characteristic parameter and, on the basis of the separation line characteristic parameter, generating a separation plane of the model to be printed; on the basis of the separation plane and the contour set, dividing the model to be printed into multiple sub-models to be printed; receiving a model printing sequence, and, on the basis of the model printing sequence, sequentially printing the multiple sub-models to be printed.

The invention discloses a laser processing path optimization method and a related device, and relates to the field of automobile manufacturing. Acquiring a plurality of contours from the part contour image; acquiring a contour nesting inclusion relation corresponding to the plurality of contours; obtaining a plurality of contour groups based on contour nesting inclusion relationships corresponding to the plurality of contours; obtaining adjacent contour candidate sets corresponding to the plurality of contours respectively; for each contour, dividing a target contour in the adjacent contour candidate set corresponding to the contour into an adjacent contour set; for each contour, acquiring a key point of which the mask attribute is true from the key points corresponding to the contour as a mask key point; and on the basis of the feature vectors, the distance matrixes, the cross matrixes and the adjacent contour sets corresponding to the multiple contour sets, the efficient laser cutting tool path corresponding to the part contour image is obtained. Therefore, the purpose of obtaining the efficient laser cutting tool path is achieved.

The invention discloses a path planning method and device for non-entity support of parts, equipment and a medium, relates to the technical field of additive manufacturing, and aims to solve the problems that the data volume of a slice contour point set for non-entity support of existing parts is large, and the number of times of switching-off and switching-off is large during printing. The method comprises the following steps: acquiring a three-dimensional model and a slice thickness of a non-entity support of a part; according to the slice thickness, extracting intersecting line segments of each triangular patch and each slice plane in the three-dimensional model to obtain a data set; performing duplicate removal and sorting processing on points in the data set to obtain a first slice contour set; deleting collinear data points meeting a preset collinear condition in the first slice contour set to obtain a second slice contour set; and performing gap filling on the second slice contour set by adopting an open contour stitching algorithm to obtain a third slice contour set. The path planning method for the non-entity support of the part is used for reducing the data volume of the section contour point set for the non-entity support of the part and reducing the number of times of printing light interruption.

The invention provides a three-dimensional measurement method and device for material deformation response in a high dynamic scene, and relates to the technical field of detection based on optics, and the method comprises the steps: obtaining a static contour of a to-be-measured material and a plurality of dynamic contours of the to-be-measured material at different loading moments through a material profile deformation measurement unit erected outside a load influence area; calculating a difference value between the dynamic contour and the static contour at each loading moment, taking the difference value as a material response deformation quantity at the corresponding moment, and integrating the material response deformation quantities at each loading moment to obtain a material response deformation contour set; and according to the material response deformation contour set and the attention moment determined by the load type, determining material response three-dimensional deformation information. According to the invention, the whole-process three-dimensional deformation information of the to-be-detected material under the influence of the load is determined through the material profile deformation measurement unit erected outside the load influence area, and a new normal form is provided for non-contact detection.

The application relates to a region detection method and device, computer equipment and a computer readable storage medium. The method comprises the following steps: obtaining a layer design diagram of a forming layer of a circuit board; the circuit board comprises a plurality of circuit board blocks, the forming layer is a layer comprising a block contour of each circuit board block, and the block contour comprises an inner contour and an outer contour of the circuit board block; contours in the layer design diagram of the forming layer are extracted to obtain a contour set; the contours in the contour set correspond to associated contour information, the associated contour information of the contour is used for representing sub-contour information and parent contour information of the contour; contours with associated contour information satisfying preset associated contour information are selected from the contour set to obtain inner contours corresponding to each circuit board block respectively, and the regions of the circuit board blocks are determined based on the inner contours corresponding to each circuit board block respectively. The method can improve the efficiency of determining the regions of the circuit board blocks.

The application discloses a railway outdoor signal device monitoring system based on computer vision and relates to the technical field of computer vision, comprising: a data synchronization module, which collects device images and synchronously monitors data; a contour evolution module, which constructs an improved Chan-Vese model, generates a device optimized contour set and a device boundary point set; a structure manifold module, which uses the Nystrom method for low-rank approximation and calculates a device structure manifold offset value; a visual coupling module, which generates a visual current coupling offset; a topological drift module, which constructs a device time sequence topological drift graph and generates a device state drift feature; and a state judgment module, which determines a device fault grade result. Through the introduction of the improved Chan-Vese model and the Nystrom method, the application realizes the accurate monitoring and early fault identification of the structural change, electrical change and continuous operation state evolution process of the railway outdoor signal device.

The invention relates to a construction method and system of a surface contour line model. The construction method comprises the following steps: S1, determining at least one ground object of a plant, and dividing the plant according to the number of the selected ground objects to form sub-plants; s2, according to the record of the factory file, screening the geometries belonging to each sub-factory, and leaving the geometries meeting a predetermined elevation condition; s3, simplifying the factory file according to a mode of only retaining the elevation of the sub-factory and the geometry meeting the predetermined elevation condition, and outputting the factory with the geometry meeting the predetermined elevation condition; and S4, carrying out fusion on the generated ContoursNew contour line set and the topographic file. The construction system can execute the construction method and comprises one or more of the following hardware: a data loading module, a space calculation module, a graphic processing unit and a storage array.

The application provides a method for judging the feasibility of inclined three-dimensional printing of a shell model, comprising: slicing an STL model to be judged according to a given inclination angle, placing the inclined slice horizontally, and obtaining the contour data of the horizontal slice; respectively biasing each contour in each slice layer inward and outward, and performing Boolean intersection operation to obtain the multi-fork tree structure contour set of each contour; and judging whether the contour in each slice layer can be stacked in a certain connected region in the multi-fork tree structure contour set of the slice layer below, and further judging whether the model can be printed in an inclined manner. The judgment method of the application is aimed at the printing structure of a shell mold, can quickly judge the feasibility of inclined printing according to the mold slice information, can assist the operator of the printer to set the model placement posture, select a suitable slice angle, and reduce the printing trial and error cost; and the judgment method of the application has wide applicability, high efficiency and strong stability.

The invention provides a scatter diagram generation method based on an object contour diagram, and belongs to the technical field of graphic processing, and the method comprises the steps: contour preprocessing: carrying out the smooth denoising processing of a contour diagram, carrying out the Gaussian blurring of the contour diagram, converting the contour diagram into a binary image, extracting a contour set of a connected region in the binary image, and carrying out the Gaussian blurring of the contour image; calculating the surrounding area of each contour and carrying out noise filtering; uniform sampling and initial scatter point generation: constructing a pixel point set, and calculating a maximum distance and a minimum distance of sampling; and scatter-contour matching optimization: traversing the contour line and the scatter set, and eliminating interference scatters to obtain a final scatter diagram of the object contour. Through the methods of uniform sampling, contour point matching, repeated point de-duplication and the like, a specified number of uniformly distributed scatter points can be quickly generated for a contour map. According to the method, the defect of scatter point generation in the current method is overcome, model training is not needed, generalization is high, and the method can be widely used in profile diagrams of various graphs.

The application relates to a high-precision map double-yellow-line post-processing method and device and electronic equipment. The method comprises the following steps: obtaining a semantic segmentation result of high-precision map data, and extracting an initial contour set from the semantic segmentation result; the initial contour set comprises candidate contours corresponding to double yellow lines; the shortest Euclidean distances between all candidate contours in the initial contour set are calculated, and according to the distance calculation result and a preset adhesion threshold, a pair of adhesion contours is determined from the candidate contours; for each contour in the pair of adhesion contours, the corresponding two contours in the pair of adhesion contours are translated by a preset translation amount in the normal direction of the contour, and a separated contour set is obtained; and a double-yellow-line geometric element is generated according to the separated contour set. The scheme provided by the application can effectively solve the misrecognition and missed detection problems of double yellow lines caused by pixel adhesion in complex scenes such as bad weather, improve the double yellow line recognition accuracy and data integrity, and further improve the production accuracy of the high-precision map.

The invention belongs to the field of 3D printing, and provides a 3D-printing-oriented in-situ material injection printing method and system.The 3D-printing-oriented in-situ material injection printing method comprises the steps that slicing is conducted on the basis of a requested three-dimensional model to obtain a contour set, and a dependency graph is generated with each contour in the contour set as a node and the dependency relationship between the contours as edges; reducing the complexity of the dependency graph based on geometric branch features of the request three-dimensional model to obtain a simplified dependency graph; based on the simplified dependency graph, searching an optimal manufacturing sequence by using a beam search algorithm; traversing all contours downwards from the top of the requested three-dimensional model, and calculating a to-be-filled area of each contour and the capacity required by each injection; and performing injection printing manufacturing on the requested three-dimensional model according to the optimal manufacturing sequence, the to-be-filled area of each contour and the capacity required by each injection. According to the method, on the premise that manufacturing feasibility is guaranteed, the execution sequence of 3D printing and material injection can be optimized, and therefore the overall manufacturing efficiency is improved.

The invention relates to the technical field of image processing, in particular to a part defect recognition and detection method and system based on an image model. The method comprises the following steps: acquiring a grating image of the surface of the piston ring through an industrial camera, and recording the grating image as a to-be-detected piston ring grating image; extracting a closed contour of a linear defect in the to-be-detected piston ring grating image, and generating a geometric defect contour set; extracting continuous areas of planar defects in the grating image of the piston ring to be detected, and generating a texture defect area set; and positioning an overlapping region of the geometric defect contour and the texture defect region based on the geometric defect contour set and the texture defect region set. According to the method, the boundary features of the composite defects can be clearly identified, misjudgment caused by the fact that a traditional algorithm depends on a single feature threshold value is avoided, and the technical problem that multiple types of defects concurrently interfere in a microcosmic area is effectively solved.

The invention discloses a sports equipment monitoring management method and system based on the Internet of Things, and belongs to the technical field of equipment supervision. The method comprises the following steps: collecting an initial vector of sports equipment during lending and storing the initial vector to a block chain; during returning, performing special outline separation according to the type of the sports equipment, and outputting an outline set with a label; extracting a deformation parameter and a texture entropy from the labeled contour set, and outputting a first damage probability through a convolutional network; obtaining a sports equipment placement process video during returning, and outputting a second damage probability; and obtaining a comprehensive use probability according to the first damage probability and the second damage probability, generating a manual review sampling inspection sequence, and giving an alarm. According to the method, through rod body direction filtering and racket surface grid reconstruction of special contour separation of the net racket type equipment, high-precision segmentation of stacked equipment is achieved, and the problem that in the prior art, due to stacking and overlapping of latticed equipment such as badminton rackets, recognition errors are caused is solved.

The present invention relates to an automatic extraction method, system and device for the time-frequency characteristics of marine mammal whistle signals, belonging to the technical field of signal processing. The method of the present invention includes noise reduction preprocessing, calculating the time-frequency spectrogram of the signal, manually selecting points and positioning, and obtaining a candidate contour set; judging the contour trend and linear fitting; extrapolating and correcting the starting point and the ending point. The present invention also provides a system and a device for running the method. The method of the present invention has better anti-interference ability and effectively improves the accuracy of contour extraction.

The present application relates to the field of image and video compression technology, and more particularly to a semantic contour generation type image coding method based on key point optimization, comprising obtaining an image to be processed and inputting a visual language model and an instance segmentation model respectively to generate an overall text description and a complete contour mask; inputting the complete contour mask into a VQ-VAE encoder to output a codebook index sequence set; for the complete contour mask, a differentiable model based on Gumbel-Softmax is used to adaptively select a group of key points; a VQ-VAE decoder generates a preliminary reconstructed contour according to the codebook index sequence set; a lightweight optimization network performs geometric correction and refinement on the preliminary reconstructed contour based on the key points to obtain an optimized contour; and the optimized contour and the overall text description are taken as control conditions to generate a high-quality reconstructed image through a conditional generation model; and the present application replaces a non-structured global pixel edge map with a structured contour set to eliminate redundant edge information in the background and the object interior.

The embodiment of the invention provides a method for determining a three-dimensional marked area of a target object and a related device. The method comprises the following steps: acquiring a contour set of a target object, wherein the contour set comprises object contours of the target object on a plurality of first sections of a three-dimensional image; determining a plurality of contour point groups based on the contour set, each contour point group comprising a single contour point on each object contour in the contour set, and for a first contour point on a current first tangent plane and a second contour point on an adjacent first tangent plane adjacent to the current first tangent plane in each contour point group; the first contour point is a contour point which is closest to the second contour point in a first target direction parallel to the plurality of first tangent planes in the contour points on the current first tangent plane; generating an envelope line based on each of the plurality of contour point groups; and determining a three-dimensional marking area containing the target object based on the contour set and the generated envelope line. According to the scheme, the accuracy and efficiency of determining the three-dimensional marking area can be improved.

The invention discloses a workpiece defect detection method and system based on sub-pixel features, and relates to the technical field of defect detection.The workpiece defect detection method comprises the steps that a machine vision device is used for collecting a workpiece image, an edge contour set of a workpiece is obtained, and the workpiece is divided into edge lines of different categories; the method comprises the following steps: performing data set division on historical workpiece defect data according to different edge line categories, performing image segmentation and morphological processing on defect samples in each historical workpiece defect data set, obtaining defect areas, performing sub-pixel-level edge extraction, and analyzing symbolic defect sub-pixel features in defect edges; after a to-be-detected workpiece image is preprocessed, a region of interest is selected for sub-pixel-level edge extraction, and the similarity between the sub-pixel-level edge of the region of interest and the sub-pixel features of the symbolic defect is calculated; and judging defect information of the workpiece according to the similarity. According to the invention, the edge is accurately positioned through sub-pixel-level edge detection, the detection precision is improved, and high-precision rapid detection of workpiece quality is realized.

The present application provides a model segmentation method for 3D printing, an electronic device, and a storage medium. The model segmentation method for 3D printing provided in the present application comprises: loading a 3D printing model, and acquiring all triangular facets and all vertex data of a selected area of the 3D printing model; obtaining edges of all the triangular facets on the basis of all the triangular facets and all the vertex data; determining a sub-model set on the basis of the edges of all the triangular facets, wherein the sub-model set comprises a plurality of sub-models, and the sub-models comprise a plurality of triangular facets having topological relationships; and setting a corresponding color for each sub-model, performing slicing on the sub-model set to obtain a contour set, and partitioning the contour set on the basis of the color corresponding to each sub-model to obtain a partitioned contour set.

The embodiment of the invention provides a method for determining an adjacency relation between spatial contours, a method and device for determining a spatial adjacency matrix, a computer readable storage medium and electronic equipment, and relates to the technical field of data processing. The method comprises the steps that a target contour set corresponding to the ith contour is obtained, a first relation and / or a second relation exists between the jth contour and the ith contour in the target contour set, the first relation is that the two contours have a shared boundary on the boundary and the internal spaces are not overlapped, and the second relation is that the two contours are partially overlapped on the internal spaces; obtaining an intersection between the boundary of the i-th contour and the j-th contour; obtaining objects of which the types are line segments in the intersection, and obtaining a target boundary; and if the length of the target boundary meets a preset condition, determining that the two space contours are adjacent to each other. According to the embodiment of the invention, the judgment accuracy of the adjacent state between the contours can be improved, and the generation of a more reasonable space adjacent matrix with more practical application significance is facilitated.

The application provides a 3D printing data processing method, system, device and medium of a porous implant. The method comprises: slicing a three-dimensional model of the porous implant to generate an initial two-dimensional cross section; extracting a solid contour in the cross section and calculating a solid area ratio and a cross section shape complexity parameter thereof; based on the parameters, classifying the solid contour into a first contour representing a junction and a second contour representing a strut; based on the distribution state of the first contour in each cross section, assigning a target slice layer thickness to a corresponding height interval and performing re-slicing; simplifying the first contour and the second contour in the re-sliced cross section respectively, and the simplification accuracy of the first contour is higher than that of the second contour; and generating printing data based on the simplified contour set. The application can reduce the consumption of computing resources and ensure the mechanical forming strength at the junction.

The application discloses a k representative G-Skyline query method, comprising the following steps: S1, preprocessing a whole data set D to be queried to obtain an ordered contour set SKY(D)={s1, s2,..., s n}; S2, constructing a dominance relation graph according to the whole data set D to be queried; S3, constructing a dominance order graph based on a replacement strategy and an expansion strategy; S4, pruning a set of data tuples in the dominance order graph which cannot become a k representative G-Skyline query result according to a pruning strategy; and S5, returning a set of the first k data tuples with the largest dominance area in the pruned dominance order graph as a final result, so that the problem of high calculation cost in the existing k representative G-Skyline query method is solved.

Embodiments of the present disclosure provide a monocular vision-based robot obstacle avoidance method, system, device and medium, comprising: outputting a category label of a target obstacle through a deep learning model for target detection on a target image taken for a target scene where a robot is located; performing contour extraction on the target image to obtain a closed contour set of the target obstacle; in a target region of interest, filtering the closed contour set based on a geometric constraint criterion to obtain a plurality of target feature samples; performing geometric ranging calculation according to the category label and a sample average pixel area of the plurality of target feature samples to obtain a real-time distance between the robot and the target obstacle; when the real-time distance is less than or equal to a safety threshold, comparing an area difference rate between a preset central region of interest and a side region of interest with a difference rate threshold, determining a planar spatial distribution trend of the target obstacle and determining a target obstacle avoidance strategy. The reliability of robot obstacle avoidance can be improved.

The invention relates to a method, a system and a device for automatically extracting time-frequency characteristics of marine mammal whistle signals, and belongs to the technical field of signal processing, and the method comprises the steps of noise reduction preprocessing, signal time-frequency spectrogram calculation, manual point selection and positioning, and candidate contour set acquisition. Performing contour trend judgment and straight line fitting; extrapolating and correcting the starting point and the ending point; the invention further provides a system and a device for operating the method. The method has better anti-interference capability, and the accuracy of contour extraction is effectively improved.

The invention discloses a classification method and system for identifying GIS equipment parts based on X-ray detection images. The classification method comprises the following steps: respectively establishing contour sets M1, M2... M6 of a circuit breaker, an isolating switch, a grounding switch, a mutual inductor, a lightning arrester and a bus structure which form GIS equipment; the method comprises the following steps: inputting and identifying an original image IOriginal, and carrying out preprocessing including graying and denoising on the original image IOriginal to obtain a target image Itarget; a step of extracting an edge contour m0 in the target image Itarget based on a Canny edge detection algorithm, normalizing the contour, and comparing whether the contour m '0 normalized by the step STP500 belongs to contour sets M' 1, M '2... M' 6 by adopting similarity measurement; according to the method provided by the invention, the contour set M for each part (such as a circuit breaker, an isolating switch, a grounding switch, a mutual inductor, a lightning arrester and a bus) of the GIS equipment is established, so that the different parts can be accurately classified. Compared with a traditional image recognition technology, the classification method can effectively reduce the possibility of misrecognition and improve the classification accuracy.

The invention discloses a piston top valve pit detection method and device based on image recognition, and particularly relates to the technical field of valve pit detection. The method comprises the following steps: acquiring a multi-angle polarization image sequence at the top of a piston, and carrying out lens distortion correction and gray scale unification processing to form a standard polarization image set; calculating a polarization degree image and a polarization angle image pixel by pixel based on the standard polarization image set, and fusing to generate a polarization reflection feature map; segmenting a sediment area at the top of the piston by adopting a polarization consistency constraint method based on the polarization reflection characteristic pattern, and outputting a sediment mask pattern; extracting candidate boundaries of the valve pit at the top of the piston by adopting an edge curvature continuity constraint method based on the polarization reflection feature map and outputting a candidate contour set; and carrying out space overlap suppression and contour continuity completion processing on the sediment mask pattern and the candidate contour set to obtain a real contour of the valve pit without sediment interference, calculating position coordinate parameters and size parameters of the valve pit, and generating a detection result of the valve pit at the top of the piston.

The invention relates to the technical field of spatial data analysis, in particular to a contour line drawing method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the spatial smoothing of input two-dimensional lattice point field data through employing a Gaussian separable convolution mode based on a set smoothing scale parameter, and obtaining a smoothed lattice point field; and based on the smoothed grid point field data, generating a contour line set through contour line tracking and spatial topology analysis. According to the method, high-efficiency smoothness is realized through Gaussian separable convolution, the innermost contour line is automatically identified based on topology analysis, intelligent labeling of high-voltage and low-voltage centers is realized in combination with regionalized extreme value extraction and spatial overlay analysis, and the data is greatly compressed while the precision is ensured by adopting third-order Bezier curve fitting, so that the accuracy of the high-voltage and low-voltage centers is ensured. And finally, the contour line with smooth vision and clear structure is output, and the visualization quality and the automation level are improved.

Provided in the present application are a multicolor printing slicing method, an electronic device and a storage medium. The multicolor printing slicing method provided by the present application comprises: acquiring original data of a 3D printing model, and loading the 3D printing model, the original data comprising a plurality of first triangular faces and first vertex data, and the 3D printing model having a first color; painting at least part of the first triangular faces of the 3D printing model with a second color; on the basis of the first vertex data, the first triangular faces and color data of each of the first triangular faces, generating model data; and slicing the 3D printing model on the basis of a preset height and the model data, so as to obtain contour sets, and dividing the contour sets on the basis of the color data to obtain divided contour sets.

The invention discloses a Raman temperature and humidity dynamic detection method based on self-adaptive light intensity adjustment, and belongs to the technical field of Raman detection. The method comprises the steps of collecting and processing spectral data to generate a preorder feature contour set, constructing a temperature and humidity parameter detection pair, simulating interference to generate a postorder feature contour set, analyzing contour feature parameters, calculating fluctuation, screening an optimal detection pair and feeding back. The system correspondingly comprises a spectral data acquisition and processing module, a temperature and humidity parameter configuration module, a feature contour analysis module, a fluctuation calculation and screening module and a feedback execution module. By dynamically adapting the optimal temperature and humidity parameter detection pair, the problem of insufficient detection precision caused by light intensity interference and low parameter matching degree in traditional Raman temperature and humidity detection is solved, manual intervention on parameter adjustment is not needed, the detection stability and efficiency are improved, and the method is suitable for various high-precision temperature and humidity detection scenes such as industrial production and environment monitoring.

The present invention relates to an image geometric feature extraction method for visual inspection of the size of an open clip. The specific steps are as follows: S1: binarizing an open clip image to obtain a binary image with a clear outline; S2: extracting a contour set from the binary image to obtain a contour point set; S3: extracting a convex hull from the contour point set, and calculating the minimum enclosing circle of the convex hull point set to obtain the center and outer diameter; S4: extracting inner arc feature points using the contour point set and the convex hull point set, calculating the distance between the center and the inner arc feature points to obtain the inner diameter; S5: adaptively segmenting the contour point set to calculate the opening distance; S6: searching and determining a bayonet straight line based on the opening feature points, searching for edge points, and calculating the bayonet width; S7: comparing the outer diameter, inner diameter, opening distance, and bayonet width obtained in S2 to S6 with the corresponding data of a standard open clip to determine whether the clip is qualified. The method can realize automatic measurement of the inner diameter, outer diameter, opening distance, and bayonet width of an open clip.

A computing device configured to receive at least a radiological image, encode, using an encoding module, a low-dimensional image as a function of the radiological image, wherein the encoding module is configured to preprocess the radiological image, generate a segmented representation of the radiological image by applying edge detection to the preprocessed radiological image, generate a reduced contour set by performing contour simplification and dimensionality reduction on the segmented representation, and generate a color-coded contour map by coloring coding one or more contours of the reduced contour set, and input the low-dimensional image into at least a machine learning process as training data.