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110 results about "Pixel classification" patented technology
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Hyperspectral image classification method and classification device based on state space model
PendingCN121121198ACharacter and pattern recognitionBiological modelsComputation complexitySerialization
The invention relates to a hyperspectral image classification method and device based on a state space model. The hyperspectral image classification method based on the state space model comprises the following steps: sequentially carrying out feature extraction and serialization processing on hyperspectral image data to obtain a shallow feature projection vector; performing global-local feature extraction on the shallow feature projection vector by adopting a neural network based on a state space model to obtain a fused feature projection vector; and carrying out pixel-by-pixel classification and dimension rearrangement on the hyperspectral image data in sequence to generate a classification result of the hyperspectral image data. According to the hyperspectral image classification method based on the state space model, long-range dependence modeling is achieved through the neural network based on the state space model with linear complexity, the calculation complexity is effectively reduced, and through feature fusion and residual error connection, the classification accuracy of the hyperspectral image is improved. And the perception capability of the neural network on different scale space-spectrum structures in the hyperspectral image is effectively enhanced.
Owner:GUANGZHOU MARITIME INST
Detection method of vehicle-mounted track inspection system
The invention discloses a vehicle-mounted track inspection system detection method, and relates to the technical field of tracks, an inspection starting point is set in a to-be-inspected line, a complete track image of the to-be-inspected line is pre-collected, a plurality of fastener images are generated through cutting with a fastener as the minimum unit, and track historical data are obtained; the track historical data are deployed on a cloud service side and a local inspection side at the same time; a vehicle-mounted track inspection system collects track real-time images, then the track real-time images are matched with an inspection starting point and cut into a plurality of fastener real-time images, region division is conducted on each fastener real-time image, track historical data of a local inspection side are called to conduct pixel grading comparison on different regions, and abnormal region images are screened; and incremental data is generated and transmitted to the cloud service side, track historical data is called to carry out refined detection on the abnormal region image, and a disease detection result is output. According to the invention, the problems of insufficient local detection performance, data accumulation and detection delay under high-speed operation of the electric passenger car are solved, and real-time track disease inspection is realized.
Owner:CHENGDU SEIKO HUAYAO TECH CO LTD
Seabed image splicing method based on suture line optimization
PendingCN121304441AGeometric image transformationCharacter and pattern recognitionParallaxFeature extraction
The invention discloses a submarine image splicing method based on suture line optimization, and the method comprises the steps: carrying out the dual-stage feature extraction of a target submarine image based on an improved ResNet50 network, and obtaining a multi-level feature map containing global structure information and local detail features; respectively carrying out global coarse registration and local fine correction on the second feature map and the first feature map based on a deformable convolutional network to obtain a sub-pixel level aligned deformed image; and carrying out cross-scale feature interaction and dynamic mask optimization on the deformed images based on a cross-image self-attention mechanism, dividing suture line weights between the spliced images, and carrying out pixel classification according to the weights to obtain seamless spliced images. According to the method, semantic fusion is guided through deformable convolution modeling elastic deformation and a self-attention mechanism, sub-pixel-level alignment and seamless splicing are achieved, and the problems of geometric dislocation and suture line artifacts caused by refraction distortion, scattering noise and dynamic deformation in large-parallax submarine image splicing are solved.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)
Water body information extraction method based on remote sensing image
The embodiment of the invention discloses a water body information extraction method based on a remote sensing image, and relates to the technical field of remote sensing image processing, and the method comprises the steps: obtaining a green light wave band value, a red light wave band value and a near-infrared wave band value of a target pixel in a to-be-processed remote sensing image; based on the green light wave band value, the red light wave band value and the near-infrared wave band value, calculating a water and land pixel measurement variable of the target pixel through a preset water body index formula; comparing the land and water pixel metric variable obtained by calculation with a preset threshold value, and classifying the target pixel as a water pixel or a non-water pixel based on a comparison result; the accuracy of land and water pixel measurement can be further improved, the phenomenon that the water body area is confused with other interference areas such as roads, building roofs and bridges is reduced, and water body recognition is more accurate.
Owner:YUNNAN POWER GRID CO LTD ELECTRIC POWER RES INST
Plateau wetland landscape component extraction method, system and program product
ActiveCN121053533ACharacter and pattern recognitionNeural learning methodsSoil scienceFeature extraction
The invention belongs to the technical field of machine learning, and particularly discloses a plateau wetland landscape component extraction method and system and a program product, and the method comprises the steps: designing a spectrum-space double-branch interaction model, extracting the spectral features of pixels at a spectrum branch through a pixel dimension raising module and a ViT architecture Transformer encoder, and carrying out the extraction of the components of the plateau wetland landscape component; extracting neighborhood spatial features of pixels through a multi-scale feature extraction module and feature enhancement in a spatial branch, then integrating the features of the two branches through a cross attention fusion module, outputting pixel classification results, and determining each plateau wetland landscape component region in the remote sensing image according to each pixel classification result. The high-efficiency and reliable extraction of the plateau wetland landscape components can be realized. The plateau wetland landscape component classification method can effectively relieve the problem of salt and pepper noise existing in a traditional pixel-by-pixel classification method, guarantees the light weight of the network while improving the plateau wetland landscape component classification precision, and provides more accurate technical support for long-time-sequence plateau wetland landscape component extraction.
Owner:GARZE TIBETAN AUTONOMOUS PREFECTURE INST OF SCI & TECH INFORMATION
Systems and methods for identifying hazard trees
PendingUS20260080678A1Character and pattern recognitionPicture interpretationAlgorithmNeural network nn
Identifying hazard trees is described. An example method includes receiving multiple images for a geographic area that includes multiple electrical assets of a power distribution infrastructure. Pixels of the multiple images are classified as hazard tree pixels or as non-hazard tree pixels using one or more convolutional neural networks. Multiple polygons are generated based on the hazard tree pixels, a polygon corresponding to one or more hazard trees in the geographic area. A height of a polygon and a distance from the polygon to an electrical asset is determined. Based on the height and the distance, the one or more hazard trees corresponding polygon are determined to represent a potential hazard to the electrical asset. A notification of the potential hazard to the electrical asset is generated and provided.
Owner:AIDASH INC
Focus segmentation model based on mask-guided multi-scale feature fusion technology and training method thereof
The invention discloses a focus segmentation model based on a mask-guided multi-scale feature fusion technology and a training method thereof, and relates to the field of focus segmentation. By introducing a mask-guided multi-scale feature fusion mechanism, the joint modeling capability of the model on global context information and local detail features is effectively enhanced. The encoder extracts multi-scale features by using the Swin Transform, down-samples original guide masks through the mask guide module and adapts the original guide masks to feature spaces of all levels, feature fusion of target perception is achieved, and the characterization capacity of a complex focus structure is remarkably improved. In the decoder, a pixel decoder uniformly upsamples fusion features into a high-resolution feature map, and a Transform decoder is combined with a set prediction normal form to realize accurate positioning and segmentation of a focus instance through layer-by-layer interaction of a learnable query vector and the high-resolution features. According to the structure, redundancy prediction and post-processing dependence caused by pixel-by-pixel classification in a traditional method is avoided, and the recognition sensitivity and segmentation precision of small focuses are improved.
Owner:HANGZHOU DIANZI UNIV
Magnetic flux leakage field scanning steel bar corrosion image recognition system and method thereof
The application discloses a magnetic flux leakage field scanning steel bar corrosion image recognition system and method, and belongs to the technical field of nondestructive testing and computer vision technology. The system rapidly acquires a two-dimensional distribution image of a magnetic flux leakage field through a magnetic sensor array, adopts a semantic segmentation network based on an encoder-decoder architecture to perform pixel-by-pixel classification on the image, and divides healthy, mild, moderate and severe corrosion areas. Spatial attention and channel attention mechanisms are introduced to identify severe corrosion features such as magnetic flux leakage field gradient mutation and polarity reversal, and to enhance detection accuracy. A domain self-adaptive strategy of adversarial training is adopted to reduce feature distribution differences under different detection scenarios and to improve generalization ability. A three-dimensional reconstruction is performed on the corrosion spatial distribution model by combining reinforcement information through coordinate registration and spatial interpolation. A repair priority list and a bill of quantities are automatically generated. The application has high detection efficiency, accurate recognition accuracy, strong adaptability and visual intuition, and provides an intelligent technical means for concrete structure health monitoring.
Owner:NAT ENG LAB FOR HIGH SPEED RAILWAY CONSTR +2
Automatic detection of colon lesions and blood in colon capsule endoscopy
The present invention relates to a computer-implemented method, capable of automatically detecting clinically relevant colonic pleomorphic lesions and blood or hematic traces in colon capsule endoscopy images, by classifying pixels as colonic pleomorphic lesions or blood or hematic traces, using a convolutional image feature extraction step followed by a classification and indexing step of such findings into a set of one or more classes.
Owner:DIGESTAID ARTIFICIAL INTELLIGENCE DEV LDA
Liquid crystal screen detection method and device with dead pixel classification function
The invention relates to the technical field of liquid crystal screen detection with a defective pixel classification function, and discloses a liquid crystal screen detection method and device with the defective pixel classification function, and the device comprises a classification base, a conveying belt arranged at the top of the classification base, a second conveying belt arranged at the top of the classification base, and a third conveying belt arranged at the top of the classification base. The surface of the classification base is fixedly connected with a support, a cleaning and detecting device is arranged above the classification base, a classification device is arranged above the classification base, and a collecting device is arranged on the surface of the classification base. When the conveying belt is started, the liquid crystal display above the conveying belt can be driven to move, when the liquid crystal display passes through the position below the cleaning soft brush, the cleaning soft brush can clean dust above the liquid crystal display, and it is avoided that the accuracy of machine detection is affected by the dust; and dust cleaned by the cleaning soft brush can enter a dust collection box through a dust collection cover through a dust collection pipe, and collection work is carried out.
Owner:SHENZHEN STANDE TECH CO LTD
Loop filtering method based on adaptive pixel classification criteria
Disclosed is a loop filter method based on an adaptive pixel classification criterion. The loop filter method based on an adaptive pixel classification criterion in an image decoding device includes a step of classifying a restored sample according to an absolute classification criterion or a relative classification criterion, a step of obtaining offset information according to a result of classifying the restored sample, a step of adding the offset value to the restored sample with reference to the obtained offset information, and a step of outputting the restored sample to which the offset value is added. Thus, errors of the restored sample can be corrected.
Owner:INDUSTRY UNIVERSITY COOPERATION FOUNDATION HANYANG UNIVERSITY
Real-time polyp segmentation system based on multi-domain hierarchical attention network
PendingCN121330280ACharacter and pattern recognitionBiological modelsPattern recognitionBoundary precision
The invention discloses a real-time polyp segmentation system based on a multi-domain hierarchical attention network, and relates to the field of medical image processing and computer vision, and the system comprises a dynamic region guide block which is used for partitioning an input image and selecting key region features through a two-stage routing attention mechanism; the potential entropy quantization channel space attention module is used for carrying out channel and space information entropy quantization calculation on the feature map and highlighting fine organization differences; the spatial frequency fusion module is used for performing pixel-level fusion on the spatial domain features and frequency domain features extracted through fast Fourier convolution, and capturing a periodic mode and global structure information; and the patch extension layer and the linear projection are used for layer-by-layer up-sampling and executing quadruple up-sampling in the final stage to recover to the input resolution, and pixel-level segmentation prediction is generated. The boundary precision and the pixel classification performance are both improved, and the real-time performance of polyp segmentation and the clinical application reliability are remarkably improved.
Owner:SUZHOU UNIV
Method to detect lane segments for creating high definition maps
ActiveUS12626518B2Character and pattern recognitionNavigation instrumentsComputer graphics (images)Carriageway
Disclosed herein are system, method, and computer program product embodiments for detecting lane segments in an image for creating high-definition (HD) maps. A neural network can be used to classify a pixel of an image of a location as belonging to a driving lane. If the pixel belongs to a first boundary line of the driving lane, it is labeled accordingly. Based on the labeled pixel and one or more additional labeled pixels as part of the first boundary line of the driving lane, a first line drawing of the first boundary line of the driving lane is constructed. A lane segment based on a combination of the first line drawing of the first boundary line of the driving lane and a second line drawing of a second boundary line of the driving lane can be created.
Owner:FORD GLOBAL TECH LLC
Machine learning based multi-modal image data automated identification system and method
ActiveCN121388215BCharacter and pattern recognitionStill image data clustering/classificationMachine learningImaging data
The application discloses a multi-modal image data automatic recognition system and method based on machine learning, relates to the technical field of image data processing, and comprises the following steps: image data is called, pixel point feature information is extracted, and a pixel point feature sequence is constructed; feature matching degree analysis is performed on the pixel points, and hierarchical division is performed; spatial feature joint index analysis is performed on the pixel points in the same layer, and hierarchical pixel correlation index is obtained by integrating the analysis data; interlayer pixel classification analysis is performed on the pixel points between adjacent layers, pixel classification correlation analysis is performed on the adjacent layers, and pixel classification correlation index of the adjacent layers is determined; correlation evaluation of pixel layer correlation logic is performed on non-repeated image data, and the best image matching combination is output; the application realizes accurate recognition of multi-modal image data, reduces the misrecognition rate and interference rate caused by coarse recognition and coarse matching, and improves the accuracy of image recognition.
Owner:HUNAN INT ECONOMICS UNIV
Vision-based detection of access sheath
This disclosure provides methods, devices, and systems for controlling robotically assisted medical systems. The present implementations more specifically relate to techniques for vision-based detection of an access sheath. In some aspects, a controller for a medical system obtains a series of images captured by a camera disposed on a distal tip of a medical instrument that is at least partially inserted through an access sheath. The controller infers a respective segmentation mask from each image in the series based on a machine learning model trained to classify each pixel of the image as depicting the access sheath or not depicting the access sheath, where the segmentation mask indicates how many pixels of the image are classified as depicting the access sheath. The controller further determines a position of the distal tip of the instrument relative to the access sheath based on the segmentation masks for the series of images.
Owner:AURIS HEALTH INC
Systems and methods for image segmentation
Provided herein are methods for image segmentation. An image of a sample having a plurality of nuclei is received. The image comprises a plurality of pixels arranged in a first dimension and a second dimension. The plurality of pixels indicates a signal from a nuclear stain of the plurality of nuclei. For each pixel of the plurality of pixels, a pixel classification is determined, thereby generating a pixel classification map corresponding to the image. Determining the pixel classification comprises determining a first classification of the pixel corresponding to the first dimension and determining a second classification of the pixel corresponding to the second dimension. A segmentation mask is determined based on the pixel classification map.
Owner:10X GENOMICS INC
Leakage magnetic field scanning steel bar corrosion image recognition system and method thereof
The invention discloses a system and a method for identifying a steel bar corrosion image by scanning a leakage magnetic field, and belongs to the technical field of nondestructive testing and computer vision. The system quickly acquires a leakage magnetic field two-dimensional distribution image through a magnetic sensor array, and performs pixel-by-pixel classification on the image by adopting a semantic segmentation network based on an encoder-decoder architecture; dividing healthy, mild, moderate and severe rusting areas; a space attention and channel attention mechanism is introduced to identify serious corrosion characteristics such as leakage magnetic field gradient mutation and polarity reversal, and the detection precision is enhanced; a domain adaptive strategy of adversarial training is adopted to reduce feature distribution differences in different detection scenes, and generalization ability is improved; performing three-dimensional reconstruction through coordinate registration and spatial interpolation in combination with reinforcement information to generate a corrosion spatial distribution model; according to the method, the detection efficiency is high, the recognition precision is accurate, the adaptability is high, visualization is visual, and an intelligent technical means is provided for concrete structure health monitoring.
Owner:NAT ENG LAB FOR HIGH SPEED RAILWAY CONSTR +2
Geological disaster post-vegetation recovery monitoring method based on high-resolution remote sensing image
ActiveCN115546636BHigh precisionaccurate classificationData processing applicationsEnsemble learningRevegetationVegetation height
The application provides a kind of geological disaster post-vegetation recovery monitoring method based on high-resolution remote sensing image, comprising: constructing fusion type "spectrum-vegetation index-texture" feature set;In sunny weather conditions, more evenly select n typical vegetation samples in the target area;Construct bagging type ensemble learning model;Analysis of the obvious differences of arbor, shrub and herbaceous vegetation in vegetation height, single plant vegetation horizontal projection coverage area, root depth and root extension range;By analyzing the vegetation change rate index and vegetation type change rate index of several continuous time phase remote sensing images according to the time phase change information, the vegetation recovery of the target area is quantitatively analyzed, so as to effectively improve the accuracy of pixel classification method, greatly improve the accuracy of quantitative analysis of vegetation in the target area, and greatly reduce the cost of long-term accurate monitoring.
Owner:SICHUAN ACAD OF FORESTRY
Rocket tank friction stir welding internal defect prediction method based on multi-physical field perception hybrid neural network
The invention discloses a rocket tank friction stir welding internal defect prediction method based on a multi-physics field sensing hybrid neural network, which comprises the following steps: synchronously acquiring multi-modal physical signals in a welding process, ensuring that each signal is strictly aligned in time and space, and constructing a multi-physics field data set; designing a hybrid neural network including hierarchical cross-gating coding, dynamic convolution kernel fusion, frequency domain filtering enhancement, attention gating decoding and a pixel classification head, taking a multi-physical field data set as input, and predicting a defect probability graph; minimizing a composite loss function for defect segmentation task optimization to iteratively search optimal parameters of the hybrid neural network architecture; and deploying the trained optimal model in actual production, performing forward reasoning on the multi-physical field data flow acquired in real time, and finally continuously outputting an intuitive internal defect graph which indicates the defect type and position. According to the method, real-time accurate prediction of the internal defects of the friction stir welding seam of the rocket tank is realized.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Processing a graph representing an image of a technical drawing
A graph processing method where the graph represents an image of a technical drawing including a view and a technical annotation. The method includes, for each view, providing the graph. The graph including nodes and edges. Each node corresponds to a classification of pixels into a semantic class of a predetermined set. Each edge connects two nodes either if the two nodes represent neighboring pixels or if the two nodes represent pixels distant from each other below a predetermined threshold. The set includes geometry, dimension, dimension-related symbol. The method includes clustering, based on the graph topology: nodes corresponding to the geometry class, to reconstruct the geometries in the view, and nodes corresponding to the dimension and dimension-related symbol classes, to reconstruct the annotations of the view. The method includes, associating reconstructed annotations to reconstructed geometries based on a detected position of the annotations and on the graph topology.
Owner:DASSAULT SYSTEMES SA
Ranging device and ranging method
PCT designated stageWO2026134182A1Optical rangefindersElectromagnetic wave reradiationControl cellEngineering
A ranging device (100) comprises: a light source (10) that emits irradiation light; a light reception unit (20) that has a plurality of pixels; a drive control unit (30) that controls the driving of the light source (10) and the plurality of pixels; and a distance calculation unit (50) that calculates the distance to an object (OBJ) on the basis of signals outputted by the plurality of pixels. The drive control unit (30): classifies the plurality of pixels into a plurality of groups each for exposing pixels therein at the same timing, the plurality of groups including a first group to which first pixels among the plurality of pixels belong and a second group to which second pixels adjacent to the first pixels among the plurality of pixels belong; drives the plurality of pixels such that, in the same frame, the timing of exposure based on emission of irradiation light differs between the plurality of groups; and drives the plurality of pixels such that, across consecutive frames, the timing of exposure based on emission of irradiation light alternates between the plurality of groups.
Owner:NUVOTON TECH CORP JAPAN
Image rendering method and device
The invention relates to the technical field of image processing, in particular to an image rendering method and device. The method comprises the following steps: acquiring an attention thermodynamic diagram and a depth map of a first image through virtual reality technology equipment; performing pixel-by-pixel classification on the first image by adopting a semantic segmentation network, obtaining semantic tag information corresponding to each pixel in the first image, and obtaining motion state data corresponding to each pixel in the first image; obtaining a significance factor of each pixel according to the attention thermodynamic diagram, the depth map, the semantic label information and the motion state data; partitioning the first image according to the significance factor and four-dimensional gradient data corresponding to the first image to obtain a grid partition set; and performing rendering processing and fusion processing on the second image corresponding to each grid partition by adopting a rendering strategy corresponding to each grid partition in the grid partition set to obtain a third image, and displaying the third image on the virtual reality technical equipment. According to the invention, the image rendering quality and convenience can be improved.
Owner:MIGU COMIC CO LTD +2
A visual-based blade spraying uniformity identification method
ActiveCN121121322BCharacter and pattern recognitionBiological modelsImage extractionImaging processing
The application discloses a kind of based on vision's blade spraying uniformity identification method, belong to image processing technical field.The application is under two kinds of light intensity acquisition blade image, obtain medium light image and high light image;Extract brightness and carry out pixel level difference, obtain two brightness difference graphs;Luminance difference graph is handled using filter core, and structural uneven intensity graph is generated according to maximum and minimum response value difference;Pixel classification is carried out to structural uneven intensity graph, distinguish smooth point and structural mutation point, and carry out binary and OR operation, obtain structure co-display graph, and structural extraction graph is obtained by morphological operation;According to structural uneven intensity graph, generate unevenness weight graph;Extract structural extraction graph and unevenness weight graph feature, carry out fusion splicing, and generate spraying uniformity score.The method utilizes the visual difference under different illumination conditions, realizes the high-precision identification of blade spraying uniformity.
Owner:SICHUAN LIANGSHANSHUILUOHE ELECTRICITY DEV CO LTD
Generating artificial color images from narrow spectral band data on camera-equipped vehicles
ActiveCN116320794BRoad vehicles traffic controlCharacter and pattern recognitionPattern recognitionBandpass filtering
A visual perception system includes a scanning camera, a color sensor having a color filter array (CFA), and a classifier node. The camera captures a full-color pixel image of a target object, such as a traffic signal light, and processes the pixel image through a narrow bandpass filter (BPF) such that the narrow BPF outputs a monochrome image of the target object. The color sensor and CFA receive the monochrome image. The color sensor has at least three color channels, each corresponding to a different color of spectral data in the monochrome image. The classifier node classifies constituent pixels of the monochrome image into different color bins as corresponding colors of interest using a predetermined classification decision tree. The colors of interest can be used to implement control actions, such as via an automatic driver assistance system (ADAS) control unit or indicator device.
Owner:GM GLOBAL TECHNOLOGY OPERATIONS LLC
A rock breaking efficiency prediction method based on image recognition and machine learning
A rock breaking efficiency prediction method based on image recognition and machine learning, acquires a rock surface image, and applies image processing technology for grayscale processing, then performs pixel classification and image segmentation to clearly divide different minerals into several independent structure graphs; modeling the rock material according to the mineral composition, and importing the boundary information of the several structure graphs into the model to generate several large particle filling rock blocks with the same size as the several structure graphs, and calibrating the mesoscopic parameter values according to the rock mechanics characteristics; a disc cutter rock breaking discrete element calculation model is established, and multiple intrusion rock breaking simulation tests are carried out on rock samples with different mineral contents; the simulation results are collected to construct a rock breaking efficiency data set; a prediction model is established based on the PSO-BPNN algorithm, and after training, the rock breaking efficiency prediction model is obtained; the established model is used for real-time prediction of rock breaking efficiency. The method can consider the influence of rock mineral composition on disc cutter rock breaking effect, and realize efficient and accurate prediction of disc cutter rock breaking efficiency by combining rock micro composition with macro rock breaking behavior.
Owner:CHINA UNIV OF MINING & TECH
Multi-modal image data automatic identification system and method based on machine learning
ActiveCN121388215ACharacter and pattern recognitionStill image data clustering/classificationMachine learningImaging data
The invention discloses a multi-modal image data automatic identification system and method based on machine learning, and relates to the technical field of image data processing.The method comprises the steps that image data are called, pixel point feature information is extracted, and a pixel point feature sequence is constructed; feature matching degree analysis is carried out on the pixel points, and hierarchical division is carried out; performing spatial feature joint index analysis on pixel points in the same hierarchy, and performing integration according to analysis data to obtain a hierarchy pixel correlation index; carrying out different-level pixel classification analysis on the pixel points between the adjacent levels, carrying out pixel classification correlation analysis on the adjacent levels, and determining pixel classification correlation indexes of the adjacent levels; performing correlation evaluation of pixel level correlation logic between the non-repeated image data, and outputting an optimal image matching combination; according to the invention, accurate identification of multi-modal image data is realized, the false identification rate and interference rate caused by rough identification and rough matching phenomena are reduced, and the accuracy of image identification is improved.
Owner:HUNAN INT ECONOMICS UNIV
Distribution of video content
Owner:TEXAS INSTRUMENTS INC
Method for representing an additional graphic information in an image of an environmental region of a motor vehicle, electronic vehicle guidance system for a motor vehicle, motor vehicle, and computer program product
PCT designated stageWO2026027307A1Geometric image transformationCharacter and pattern recognitionGraphicsObject Class
The invention relates to a method for representing an additional information in an image of an environmental region (34) of a vehicle (10), containing contents that are represented by pixels on a display of a display device (16) of the vehicle (10), wherein the additional information is represented as overlay on top of the contents. Therein, a pixelwise classification of the contents is performed, wherein each pixel of the image is assigned to an object class. Then an assigning of a pixel value to each pixel depending on the object class and a storing of the pixel values is effected. Then the pixel values of the pixels within a region of the image to be currently overlaid by the additional information are determined and an overlaying of the additional information is effected only on top of pixels with pixel values within a predetermined range.
Owner:CONNAUGHT ELECTRONICS
Crop growth monitoring method and system based on unmanned aerial vehicle image
The invention belongs to the field of crop growth monitoring, and discloses a crop growth monitoring method and system based on an unmanned aerial vehicle image, and the method comprises the steps: obtaining boundary coordinates of a preset monitoring region, determining a target resolution range according to a crop type and a growth stage, and calculating an optimal flight height interval in combination with unmanned aerial vehicle performance parameters; a self-adaptive route planning algorithm is adopted, the flight path is dynamically adjusted in the optimal flight height interval, it is ensured that the whole monitoring area is covered, and meanwhile the image resolution is maximized; the method comprises the following steps: collecting crop image data through a multispectral imaging device, and preprocessing an original image by using a preset radiation correction model to obtain a standardized multispectral image data set; and deploying the trained feature extraction model, and carrying out pixel-by-pixel classification on the preprocessed multispectral image to obtain a semantic segmentation result of each part of the crop. And according to a semantic segmentation result, calculating preset growth index parameters, and generating a crop growth state quantification report.
Owner:CHENGDU VOCATIONAL COLLEGE OF AGRI SCI & TECH
