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376 results about "Delaunay triangulation" patented technology

In mathematics and computational geometry, a Delaunay triangulation (also known as a Delone triangulation) for a given set P of discrete points in a plane is a triangulation DT(P) such that no point in P is inside the circumcircle of any triangle in DT(P). Delaunay triangulations maximize the minimum angle of all the angles of the triangles in the triangulation; they tend to avoid sliver triangles. The triangulation is named after Boris Delaunay for his work on this topic from 1934.

PSInSAR deformation estimation method applicable to complex urban area infrastructure in windy and rainy conditions

InactiveCN106940443AFit closelyImprove estimation robustnessRadio wave reradiation/reflectionLayoverCompressed sensing
The invention relates to the technical field of synthetic aperture radar interferometry, and specifically relates to a PSInSAR estimation method applicable to complex urban area infrastructure in windy and rainy conditions. The method includes following steps: performing data preprocessing on InSAR data; establishing a Delaunay triangulation network and an adaptive encryption network; estimating an arc segment relative parameter through a robust estimator; performing Tikhonov regularization adjustment operation; establishing a local star network; recognizing single PS points and layover PS points; calculating the single PS points in remaining pixels through the robust estimator, and detecting the layover PS points through a compressed sensing algorithm; and outputting heights and deformation results of the single PS points and the layover PS points. According to the method, combined calculation of the single PS points and the layover PS points is realized through mixed network establishment without removing the atmosphere in a global manner, a temperature non-linear deformation model is introduced, the fitting degree of the time sequence phase is improved, accurate estimation of the PS points is realized by employing the robust estimator, and the layover PS points of the complex urban environment are extracted by employing super-resolution MD-TomoSAR imaging.
Owner:洪都天顺(深圳)科技有限公司

Adaptive spatial clustering method

InactiveCN102163224AVisualization of clustering resultsAdapt to complexitySpecial data processing applicationsDensity basedSpatial cluster analysis
The invention discloses an adaptive spatial clustering method, comprising the following steps of: (1) preprocessing spatial data and selecting features; (2) creating a Delaunay triangulation network according to spatial attribute; (3) performing clustering analysis operations according to the spatial attribute; (4) turning to a step (5) if a spatial solid obstacle is needed to be further considered, and turning to a step (6) if a thematic attribute is needed to be considered, otherwise, ending the spatial clustering operations; (5) introducing a spatial obstacle layer, performing overlap analysis on the spatial obstacle and the side length of the Delaunay triangulation network between the entities in each spatial cluster, and breaking the side length if the spatial obstacle is intersected with the side length; (6) performing the thematic attribute clustering by an improved density-based spatial clustering method; (7) visualizing the clustering result, and outputting the clustering result. The adaptive spatial clustering method is simple and convenient to operate, high in degree of automation, high in calculation efficiency, perfect in functions, strong in applicability and the like, and can effectively improve capability of spatial clustering analysis to excavate deep-seated geoscience rules.
Owner:CENT SOUTH UNIV

High-resolution remote sensing image plane extraction method based on skeleton characteristic

The invention discloses a high-resolution remote sensing image plane extraction method based on skeleton characteristics, comprising the following steps: selecting a remote sensing image edge detection algorithm based on embedded confidence coefficient for edge detection, and realizing the remote sensing image edge detection algorithm based on embedded confidence coefficient; vectorizing a groundfeature target edge; extracting a ground feature skeleton base line from the vector edge of a ground feature based on a constraint Delaunay triangulation network algorithm; carrying out the target main skeleton extraction algorithm based on a binary tree structure; carrying out feature analysis on the target main skeleton of the plane; and realizing the automatic identification method of a plane target. By means of the invention, the plane target can be automatically identified and extracted and better identification extraction effect is obtained. The plane target skeleton has the excellent characteristics of rotation invariance and high discrimination index with other ground features, the vector edge of the ground feature target can be efficiently and precisely extracted from a remote sensing image with high spatial resolution, and the improved target skeleton can be extracted.
Owner:NANJING UNIV

Delaunay-triangulation-network-based multi-redundancy network RTK atmospheric error interpolation method

ActiveCN106970404AIncrease the number ofSolve the problem of not being able to take advantage of redundant baselinesSatellite radio beaconingCentimeterBaselining
The invention discloses a delaunay-triangulation-network-based multi-redundancy network RTK atmospheric error interpolation method. A network RTK data processing center constructs a Delaunay triangulation network based on a correct coordinate of a CORS base station; after a user is accessed to a data processing center, an optimal triangular unit and a suboptimum triangular unit of the location of the user are selected; an atmospheric error interpolation base line number is extended; an MLIM ionized layer interpolation model and an RELIM tropospheric interpolation model are established; and an atmospheric interpolation completeness monitoring method of a moving station in a grid is provided. The interpolation precision of the MLIM ionized layer interpolation model is higher than that of the traditional model by three times and the interpolation precision of the RELIM tropospheric interpolation model is higher than that of the traditional model by 6 to 30 times; and the two models can still have high interpolation precision at an area with a large elevation difference at the base station. A regional CORS ionized layer and tropospheric completeness index can reach a centimetre-level interpolation precision, so that real-time positioning completeness monitoring of a network RTK user can be realized. With the method provided by the invention, a CORS base station around a user can be utilized fully; the atmospheric delay interpolation precision of the area can be improved; and the rapid and high-precision positioning of the user can be guaranteed.
Owner:SOUTHEAST UNIV

Train compartment cargo volume and bulk density detection method based on point cloud data processing

The invention discloses a detection method for a cargo volume and a bulk density of a train compartment, comprising the following steps of: obtaining two sets of distance detection data on an x-axis and a z-axis of the train compartment by using a two-dimensional scanner; performing a united computation on motion data of the car along the y-axis direction calculated by an OPC-Client system and thetwo sets of distance detection data to obtain the two sets of three-dimensional point cloud data; performing a down sampling and an irrelevant point removal processing on the obtained three-dimensional point cloud data to obtain two sets of streamlined three-dimensional point cloud data of the train compartment; creating a Delaunay triangulation network for two sets of streamlined three-dimensional point cloud data to obtain the top surface and the bottom surface of the train compartment; transforming a total volume of cargo in the train compartment into an aggregate form by a projection processing; calculating the volume of the transformed aggregate, performing a summation processing to obtain a total volume of the cargo in the train compartment; calculating a bulk density parameter of the cargo carried and judging the stability by using the calculated total volume of the cargo and the weight data provided by a rail weighbridge.
Owner:河北燕大燕软信息系统有限公司

Image segmentation by hierarchial agglomeration of polygons using ecological statistics

A method for rapid hierarchical image segmentation based on perceptually driven contour completion and scene statistics is disclosed. The method begins with an initial fine-scale segmentation of an image, such as obtained by perceptual completion of partial contours into polygonal regions using region-contour correspondences established by Delaunay triangulation of edge pixels as implemented in VISTA. The resulting polygons are analyzed with respect to their size and color/intensity distributions and the structural properties of their boundaries. Statistical estimates of granularity of size, similarity of color, texture, and saliency of intervening boundaries are computed and formulated into logical (Boolean) predicates. The combined satisfiability of these Boolean predicates by a pair of adjacent polygons at a given segmentation level qualifies them for merging into a larger polygon representing a coarser, larger-scale feature of the pixel image and collectively obtains the next level of polygonal segments in a hierarchy of fine-to-coarse segmentations. The iterative application of this process precipitates textured regions as polygons with highly convolved boundaries and helps distinguish them from objects which typically have more regular boundaries. The method yields a multiscale decomposition of an image into constituent features that enjoy a hierarchical relationship with features at finer and coarser scales. This provides a traversable graph structure from which feature content and context in terms of other features can be derived, aiding in automated image understanding tasks. The method disclosed is highly efficient and can be used to decompose and analyze large images.
Owner:TRIAD NAT SECURITY LLC

Road network reconstruction method and system based on mobile phone positioning data

The invention discloses a road network reconstruction method and system based on mobile phone positioning data. The method includes: acquiring an original dataset which includes a training dataset anda prediction data set, wherein the original dataset is formed by track points acquired according to mobile phone positioning data; respectively utilizing two dimensionalities like time and density toperform feature construction and combination on the training dataset and the prediction dataset, and generating a training set and a prediction set accordingly; using the generated training set, andacquiring a sampling point classifying model on the basis of an algorithm in machine learning; applying the learned classifying model to the prediction set to divide the track points into road pointsand non-road points; performing road reconstruction on the recognized road points on the basis of a constraint Delaunay triangulation network; according to a topological relation, modifying a road central line to complete reconstruction of a road network. A new mode for high-quality refined road network production and updating is put forward, so that technical support can be provided for seamlessnavigation technology, refined road networks especially, and coverage of path navigation service is expanded.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)

Mass airborne LiDAR point cloud Delaunay triangulation network parallel construction method and apparatus thereof

The invention relates to a mass airborne LiDAR point cloud Delaunay triangulation network parallel construction method. The method comprises the following steps: carrying out data block division and task distribution on mass airborne LiDAR point cloud data; applying a pointwise insertion algorithm to each data block respectively so as to construct a sub-triangulation network in parallel, and acquiring a sub-triangulation network set; using a merging algorithm to connect the adjacent two sub-triangulation networks so as to generate the merged triangulation network; using an optimization algorithm to carry out optimization on a newly generated triangle and the adjacent triangle so as to obtain the merged triangle which accords with a Delaunay rule; repeating the merging and the optimization until all the sub-triangulation networks are merged and the complete Delaunay triangulation network can be obtained. The invention also provides a corresponding apparatus for executing the above method. By using the method and the apparatus of the invention, a post-treatment speed of the mass airborne LiDAR point cloud can be substantially increased. The method and the apparatus of the invention have great significance for practical application.
Owner:CHINESE ACAD OF SURVEYING & MAPPING

Star-network-based BDS/GPS broadcast type network RTK algorithm

The invention discloses a star-network-based BDS/GPS broadcast type network RTK algorithm. All base stations form a triangulation network based on a Delaunay triangulation algorithm; and a controllable full-region star network formed by a plurality of star network elements is generated based on the triangulation network. Data of the base stations are obtained in real time and network element calculation is carried out to generate a baseline atmospheric error. Meanwhile, a server side broadcasts a main station observation value, a base station coordinate and the baseline atmospheric error to auser by using the star network as a unit based on a UDP protocol; the user selects one network element based on an own approximate position and the position of the main station; interpolation is carried out on an inter-station single-difference atmospheric error of the baseline formed by the user and the main station and the obtained atmospheric error is corrected to the observation value of the main station to carry out baseline calculation. Besides, the user also can uploads an approximate coordinate by two-way communication and the server side broadcasts difference data of the network element in which the user is located. And difference data broadcasting by equipment like ground equipment, an aircraft or a satellite is also supported.
Owner:SOUTHEAST UNIV
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