473 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 discloses a design scheme generation method based on an information retrieval technology, and belongs to the field of information retrieval and image-text generation. Collecting the text description and an image matched with the content of the text description, preprocessing the text description and the image respectively, and performing feature extraction processing to obtain extracted visual feature monk and semantic features: extracting the visual features in the image data; for character description data matched with the image, processing the character image by using a semantic segmentation network so as to identify and segment a character region, extracting uniformly distributed semantic feature points through a quadtree distribution algorithm, and integrating the semantic feature points of all the regions to form a complete semantic feature point set corresponding to the image data including characters; a multi-scale feature map is constructed by using a feature pyramid network, the extracted visual features and semantic features are mapped to a unified feature space in the multi-scale feature map, and it is ensured that key information of the respective features is reserved in the mapping process.

The invention relates to the technical field of image processing, in particular to a slope deformation monitoring method based on image recognition, and the method comprises the steps: obtaining a slope interferometric phase diagram; segmenting the slope interferometric phase diagram to obtain a plurality of sub-regions, and obtaining local differences of phase points in the sub-regions; determining the difference expression degree of the phase values corresponding to the phase points and the phase difference of the sub-regions; carrying out region segmentation; determining distribution similarity and overall similarity of adjacent sub-regions when segmentation is finished; calculating the comprehensive similarity of the sub-regions at the end of segmentation; carrying out region merging; and filtering is carried out according to the standard deviation of the final sub-region so as to realize slope deformation monitoring. By dynamically judging whether region segmentation and merging are carried out or not, compared with a fixed threshold mode, the method is more accurately adapted to the spatial variability of a deformation mode in a slope interferometric phase diagram, the quadtree filtering effect is effectively improved, and slope deformation monitoring is more accurate.

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 provides a three-dimensional war game map construction method based on DEM and remote sensing ground feature classification, which comprises the following steps: obtaining digital elevation model DEM data, performing block and layer processing on the digital elevation model DEM data through secondary quadtree index coding, and performing data conversion; constructing a regular grid model based on the DEM data after data transformation; performing terrain rendering by using the regular grid model in combination with hardware to generate a three-dimensional terrain; performing terrain texture mapping on the obtained three-dimensional terrain based on remote sensing terrain classification so as to position and map the texture of a specific landform on the terrain; based on a multi-channel mixed color map Splatmap, texture mixing processing is carried out on the three-dimensional terrain subjected to terrain texture mapping, and natural transition between terrain textures in a real scene is simulated; in addition, dynamic scheduling and real-time drawing are realized in combination with a multi-thread mechanism and an object pool strategy. Compared with the prior art, the method has the advantages of high three-dimensional terrain generation efficiency and real texture mapping.

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 a map hierarchical path planning method based on an aggregated quadtree. The method comprises an offline preprocessing stage and a real-time searching stage. In the off-line preprocessing stage, original grid maps are aggregated to form aggregation grids with the same size, the positions and the number of passing nodes are determined according to the width of passable channels on the boundary of the aggregation grids, and a first-layer abstract map is formed; based on the first-layer abstract map, the equal-weight passable aggregation grids are aggregated according to a quadtree aggregation rule to form an equal-weight aggregation area, the traffic nodes of the aggregation area are optimized, an inner edge and an outer edge are obtained through further calculation according to the traffic nodes and stored in a local data table, and a second-layer abstract map is formed. In the real-time searching stage, the starting point and the ending point are given, the optimal abstract path is calculated based on the second layer of abstract map, the optimal path based on the original map is further refined after the local data table is inquired, and the quality of the generated path can be remarkably improved while the real-time searching efficiency of the path can be improved.

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 relates to the technical field of unmanned aerial vehicle data processing, in particular to an unmanned aerial vehicle data processing method and system based on embedded combination with off-line map fusion, and the method comprises the following steps: before an unmanned aerial vehicle is started, pre-loading and dividing flight area map data, and classifying and storing the map data according to geographic areas and importance; and generating a plurality of region classification map data. According to the method and the device, the map data is preloaded and classified and stored before the unmanned aerial vehicle flies, so that the autonomous navigation capability of the unmanned aerial vehicle in a complex environment is improved, especially under the condition that a network is unavailable or signals are weak. The introduction of the quadtree spatial index optimizes the indexing and retrieval process of the map data, accelerates the response time and reduces the consumption of computing resources. The ant colony algorithm is used for path optimization, the data access mode and the access frequency of the current flight area are adjusted, and the efficiency and the economical efficiency of path planning are improved.

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.

The invention discloses an autonomous parking path collision detection method based on a quad-tree map, which comprises the following steps: acquiring obstacle information in real time through an ultrasonic radar, dispersing an obstacle into points, determining a quad-tree map node where the obstacle is located, and storing the discrete points in a minimum unit node of the quad-tree map, using an AABB bounding box as a discrete point bounding body to construct a quadtree map; a planned parking path is obtained, and a path point closest to the current vehicle serves as a starting point to preview a section of path forwards. The vehicle AABB bounding box and OBB bounding box set is traversed in sequence, screening is carried out according to whether the vehicle AABB bounding box intersects with the quadtree node AABB bounding box with the obstacle discrete points, and collision detection is carried out through iteration of the vehicle OBB bounding box and the screened quadtree node AABB bounding box. The problem that a traditional path collision detection method consumes long time in a complex scene is solved. The time consumption of the collision detection method in a complex scene is reduced, and the detection efficiency is improved while the path collision detection precision is improved.

A partitioning method comprises determining whether a current block of a picture is a boundary block and whether the size of the current block is larger than a minimum allowed quadtree leaf node size; and if the current block is the boundary block and the size of the current block is not larger than the minimum allowed quadtree leaf node size (MinQTSize), applying forced binary tree (BT) partitioning to the current block. A method comprises making a determination that a current block of a picture is a boundary block and that a size of the current block is less than or equal to a minimum allowed quadtree (QT) leaf node size (MinQTSize); and applying, in response to the determination, forced binary tree (BT) partitioning to the current block.

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 relates to a commanding height analysis method and system based on double spatial indexing, and the method employs a double index construction method through an index construction link, i.e., constructing double indexes of a tile quadtree and a triangular patch K-D tree, thereby achieving the quick positioning of a triangular patch intersecting with a ray in a live-action three-dimensional model. By means of the powerful operational capability of a computer, potential hidden danger commanding height points along the security and protection route can be accurately found, the commanding height point calculation efficiency is greatly improved, the practical feasibility of completing large-scale commanding height point calculation based on a live-action three-dimensional model is enhanced, and security and protection work is promoted to be developed more scientifically and efficiently.

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.

The embodiment of the invention provides an image coding division decision method and device, equipment, a storage medium and a product. According to the technical scheme provided by the embodiment of the invention, the quadtree division decision result is obtained by performing the quadtree division decision on the current coding block, and the optimal mode information of the four sub-coding blocks obtained by performing the quadtree division on the current coding block is determined according to the quadtree division decision result; and determining skipping decision information in the preset direction according to the consistency of the optimal mode information in the preset direction, and skipping a division decision of the current coding block in the preset direction when the skipping decision information is a division decision of skipping the preset direction. According to the embodiment of the invention, the target division decision result of the current coding block can be determined according to the quadtree division decision result and the multi-type division result, the division decision quality is ensured, the data processing amount of the division decision can be effectively reduced, and the division decision efficiency is 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 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.