59 results about "Edge strength" patented technology

The invention discloses a weldment welding seam automatic detection method and device based on machine vision, and relates to the technical field of machine vision intelligent detection. The weldment welding seam automatic detection method and device based on machine vision comprises the steps that S1, surface images and forming feature data of a weldment are collected and preprocessed to construct a standardized image feature data set; s2, the boundary clearness of the weld joint is evaluated by combining the edge strength and the contour coherence, and the main contour extraction range is dynamically adjusted; s3, analyzing abnormal focusing characteristics of the candidate area, and adjusting a defect labeling range and a detection priority; and S4, integrating the boundary definition and the abnormal focusing features, analyzing the structure abnormality, and dynamically controlling and verifying a resource allocation strategy. The problems that in the weldment detection process, obvious light reflection and texture blurring phenomena exist in a heat affected area at a weld joint, a traditional image enhancement and edge extraction algorithm is difficult to stably recognize microdefects, and the credibility of a detection result is reduced are solved.

The invention provides a low-light large dynamic image enhancement method based on dynamic weight and pyramid fusion. The low-light large dynamic image enhancement method is suitable for complex illumination imaging in security monitoring. According to the method, the global weight and the detail weight of an image are obtained according to the global average brightness, the local brightness and the gradient of an image sequence, and the total weight is obtained through weighting. And the halo phenomenon easily occurring in the fusion process is reduced through guide filtering. And combining Gaussian pyramid and ratio pyramid decomposition and weighting to obtain a final fusion image. According to the method, the problems of detail loss and limited dynamic range in the low-light scene are effectively solved. Experiments show that the method is superior to the prior art in information entropy, average gradient, edge strength, spatial frequency and other key indexes. The technology has an all-time adaptive capability, is suitable for the fields of intelligent transportation, urban security and protection, low-illumination monitoring and the like, and has a wide market prospect.

The invention relates to the technical field of image processing, and provides an image artifact detection method and system based on a deep learning technology, and the method comprises the following steps: carrying out the preprocessing of an obtained to-be-processed image, and carrying out the feature extraction of the preprocessed image; position coding is carried out on the extracted feature map A, and the extracted feature map A is fused with the feature map A; performing multi-layer encoding and decoding on the fused feature map through an encoder and a decoder to obtain a feature map B containing an artifact target area; and generating an anchor frame of an artifact region for a target region in the feature map B, and dynamically adjusting the size and position of the anchor frame according to local information of the down-sampling rate, texture complexity and edge strength of the feature map B to obtain an artifact region detection result after the anchor frame is labeled. Automatic artifact detection and quantitative evaluation of the influence degree can be achieved, the accuracy and efficiency of medical image interpretation are improved, and more reliable data support is provided for clinical decision making.

The invention relates to a sub-pixel edge extraction method based on an interpolation method, and belongs to the technical field of image processing and computer vision, and the method comprises the steps: obtaining a gray level image, and calculating the gradient of the gray level image in at least one direction based on a preset operator, so as to obtain the gradient amplitude of the gray level image; compressing the gradient magnitude to a preset threshold value, and calculating the gradient direction of each pixel in the gray level image; based on a preset interpolation model, in a preset period, repeatedly fitting the edge intensity in the gradient direction until a complete sub-pixel contour point set is obtained; and deploying the trained interpolation model as a sub-pixel edge extraction model so as to improve the image processing precision in edge detection. By means of the method, the problem that a traditional pixel-level edge detection method is insufficient in precision can be solved, and the detection precision and the measurement repeatability can be effectively improved in the field of high-precision measurement.

The invention discloses a discharge channel extraction method and system based on edge detection and texture feature fusion, and belongs to the technical field of power equipment fault diagnosis and digital image processing, and the method comprises the steps: obtaining an ultraviolet weak light image of power equipment, and carrying out the preprocessing; multi-scale edge detection is executed based on the preprocessed image, edge information is fused through a multi-scale voting mechanism, and a candidate edge graph is generated by combining direction consistency connection fracture edges; extracting texture features of the pre-processed image, wherein the texture features comprise a rotation invariant local binary pattern uniformity feature and a multi-direction gray level co-occurrence matrix feature; according to a dynamic distribution weight coefficient of a discharge type, carrying out weighted fusion on the edge intensity of the candidate edge graph and the texture features, and generating a discharge channel confidence score graph; and carrying out binarization segmentation and contour optimization processing on the confidence score graph of the discharge channel, and extracting morphology quantization parameters of the discharge channel.

The invention relates to the technical field of computer vision, in particular to a three-dimensional scene reconstruction rendering method and system. The method comprises the following steps: generating a corresponding 3D Gaussian ellipsoid for each sparse point cloud of a scene to be reconstructed; obtaining a re-projection area of each 3D Gaussian ellipsoid on the two-dimensional image of different visual angles; taking each re-projection area as a center, and taking all re-projection areas within a set pixel distance range as adjacent re-projection areas of the re-projection area; the method is based on the sum of Gaussian kernel function values from the center of a re-projection area of each 3D Gaussian ellipsoid on a two-dimensional image of different visual angles to the center of each adjacent re-projection area of the area, the edge strength, the local variance, the normalized gradient magnitude, and the absolute value of the dot product of a gradient vector and a normal vector. Calculating a split control function value of each re-projection area; and comparing the splitting control function value of each re-projection area with a set threshold value, and controlling the 3D Gaussian ellipsoid to split. According to the invention, the reconstruction rendering precision of the three-dimensional scene is improved.

The invention provides a three-dimensional map construction and camera trajectory estimation method based on edge information fusion, and belongs to the field of computer vision and robot perception. Collecting an image sequence in a scene, executing edge detection and then generating a two-dimensional edge intensity graph; initializing or updating a three-dimensional Gaussian point cloud: generating an initial point cloud by a first frame through color, depth and edge intensity values of the first frame through back projection; point clouds are newly added to the required areas of subsequent frames according to rendering differences; initializing a current frame of camera pose, generating a prediction map based on the pose and a previous frame of point cloud rendering, and constructing a loss function to optimize the camera pose; rendering is carried out again based on the optimized pose and the point cloud of the previous frame, a loss function is constructed to optimize the point cloud attribute, and the point cloud of the current frame is generated; and processing the sequence frame by frame, accumulating and optimizing the point cloud to form a global three-dimensional map, and accumulating the camera pose to output the camera motion trail. According to the method, the SLAM precision, stability and reconstruction quality in various complex scenes, especially in low-texture and strong-structure environments are improved.

The application provides a three-dimensional map construction and camera trajectory estimation method based on edge information fusion, and belongs to the field of computer vision and robot perception. An image sequence in a scene is collected, and a two-dimensional edge intensity map is generated after edge detection; a three-dimensional Gaussian point cloud is initialized or updated: an initial point cloud is generated by back projection of the color, depth and edge intensity value of the first frame; a point cloud is added in the required area according to the rendering difference in subsequent frames; the camera pose of the current frame is initialized, a prediction map is generated based on the pose and the point cloud of the previous frame, a loss function is constructed to optimize the camera pose; the point cloud attributes are optimized again based on the optimized pose and the point cloud of the previous frame, and the point cloud of the current frame is generated; the sequence is processed frame by frame, the optimized point cloud is accumulated to form a global three-dimensional map, and the camera motion trajectory is output by accumulating the camera pose. The application improves the SLAM precision, stability and reconstruction quality in various complex scenes, especially in low-texture and strong-structure environments.

The invention belongs to the technical field of image data processing, and particularly relates to an industrial robot efficient communication method and system based on edge computing, and the method comprises the steps: determining all narrow edge pixel points of each frame of image; determining an edge intensity factor of each frame of image; determining a structured edge factor of each frame of image; determining an optimization coefficient of an effective frame screening threshold value of each frame of image to obtain an optimized effective frame screening threshold value of each frame of image; and each frame of image is judged, and effective frames of the image are screened. According to the method, the gradient magnitude and gradient direction features of the narrow edge pixel points of each frame of image are analyzed, the effective frame screening threshold value of each frame of image is optimized, the limitation of the fixed effective frame screening threshold value is overcome, the effective frame images are screened, and the timeliness and robustness of industrial robot communication are improved.

The application discloses a kind of indexable turning inserts, including center line, upper surface, lower surface and multiple side surfaces connecting upper surface and lower surface, two adjacent side surfaces are connected by circular arc surface, the height of each relative reference surface of circular arc cutting edge and main cutting edge is consistent, the height of each relative reference surface of transition cutting edge gradually reduces along the direction away from circular arc surface, the height of each of auxiliary cutting edge is consistent with the lowest point of transition cutting edge;The height of first protruding portion top surface, second protruding portion top surface and mounting positioning surface relative reference surface increases in turn;Upper surface is provided with third protruding portion symmetrically distributed about angle bisector, third protruding portion is located on third rake surface and is connected with second protruding portion.The present indexable turning insert has the advantages of facilitating to guide chip lateral curling, considering the edge strength of nose region, controllable chip shape and chip flow direction, reducing friction, avoiding chip blocking or chip holding and the like.

The application provides a dynamic anti-aliasing rendering method and system based on edge detection and motion perception, and relates to the technical field of computer graphics rendering. The method comprises the following steps: performing 8-direction edge intensity detection on a pixel point in an original scene image by using a 3*3 sampling matrix and calculating an edge intensity value; calculating a motion factor and dynamically adjusting an edge detection threshold; if the edge intensity value of the pixel point is greater than the edge detection threshold, performing adaptive blur processing based on a 9-point weighted average algorithm to generate a blurred pixel value, calculating a mixing factor, mixing the original pixel value of the pixel point and the blurred pixel value to generate a final pixel value; if the edge intensity value of the pixel point is less than or equal to the edge detection threshold, keeping the original pixel value of the pixel point unchanged, and the final pixel value is the original pixel value, and finally outputting a final scene image by collecting the final pixel value, so that the anti-aliasing processing strategy can be adaptively adjusted according to the static and dynamic characteristics of the scene, the rendering performance is optimized while the image quality is ensured.

The invention relates to a hexagon edge effect optimization method and system based on a mobile platform. The method comprises the following steps: step 1, defining a hexagon constant; 2, calculating the inscribed circle radius of the hexagon; 3, obtaining the thickness from each pixel to six sides of the hexagon according to the hexagon constant and the inscribed circle radius of the hexagon; 4, taking the maximum thickness as an edge strength factor; and step 5, controlling the edge color mixing effect according to the edge intensity factor, calculating the edge coordinate and thickness in real time, providing a finer and more flexible edge effect, and being suitable for mobile platform games and graphic rendering.

The invention discloses an image processing method and device, equipment, a storage medium and a computer program product, and belongs to the technical field of image processing. The method comprises the following steps: mapping a target pixel point in a target image to an original image to obtain a coordinate of a target mapping point; determining a plurality of reference pixel points from the original image based on the coordinates of the target mapping point; determining the edge intensity of the target pixel point based on the gray values of the plurality of reference pixel points; based on the edge intensity of the target pixel point and the distances between the multiple reference pixel points and the target mapping point, weights corresponding to the multiple reference pixel points are determined; and determining the pixel value of the target pixel point based on the pixel values of the plurality of reference pixel points and the weights corresponding to the plurality of reference pixel points. As the edge intensity can well distinguish the image edge and noise, the weight of each reference pixel point is adjusted by adding the edge intensity of the target pixel point, the image noise can be reduced, the image edge can be enhanced, and the image contrast can be improved.

The invention provides a grounding grid detection method and device based on image fusion, equipment and a storage medium. The method comprises the following steps: measuring a first detection image, a second detection image and a third detection image of a to-be-detected area; performing Laplacian pyramid fusion on the first detection image, the second detection image and the third detection image to obtain a grounding grid fusion image; performing edge detection on the grounding grid fusion image to obtain an edge image corresponding to the grounding grid fusion image; and detecting the edge strength of the corrosion area in the edge image to represent the corrosion degree of the corrosion area. According to the invention, three imaging technologies of electrical impedance, ultrasonic wave and infrared thermal are adopted, and through image registration and Laplacian pyramid fusion, non-destructive and real-time on-line detection of the state of the grounding grid is realized, multi-dimensional information such as resistivity, structure and temperature can be comprehensively reflected, the accuracy of corrosion positioning and evaluation is effectively improved, and the reliability of the system is improved. And visual and reliable technical support is provided for safe operation and maintenance of a power system.

The invention belongs to the technical field of computer videos, and particularly relates to a monitoring video stream distortion correction and two-dimensional-to-three-dimensional fusion method and a monitoring video stream distortion correction and two-dimensional-to-three-dimensional fusion system. The non-uniform mapping relation is established by calculating the distortion offset of the pixel coordinates, and the interpolation weight is dynamically calculated based on the pixel distance and the local edge intensity, so that the non-uniform distortion of the lens can be accurately corrected, the edge detail features of the image are effectively reserved, image blurring or detail loss in the correction process is avoided, and the correction efficiency is improved. And the definition and the accuracy of the corrected image are greatly improved.

The invention relates to a water body rendering method and device, equipment, a storage medium and a program product, and the method comprises the steps: superposing periodically continuous waveform data and noise data to all vertexes of a horizontal grid, and obtaining a wave pattern; coloring the wave white mold to obtain a wave model; respectively carrying out derivation processing on the waveform data and the noise data at each vertex in the wave pattern to obtain a first space gradient corresponding to the waveform data and a second space gradient corresponding to the noise data; performing composite processing on the first space gradient and the second space gradient to obtain a composite gradient of each vertex; obtaining a vertex normal vector of each vertex based on the composite gradient of each vertex; based on the vertex normal vector and the line-of-sight direction vector of each vertex, generating edge intensity data of the wave contour; and superposing the edge strength data to the wave model to obtain a water body rendering result. According to the scheme, the vertex normal vector is dynamically determined based on the composite gradient, so that the rendered water body has a dynamic surge effect.

The application provides an image post-processing optimization management method for intelligent taking of a cabinet of electric power materials, and belongs to the technical field of electric power material management, and comprises the following steps: S1, taking and placing registration; S2, overlay image acquisition; S3, feature extraction; S4, recognition matching; S5, inventory management whole process and the like; the application collects multi-angle images of the materials through a high-resolution camera, constructs a multi-directional convolution framework by using a spatial gradient energy kernel, and strengthens the extraction capability of geometric contour, surface texture and identification features. The core technology adopts three-dimensional differential operation to analyze the edge strength, curvature change and deformation characteristics step by step, combines a multi-scale texture analysis and an adaptive light compensation algorithm, eliminates environmental interference and generates a unique feature coupling factor, matches a pre-stored feature fingerprint library in real time through an elliptical envelope detection algorithm, accurately identifies the types and quantities of the materials, and forms a closed-loop management from permission verification, accurate identification to intelligent early warning.

This invention relates to the field of hydropower station technology, and discloses a method, apparatus, equipment, and medium for detecting crack defects in hydropower station dams. The invention calculates the maximum value of the ridge variation coefficient through single-layer discrete two-dimensional wavelet decomposition and ridge transform, and then determines the true crack edge direction based on this maximum value, improving the edge feature enhancement effect and making the edge boundaries clearer. Furthermore, a crack edge image is constructed based on multiple pixels corresponding to the absolute values ​​of multiple gradients along the crack edge direction, and the crack defect detection result of the hydropower station dam to be detected is determined based on the constructed crack edge image. Therefore, by implementing this invention, the edge strength and recognition rate of image recognition are improved by enhancing edge features, thereby improving the accuracy of crack defect detection results.

The invention provides a dynamic anti-aliasing rendering method and system based on edge detection and motion perception, and relates to the technical field of computer graphic rendering, and the method comprises the steps: employing a 3 * 3 sampling matrix to carry out 8-direction edge intensity detection on pixel points in an original scene image, and calculating an edge intensity value; calculating a motion factor and dynamically adjusting an edge detection threshold value; if the edge intensity value of the pixel point is greater than the edge detection threshold value, performing adaptive fuzzy processing based on a nine-point weighted average algorithm to generate a fuzzy pixel value, calculating a mixing factor, and mixing the original pixel value of the pixel point and the fuzzy pixel value to generate a final pixel value; if the edge intensity value of the pixel point is smaller than or equal to the edge detection threshold value, the original pixel value of the pixel point is kept unchanged, the final pixel value is the original pixel value, the final pixel value is summarized, and a final scene image is output, so that the anti-aliasing processing strategy can be adaptively adjusted according to the static and dynamic characteristics of the scene, and the image quality is improved. And the rendering performance is optimized while the image quality is ensured.

The application discloses a kind of ice thickness measurement method and device based on visual perception of ice storage coil, and the method comprises: setting annular or fan ring-shaped calibration disc on ice storage coil.The calibration disc is provided with multiple different color stripe regions arranged concentrically and along radial direction.Judge whether each stripe region is completely covered by ice layer according to the brightness change of calibration disc covered by ice layer in image, and each stripe region is divided into completely covered interval, partially covered interval and uncovered interval.For partially covered interval, the ice layer covering ratio of partially covered interval is obtained, and thus the ice layer thickness is obtained.The application provides the accuracy of ice thickness detection by stage ice thickness analysis, specifically, the ice layer completely covered by ice layer is determined by using the segmentation and brightness of different color stripe regions, and then for the partially covered stripe region, the comprehensive edge strength of integrated gradient edge strength and phase consistency edge strength is used for coverage ratio calculation.

The present application discloses a method and apparatus for sample adaptive compensation in video coding. The method comprises: obtaining coding depth information and quantization information of a video coding unit, and calculating a boundary information value based on the coding depth information and the quantization information; skipping the sample adaptive compensation calculation if the boundary information value is less than a preset threshold; calculating edge strength values ​​for different preset directions using an edge direction estimation algorithm if the boundary information value is not less than the preset threshold, and screening boundary compensation modes based on the edge strength values; and traversing preset categories in the screened boundary compensation modes to perform sample adaptive compensation. This solution optimizes the sample adaptive compensation mechanism and improves overall coding efficiency and speed.

The invention relates to a method for efficiently producing ultra-thin elements (2, 4) of glass-based material, the material thickness (d) of which is between 5 m and 100 m, into which filiform damages (14) are introduced by irradiation with an ultra-short laser pulser, the distance (A) between adjacent filiform damages (14) being between 0.4 m and 4.0 m. This advantageously achieves high edge strength. The invention also relates to ultrathin elements (2, 4) of glass-based material and to the use thereof.

The invention relates to an image processing method, an image processing system, an image processing device and a storage medium, light with different wavelengths is used as a light source to acquire a real-time target image, the image is segmented into a plurality of sub-image blocks, and histogram equalization is carried out to enhance local contrast. And the probability density of the gray level of the histogram is calculated and then cutting is carried out, and the contrast of each gray level is limited, so that image distortion caused by excessive enhancement is avoided. The method comprises the following steps of: merging sub-image blocks by adopting bilinear interpolation, enhancing the edge strength and direction of a merged image, carrying out local non-maximum suppression, only retaining the strongest pixel in the gradient direction, removing redundant edges, classifying the edges by adopting a dual-threshold method, only retaining weak edge pixels to be connected with the strong edge pixels, and obtaining an edge region of the image; and the image is restored and then displayed through false color transformation, so that the target features on the image can be checked conveniently, the accuracy and efficiency of target feature recognition in the image are improved, and powerful support is provided for subsequent analysis of the target features.

The invention relates to a high-resolution remote sensing satellite image restoration method combining constrained least square filtering and guiding filtering, and belongs to the field of satellite remote sensing data processing. Carrying out deblurring processing on the to-be-restored input degraded image by adopting constrained least square filtering; and carrying out edge enhancement processing on the obtained deblurred image, outputting an image after edge enhancement, and carrying out denoising processing with edge characteristics by adopting guide filtering to obtain a restored image. The method has the advantages that balance can be kept in edge keeping and noise weakening, edge details are more highlighted, the edge strength is improved, the ringing phenomenon is avoided on the premise that the restoration effect meets a certain signal-to-noise ratio, and the method is high in practicability and can be expanded to multi-spectrum remote sensing images for image restoration.

The application provides a sub-pixel edge positioning method based on conversion intensity and stable edge domain, comprising: S101, performing edge detection on an original image to obtain an edge detection result; S102, traversing each edge pixel based on the edge detection result to determine whether each edge pixel is in a current stable edge domain; S103, if the edge pixel is not in the current stable edge domain, obtaining a stable discrete direction sequence of the edge pixel, expanding the discrete direction sequence along a tangent direction to obtain an expansion result; S104, updating the current stable edge domain based on the expansion result to obtain an updated stable edge domain, repeating steps S102-S104 to obtain a standard stable edge domain; S105, solving effective statistical parameters in the standard stable edge domain; and S106, performing calculation based on a conversion relationship between the statistical parameters and an integral of an edge intensity curve and a step function under a continuous space to obtain a sub-pixel coordinate. The method improves positioning precision on the basis of improving operation efficiency.

The invention relates to a method for producing ultrathin elements and elements made of glass-based material (2, 4) and their use, in particular made of glass and / or glass-ceramic, with a material thickness (d) of 5 to 100 µm, using at least one ultrashort pulse laser (16) with a laser wavelength at which the glass-based element is at least substantially transparent, wherein the beam profile of the laser beam (20) is shaped such that it has a laser preferred direction LVR. This introduces defects (14) into the ultrathin glass-based element (2, 4) along a parting line (12, 121, 122), wherein adjacent defects (14) have a spacing (A) of 15 µm to 50 µm. This results in particularly good edge strength.

An electronic apparatus performs a method of decoding video signal, including: receiving, from the video signal, a picture frame that includes a first component, and a second component; selecting an edge direction across a collocated sample of the first component or a current sample of the second component relative to the respective sample of the second component; calculating a first edge strength determining a difference between values of two samples from the group consisting of the collocated or current sample, a first neighbouring sample, and a second neighbouring sample; quantizing the first edge strength into M segments according to M−1 threshold values; determining the classifier for the respective sample of the second component based on the M segments; determining a sample offset for the respective sample of the second component according to the classifier; and modifying the respective sample of the second component based on the determined sample offset.

The invention discloses a three-dimensional point cloud feature detection method and device, equipment, a medium and a product, and relates to the technical field of point cloud processing, and the method comprises the steps: obtaining ordered point cloud data which are three-dimensional point cloud data which are orderly arranged in an X direction and a Y direction; determining a first distance between the target point and a previous point of the target point in the X direction in the ordered point cloud data; according to the first distance, determining edge strength corresponding to the target point; according to the edge strength and a preset edge threshold range, determining edge points in the ordered point cloud data, the edge points being target points whose edge strength belongs to the preset edge threshold range; and determining three-dimensional geometric features according to the edge points. According to the method, the efficiency of determining the edge points in the three-dimensional point cloud can be improved, so that the detection speed of the three-dimensional geometric features is improved, and the applicability of a three-dimensional scanning detection technology in high-speed detection is ensured.

This invention belongs to the field of image data processing technology, specifically relating to an efficient communication method and system for industrial robots based on edge computing. The method includes: determining all narrow-edge pixels in each frame of an image; determining the edge intensity factor of each frame; determining the structured edge factor of each frame; determining the optimization coefficient of the effective frame filtering threshold for each frame, thus obtaining the optimized effective frame filtering threshold for each frame; and judging each frame to achieve effective frame filtering. This invention optimizes the effective frame filtering threshold for each frame by analyzing the gradient magnitude and gradient direction characteristics of the narrow-edge pixels in each frame, overcoming the limitations of a fixed effective frame filtering threshold, and filtering effective frames to improve the timeliness and robustness of industrial robot communication.

The present disclosure relates to an image processing method, apparatus, device, and storage medium. The image processing method includes: obtaining a first chrominance component value, where the first chrominance component value refers to a value obtained by upsampling the chrominance component of a pixel point in a video frame; performing a predetermined optimization process on the first chrominance component to obtain a second chrominance component value; performing edge intensity detection on the pixel point to obtain an edge intensity value of the luminance component and an edge intensity value of the chrominance component of the pixel point; and determining the value of the chrominance component of the pixel point as the second chrominance component value when the edge intensity value of the luminance component satisfies a first predetermined condition or the comparison result between the edge intensity value of the chrominance component and the edge intensity value of the luminance component satisfies a second predetermined condition.