356 results about "Specularity" patented technology

The invention discloses an online monitoring method and system for the light transmittance of an optical lens, and relates to the technical field of precise optical detection. The objective of the invention is to solve the problem of large light transmittance calculation error caused by halo scattering noise interference, low optical path calibration precision of a complex curved lens, a measurement blind area of a large-aperture lens and environmental disturbance of a high-reflection / high-light-transmittance lens in the prior art. According to the scheme, a three-dimensional curved surface model is constructed based on Gray code structured light projection and ICP registration, a dynamic partition scanning instruction set is generated through an improved genetic algorithm, and multi-wavelength polarized light is driven to scan and collect multi-dimensional data; specular reflection and scattering noise are suppressed by combining an improved Stokes vector algorithm and an attention mechanism U-Net network, and the data precision of the complex curved surface is improved by adopting Bayesian optimization and Zernike polynomial weighted fusion; constructing a double-loop coupling optimization architecture to realize closed-loop adaptive optimization; according to the invention, the anti-interference capability, the complex lens adaptability and the full-aperture detection precision are obviously improved.

The invention relates to the technical field of tooth modeling, and discloses a three-dimensional tooth modeling system based on computer vision, computer equipment and a readable storage medium. According to the method, mirror reflection, diffuse reflection and subsurface scattering components in an original image are separated, mirror reflection intensity is normalized in combination with a dynamic truncation algorithm, pixel saturation is eliminated, groove and nest textures are reserved, a complete point cloud is obtained based on a two-dimensional texture image and cubic spline repair, and a multi-exposure point cloud sequence is obtained through bimodal calibration. The method comprises the following steps: solving the problem of data dislocation, carrying out weight assignment and data fusion on three-dimensional points in a plurality of exposure point cloud sequences to obtain three-dimensional fusion feature data, combining layered optical modeling and photon tracking compensation deviation, fusing clinical constraints, finally dynamically adjusting parameters, feeding back and optimizing, and outputting a micron-sized precision model. The modeling defect caused by difficulty in effectively coordinating feature contribution degrees under different exposure conditions is overcome, and high-precision modeling is realized.

A lure for fishing according to one embodiment of the present invention comprises a main body portion having a cavity therein; a weight provided in the cavity of the main body portion and movable in the cavity; and a hollow cover member provided in the cavity of the main body portion, covering the weight from an outer side, and capable of guiding the weight to an inner side, in which the cavity is partially or entirely visually recognizable from an outside, and one or a plurality of reflecting surfaces or reflectors capable of performing specular reflection of light from the outside is provided on an outer surface of the hollow cover member.

The invention relates to the technical field of machine vision image analysis, in particular to a lubricating oil abrasive particle quality analysis method and system based on machine vision, and the method comprises the steps: obtaining a thickness distribution diagram of an oil residual layer on the surface of an abrasive particle through a gray ratio relation between a first transmission image and a second transmission image; performing optical compensation on the first transmission image to obtain a final compensation image, and performing phase consistency edge detection to obtain an abrasive particle edge enhanced image; calculating the polarization reflectivity ratio of each abrasive particle area; extracting the mirror reflection intensity difference of each abrasive particle in the abrasive particle edge enhanced image; and when the abrasive particles are analyzed as metal attributes according to the polarization reflectivity ratio and the specular reflection intensity difference, identifying the morphological characteristic parameters of the abrasive particles, matching the morphological characteristic parameters with a pre-stored abrasive particle wear characteristic library, and outputting a quality evaluation report of the lubricating oil according to a matching result. The influence of oil film interference is effectively inhibited, the metal particles are accurately distinguished, and high-precision analysis on the lubricating oil abrasive particles is realized.

The invention discloses a metal processing detection system and method based on computer vision, and relates to the technical field of defect detection.Rotatable polarization filters are installed in front of a lens of a vision sensor, the polarization filters are arranged at four angles respectively, and four sets of polarization images are collected; calculating the polarization degree of each pixel point on the surface during metal processing by using the gray values of the four groups of polarization images, setting a polarization region interval, and dividing a metal surface reflection region into a specular reflection region and a diffuse reflection region; acquiring images of different wavebands by using a multispectral vision sensor, and constructing a multispectral image set; for the same wave band, the images of different exposure times are synthesized to obtain an HDR high dynamic range image; setting a weight for the HDR image of each wave band, and combining the weighting of the HDR image and the suppression of the polarization degree to carry out multispectral image fusion so as to obtain a final image; and a gray threshold value and an area threshold value are respectively calculated through the average value and the standard deviation, and the metal processing defects are judged by using the two threshold values.

The invention discloses a hot-dip galvanized steel pipe ground cage verticality measuring system based on machine vision, and relates to the technical field of physical measurement, and the system comprises a projection unit which is used for projecting polarization gray scale stripes with polarization codes to a to-be-measured hot-dip galvanized steel pipe ground cage; the imaging unit comprises at least two cameras which form a triangulation base line with the projection unit so as to synchronously acquire multi-view images from different views; and the processing unit is configured to perform polarization difference fusion on the multi-view images to suppress mirror reflection, generate corresponding polarization difference fusion images, reconstruct pipe body three-dimensional point clouds of all the hot-dip galvanized steel pipes in the corresponding hot-dip galvanized steel pipe ground cages, generate pipe body axial vectors by adopting robust cylinder axis fitting, and obtain the pipe body three-dimensional point clouds of all the hot-dip galvanized steel pipes in the corresponding hot-dip galvanized steel pipe ground cages. And calculating the perpendicularity deviation angle of the pipe body according to the axial vector of the pipe body and the gravity direction. Therefore, on the premise that the measurement precision is guaranteed, the spatial postures of the multiple steel pipes are synchronously collected and recognized at a time, multi-point repeated scanning is not needed, and the detection efficiency is remarkably improved.

The invention relates to the technical field of workpiece detection, and discloses an intelligent visual detection method and system for the surface of a workpiece, and the method comprises the steps: projecting a polarization structure light pattern to the surface of the workpiece, and synchronously collecting an image of the polarization structure light pattern after deformation on the surface of the workpiece; separating a structured light component and a polarized light component from the image, reconstructing a surface three-dimensional shape according to the structured light component, and generating surface polarization degree distribution according to the polarized light component; performing multi-scale gradient scanning on the surface three-dimensional morphology, extracting edge change features, performing texture consistency analysis on the surface polarization degree distribution, and identifying an abnormal texture mode; identifying a mirror reflection area based on the surface polarization degree distribution, performing height compensation on a corresponding area in the surface three-dimensional morphology, generating a corrected surface three-dimensional morphology, and combining edge change features and an abnormal texture mode; according to the invention, the accuracy and robustness of defect identification can be improved, and the reliability and efficiency of the system in industrial field application are enhanced.

The invention provides an apparent defect detection system and method based on CCD image recognition. A specular reflection interference area meeting a preset difference condition is recognized through a first surface reflection image and a second surface reflection image of a target patch element; extracting corresponding orthographic gray scale data from a third surface orthographic image obtained by adopting coaxial light source irradiation based on the specular reflection interference area; according to the brightness distribution gradient of the specular reflection interference area in the first surface reflection image and the second surface reflection image, constructing a texture restoration guide map, and using the texture restoration guide map to carry out texture restoration on the orthographic gray scale data to generate a texture restoration image of the specular reflection interference area; and generating a defect identification reference image for eliminating specular reflection interference based on the texture repair image, and outputting an appearance defect identification result of the target patch element by the defect identification reference image. According to the technical scheme provided by the invention, the defect detection of the patch element can be realized under the interference of mirror reflection.

The invention belongs to the technical field of image processing, and particularly relates to an aluminum bar quality detection method and system based on machine vision, and the method comprises the steps: obtaining a gray image of the surface of an aluminum bar; constructing a structure tensor for describing the distribution of the pixel points in the local gradient direction, and obtaining gradient coherence indexes of the pixel points according to feature values of the structure tensor; according to the gradient coherence index, the gray value of the pixel point and the gray value mean value and the gray value standard deviation in the neighborhood, obtaining coherence weighted saliency of the pixel point; according to the coherence weighted saliency and the coherence weighted saliency of all the pixel points in the pixel point neighborhood, acquiring a defect probability index of the pixel points; and performing aluminum bar surface quality discrimination according to the defect probability index. According to the method, through combination of gradient coherence and local brightness statistical characteristics, interference of specular reflection light spots on the surface of the aluminum bar and wiredrawing texture noise is effectively inhibited, and accuracy of detection of weak defects such as scratches is improved.

The invention discloses a machine vision-based enzyme freeze-dried powder quality detection method, and belongs to the technical field of machine vision, and the method specifically comprises the following steps: in a closed optical cavity, synchronously collecting a multispectral polarization sequence of a sample through annular multispectral polarization illumination and microscopic imaging; performing short-time airflow pulse disturbance and continuous imaging on the sample, and constructing a polarization time sequence texture map by means of inter-frame polarization retention difference; according to Stokes parameters, calculating a deskewness graph and a specular reflection component graph, and carrying out joint normalization on the deskewness graph and the specular reflection component graph and the polarization time sequence texture graph to form a multi-channel feature stack; constructing a double-branch encoder, and performing comparative learning on the feature stack to generate an impurity prototype dictionary; using the dictionary to match the feature stack pixel by pixel, and tracking and inhibiting powder agglomeration false detection through a topological constraint connected domain; and recovering a height map by using an oblique incidence fringe phase shift method, performing pixel-level fusion with the candidate image, retaining targets with height abrupt change and consistent polarization characteristics, and outputting an impurity mask.

The invention belongs to the technical field of three-dimensional shape measurement, and discloses a three-dimensional measurement method for a non-Lambert metal surface, which comprises the following steps of: projecting polarization coding structured light on the non-Lambert metal surface, synchronously acquiring reflection images and ambient light noise data, and removing light noise from each reflection image to obtain a non-Lambert metal surface; extracting and calculating the light intensity value, the light polarization value and the light deflection angle of each pixel point in different polarization states, constructing a grayscale image to distinguish a high polarization point from a low polarization point, marking mirror reflection and diffuse reflection areas, resolving a phase field based on the processed reflection image, and correcting the phase jump; a continuous phase field and polarization reflectivity characteristics are combined to input a double-branch network model, the model is fused and optimized, a control point coordinate matrix and a weight matrix are output, an NURBS curved surface is constructed for defect detection, a high-precision three-dimensional surface shape is reconstructed, and the problems of reflection interference, dynamic efficiency and industrial adaptation in non-Lambert metal surface three-dimensional measurement are systematically solved. And a solution is provided for high-precision industrial detection.

The invention provides a video manuscript abnormal data detection method and system based on artificial intelligence, and the method comprises the steps: obtaining a video manuscript which comprises a text instruction and a video frame; generating an enhanced semantic tag based on the text instruction and the video frame; the mirror reflection light component and the diffuse reflection light component in the video frame are separated by adjusting the lens polarization angle in real time, and an anti-interference image is generated; aligning the enhanced semantic tag and the anti-interference image in a shared semantic space, and calculating the feature similarity between the aligned enhanced semantic tag and the aligned anti-interference image; and determining a target anomaly score according to the feature similarity. According to the invention, the accuracy and robustness of video anomaly detection in a dynamic illumination scene are improved.

A method and system for eliminating 2D features from planar surfaces in 2D images. Three digital images are taken, from a single camera at a fixed position, of a subject such as a pallet of boxes. One image (IA) is taken with ambient lighting, one image (I1) has ambient lighting plus a first added light source, and one image (I2) has ambient lighting plus a second added light source. An output image Q is then computed by Q=(I1−IA) / (I2−IA). Subtracting the ambient image removes ambient diffuse and specular reflections. Division eliminates all variations in the output image caused by color. The only variations that remain are those due to the angle between each surface point's normal direction and the direction from the light to that point. The output image Q, devoid of all colors and 2D features, is well suited for computing a robot grasp of an object in the image.

The invention discloses a three-dimensional surface shape digital measurement-based cosmetic plastic auxiliary analysis method and system, and the method comprises the steps: obtaining a medical image data set, carrying out the noise processing through employing a Gaussian filtering algorithm, judging a noise point if the difference between a pixel gray value and a neighborhood mean value exceeds a preset threshold value, and carrying out the smoothing processing, and obtaining a first image data set; constructing an energy function according to the first image data set, and filling and repairing a defect region in the image through superposition calculation of a single-point energy item and an adjacent-point interaction energy item to obtain a second image data set; extracting point cloud data from the second image data set and constructing a gradient field, and if the point cloud density is lower than a preset threshold value, executing local encryption processing to generate a three-dimensional face model; grid vertex coordinates and normal vector information of the three-dimensional face model are obtained, and the environment light component, the diffuse reflection component and the mirror reflection component are fused through an illumination intensity calculation formula to generate a visual image, so that the precision and efficiency of medical image processing and three-dimensional visualization are improved.

The invention provides an AGV (Automatic Guided Vehicle) visual texture navigation path map real-time generation method, which comprises the following steps: collecting ground glossiness and a gray scale saturation region area, comparing the brightness difference between the gray scale saturation region and a normal region, and identifying the distribution position and the coverage range of a high-reflection region; according to the distribution position and the coverage range of the high-reflection area, extracting a texture missing part covered by the specular reflection patches, and determining boundary coordinates of the texture missing part; according to the optimized light incident angle distribution, the gray jump amplitude when the AGV drives into the polished tile area from the rough cement ground is collected, and the transition intensity of material change is evaluated; and filling a texture missing region in the path map by using the reconstructed complete texture features, and integrating the texture information of the path map to generate a complete AGV navigation path map.

Systems and methods of virtual displays to generate virtual images. Some display systems comprise a light source and a plurality of specular reflectors to produce virtual images that have a monocular depth that is closer to a viewer than an exit aperture optic or other optical component of the display system. In some embodiments, sensors or cameras detect a property of a viewer or of an environment to impact the virtual image or to provide sensory feedback to the viewer.

The invention relates to the technical field of image processing, and discloses an endoscope image imaging method and an endoscope, and the endoscope image imaging method comprises the steps: obtaining a real-time collection image of the endoscope and a light source parameter of the endoscope; positioning a target light spot in the real-time acquired image based on light source parameters of the endoscope; suppressing a specular reflection component of a target area where the target light spot is located to obtain an endoscope imaging image; the method comprises the following steps: firstly, positioning a light spot in a real-time acquired image based on a light source parameter to obtain a target light spot; the specular reflection component of the target area where the target light spot is located is further suppressed, so that the overexposure spots can be suppressed while global processing damage to normal highlight areas such as highlight bleeding spots and highlight mucous membranes can be avoided, and the original expression of the image can be restored.

Methods and systems for generating a sound. The method includes obtaining meshes representing at least one object in a frame of an environment, the environment including a source and a receiver; determining spatial continuity information and reflection normal information of the meshes; determining, based on the spatial continuity information and the reflection normal information, reflection paths between the source and the receiver involving the at least one object, each of the reflection paths having at least one reflection point associated with the at least one object; obtaining spatially sampled results by spatially sampling a space around the at least one reflection point of reflection paths using multiple distributions of rays, the spatially sampled results correlating with geometric information of the meshes; generating reflection amplitude responses for each of multiple audible frequencies in the environment based on the spatially sampled results; and producing a sound based on the reflection amplitude responses.

The invention provides an unmanned aerial vehicle inspection tour anti-dazzle visual angle optimization method and system based on background perception. Acquiring a key detection area of the inspection target; candidate shooting poses of the unmanned aerial vehicle are generated for the key detection area; constructing a glare risk function based on the material type parameters, the solar incident angle and the deviation angle between the camera observation direction and the mirror reflection direction; constructing a contrast scoring function based on the brightness corresponding to the background type and the reflection brightness corresponding to the key detection area; a target shooting position is selected according to the glare risk function and the contrast scoring function, and an unmanned aerial vehicle inspection track is generated; the shooting visual angle of the unmanned aerial vehicle is automatically selected and adjusted in a complex natural light environment, the image failure risk caused by high reflection, silhouette and low contrast is reduced, and the detectability of defects of key parts is improved.

An X-ray device includes an X-ray source, a scintillator, a single mirror, and a camera. The camera has a field-of-view around an optical axis of the camera. The single mirror fully contains the field-of-view as the field-of-view is folded by the single mirror toward the scintillator. The single mirror is positioned at an angle with respect to a plane that is normal to the optical axis at a point where the optical axis intersects the single mirror. The angle is decreased from forty-five degrees to reduce a volume of the folded field-of-view of the camera. The angle is greater than or equal to a threshold angle that prevents triple specular reflections of light between the single mirror and the scintillator.

The invention relates to the technical field of impregnated paper defect detection, in particular to an impregnated paper surface defect detection system and method. The method comprises the following steps: respectively acquiring reflection images of visible light and near-infrared bands by adopting a vertical illumination light source, calculating a reflection intensity difference index to separate a specular reflection dominant region from an impregnated paper body reflection region, and inhibiting the specular reflection dominant region through difference analysis and a binary mask. The problem that surface image acquisition of the impregnated paper is seriously interfered by mirror reflection is avoided; and combining the impregnated paper body reflection region and the suppressed specular reflection dominant region to obtain an impregnated paper integrated image, comparing the impregnated paper integrated image with an impregnated paper standard image, marking all suspicious regions, and identifying defect types according to image feature data of all suspicious regions. And the qualified state of the impregnated paper is judged based on the defect degree index corresponding to the defect type, so that automatic and standardized impregnated paper surface quality evaluation is realized, and the impregnated paper detection efficiency and detection reliability are improved.

The invention discloses a vehicle distance measurement and calibration method based on laser radar and binocular vision fusion, relates to the technical field of measurement and calibration, and is used for solving the problem that the precision of a vehicle distance calibration result is reduced when a laser radar used for calibrating a highway vehicle distance snapshot system is under the conditions of rain, snow, wet and slippery or waterlogging road surfaces. Joint modeling is carried out on spatial distribution and echo energy characteristics of laser radar low-height point cloud, a point cloud echo coefficient and a low-height number proportion are introduced, a specular reflection state code is constructed, a self-calibration mechanism is adaptively triggered accordingly, and a specular reflection state is obtained. The discrete characteristic of a laser radar vehicle distance time sequence and the degradation trend of binocular vision parallax connectivity are subjected to quantitative analysis, the dominant source of ranging abnormity is judged through symbolic analysis, and an offset calibration or fusion correction strategy is selected according to the dominant source. Reliability and engineering adaptability of vehicle distance measurement under the wet and slippery road surface condition can be improved under the condition of not depending on an additional sensor.

The invention discloses a hydraulic oil cylinder quality online detection and defect classification method based on industrial vision. The method comprises the following steps that multiple sets of industrial cameras arranged around a conveying line and a combined illumination light source collect original images of the surface of an oil cylinder; 360-degree dead-corner-free imaging of the cylindrical surface of the oil cylinder is achieved through cooperative configuration of multiple sets of industrial cameras and a combined illumination light source, specular reflection and cutting fluid interference are effectively restrained, a deep learning segmentation network combined with a coordinate attention mechanism is adopted to accurately extract an area, the positioning problem under the complex background is solved, and the positioning precision is improved. Through a cascade detection network and a multi-scale feature extraction strategy, the detection sensitivity of difficult samples such as slight scratches and pits is remarkably improved, the attention fusion network is used for dynamically adjusting form and texture feature weights, fine classification of five types of defects is achieved, finally, the detection efficiency is guaranteed, meanwhile, the missing detection rate and the false alarm rate are greatly reduced, and the detection accuracy is improved. And the zero-defect delivery requirement of the high-end hydraulic oil cylinder is met.

The invention discloses an illumination scene rendering method and device, a computer readable storage medium and a computer program product, and the method comprises the steps: setting a plurality of illumination probes in a three-dimensional Gaussian splashing scene, and determining a first spherical harmonic coefficient of each illumination probe based on the light field data of the three-dimensional Gaussian splashing scene, the illumination probe is used for collecting omnidirectional illumination information of a spatial point of a three-dimensional Gaussian splashing scene; for each unshielded pixel of the to-be-rendered object, determining indirect diffuse reflection light for the to-be-rendered object based on a target spherical harmonic coefficient of a target illumination probe determined by the unshielded pixel, the to-be-rendered object being an object placed in the three-dimensional Gaussian splash scene; for each unshielded pixel, based on the normal direction of the unshielded pixel and the constructed hierarchical Z buffer, indirect specular reflection light for the to-be-rendered object is determined through screen space reflection and a reflection ball; and fusing the indirect diffuse reflection light, the indirect specular reflection light and the direct light to generate an illumination rendering result for the to-be-rendered object.

The invention relates to the technical field of radar remote sensing monitoring, in particular to an airport runway seaworthiness intelligent evaluation method and system based on satellite-ground collaborative awareness, and the method comprises the steps: calculating the signal prominence intensity through the local saliency based on the SAR image pixel amplitude, and primarily screening highlight pixel points; a side lamp possibility index is constructed by combining double constraints of a straight line distribution rule and time sequence position reproducibility, and high-credibility side lamp pixel points are accurately identified from a low-signal-to-noise-ratio background; reversely positioning a runway pixel point area based on the matched parallel edge lamp fitting straight line; constructing a local deformation reference surface by taking an unwrapping phase of adjacent edge lamp pixel points as a benchmark, calculating the reliability of the runway and reconstructing a phase of an untrusted point, and generating a denoised image for airworthiness evaluation; according to the airport runway airworthiness evaluation method, the runway sidelight is used as a phase reference for time-space stability, the problem of phase incoherence caused by specular reflection in a flat runway area is effectively solved, and the accuracy and robustness of airport runway airworthiness evaluation are remarkably improved.

The invention discloses a ship dynamic high-precision positioning and abnormal behavior recognition method, and particularly relates to the technical field of navigation positioning. The method comprises the following steps: performing time sequence synchronization and noise elimination on satellite signal propagation time ranging data, carrier phase data and ship attitude data received by a ship; outputting a reflection path coupling relation parameter by analyzing a time-varying coupling relation between the rolling and pitching states of the ship body and a sea surface specular reflection path; by establishing a multi-path deviation correction model, error correction values of satellite signal propagation time ranging data and carrier phase data are calculated; ship track motion state data are output by extracting ship space attitude change features and track geometric morphology features; and updating the ship trajectory motion state data by using the corrected satellite signal propagation time ranging data and carrier phase data to obtain ship positioning trajectory data, and outputting a ship abnormal behavior identification result. And the detection accuracy and reliability of the abnormal behaviors of the ship are improved.

The invention discloses a sealing ring processing quality monitoring system, and relates to the technical field of sealing ring processing monitoring. The system comprises a polarization-dark field composite imaging module which is used for obtaining a target image which eliminates specular reflection and highlights scattering characteristics of tiny bubbles through the synergistic effect of polarization filtering and annular dark field illumination; the microbubble feature enhancement module is used for carrying out feature extraction and enhancement on the target image by adopting a deep learning network comprising a multi-scale cavity convolution unit and a self-adaptive attention mechanism unit; and the self-adaptive threshold segmentation module is used for processing the enhanced image in combination with segmentation strategies of the dual-threshold screening unit and the attention map guide segmentation unit so as to accurately segment a micro bubble region. Through cooperation of polarization-dark field composite imaging, a microbubble feature enhancement network and adaptive threshold segmentation, high-precision rapid detection of the microbubbles on the surface of the transparent silica gel sealing ring is realized.

The invention discloses an automatic driving laser radar simulation method for high-fidelity material modeling, and the method comprises the steps: carrying out the high-fidelity modeling of a complete physical process of a single laser channel, and designing a complete technical chain from laser beam modeling, material reflectivity modeling, light path modeling to post-processing. In laser beam modeling, energy space distribution is accurately depicted by introducing an angle attenuation conical beam model; in material reflectivity modeling, a bidirectional reflection distribution function system covering Lambert body, specular reflection, transmission, retroreflection and general materials is established; in light path modeling, traditional single reflection hypothesis is broken through, time-resolved Monte Carlo path tracking and kernel density estimation are adopted, simulation of multi-path reflection and transmission effects is achieved, traditional model bottlenecks are broken through, complex optical phenomena are simulated, the generation mode has expandability and controllability, rare key scenes are efficiently synthesized, and the method is suitable for large-scale popularization and application. And the method has wide field extension potential and high technical universality.