409 results about "Reference Region" patented technology

The invention provides a hull surface defect detection system based on machine vision, and relates to the technical field of data processing. The image correction module is used for carrying out illumination equalization processing and geometric distortion correction; the region construction module is used for identifying a defect-free stable region and generating reference region data which comprises a brightness model and a texture model; the candidate generation module is used for detecting a region where texture interruption or abnormal bright spots exist locally to form candidate defect data, and the candidate defect data comprise pixel positions and local contrast parameters; the stability judgment module is used for carrying out projection matching in the multiple frames of images and simultaneously carrying out joint comparison with the brightness model and the texture model of the reference area data to form real defect data and false defect data; the result output module is used for generating a detection result containing defect coordinates, defect contours, image frame numbers and interference sample prompts; the accuracy of hull surface defect detection is improved.

A method comprising: receiving an image block unit of a frame, the image block unit comprising samples in color channels comprising at least one chrominance channel and one luminance channel; reconstructing samples of said luminance channel of the image block unit; determining a reference area for predicting target samples of at least one color channel of the image block unit, wherein said reference area comprises one or more reference samples in a neighboring block in current color channel / frame, in the neighboring of a co-located block in reference color channel / frame; and / or inside the co-located block in reference color channel / frame; determining weights for predicting said target samples based on a ratio between a normalized luminance histogram in said reference area and a normalized luminance histogram co-locating said target samples; determining filter coefficients of a filter for said predicting based on the weights, the reference samples and a shape of the filter; and predicting samples of at least one color channel of the image block unit based on the samples of said luminance channel and the filter coefficients.

Disclosed herein are a method, an apparatus and a storage medium for image encoding / decoding. Methods for performing more accurate prediction are disclosed when performing prediction using a block vector. A block vector for a target block is derived by template matching, and a prediction block for the target block is determined based on the derived block vector. Various and detailed embodiments for a plurality of pieces of information used to derive a block vector, such as a search area, a block vector candidate list, a reference region, a buffer, and a tree type, are provided.

The invention relates to the technical field of projection, and discloses a method, a device and equipment for measuring a projection ratio and an off-axis ratio, and a medium. The method comprises the following steps: acquiring a projection test image obtained by sampling a projection area and a reference area by an image sampling device of the projector; performing area feature extraction processing on the projection test image to obtain image size information and central point pixel information of a projection area and image size information of a reference area; determining the projection ratio of the projector based on the image size information of the projection area, the projection distance information of the projector and the image size information and the actual size information of the reference area; and determining the off-axis ratio of the projector based on the central point pixel information of the projection area, the optical axis pixel information of the projector and the image size information and the actual size information of the reference area. According to the embodiment of the invention, the cost of measuring the projection ratio and the off-axis ratio can be reduced.

The invention relates to the technical field of infrared measurement, in particular to an intelligent calibration method and system for temperature measurement of an infrared sensor, and the method comprises the steps: enabling an infrared camera to align with a blackbody radiation source to form a calibration scene, collecting the output of a plurality of groups of pixels under different radiation temperatures and different internal part temperature states, fitting a temperature signal response model containing an exponential term and a bias term according to least square to obtain amplitude, exponential, temperature offset and output bias parameters; during measurement, a thermal image containing a target object and two reference blackbody sources is obtained, and parameters such as emissivity, environment equivalent radiation temperature, transmission medium and optical transmission, camera temperature and the like are synchronously obtained; performing non-uniformity and offset correction and abnormal pixel replacement on the thermal image; the initial temperature is inverted based on radiation transfer decomposition and compensation of internal radiation of the camera; and carrying out statistical averaging on the temperatures of the two blackbody reference regions to obtain a double-point correction coefficient, and outputting correction temperature or temperature distribution. According to the method, the problems that temperature inversion model parameters are difficult to adaptively update along with working conditions and on-site temperature measurement errors are difficult to effectively suppress when an existing infrared sensor array is in a long-distance non-contact temperature measurement scene can be solved.

The invention relates to the technical field of infrared temperature measurement of power equipment, and provides an infrared temperature measurement compensation method combining physical transmission and depth residual error, which comprises the following steps: acquiring an infrared image and physical parameters related to radiation transmission; establishing a differentiable forward physical model, and calculating radiation brightness; performing first-order physical inversion according to the differentiable forward physical model to obtain a baseline temperature of the target area; constructing a deep residual learning network, taking the infrared image, the baseline temperature and the physical parameters as input, outputting a pixel-level temperature residual estimation value, and correcting the baseline temperature to obtain a corrected temperature; closed-loop joint optimization is constructed and executed, and the closed-loop joint optimization is based on the consistency constraint of the simulated radiance and the actually measured radiance, and parameters of the target distance and the deep residual learning network are synchronously updated; and based on the corrected temperature after closed-loop joint optimization, calculating the temperature difference between the hot spot area and the reference area, carrying out distance normalization processing on the temperature difference, and outputting a standardized temperature difference result.

A surface estimation method includes a region-setting step and an estimation step. In the region-setting step, a reference region that is one of a three-dimensional region and a two-dimensional region is set. The three-dimensional region includes three or more points and is set in a three-dimensional space. The three-dimensional space includes three-dimensional coordinates of three or more points on a subject calculated on the basis of a two-dimensional image of the subject. The three-dimensional coordinates of the three or more points are included in three-dimensional image data. The two-dimensional region includes three or more points and is set in the two-dimensional image. In the estimation step, a reference surface that approximates a surface of the subject is estimated on the basis of three or more points of the three-dimensional image data corresponding to the three or more points included in the reference region.

The invention relates to the technical field of computer vision, in particular to a screw conveyor blade pressing quality detection method based on image recognition, and the method comprises the steps: obtaining a target image and a reference image of a to-be-detected screw conveyor blade; if it is detected that the suspected abnormal pixel points exist in the target image, obtaining a suspected defect area according to the gray distribution feature and the texture feature of each suspected abnormal pixel point in the target image; obtaining a reference area of each suspected defect area in each reference image, and obtaining a defect coefficient of each suspected defect area according to the gray level change characteristics and gradient values of the pixel points in each suspected defect area and the gray level distribution characteristics of the pixel points in each reference area; the defect coefficient of each suspected defect area is utilized to optimize the gray value of the pixel point of each suspected defect area to obtain an optimized image, and the threshold segmentation algorithm is utilized to segment the optimized image, so that the accuracy of propeller blade defect detection is improved.

The invention provides a question image searching method, device and equipment and a readable storage medium, and the method comprises the steps: carrying out the segmentation processing of an input question image, recalling a primarily selected question image through a feature vector, preliminarily screening out possibly related images, determining a reference region and a non-reference region based on the structural layout of a question in a candidate question image, and carrying out the searching of the question image through the reference region and the non-reference region; the layout similarity is determined by using the relative distance between the region pairs when the candidate question image and the region pairs are mapped to the input question image, and the image similarity between the candidate question image and the input question image is determined by integrating the layout similarity of each region pair, so that a target question image is determined; image search is performed by analyzing the image content features of the image and the structural layout features in the image, character recognition is not depended on, topic images of different languages can be directly processed and matched, unified search of topics of different languages is achieved, the image search accuracy is improved, and the image search efficiency is improved. And the user can quickly acquire the target question image.

A method for coding a video implemented in an encoder or a decoder including the enhanced interpolation filter, EIF, for motion compensation, the method comprising: i) determining control point motion vectors, CPMVs, for a block according to affine inter-prediction, the block being an affine block or a sub-block of the affine block; ii) for a predefined sub-block size determining a reference area for a sub-block with the predefined sub-block size according to values of the CPMVs; iii) comparing the determined reference area with a predefined threshold; iv) applying EIF for motion compensation, comprising deriving the pixel-based motion vector field for the block; wherein if the determined reference area is larger than the threshold, deriving the pixel-based motion vector field for the block further comprises motion vector clipping, wherein motion vector clipping range is determined based on motion model of the block and the size of the block.

The invention relates to a geoid-like model processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: dividing an area along a railway into a plurality of elevation reference areas according to terrain information and railway information of the area along the railway; according to the gravity data of each elevation reference region, obtaining elevation abnormal data of each elevation reference region; based on the elevation abnormal data of each elevation reference region, performing whole-line modeling processing on each elevation reference region to obtain a whole-line quasi-geoid model of the region along the railway; carrying out zoning modeling processing or zoning modeling processing on each elevation reference region on the basis of a full-line geoid-like model to obtain a target geoid-like model of each elevation reference region; the model precision of the target geoid-like model is higher than that of the full-line geoid-like model. By adopting the method, the model precision of the target geoid model of the region along the railway can be improved.

The invention relates to the field of GNSS-R SAR image cross-correlation registration, in particular to a GNSS-R SAR image cross-correlation registration method based on an improved window function. The scheme comprises the following steps: extracting a matching region from a main image, and extracting a reference region from a slave image; performing sliding traversal in the matching region and the reference region by using an improved elliptical weighted window function, and calculating coherence coefficients under translation positions one by one to obtain a coarse registration offset; performing multiple cubic interpolation on the time sequence image to obtain a primary image and secondary image interpolation result with sub-pixel precision, re-selecting a matching area and a reference area on the interpolated image, and repeating sliding traversal and coherence coefficient calculation to obtain a fine registration offset; and performing interpolation resampling on all the slave images based on the final registration offset to obtain a time sequence image set of which the registration precision is a sub-pixel level. The GNSS-R SAR image cross-correlation registration method is suitable for GNSS-R SAR image cross-correlation registration.

The invention discloses a differential measurement-based satellite-borne synthetic aperture microwave radiometer imaging correction method, which comprises the following steps of: respectively selecting a reference area and a correction area in a global range, and respectively intercepting scientific data and auxiliary data in a specific time period in the reference area and the correction area based on load normal earth observation data; averaging the visibility functions intercepted in the reference area to obtain a reference visibility function; generating a reference brightness temperature and a correction brightness temperature through a simulation model by using the auxiliary data intercepted in the reference area and the correction area respectively; performing difference and inversion processing on the normal earth observation visibility function to be subjected to imaging processing by using the reference visibility function to obtain a difference inversion brightness temperature; calculating a correction coefficient by using the reference visibility function, the reference brightness temperature, the visibility function intercepted in the correction area and the correction brightness temperature; and correcting and compensating the differential inversion brightness temperature by using the correction coefficient and the reference brightness temperature to obtain the final inversion brightness temperature.

The invention provides a structural decomposition and information identification method of multi-modal data, a medium and equipment, and the method comprises the steps: obtaining to-be-processed multi-modal literature data, the multi-modal literature data being documents or pictures, the types of the documents including word documents and PDF (Portable Document Format) documents; the method comprises the following steps: converting to-be-processed multi-modal literature data into to-be-processed literature data in an image form, preprocessing the to-be-processed literature data to obtain input image data, inputting the input image data into a field fine-tuning DETR model, identifying a logic region category of the input image data through the field fine-tuning DETR model, obtaining a region category identification result, and outputting the region category identification result. The logic region category comprises a title region, an author region, an abstract region, a text region, an illustration region, a table region, a formula region, a footer region and a reference region; and carrying out differential information extraction on each region category identification result to obtain information corresponding to each region category identification result so as to realize accurate identification of information in the multi-modal data.

The invention discloses a traditional Chinese medicinal material defect detection method based on machine vision, relates to the technical field of intelligent detection, and solves the problems that in the prior art, a threshold cannot be migrated, so that an inter-batch judgment standard is unstable, and high-resolution block reasoning causes boundary pseudo defects and instance wrong affiliation. According to the method, a reference area is constructed in a batch domain, a statistical descriptor is extracted, and monotone mapping calibration is performed on defect scores so as to realize cross-batch unified judgment; meanwhile, a seam continuity field is introduced in the image block splicing process, defect connected domains are fused through a cross-window adjacency relation, and accurate attribution of defects and medicinal material pieces is achieved based on bipartite graph matching; according to the method, the judgment stability and the statistical reliability in the traditional Chinese medicinal material defect detection process are remarkably improved.

A method comprising receiving an image block unit of a frame, the image block unit comprising samples in a first chrominance channel, chrominance channel, a second chrominance channel and one luminance channel; defining co-located reference areas over luminance components of the luminance channel, chroma components of the first chrominance channel and chroma components of the second chrominance channel; performing motion-compensated prediction for the luminance component, the first chrominance component and the second chrominance component using reference frames and motion vectors; obtaining a first mapping function that maps the luminance component into the first chrominance component and a second mapping function that maps the luminance component into the second chrominance component using the co-located luminance prediction and the chrominance predictions; reconstructing a luminance residual; and obtaining a first chrominance prediction by using the first function and the luminance residual, and a second chrominance prediction by using the second function and the luminance residual; and obtaining a first chrominance prediction by using the first function and the luminance residual, a second chrominance prediction by using the second function and the luminance residual.

The invention discloses a chip packaging method and a related device, and the method comprises the steps: determining an overlapping region, a reference region and a shielding boundary curve according to imaging data, and obtaining interconnection nodes and rigidity constraint data in the overlapping region; acquiring polarization intensity data in the overlapping region, and obtaining a surface slope field through a dual-band intensity ratio and multidirectional fusion conversion; taking the reference area as a Dirichlet boundary condition, taking a normal derivative of the shielding boundary curve as a Noiemann boundary condition, and carrying out Poisson integration on the surface slope field to obtain a relative height map of the upper chip; and solving low-order deformation parameters of the lower-layer chip through elastic constraint energy minimization according to displacement observation and interconnection rigidity constraint of the relative height map at interconnection nodes. According to the scheme, the technical problems that in a traditional method, geometric benchmark missing exists in an overlapping band, and a shielded layer cannot be observed can be solved.

The invention relates to the technical field of image processing, and discloses a sulfur hexafluoride ring main unit gas leakage detection method and system based on thermal imaging, and the method comprises the steps: obtaining an infrared thermal imaging multispectral sequence image of a ring main unit; identifying a plurality of candidate regions of the multispectral sequence image, selecting a gas reference region, and calculating an average multispectral vector of the gas reference region as a gas reference spectrum; calculating the intra-group variance of each spectrum channel, and determining a weight vector and an angle threshold value; calculating a weighted spectral angle between the multispectral vector of the pixel point to be detected and the gas reference spectrum; judging the to-be-detected pixel point which simultaneously meets the following conditions as a gas leakage point: the weighted spectral angle is smaller than an angle threshold value, and the temperature of the to-be-detected pixel point is lower than a preset temperature threshold value; and generating a visual image of the gas leakage area according to all the judged gas leakage points. According to the invention, the anti-interference capability of detection is improved, and reliable identification of sulfur hexafluoride gas leakage can be realized under a complex background.

The embodiment of the invention provides a user interface defect image generation method, a model training method, a user interface defect detection method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of image processing. The method comprises the steps that segmentation information, element information and copywriting information of a screenshot of a user interface are obtained, the segmentation information is used for indicating a segmentation area corresponding to each pixel in the screenshot, different segmentation areas represent different control elements, and the element information indicates a reference area, in the screenshot, of each control element in the user interface; the copywriting information indicates a copywriting area of each copywriting in the screenshot; and respectively processing the screenshots through the construction mode of the at least one user interface defect image and the target information required by the corresponding construction mode to obtain the user interface defect image of the at least one defect type. User interface defect images of various defect types can be generated without limiting the number, and the problem that the number of model samples is small is solved.

According to embodiments of this disclosure, a method and apparatus for data processing are provided. The method includes: determining a reference region corresponding to a target traffic light indicated by map data in an image coordinate system corresponding to a perceived image; determining a set of candidate objects from a plurality of candidate objects identified based on the perceived image, based on the positional relationship between the reference region and a plurality of candidate regions, wherein the plurality of candidate regions correspond to the plurality of candidate objects identified as traffic lights; determining a first correlation between a first attribute of the target traffic light and a second attribute of the set of candidate objects, wherein the first attribute is determined based on the map data and the second attribute is determined based on the perceived image; and matching the target traffic light with the target objects in the set of candidate objects based on the first correlation. Based on this approach, embodiments of this disclosure can more accurately identify and match traffic lights.

A video decoding method according to an embodiment comprises: obtaining flag information indicating whether MIP is applied and prediction mode information of a current block; when the flag information indicates that MIP is applied and a prediction mode of the current block is an MIP prediction mode, setting a reference region used for MIP on the basis of condition information of the current block; determining a matrix used for MIP; and obtaining a prediction sample of the current block on the basis of the reference region and the matrix.

The present disclosure relates to systems, software, and computer-implemented methods for automatically identifying handwritten tips. An example method includes obtaining an image of a receipt, where the image includes a reference region in a pre-set format, a plurality of category identifiers, and at least one set of handwritten characters. The reference region and the plurality of category identifiers can be printed. The plurality of category identifiers can be located at pre-set positions relative to the reference region. The method further includes obtaining optical character recognition (OCR) information of the image and identifying the reference region from the OCR information based on the pre-set format of the reference region. The method further includes determining a plurality of amounts based on the OCR information and the reference region, where at least one of the plurality of amounts is associated with a tip category.

A method and a device for encoding / decoding an image according to the present invention may determine a reference region for intra prediction of a current block, derive an intra prediction mode of the current block on the basis of a predetermined MPM candidate group, and perform intra prediction on the current block on the basis of the reference region and the intra prediction mode.

This invention relates to the field of display control, and more particularly to a TFT-LCD liquid crystal display based on intelligent control, comprising: a display module for receiving image signals and converting them into visual images; a control analysis module for determining a region prediction strategy based on a display dynamic index and a display complexity index; a prediction processing module for determining a prediction execution mode based on a trajectory freedom index and a master control execution dynamic index; a prediction execution module for determining predicted brightness parameters based on prediction key coefficients and reference area focus coefficients; an equalization processing module for determining predicted brightness parameters for each dynamic control area based on reference area complexity parameters and reference area dynamic parameters; and an equalization execution module for determining an adjustment execution mode based on an execution distribution index and an execution proportion index. This invention reduces the energy consumption of the liquid crystal display while ensuring the overall coordination and smoothness of the presented image.

This invention belongs to the field of medical image processing and deep learning inference technology, specifically relating to a method, device, and storage medium for denoising and enhancing low-dose CT images. The denoising and enhancement method includes the following steps: S1, acquiring a low-dose CT image; S2, calculating the noise level parameter N; S2.1, generating a uniform reference region mask; S2.2, robust noise estimation within the mask; S2.3, robust fusion of the noise level parameter; S3, generating a denoised image I_dn based on the CT image to be processed using a deep learning denoising network; S4, calculating the denoising intensity coefficient s according to the noise level parameter N, and performing weighted fusion of the CT image to be processed and the denoised image I_dn to obtain the output enhanced image. This invention has the advantages of strong adaptability, no need for manual ROI selection, good robustness, and easy deployment.

The present application relates to the technical field of computer vision, and particularly relates to a spiral machine blade pressing quality detection method based on image recognition, which obtains a target image and a reference image of a spiral machine blade to be detected; if it is detected that there are suspected abnormal pixel points in the target image, then according to the gray distribution characteristics and the texture characteristics of each suspected abnormal pixel point in the target image, a suspected defect region is obtained; a reference region of each suspected defect region is obtained in each reference image, and according to the gray variation characteristics and the gradient value of the pixel points in each suspected defect region and the gray distribution characteristics of the pixel points in each reference region, a defect coefficient of each suspected defect region is obtained; the gray value of the pixel points of each suspected defect region is optimized by using the defect coefficient of each suspected defect region, an optimized image is obtained, and the optimized image is segmented by using a threshold segmentation algorithm, so that the accuracy of the propeller blade defect detection is improved.

Embodiments of the present application provide an interface operation instruction generation method, electronic equipment, storage medium and program product. It is related to the field of human-computer interaction and the field of computer vision technology. The method comprises: obtaining fusion features based on visual features of an operation interface and current semantic features of a user instruction; generating a target region frame corresponding to a current interface element according to the fusion features by using a region frame regression module, the current interface element being an interactive element in the operation interface, the target region frame being used to represent an interactive region of the current interface element, and the region frame regression module being trained based on reference interface elements with labeled reference region frames; and generating an operation instruction for executing an operation based on the target region frame. In the technical solution of the embodiments of the present application, the present application solves the technical problem of inaccurate interface element recognition in related technologies, which leads to unsatisfactory accuracy of automatic operation execution.

The present application discloses an encoding method, a decoding method, a code stream, an encoder, a decoder, and a storage medium. The method comprises: determining one or more vector parameters of a current block; determining at least one second reference region on the basis of a first reference region indicated by the one or more vector parameters, wherein the second reference region is obtained by merging first reference regions indicated by at least some vector parameters among the one or more vector parameters; determining one or more prediction modes of the current block on the basis of the at least one second reference region, wherein the one or more prediction modes are determined on the basis of gradient information derived from the at least one second reference region; and determining a prediction sample of the current block on the basis of the one or more prediction modes.