9results about How to "Remove image distortion" patented technology

The invention belongs to the field of image spectrum detection, and particularly relates to a high-precision detection device and method for a liquid meniscus contour in a capillary tube. Comprising a telecentric lens, an industrial camera, a displacement platform, a light source, a capillary tube and a culture dish, the industrial camera, the capillary tube and the culture dish are installed on different displacement platforms respectively, the light source is provided with a rotary telescopic rod and can move in all directions, when the liquid meniscus contour in the capillary tube is shot, the light source, the meniscus of the capillary tube and the industrial camera are adjusted to be aligned to the same horizontal plane, and on the basis of the telecentric imaging principle, according to the light refraction principle, the liquid meniscus contour in the capillary tube is obtained. And deriving a distortion correction function of the meniscus contour in the capillary tube. According to the invention, the industrial camera and the telecentric lens are matched for use, the problem of shape distortion caused by object distance change is avoided, and the difficulty of image distortion correction is reduced. The meniscus contour distortion correction function derived based on the telecentric imaging principle can accurately calculate the actual value of the meniscus contour and restore the actual meniscus contour.

The invention provides a standing bell jar welding method and a welding robot. The standing bell jar welding method comprises the steps that image collection is conducted on a to-be-welded workpiece; according to the single-frame welding line image, extracting welding line center line coordinates and welding line widths corresponding to all center line points; splicing a plurality of frames of images by adopting a weighted fusion mode to obtain a full-circle weld joint panoramic expansion view; welding seam areas with different widths are classified and positioned according to threshold values, corresponding area masks are generated, the masks are fused with the whole-circle welding seam panoramic expansion graph to achieve color coding visual marking, and a welding seam width marking graph is output; segmenting the welding seam width marking graph according to a preset welding seam width threshold value to obtain segmented graphs; and the image coordinate system in the segmented graph is compared with the workpiece coordinate system of the workpiece to be welded, and the welding speed is controlled according to the welding seam width corresponding to the segmented graph. According to the method, the influence of image distortion is reduced, the welding quality is improved by combining the welding seam width, and the wide application prospect is achieved.

The invention belongs to the technical field of optical detection and color measurement, and particularly relates to a chromatic aberration measurement method and system based on hyperspectral global scanning imaging and a storage medium. Comprising the following steps: acquiring a hyperspectral scanning result of a to-be-detected chromatic aberration sample including a hyperspectral scanning sub-image; splicing the to-be-spliced hyperspectral scanning images to obtain a global hyperspectral scanning result of the to-be-detected chromatic aberration sample; the hyperspectral scanning image to be spliced is a hyperspectral scanning sub-image or an intermediate image formed by splicing; the splicing method comprises the following steps: carrying out feature point detection on a to-be-spliced hyperspectral scanning image to obtain a feature point descriptor set of the to-be-spliced hyperspectral scanning image, matching the feature point descriptor set of the to-be-spliced hyperspectral scanning image, and carrying out two-dimensional rigid body coordinate transformation based on a matching result to obtain the to-be-spliced hyperspectral scanning image. The hyperspectral scanning images to be spliced are spliced; and performing chromatic aberration calculation on the global spectrum scanning image of the chromatic aberration sample to be detected and the standard sample to obtain a chromatic aberration calculation result.

The invention provides a working face dynamic machine-following panoramic video stitching method and device. The method comprises the following steps: calling an original video stream of a target camera; wherein the target cameras are a plurality of cameras which are determined according to the position information of the coal mining machine and are within a preset range with the coal mining machine as the center; mapping the plurality of original video streams to a global coordinate system of the same working face according to the position information through a dynamic coordinate system conversion algorithm to obtain a machine-following panoramic video stream; performing local correction on the machine-following panoramic video stream through a local deformation correction algorithm to obtain a corrected video stream; fusing the overlapping areas of the adjacent cameras in the machine-following panoramic video stream through a multi-band fusion algorithm to obtain a fused video stream; the dynamic panoramic video which takes the coal mining machine as the center and continuously changes along with the movement of the coal mining machine is generated, and the remote control operation efficiency is remarkably improved. And the visual quality and naturalness of the dynamic panoramic video are ensured.

This invention discloses a method and system for multi-component analysis of aircraft exhaust plumes using micro-on-chip spectral imaging. The method involves acquiring multispectral image data of the exhaust plume region using a micro-on-chip spectral imaging system. This invention unmixes the mixed spectra using a non-negative matrix factorization algorithm and, combined with a pre-built fuel component spectral library, accurately identifies and quantitatively calculates the concentration distribution of key components such as carbon dioxide, carbon monoxide, nitrogen oxides, and unburned hydrocarbons in the exhaust plume. This method overcomes the errors caused by component overlap in traditional spectral analysis. By establishing a three-dimensional spatial coordinate model, high-precision extraction of the exhaust plume region is achieved, avoiding background interference. Furthermore, convolutional neural networks are used to perform spatiotemporal correlation modeling of the multi-component concentration data, generating a three-dimensional dynamic evolution map of the exhaust plume chemical components. This map reflects the diffusion patterns of exhaust plume components over time and space in real time, providing crucial data support for environmental impact assessment, aircraft emission control, and accident emergency response.

The invention relates to the technical field of image recognition, and discloses a highway tunnel inspection method and system, and the method comprises the steps: shooting an image of the inner wall of a tunnel when an inspection vehicle runs along the tunnel; extracting key points from the image of the inner wall of the tunnel, and calculating a transformation matrix according to the key points; performing perspective transformation on the image of the inner wall of the tunnel by using the transformation matrix; inputting the image of the inner wall of the tunnel after perspective transformation into a preset neural network model, and identifying a position with a damage condition from the image of the inner wall of the tunnel by the neural network model; analyzing the level of the damage condition according to a preset strategy; and when the level of the damage condition is higher than a preset level, alarm information is sent to prompt to take measures to deal with the damage condition. According to the method, perspective transformation is carried out on the image to eliminate image distortion caused by the tunnel top curved surface, the damage condition of the tunnel inner wall is identified by using the deep learning technology, and the damage condition of the tunnel inner wall can be efficiently and accurately identified in a complex and changeable tunnel environment.

The application discloses a super-small-pad micro-component visual positioning and precision mounting system and relates to the field of visual alignment. The system comprises an imaging module, a processing module and the like. The imaging module is used for applying a space-restricted light field to the pad area of a to-be-mounted substrate and the micro-component to be mounted, and arrayed imaging original data of the corresponding area is synchronously collected. The processing module is used for receiving the arrayed imaging original data, performing global normalization processing on the data, and generating a standardized imaging mapping data set. Through coaxial projection and synchronous collection of the space-restricted light field, complete imaging data covering the full depth of field of the pad and the full profile of the component can be obtained in a single exposure period, effectively solving the industry pain points of insufficient depth of field and difficulty in extracting edge features in micro-component mounting.

A method for detecting internal body defects of a crystal comprises the following steps: S1, taking a crystal with internal body defects after detection; S2, irradiating the crystal from the side with a line light source to obtain a crystal tomography image of scattered light containing the internal body defects of the crystal; performing size correction on the crystal tomography image; S3, performing time series analysis and processing on the corrected crystal tomography image to highlight the characteristics of the defect point; S4, combining the internal defect position of the known crystal and the detection time series signal of the position, training an RNN model to obtain a crystal internal defect detection model; S5, repeating the training to obtain a final crystal internal defect detection model; S6, inputting the time series signal of the crystal to be tested obtained by the S2-S3 processing into the final model, i.e. obtaining the internal defect position information; S7, filtering out false defects according to the representation of the defect on the plane. The present invention solves the problems of complex crystal internal defect recognition process and low recognition efficiency.

The application discloses a kind of robot motion intelligent control method and system based on machine vision, it is related to robot motion intelligent control technical field, by visual image acquisition processing module and ground texture detail extraction module, can make full use of ground crack, joint seam and special mark and so on texture details, form more stable visual feature base.Compared with the scheme of traditional dependence GPS or IMU, this design can still maintain higher positioning accuracy and stability in the environment of GPS signal loss, IMU drift accumulation is serious, reduce the deviation and misjudgment direction that robot appears in narrow space or repetitive trajectory task.Ground mark matching and feature point screening module not only extracts feature point, but also combines texture direction consistency index to carry out stability screening to feature point, eliminate weak feature point in unstable area, output high confidence ground mark matrix;Make robot can rely on reliable ground mark to carry out continuous self-positioning and trajectory keeping.