405 results about "Quadtree" patented technology

A block chain double-chain cold chain traceability management system for meat quality fluctuation belongs to the technical field of traceability management systems and comprises a data acquisition and preprocessing module, a composite index module, a security verification module, a federated learning and AI resource management module, a fragmentation and verification architecture module and an automatic error correction module. According to the method, data chain storage environment data hash and transaction chain record operation logs are innovatively separated through a block chain double-chain architecture, hash fingerprints are synchronized in combination with an anchoring technology, cross-chain consistency is ensured, long-term non-tampering of data is realized through an anti-quantum hash algorithm, resource allocation is optimized through hierarchical storage design, and the method is suitable for large-scale popularization and application. The composite index technology is fused with hypergraph dynamic index to trace production batches, vehicles, warehouses and space-time quadtree dynamic subdivision areas, complex query response time is remarkably compressed, path deviation real-time alarm is achieved, the edge node cache hit rate is increased, and full-link data safety and query efficiency are remarkably improved.

The invention provides a large-scale satellite three-dimensional image data processing method, medium and system, and belongs to the technical field of satellite three-dimensional image data processing.The method comprises the steps that Gaussian filtering and wavelet noise reduction preprocessing is conducted on an image, and then cooperative computing of a GPU and a CPU is achieved based on a computing task distribution function. Through multi-scale feature extraction and matrix optimization, a stable feature matrix and a variable feature matrix are obtained. A quadtree spatial index is adopted to carry out data partitioning, and SIFT feature extraction and K-means clustering are combined to optimize feature representation. And establishing a stereoscopic image registration model, determining an optimal splicing sequence through a minimum spanning tree algorithm, realizing image splicing by adopting a progressive texture fusion method, and finally generating a high-precision three-dimensional earth surface model. According to the invention, the unification of processing efficiency and precision is realized, and the technical problem that the processing efficiency of large-scale stereoscopic image data is difficult to improve on the premise of ensuring the processing precision in the prior art is solved.

The invention relates to the technical field of digital fusion, in particular to an electronic chart drawing method and system based on a data fusion technology, and the method comprises the steps: S10, building and dynamically updating a mixed index structure based on a preset electronic chart database and an incremental data packet collected in real time; s20, matching the same-name elements, fusing the identified space overlapping regions, and outputting a de-duplicated global sea chart data set; s30, dividing a plurality of sub-regions, constructing a quadtree-R tree index, and outputting a quadtree-R tree double-layer mixed index structure; s40, converting the screen coordinates into geographic coordinates, screening visible elements, and outputting a visible region element set; and S50, based on the visible area element set and a preset style rule, allocating a rendering task, optimizing and matching a GPU instruction set, and outputting a real-time sea chart picture with a preset frame rate. According to the method, the real-time processing efficiency and the visualization fluency of the electronic chart are remarkably improved, and the user interaction experience is optimized.

The invention discloses a city-level CIM scene streaming rendering method based on multi-modal fusion, and the method comprises the following steps: S1, collecting city data, and carrying out the preprocessing of the city data; s2, establishing a cross-modal entity alignment relationship, and constructing a city object structure body; s3, dividing a space by adopting a quadtree method, generating rendering sub-blocks and distributing a unique space code; s4, binding the rendering sub-blocks with the urban object structure body, constructing a multi-modal fusion network, and generating a multi-modal rendering unit set; s5, constructing an inter-frame rendering cost function, and scheduling and sequencing the multi-modal rendering unit set to form an inter-frame scheduling sequence; s6, loading the rendering units according to the inter-frame scheduling sequence to form a city-level three-dimensional view of continuous frames; and S7, updating the scheduling sequence, dynamically adjusting the loading sequence, and realizing stable and efficient streaming rendering of the city-level CIM scene. According to the method, the fusion efficiency and rendering performance of the urban large-scale three-dimensional data are improved, and the method has remarkable engineering applicability and popularization value.

The invention provides a robot intelligent path planning method based on K-value adaptive multi-algorithm cooperation, and belongs to the field of robot path planning. The robot path planning method mainly comprises the following steps: preprocessing an environment map, and constructing a three-layer data structure of a quadtree, a Voronoi graph and a connected graph; generating an initial path based on an improved fast extension random tree algorithm, and extracting key points; establishing a K value evaluation system including five dimensions of obstacle density, local complexity, channel characteristics, path curvature and topology complexity, and realizing accurate quantification of the environment; carrying out adaptive region division based on the K value, and dividing the environment into an open region, a narrow channel region and an obstacle dense region; aiming at the characteristics of different regions, an improved bidirectional A algorithm and an improved fast expansion random tree algorithm are respectively adopted to carry out collaborative planning; and finally, smoothing the path through a Bezier curve. According to the method, the quality and the planning efficiency of path planning in a complex environment can be improved, and higher robustness is achieved.

The invention provides an urban ecological risk prediction system based on a cellular automaton. The system integrates and obtains remote sensing images, meteorological data and human activity data through a data acquisition module, and extracts green land coverage, land utilization types and species distribution information of cities. Thirdly, a space grid is divided through a space grid division module by means of a dynamic quadtree algorithm, ecological units are generated, and therefore microcosmic space heterogeneity is captured; then, the system utilizes a cellular automaton model to optimize a state transition rule through deep reinforcement learning, and couples a soil erosion model and a hydrological model to simulate the dynamic change of urban ecology. And finally, quantizing parameter uncertainty through a risk assessment module by using a Bayesian belief network and Monte Carlo simulation. According to the system, urban ecological risks can be effectively simulated and predicted, the spatial precision and scientificity of prediction are improved, and the coupling influence of multiple ecological factors is considered at the same time.

A dynamic vision SLAM (Simultaneous Localization and Mapping) method based on an extended Bayesian model belongs to the technical field of autonomous robot navigation and computer vision crossing, and mainly comprises the following steps: performing prior dynamic object recognition on a current frame image by using an improved PWt-YOLO network, and outputting a binary mask and semantic probability distribution; oRB feature extraction is carried out by using a hierarchical quadtree algorithm and combining an adaptive threshold value; establishing an extended Bayesian probability model, fusing semantic prior, optical flow residual and epipolar geometric constraints of two-dimensional Gaussian distribution constructed based on dynamic object boundaries, realizing time sequence transmission of dynamic feature probabilities through a Markov chain, and executing feature point filtering according to joint dynamic probabilities; and robust pose estimation is realized through RANSAC-PnP, a sliding window and the like. According to the method, the problem of SLAM system positioning drift in a dynamic environment can be effectively solved by constructing a multi-modal fusion dynamic feature discrimination system.

The invention relates to the technical field of data processing, and discloses a visual data comprehensive processing method for automobile industrial data based on digital twinning. The method comprises the following steps: performing recursive quartering on a three-dimensional space of an automobile general assembly workshop through a workshop process pixel quadtree index algorithm, performing process type marking on multi-source heterogeneous data according to a process identification mapping rule, and allocating a workshop real-time data set to a quadtree index structure according to space coordinates to perform process state aggregation, and according to the viewport pixel mapping relation, performing weighted aggregation calculation on the process state aggregation matrix to obtain a pixel comprehensive display value, and based on the pixel comprehensive display value, performing layered rendering processing on the workshop multi-process parallel scene. According to the invention, the visual processing efficiency and the user interaction response speed of the digital twin system in the automobile industry are improved.

The invention relates to the technical field of low-altitude traffic management, and discloses a low-altitude traffic situation analysis method and system based on digital twinning, and the method comprises the steps: constructing a non-uniform adaptive quadtree spatial index structure; generating a space-time risk probability field, and calculating a conflict risk probability by adopting trajectory prediction of multi-model fusion; constructing a scene adaptive classification model, and dynamically adjusting a decision strategy according to traffic scene characteristics; collaborative decision optimization is realized, and a hierarchical decision structure and a passing right distribution algorithm based on an auction mechanism are adopted; establishing a digital twinborn situation analysis platform, mapping a low-altitude traffic state in real time and providing decision support; according to the method, through organic combination of technologies such as non-uniform adaptive quadtree spatial indexing, multi-model fusion trajectory prediction, space-time risk probability field calculation, hierarchical collaborative decision optimization and a digital twinborn situation analysis platform, accurate perception, analysis and prediction of low-altitude traffic are realized.

The invention discloses an interest point recommendation method based on a region perception dynamic hypergraph and double-layer modeling, and the method comprises the steps: generating a sign-in record representation containing a region code through quadtree region coding and coarse-grained geographic information; constructing a dynamic hypergraph; capturing a dependency relationship between sign-in records in a single user target track through a self-attention mechanism, and obtaining sign-in record characterization; generating initial feature representation of each track through hypergraph volume accumulation and sign-in record representation; carrying out convolution operation on the hyperedges, fusing high-order correlation information of tracks including tracks associated with the target track in the track-track correlation matrix among the tracks, and obtaining final target track feature representation; and mapping the final target track feature representation to an ID space of a point of interest POI, and recommending a next point of interest to the user. According to the method, through regional perception and double-layer modeling, the problem of data sparsity is effectively relieved, the capability of capturing the dynamic movement mode of the user is enhanced, and the accuracy and reliability of recommendation are improved.

The invention belongs to the technical field of image processing, and particularly relates to a monitoring image defogging enhancement method in a high-dust environment of a mineral separation site, which comprises the following steps of: performing smooth denoising on an original image by using weighted guided filtering, and obtaining global atmospheric light through a quadtree subdivision method; constructing a same-color heterogeneous discrimination index combining a spectrum similarity factor and a texture confidence factor for distinguishing dust and ore with similar colors; calculating a pixel-level dynamic defogging coefficient based on the discriminant index, and obtaining an adaptive transmissivity in combination with dark channel prior; and finally, restoring the image by using an atmospheric scattering model and carrying out contrast-limited adaptive histogram equalization processing. According to the method, the problem of misjudgment caused by the fact that the colors of the ore and the dust on the ore dressing site are similar is effectively solved, powerful defogging of the dust area and detail reservation of the ore area are achieved, and the definition and the contrast ratio of the monitoring image are improved.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses an image edge feature enhancement correction fusion method based on a guide filter, and aims to solve the problems that detail features of a low-illumination visible light image and an infrared image are not obvious, focusing edge information is not clear, and registration of a multi-focus image is wrong. The invention provides an edge feature enhancement correction fusion method based on a guide filter. In the illumination enhancement stage, a visible light image is divided into a base layer and a detail layer through a guide filter, and the image contrast and detail information are enhanced. For an infrared image, an infrared background is reconstructed by using a quadtree decomposition and Bezier interpolation method, unclear focusing edge feature information is extracted, and the visibility of image details is enhanced. And finally, reconstructing the two processed images by using a multi-scale weighted gradient method, and performing fusion by calculating large-scale and small-scale weight scales.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

According to the emergency safety management GIS big data vector slicing service map, the vector data are thinned and simplified under each level by using the optimized global constraint algorithm, and the simplified and thinned vector data are cut and sliced and are published in a service form. The style of the tile is designed, and the client renders and visualizes the requested vector tile according to the specified style. And designing a cutting thought, and cutting point, line and surface elements in the vector data. And organizing and storing the generated tiles by using a quadtree index. A cache strategy of a client is designed, existing WMS and WMTS service standards are expanded, a vector tile map style is designed, and vector tiles are published in a service form. According to the method, a prototype system is created, static and dynamic slicing services of the vector map are realized, loading and rendering are carried out at a client, and particularly, when the emergency safety management quantity is huge and the quality is poor, the map precision and efficiency advantages are obvious.

The invention belongs to the field of unmanned aerial vehicle (UAS) traffic management (UTM) and computer science, and particularly relates to a method and system for airspace modeling and path planning of a logistics unmanned aerial vehicle, and the method comprises the steps: S1, receiving multi-source data, and constructing a hierarchical mixed data model; s2, coding the control constraint data and the dynamic environment data into semantic attributes of nodes in a two-dimensional quadtree layer and / or voxels in a three-dimensional octree layer so as to generate a semantic airspace model containing computable rules; s3, based on the semantic airspace model, executing a hierarchical path planning algorithm to determine a flight path from the starting point to the ending point; and S4, combining the refined paths, and outputting a four-dimensional flight path containing a timestamp. The airspace rule is internalized into the model attribute, the real-time performance, safety and compliance of path planning are remarkably improved, the airspace resource utilization efficiency is improved, and key technical support is provided for large-scale urban unmanned aerial vehicle logistics operation.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses a seepage field adaptive analysis method and device based on a flexible polygon unit, and the method comprises the steps: dividing the polygon unit into a plurality of sub-regions, and constructing an internal water head field of each sub-region; recognizing a free water surface according to water head features extracted from the internal water head field of each sub-region; if the free water surface is recognized for the first time at present, or the error of the positions of the free water surfaces recognized by two adjacent rounds of iteration does not meet a preset condition, quadtree decomposition is carried out on the free water surface to obtain new sub-regions; returning to the step of extracting the water head features according to the internal water head field of each sub-region until the error of the positions of the free water surfaces identified by two adjacent rounds of iteration meets a preset condition, and obtaining a grid division result of the polygon unit; and performing seepage field analysis on the polygon units based on a grid division result to obtain a seepage field analysis result. According to the method, the complex seepage field is accurately simulated, and the optimal balance between high-precision discretization near the free water surface and the overall calculation efficiency is realized.

The invention discloses a three-dimensional model wall thickness measuring method, device and equipment combining a ray method and a spherical surface method, and a storage medium, and is applied to the field of three-dimensional models. Processing the input three-dimensional model by adopting a self-adaptive subdivision algorithm of a quadtree to generate an optimized triangular mesh; the method comprises the following steps: constructing an axial alignment bounding box (AABB) hierarchical tree structure optimized based on a superficial area heuristic (SAH) cost function, and in a wall thickness calculation stage, combining the advantages of a ray method and a spherical method: performing dynamic judgment according to an included angle between a normal vector at an intersection point of a ray and the inner surface of a model and an initial ray direction; the hybrid strategy ensures that reliable and efficient measurement results can be obtained in different geometric feature regions; a visual distribution diagram of color coding can be generated; according to the method, through adaptive grid optimization, efficient SAH-AABB acceleration and ray / spherical surface method mixed measurement, high-precision and efficient global measurement of the wall thickness of any three-dimensional model, especially a complex structure model, is realized.

The invention provides a dynamic grid updating and scheduling method and system for watershed scale ecological restoration. The system comprises a data fusion access module, a dynamic grid generation module and a central cooperative controller. The data fusion access module is used for receiving multi-source heterogeneous data, the dynamic grid generation module is used for constructing an initial watershed grid by adopting a quadtree space division algorithm based on the multi-source heterogeneous data, and the central cooperative controller is used for periodically scanning a full-watershed grid set. Comprehensively judging information value density and updating urgency of each grid according to a multi-dimensional index; by adopting the above technical scheme, the autonomous evolution and precise adaptation of the watershed spatial discretization unit can be realized, the global monitoring breadth and the local description precision are dynamically balanced, and the response sensitivity to an emergent ecological event is improved.

The invention relates to the technical field of capacitive touch, and discloses a capacitive touch signal self-adaptive compensation method and device. The method comprises the following steps: collecting original capacitance signal grid data in an initial contact stage, and constructing a dynamic contact quadtree; on the basis of the quadtree, a first point position prediction algorithm of contact dynamics perception is operated, and stable coordinate prediction mapping with confidence is constructed; and executing multi-mode first point decision and touch event generation based on the mapping, outputting a touch event and feeding back the touch event to an operating system. According to the method, initial contact signal features are captured through the dynamic contact quadtree, stable coordinate prediction mapping and multi-modal decision are combined, the problem of jumping coordinates in the initial touch stage of an existing system is solved, the touch accuracy of scenes such as vehicle-mounted center control and industrial HMI is improved, the operation risk is reduced, and the application value of the capacitive touch technology is expanded.

The invention relates to the technical field of mobile robot autonomous navigation path planning, and discloses a complex orchard scene-oriented hybrid sampling global path planning method, which comprises the steps of adopting a Gaussian hybrid sampling strategy, switching between global uniform sampling and Gaussian offset sampling through a probability threshold, and considering global exploration and key area guidance; a dynamic node expansion strategy is adopted, the expansion step length is adaptively adjusted according to the distance between the expansion step length and a target point, and the expansion direction is optimized by fusing vectors facing a sampling point and the target point and introducing an obstacle influence factor; a layered collision detection strategy is adopted, and step-by-step filtering is carried out through rough detection based on a quadtree, secondary screening based on an axis alignment bounding box and accurate geometric judgment in sequence so as to improve the efficiency; and a dynamic iteration termination mechanism is adopted, and the minimum number of iterations and the path quality convergence state are combined as composite termination conditions. The method can quickly generate a smooth and safe path, and is especially suitable for structured scenes such as orchards.

The invention discloses a CAD model broken surface processing method and device, equipment and a medium, and relates to the technical field of computer aided design, and the method comprises the steps: importing and repairing an initial CAD model, building a watertight grid data structure, and obtaining a virtual surface; traversing and identifying that the current virtual surfaces meeting a preset broken surface judgment condition are broken surfaces, and obtaining a broken surface set; re-grouping the broken surface set according to a set division mode of sharing the same boundary or vertex to obtain a plurality of broken surface groups; virtual edge merging, boundary topological relation updating and discrete grid fusion processing are carried out on all the broken surfaces in each broken surface group, and a target virtual surface after broken surface merging is obtained; and performing two-dimensional mapping processing of discrete grids on the target virtual surface to obtain two-dimensional discrete grid distribution on a two-dimensional plane, and fitting a corresponding virtual continuous curved surface by using a quadtree search structure and based on the two-dimensional discrete grid distribution. While the broken surface is automatically processed, the original geometric data is not changed, and the operation is completely reversible.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a low-delay high-performance image semantic-channel joint coding system, and relates to the technical field of communication and image processing, and the method comprises the steps that a sending end extracts semantic features through a neural analyzer, and divides the semantic features into a plurality of partitions through a quadtree structure; and coding each partition step by step by using a context-aware feature coding strategy, and finally mapping to a complex value channel symbol to be sent to a receiving end. And a receiving end reconstructs the semantic features through a corresponding decoding and synthesizing module and generates a reconstructed image, so that end-to-end efficient image transmission is realized. According to the method, a context-based partition coding mechanism and a quadtree partition module strategy are introduced into a coding structure, so that the method has higher context modeling capability and parallel processing capability, and the adaptive capability to an image structure and semantic content can be effectively improved; transmission delay can be reduced, and image reconstruction quality and channel interference resistance can be enhanced.

The invention discloses a Web-based visual editing method, belongs to the technical field of industrial configuration, and aims to solve the problems of complex deployment of traditional configuration software and insufficient Web scheme performance. The method comprises the following steps: constructing a front-end architecture (Vue. Js + Konva.js) containing a graphic element module, a canvas management module and the like; the primitive adopts JavaScript prototype chain inheritance + SVG / Canvas double-layer rendering, and a canvas is divided into four layers and is provided with a quadtree index; an editor and an expression engine are generated by using a factory pattern for attribute configuration; page management supports state capture recovery; real-time communication is based on WebSocket + PubSub, and data aggregation and incremental updating optimization are combined. Cross-platform zero deployment and Web environment near-desktop performance are achieved, editing efficiency is improved, industrial protocols such as OPC UA are compatible, and the method is suitable for the field of energy and intelligent manufacturing.

The invention provides a tower crane low-altitude path planning method, device and equipment based on configuration space, and relates to the technical field of path planning. According to the method, a configuration space composed of the variable-amplitude freedom degree of the tower crane, the rotation freedom degree of the tower crane and the self-rotation freedom degree of a hoisted object is constructed, an obstacle bounding box is generated and expanded and mapped to the configuration space, dangerous nodes are identified through quadtree division and collision detection, adjacent plane nodes are connected, and an optimal planning path is obtained through planning by using an A * algorithm. And the tower crane is operated to run according to the optimal planning path. The problems that in traditional path planning, the path is complex, operability is low, and self-rotation of the hoisted object is not considered can be solved, calculation efficiency and path precision are improved, operation cost is reduced, and the method is suitable for hoisting tasks with rotation requirements for the hoisting point and the target point.

The invention belongs to the technical field of submarine topography information processing, and discloses a submarine topography modeling method and system of a multi-resolution grid. The method comprises the following steps: generating a quadtree-based multi-resolution grid model; obtaining a multi-resolution grid model according to the terrain complexity evaluation index, and obtaining a node subdivision evaluation index for the terrain complexity; in the process of multi-resolution grid display rendering, cracks generated by splicing of adjacent grids with different resolutions are eliminated by using an edge adding method. Through the combination of the quadtree storage structure and the multi-resolution grid, the number of high-precision grid points is reduced, so that the space redundancy of data storage is remarkably reduced. According to the method, the spatial redundancy is reduced, the terrain features and the gradient are considered through the subdivision evaluation function, the complex features of the terrain can be well reserved, and the overall terrain precision is ensured.

The invention relates to the technical field of live ammunition point positioning, in particular to a simulated live ammunition point accurate positioning method. According to the method, the time and the displacement value of track segmentation are calculated based on the shooting parameter set, the coordinate set of each track segment is defined, the longitudinal deviation value is calculated in combination with the gravitational acceleration, segmentation processing of track generation is refined, the track calculation accuracy is ensured, and the target range is determined by judging the relation between the coordinate points and the target range point by point. The Euclidean distance between candidate points and the center of the target is calculated in combination with a gradient descent method, the screening process of hit point positions is optimized, the offset between a to-be-hit point and the center of the target is reduced by adjusting the initial velocity and the shooting angle of a bullet for multiple times, coordinate points exceeding the boundary of a target range are corrected through a quadtree segmentation algorithm, and the accuracy of target shooting is improved. The re-segmentation calculation of the track points meets the constraint condition of the space boundary, the effectiveness of the track point set and the accuracy of the drop point positioning are improved, and comprehensive data support is provided for weapon debugging and training.

The invention relates to the technical field of geological disaster monitoring, and discloses an unmanned aerial vehicle aerial survey intelligent identification and grading method and system for geological disaster hidden danger points, and the method comprises the steps: converting a pixel-level identification result into hierarchical data which retains a spatial topological structure through constructing a confidence quad-tree; establishing a weighted decision grid based on aerial survey parameters to realize coupling modeling of observation conditions and confidence uncertainty, calculating topology difference to generate a spatial difference field to quantify the deviation degree of a confidence field and a standard grading decision surface, and finally executing self-adaptive grading judgment to output a risk grade result with a confidence label; according to the method, the problem of confidence field and decision boundary space topology mismatch caused by truncation of confidence continuous measurement information in a grading stage in a traditional serial architecture is solved, systematic underestimation of misjudgment risks in observation condition limited areas such as alpine and gorge areas is avoided, and consistency of actual credibility of a risk quantification result and a nominal grade is realized.