565 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.

The invention discloses a dynamic calibration type laser surface real-time detection method and system, and the method comprises the following steps: obtaining initial calibration parameters of a laser projection module and a high-speed imaging module through a standard calibration plate, building an initial measurement coordinate system through a camera calibration method, and building a dynamic calibration model; through a dynamic calibration mechanism, calibration parameters are updated in real time, and a sub-pixel-level laser light strip center coordinate extraction method is combined, so that the detection precision is effectively improved, and tiny surface defects can be detected; by responding to changes of environmental parameters such as vibration, temperature and illumination intensity in real time and automatically triggering a calibration process, it is ensured that a high-precision detection result can still be kept in a complex industrial environment; by adopting the mode of combining the standard calibration plate and the workpiece reference area, the calibration time is shortened, and for workpieces of different models, quick adaptation can be achieved through quick migration of pre-training model parameters and a federal learning mode, and the production efficiency 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 (900); reconstructing samples of said luminance channel of the image block unit (902); determining a reference area for predicting samples of at least one color channel of the image block unit, wherein said reference area comprises one or more of 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 (904); determining filter coefficients of a filter for said predicting based on the reference samples and a shape of the filter (906); and predicting samples of at least one color channel of the image block unit by performing a convolution between the samples of said luminance channel and the filter coefficients (908).

The invention relates to the technical field of image enhancement, in particular to a field-level crop image enhancement system based on multi-source remote sensing data, and the system comprises an artifact joint detection module which analyzes the mutation or periodicity of a statistical mean value and a variance value in the row and column directions of an input field-level remote sensing image, and recognizes an artifact stripe region. According to the invention, the method achieves the high-precision removal of thin clouds and stripe artifacts through carrying out the mutability analysis of the local mean and variance of the input remote sensing image in the row and column directions, positioning a stripe artifact region, and building an attenuation numerical relationship in combination with the spectral information of an adjacent clear sky reference region, and reduces the ground feature information loss in the image. Multi-scale coefficient decomposition is further performed on the image after artifact removal, texture features are extracted from homogeneous crop canopies in adjacent undamaged areas, and high-frequency coefficients of damaged areas are dynamically replaced and reconstructed, so that the texture structures of the damaged areas are highly consistent with those of the adjacent areas, and the regional texture continuity and authenticity are improved.

The embodiment of the invention provides an interface operation instruction generation method, electronic equipment, a storage medium and a program product. The method relates to the field of man-machine interaction and the technical field of computer vision, and comprises the following steps: obtaining fusion features based on visual features of an operation interface and current semantic features of a user instruction; according to the fusion features, a region frame regression module is adopted, a target region frame corresponding to the current interface element is generated, the current interface element is an interactive element in the operation interface, and the target region frame is used for representing an interactive region of the current interface element; the region frame regression module is obtained by training based on reference interface elements marked with reference region frames; and generating an operation instruction for executing operation based on the target area frame. In the technical scheme of the embodiment of the invention, the technical problem that the accuracy of automatic operation execution is not ideal due to inaccurate interface element recognition in related technologies is solved.

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 method includes receiving an image block unit of a frame, the image block unit including samples in a first chrominance channel, a second chrominance channel, and one luminance channel; defining a co-located reference area across a luminance component of the luminance channel, a chrominance component of the first chrominance channel, and a chrominance component of the second chrominance channel; performing motion compensation prediction of the luminance component, the first chrominance component, and the second chrominance component using the reference frame and a motion vector; obtaining a first mapping function that maps the luminance component to the first chrominance component and a second mapping function that maps the luminance component to the second chrominance component using the co-located luminance prediction and chrominance prediction; reconstructing a luminance residual; and obtaining a first chrominance prediction by using the first function and the luminance residual and obtaining a second chrominance prediction by using the second function and the luminance residual.

The invention discloses a defect abandoning and curved surface fitting method and system based on point cloud data and a medium. The method comprises the following steps: preprocessing the point cloud data; segmenting the preprocessed point cloud data into a plurality of rectangular regions; based on a geometric shape defect detection method, whether defects exist in the rectangular areas or not is judged, and the areas with the defects are removed; carrying out effective sampling based on region features on the reserved region; in the reference area, performing curved surface fitting by using a non-uniform rational B spline to obtain a fitting curved surface of the reference area; and taking the fitting curved surface of the reference region as an initial curved surface, constructing an overall fitting objective function, introducing a smoothness penalty term of a curved surface second derivative to make the curved surface complexity, and completing overall curved surface fitting. According to the method, high-precision curved surface fitting can be realized, and the problems of insufficient fitting precision and poor local detail capturing capability in the prior art are effectively solved.

The invention relates to the technical field of spectrum correction, and discloses a spectrum information correction method and system for a spectrum abnormal region, and the method comprises the steps: collecting original spectrum data through an optical fiber confocal microscopic Raman spectrum system, and carrying out the multi-scale gradient analysis, and obtaining the characterization data of a multi-layer gradient flow field; performing flow field topology analysis on the characterization data of the multi-layer gradient flow field to obtain a spectrum abnormal region and a boundary point set; carrying out thermonuclear function processing on the normal spectrum region to obtain a multi-scale characteristic spectrum set and a normal reference region; executing gradient guide reconstruction according to the multi-scale characteristic spectrum set and the normal reference region to obtain preliminary correction data of a spectrum abnormal region; according to the method, the topological relation between the abnormal region and the normal region can be accurately described, and the structural integrity and continuity of the spectrum can be better maintained in the correction process.

The invention provides a processing method, processing equipment and a storage medium, and the processing method can be applied to the processing equipment, and comprises the steps: determining or obtaining a prediction mode of at least one sub-block of a current block according to at least one reference region of the current block. According to the technical scheme of the invention, the prediction accuracy of the local region of the image block can be effectively improved, and the prediction effect of video coding and / or decoding can be improved.

A multilayer ceramic electronic component includes a first extension portion including a bent portion in a cross section. The multilayer body is divided into four regions by a straight line passing through a middle portion of the multilayer body in a lamination direction and a straight line passing through a middle portion of the multilayer body in a length direction, and a region adjacent to a first main surface and a first end surface among the divided four regions is defined as a first reference region, and a regression line derived based on values of x and y with respect to the bent portion in a reference region is defined as a virtual connection line, the virtual connection line intersects an effective layer portion.

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 a method and a system for realizing fast and uniform focusing of emergent light spots of a multi-mode optical fiber based on superpixels, belongs to the technical field of novel optical imaging and light field regulation and control, and integrates online speckle acquisition, offline amplitude optimization and an online speckle acquisition stage. When a certain modulation area is in an activated state, respectively capturing a non-interference speckle image of the emergent end of the multimode optical fiber and an interference speckle image generated when the area and the reference area are activated at the same time, and traversing all the modulation areas to totally obtain a speckle image; in the off-line amplitude optimization stage, a focusing light spot is preset, and calculation is carried out by utilizing intensity information of a corresponding focusing position in the speckle image. And analyzing all the focusing light spots one by one so as to construct a binary amplitude modulation mask. And the masks are loaded to the spatial light modulator one by one, so that accurate point-by-point focusing of N emergent light spots of the multimode optical fiber is realized, and the focusing efficiency and uniformity are greatly improved.

The invention relates to the technical field of image data processing, in particular to a boiler coke accumulation detection system based on unmanned aerial vehicle inspection, the system comprises a processor and a memory, and the processor executes a computer program of the memory to realize the following steps: obtaining at least two correction images and one fusion image of any to-be-detected part in a boiler, if it is detected that a suspected focus area exists in the fused image, a reference area corresponding to the suspected focus area is obtained from each corrected image, and the corrected image is obtained according to the gray value difference of pixel points in the suspected focus area and each reference area, the gray value change features of the pixel points in the suspected focus area and the gray value difference. Obtaining the focus accumulation confidence degree of each suspected focus accumulation area in the fused image; according to the focus accumulation confidence degree of each suspected focus accumulation area, the total weighted frequency number of each gray value in the fused image is obtained, histogram equalization is utilized to carry out enhancement processing on the fused image, an equalized image is obtained, and the accuracy of focus accumulation detection is improved.

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.

An image encoding / decoding method according to the present invention comprises determining at least one intra prediction mode for a current block; and on the basis of the at least one intra prediction mode, performing intra prediction on the current block. Here, the at least one intra prediction mode may be determined via a histogram derived from a reference region of the current block.

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.

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.

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.

Provided in the embodiments of the present application are an image detection method, and an electronic device and a storage medium. The method comprises: acquiring an image to be subjected to detection; inputting said image into a feature extraction model for feature extraction, so as to obtain a feature vector group to be subjected to detection that corresponds to a region to be subjected to detection in said image, wherein the region to be subjected to detection corresponds to a feature vector library, the feature vector library comprises at least one reference feature vector group, the at least one reference feature vector group corresponds to at least one reference region on a one-to-one basis, and the region to be subjected to detection that corresponds to the feature vector library and the at least one reference region both correspond to the same image position; comparing, with reference feature vector groups stored in the feature vector library corresponding to the region to be subjected to detection, the feature vector group to be subjected to detection that corresponds to the region to be subjected to detection, so as to determine whether the region to be subjected to detection meets a first preset requirement; and when the region to be subjected to detection does not meet the first preset requirement, determining that the region to be subjected to detection is an abnormal region. The solution facilitates an improvement in the efficiency of image detection.

The invention discloses an FPC golden finger surface defect detection method based on image analysis, and relates to the field of image analysis, and the method comprises the steps: uploading circuit board structure parameters, edge pin sizes and distribution information, and constructing a circuit board three-dimensional model based on the circuit board structure parameters, edge pin sizes and distribution information; selecting a reference surface on the circuit board three-dimensional model, picking up a reference area on the selected reference surface, and using the picked-up reference area for circuit board defect detection; the application process supports user-defined threshold values and flexibly adapts to different detection requirements, unqualified products can be accurately injected into defect areas, the detection efficiency and reliability are improved, and production line quality control is assisted.

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 video encoding / decoding method and apparatus according to the present invention can: determine a reference area for intra-frame prediction of a current block; derive an intra-frame prediction mode of the current block; and decode the current block based on the reference area and the intra-frame prediction mode.

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.