15 results about "Edge matching" patented technology

The invention discloses a distributed urban and rural planning decision support method and system, and relates to the technical field of data analysis, and the method comprises the following steps: S100, drawing a planar graph of a to-be-planned region, dividing the planar graph of the region according to a Morse decomposition method, and constructing a region matrix, S200, calculating the coverage rate of the region matrix, and S300, calculating the coverage rate of the region matrix. And planning the surveying and mapping path. According to the method, planning units and surveying and mapping grids are unified into the same quadrilateral matrix through Morse complex, repeated zoning and edge matching errors are effectively avoided, the edge weight is inversely proportional to the building coverage rate, an unmanned aerial vehicle and a surveying and mapping vehicle automatically and preferentially encrypt a high built-up area, field working hours are saved, the data precision of a core construction area is guaranteed, and the construction efficiency is improved. The regional matrix naturally corresponds to edge nodes, and each node only communicates with an adjacent unit, so that the MST and the local route can be locally solved, the communication complexity is reduced, and the method is suitable for large-scale regional surveying and mapping.

The invention provides an edge matching positioning method and system. The method comprises the following steps: acquiring a real-time image and a reference image in a sample library; inputting the real-time image and the reference image into a pre-constructed region score model to obtain a matching calculation score output by the region score model; based on the matching calculation score, performing paraboloid fitting by taking a matching peak value and a neighborhood as sampling points to obtain a sub-pixel position offset; and adding the sub-pixel position offset to the coordinate value of the current matching position to obtain a final positioning position coordinate. The technical problem that the positioning precision of edge matching calculation is low is solved.

The application discloses a motor insert sheet defect detection method based on multi-sensor fusion, relates to the technical field of motor insert sheet defect detection, and comprises the following steps: in the presence of boundary penetration, calculating edge matching mismatch degree, edge jump rate, edge inversion proportion and edge closure deviation to form a geometric conflict feature set of an insert sheet edge, which is used for representing image geometric expression differences caused by boundary penetration; inputting the geometric conflict feature set into a fusion confidence evaluation function to obtain a fusion confidence evaluation factor, which is used for identifying whether the insert sheet edge has a fusion distortion risk. The application solves the structural expression conflict problem caused by boundary penetration in the multi-view imaging fusion process of the motor insert sheet, constructs a fusion confidence evaluation mechanism to identify the fusion distortion risk, dynamically limits the image participation fusion condition, and thus improves the recognition accuracy of the edge structure and the stability of the fusion result in the insert sheet defect detection.

The application discloses a shipping accident analysis method, comprising the following steps: constructing a shipping accident knowledge graph; inputting a question, searching the shipping accident knowledge graph by using a search enhancement generation method, and generating an answer; wherein the search enhancement generation method comprises the following steps: analyzing the question by using a large language model, generating a query statement, searching the shipping accident knowledge graph according to the query statement, outputting nodes and edges matched with the query statement from the shipping accident knowledge graph, generating a Bayesian network according to the matched nodes and edges, generating a query result according to the conditional probability of a target node and its parent nodes and / or the posterior probability of the target node and its child nodes in the Bayesian network, inputting the query result into the large language model, and generating an answer according to the query result by the large language model. The application further discloses a shipping accident analysis device, a computer device and a storage medium. By using a large language model combined with a knowledge graph to extract and store shipping accident data, and by using a Bayesian network analysis model to analyze the shipping accident data, the occurrence probability of a complete cause-and-effect chain from causes to results of an accident can be obtained, so that objective and accurate causes and effects of a complex shipping accident can be sorted out, and reliable conclusion opinions can be provided for subsequent shipping business.

The application discloses a photovoltaic array fault detection and positioning method based on bipartite graph matching, comprising the following steps: 1) based on the connection structure of a photovoltaic array, a photovoltaic array bipartite graph is established, and the connection points of components on the same photovoltaic component string constitute an independent node set in a sub-bipartite graph; 2) under the complete matching rule of the bipartite graph, the minimum edge covering rule and the constraint that equal-weight points in the bipartite graph are not connected, edge matching of the bipartite graph is derived, the edge is converted into a voltage sensor, and optimal configuration of the voltage sensor is obtained; 3) the fault voltage threshold of the photovoltaic component under different faults is calculated, the actual measured value of the photovoltaic component voltage collected by the voltage sensor is compared with the fault voltage threshold, and photovoltaic array fault detection and positioning are realized. The application realizes accurate detection and positioning of open-circuit, short-circuit, aging and shading faults of each photovoltaic component by using fewer voltage sensors, and the voltage sensor only needs to be connected between adjacent photovoltaic component strings, and is easy to operate.

The invention is suitable for the technical field of operation and maintenance management of Internet of Things equipment, and provides an Internet of Things equipment repair process management method and system and computer device.The method comprises the steps that on the basis of a directed graph structure, a repair process model comprising multiple nodes and multiple edges connected with the nodes is constructed in advance; binding an automatic task node in the repair process model with a task script, and respectively configuring circulation conditions for a plurality of edges led out from the automatic task node; when a repair request is received, creating a work order based on the repair request and starting a repair process instance; when the repair process instance flows to the automatic task node, automatically triggering and executing the task script bound with the repair process instance; and according to the received execution feedback data, a target edge with a transfer condition matched with the execution feedback data is decided in the repair process model, and the repair process instance is driven to transfer to a next node along the target edge. According to the invention, the problems of slow response and low efficiency of repair management of the existing Internet of Things equipment are solved.

The invention belongs to the technical field of surveying and mapping, and particularly relates to a multi-source digital elevation model splicing optimization method combining a third-order polynomial and a Bezier curve. The method is suitable for splicing DEM data obtained by unmanned aerial vehicle oblique photography and RTK measurement, and is especially used for solving the abrupt and discontinuous problems of heterogenous digital elevation model (DEM) data in an edge matching area due to inconsistent resolution and elevation precision. The method comprises the steps of data acquisition and conversion, grid resampling, overlapped region extraction and weighted splicing, third-order polynomial fitting processing, Bezier curve smooth correction and the like. Buffer areas are constructed on the two sides of the splicing line, a similarity threshold value is set, trend surface fitting and transition curved surface construction are guided, and the elevation continuity and the model smoothness of the splicing area are effectively improved. And finally, precision verification is carried out through a root mean square error (RMSE), and the consistency and availability of the spliced DEM in spatial expression are ensured.

The invention discloses a motor insert defect detection method based on multi-sensor fusion, and relates to the technical field of motor insert defect detection, and the method comprises the following steps: calculating an edge matching mismatch degree, an edge jump rate, an edge inversion ratio and an edge closing deviation under the condition of boundary interspersion, forming a geometric conflict feature set of insert edges, and calculating the edge matching mismatch degree, the edge jump rate, the edge inversion ratio and the edge closing deviation; the representation module is used for representing image geometric expression differences caused by boundary interpenetration; and inputting the geometric conflict feature set into a fusion confidence evaluation function to obtain a fusion confidence evaluation factor for identifying whether the edge of the insert has a fusion distortion risk or not. According to the method, the problem of structural expression conflict caused by boundary interpenetration in the multi-view imaging fusion process of the motor insert is solved, a fusion confidence evaluation mechanism is constructed to identify the fusion distortion risk, and the image participation fusion condition is dynamically limited, so that the identification accuracy of an edge structure and the stability of a fusion result in insert defect detection are improved.

This application discloses a method, apparatus, device, and storage medium for recognizing the edge contour of a graphic, relating to the field of machine vision technology. The method includes: image processing of an image to be recognized to obtain pyramid gradient images at different levels of the image; inputting the pyramid gradient images into a preset edge matching model to obtain a set of candidate points for the contour of a target graphic in the image to be recognized, wherein the preset edge matching model is a model trained based on sample images labeled with the target graphic using a sparse sampling method and an adaptive threshold segmentation method; and connecting the candidate points in the candidate point set to obtain the target graphic in the image to be recognized. In this application, the adaptive threshold segmentation method clearly distinguishes the contour of the target graphic from the contours of other graphics, and the sparse sampling method reduces the number of candidate points obtained. Therefore, the preset edge matching model can obtain a small number of accurate candidate points, thereby improving the accuracy of recognizing the target graphic using the matching method.

The application relates to the technical field of image change detection, in particular to a low-altitude unmanned aerial vehicle video frame extraction and orthographic image change detection method based on deep learning, which is characterized in that unmanned aerial vehicle video is acquired to perform frame-by-frame semantic segmentation and grid feature extraction, adjacent frame grid distribution is compared to screen change-related frames, spatial mapping of the change-related frames and orthographic images is constructed through edge matching, images are spliced according to positions and edge transition processing is performed to generate a continuous sequence, finally, new and old image ground categories are compared based on a geographic coordinate system, and video frame extraction and image change detection results are output. According to the application, grid time sequence description based on ground semantics is introduced, change recognition is converted into category evolution analysis with semantic meaning, key space-time regions with attribute transfer are focused, continuous image organization under a unified geographic reference is combined, content space continuity is ensured, result time sequence direction and spatial certainty are strengthened, and expression stability and explanation clarity of patrol change information are improved.

The invention discloses a multi-dimensional edge matching load identification method based on electricity utilization acquisition and breadth search, relates to the related field of load identification technologies, and aims to solve the core problem that the accuracy of power event detection and load state identification is seriously insufficient in the prior art. The method comprises the steps of firstly defining a load type, then dividing power slow change and sudden change by using first-order and second-order difference regions, extracting multi-dimensional edge features, designing a dynamic threshold adjustment mechanism, realizing multi-dimensional breadth-first search matching of a rising edge and a falling edge, and simultaneously extracting multi-dimensional load features to distinguish similar loads. And the load electricity consumption is planned and distributed in real time according to the breadth-first search result, and a set of full-flow technical scheme from power signal detection to load identification and energy consumption metering is formed. Accurate detection of a power event and effective identification of a full working state of a load are realized, the overall accuracy of non-intrusive load identification is improved from a core link, and a foundation is laid for subsequent load decomposition and accurate energy consumption metering.

The invention relates to the technical field of crossing of computer graphics, geographic information technology, digital twinning and intelligent traffic, and discloses a multi-source three-dimensional geographic information data fusion method and system, and the method comprises the steps: obtaining an oblique photography surface model to be fused, a fine three-dimensional structure model and a digital elevation model; obtaining a live-action model and a terrain model which are spatially aligned; respectively determining a first edge matching area and a second edge matching area based on the outline and the spatial position of the fine three-dimensional structure model; performing driving reconstruction related to the fine three-dimensional structure model on the terrain model; transitional deformation related to the fine three-dimensional structure model is carried out on the real scene model so that the deformed real scene model can be smoothly connected with the fine three-dimensional structure model in the second edge matching area; and integrating the fine three-dimensional structure model, the deformed real scene model and the reconstructed terrain model. According to the method, the seamless effect in the true geometric sense is achieved, and a reliable geometric foundation is laid for high-precision engineering application.

The application discloses a background knife-edge matching image acquisition device and a background schlieren image acquisition method, and belongs to the technical field of schlieren imaging. The background knife-edge matching image acquisition device uses a transparent background particle plate as a particle background of a background schlieren image, and places the transparent background particle plate in a knife-edge schlieren light path to form a fusion light path. The knife-edge schlieren image and the background schlieren image are integrated on the same fusion light path, so that the matching image between the background schlieren image and the knife-edge schlieren image under the same flow field and the same visual angle condition of a gas density disturbance flow field can be collected. Further, the image A and the image B are subjected to pixel difference value calculation and filtering to remove particle residual images, so as to obtain an image D which only carries the knife-edge schlieren image; the image A and the image D are subjected to difference value calculation and particle morphology enhancement to obtain an image E which only contains particle information, and then particle displacement calculation is performed; the operation is simple, the calculation complexity is low, and the accurate background schlieren image can be quickly obtained.

The application discloses a kind of laser radar-camera online self-calibration method based on semantic edge alignment.First, the data collected by image and laser radar are carried out semantic segmentation, obtain image semantic segmentation and point cloud semantic segmentation result;Then, the edge of image semantic segmentation result is extracted, and the edge of point cloud semantic segmentation result is extracted after ring view transformation and filling.In the use of existing deviation initial external parameter, the point cloud semantic edge is projected to the image pixel coordinate system, and the external parameter between laser radar and camera is optimized and corrected by the way of constantly fine search maximum matching score from rough to fine.The application realizes online joint external parameter self-calibration without depending on calibration board, can adapt to the edge matching of arbitrary shape semantic category, does not depend on specific scene, and has high calibration accuracy and good reliability, improves the scene adaptability of laser radar and camera online self-calibration, and has high practical value for accurate multi-sensor fusion of automatic driving.