137 results about "Perspective distortion" patented technology

The invention discloses a cross-modal fusion and multi-frequency coding view angle image generation method in an ultra-low orbit scene, and solves the problem of view angle condition generation and single image three-dimensional reconstruction method based on diffusion prior in the ultra-low orbit scene of an aircraft target. Due to insufficient condition information fusion capability, limited radiation or illumination characterization and insufficient cross-view-angle geometric constraint, a problem that a new view angle image with visual coherence and geometric consistency of texture details is difficult to obtain at the same time under large-range view angle and scale change is solved; according to the method, multi-order angle information of direction distribution is effectively captured through perceptual coding of a light direction vector, then the position of a light starting point coordinate is coded, and finally the pose of a camera pose parameter is coded, so that the influence of a relative pose on depth perception and perspective distortion in an image generation process can be depicted; the three coding results are used for a decoding stage of the potential diffusion model, and geometric consistency of detail recovery under a new view angle is effectively improved.

Methods, systems, and apparatus, including medium-encoded computer program products, for camera detection of projectile point of impact include: processing at least one of multiple images of a physical target in a field of view of a camera to determine an orientation of the physical target, correct spatial perspective distortion for the physical target, establish a metric for the physical target that relates a pixel-to-pixel distance with a real-world distance, or a combination thereof; comparing respective images in a sequence of images from the multiple images to identify image data representing a projectile having hit the physical target; determining a point of impact of the projectile on the physical target based on the image data representing the projectile having hit the physical target; and providing the determined point of impact for scoring and presentation on a display device.

The invention relates to the technical field of object recognition based on image and point cloud fusion, and discloses a machine vision-based obstacle detection method and system in a container moving process, and the method comprises the steps: obtaining three-dimensional point cloud data through a laser radar installed on container carrying equipment, and obtaining a two-dimensional image through an industrial camera; performing terrain reference correction on the three-dimensional point cloud data, and establishing an inclined coordinate system matched with the ground gradient; performing perspective distortion correction on the two-dimensional image based on the inclined coordinate system to obtain a corrected two-dimensional image; extracting edge features, angular point features and semantic features from the corrected two-dimensional image; extracting geometric features and reflection intensity features of the three-dimensional point cloud data under the inclined coordinate system; performing cross-modal fusion on the edge features, the angular point features, the semantic features, the geometric features and the reflection intensity features to generate fusion features; and the obstacle type is identified based on the fusion feature, and the obstacle sensing reliability in the complex industrial environment is improved.

The invention discloses a power line image super-resolution recovery system and method for power transmission line patrol, and relates to the technical field of unmanned aerial vehicle image processing. The system provided by the invention comprises three core modules, namely a physical perception generator, a differentiable physical discriminator and a spatial transformation network (STN), wherein the generator is combined with a U-Net and a residual structure, and the output is ensured to accord with the geometry and material characteristics of a power line through physical constraint loss; the discriminator adopts a double-branch structure, and synchronously evaluates image authenticity and physical rationality; and the STN module corrects perspective distortion by using the pose data of the unmanned aerial vehicle to realize geometric alignment of the power line. The system integrates advanced components such as Swin Transformer, ViT and differentiable RANSAC, supports end-to-end processing from original Bayer data to a high-definition image, and outputs a defect detection confidence map with enhanced physical constraints. Compared with a traditional data driving method, the method strictly guarantees the physical credibility of a reconstruction result while improving the resolution, and is suitable for a power line inspection task in a complex environment.

The invention discloses an instrument data reading and collecting system and method based on image recognition, relates to the field of instrument image recognition, introduces a specially trained Meter-CornerNet deep learning model, and can accurately position four key angular points of an instrument panel from an original image containing perspective distortion and uneven illumination. After the angular points are obtained, an inclined instrument area is corrected into a standard front rectangular view through perspective transformation, and illumination normalization is carried out, so that the interference of the angle and illumination problems on the image quality is improved. And then, digital segmentation and OCR identification are carried out on the processed high-quality image, a result is verified, and finally, an accurate reading is sent to an Internet of Things platform. According to the method, high robustness and high accuracy of the whole system in a complex real scene are ensured through a strategy of first accurate correction and then identification verification.

The invention provides an electrical equipment defect identification method and device based on pose fusion, the method is applied to an identification device comprising a data processing module, a model construction module and a defect identification module, and the method specifically comprises the following steps: obtaining historical image data and corresponding defect information, and aligning pose data with the historical image data according to a shooting timestamp; performing perspective distortion correction and deblurring processing on the historical image data according to the corresponding pose data to obtain a corresponding equipment area image, and training a YOLO model in combination with the corresponding pose data and defect information to obtain a power equipment defect identification model; and constructing a recognition sample according to the currently collected image data and pose data of the power equipment, and inputting the recognition sample into the power equipment defect recognition model to obtain a defect recognition result of the power equipment. According to the method, the pose data can be fused into the pre-training data preprocessing stage and the training stage of the model, the method can adapt to defect identification of power equipment in different pose scenes, and the accuracy is guaranteed.

The invention discloses an intelligent archive digital processing method and system, and the method comprises the steps: carrying out the synchronous scanning of a paper archive through a multi-spectral linear array scanner, and collecting the archive image data of a visible light wave band and a near-infrared wave band; performing non-uniform illumination correction and perspective distortion correction on the archive image data to generate a geometric and color standardized dual-channel fusion archive image; based on the dual-channel fusion file image, outputting structured layout description information including a text area, a table area, a signature area and an illustration area; generating a preliminary archive information atlas according to the structured layout description information; and based on the archive information atlas and a preset archive metadata specification, finally outputting a fully structured digital archive object conforming to an archive standard. According to the embodiment of the invention, the fully-structured digital archive object can be automatically generated in a high-fidelity manner, and the accuracy, integrity and knowledge degree of digital processing are improved.

The invention relates to the technical field of power distribution networks, and particularly discloses a power distribution network hot-line work discrimination method based on image recognition. The method is used for solving the problems that a small target of a grounding ring is difficult to stably identify under the condition of scale and posture change due to factors such as strong light glare, appliance shielding, strong reflection metal highlight and perspective distortion in live-line work of a power distribution network, installation in-place and safe distance are difficult to accurately judge, threshold calibers are not uniform, and linkage lag is caused by time sequence jitter. Comprising the steps of scene acquisition and adaptive homomorphic preprocessing, multi-scale target detection modeling, loss calculation and training convergence, target output and label merging, geometric measurement construction, operation state judgment, safety linkage and back-off alarm, record uploading and quality closed loop. According to the method, through cooperation of the adaptive homomorphic preprocessing, the improved YOLOX embedded with geometric priori, the assembly geometric quantity and the time sequence consistent criterion, the identification and the positioning of the grounding ring under the hard light shielding are more stable and accurate, and the wrong judgment and the missed judgment are reduced.

The invention relates to the technical field of physical property testing, and discloses a mobile phone appearance multi-angle automatic detection system and method based on a multi-face reflection structure, and the system comprises a panorama collection unit which obtains an original panorama image formed by a to-be-detected mobile phone through a multi-face panorama reflection mechanism; the reference data storage unit is used for storing standardized three-dimensional model data of the mobile phone to be tested; the central processing unit is used for establishing the three-dimensional model data as a space measurement reference, constructing an optical path mapping matrix according to the distribution parameters, mapping a surface grid of the three-dimensional model data to a camera coordinate system to determine geometric distortion sampling coordinates, extracting pixels to complete space topology reconstruction, and generating a standardized surface expansion view; according to the invention, nonlinear perspective distortion in reflection imaging is eliminated, tight alignment of pixel sites and physical topology is realized, and physical balance with objective scales is provided for quantitative analysis of flaws.

The invention discloses a laser-point-cloud-guided tunnel multi-view area-array camera distribution map generation method and system, and the method comprises the steps: carrying out the calculation of a spatial mapping relation between a synchronously collected multi-view image and corresponding laser radar point cloud data based on the calibration parameters of a camera and a radar; geometric correction is carried out on the original image, and brightness adaptive equalization preprocessing is carried out on the corrected image; carrying out image feature point extraction and matching on the ROI of the image based on a deep learning model; recording an image matching relationship in a metadata form and creating an index; and based on the constructed image matching relationship metadata and indexes, realizing rapid generation of a panoramic distribution map. According to the method, the generated distribution image splicing error caused by factors such as uneven image brightness and perspective distortion can be relieved; large-scale image data matching and fusion based on adjacent image coincidence ROI constraint significantly improve efficiency; and based on a lightweight deep learning model, the reliability of extracting and matching the feature points of the low-illumination and weak-texture image of the tunnel scene is improved.

The application relates to the technical field of image data processing, in particular to a blister product defect intelligent detection method and system based on industrial vision. The method comprises the following steps: acquiring product images of to-be-detected blister products and calibration plate images of calibration plates respectively photographed on multiple detection stations; determining a relative offset amount of a finished product image relative to a finished calibration plate image based on the positions of physical marking points in the product images and the calibration plate images photographed on the multiple detection stations; evaluating a perspective distortion degree of the finished product image based on the morphological feature difference between a blister product region in the finished product image and a calibration plate region in the finished calibration plate image; and performing perspective transformation calibration on the finished product image based on the relative offset amount and the perspective distortion degree, wherein the calibrated finished product image is used for intelligent defect detection. The method can eliminate the influence of distortion on defect detection and improve the accuracy of defect detection.

The present application belongs to the technical field of oil use peony phenotype parameter automatic extraction method, especially relates to a kind of oil use peony phenotype parameter automatic extraction method and system based on multi-organ image analysis, obtain the high-resolution original image of oil use peony multi-organ containing ColorChecker24 standard color card, the organ at least includes petal, blade, fruit pod;Color correction and geometric correction are executed to original image, 24 color blocks of color card are positioned using computer vision algorithm, color conversion matrix is constructed to map image from device-dependent RGB space to standard color space, while calculating pixel scale based on color block physical size;Four corner points of bearing tray are detected for fruit pod image, and perspective transformation matrix is constructed to complete perspective distortion correction.

The invention relates to the technical field of microscopic imaging, and provides a microscopic imaging method and system based on a transmission-type relay projection screen, and the method comprises the steps: S1, enabling a laser to emit a light beam to irradiate a sample, and enabling the diffraction light of the sample to be projected to the transmission-type relay projection screen; s2, shooting the transmission-type relay projection screen on the other side of the transmission-type relay projection screen, and recording a power spectrum image of the sample; wherein the laser, the sample and the shooting camera are on the same axis, and the axis is perpendicular to the transmission-type relay projection screen; and S3, reconstructing the power spectrum image of the sample to obtain a target reconstructed image. The scheme has the characteristics of coaxial arrangement, simple structure, easy integration, long working distance, large depth of field, wide field of view and high resolution, can effectively reduce perspective distortion, and is convenient to combine with other technologies. The system does not need scanning measurement or wavefront modulation, so that the cost, complexity and operation difficulty of the system are reduced.

The application provides a kind of visual quality inspection and machining precision closed-loop control method and system of intelligent manufacturing unit, specifically collect the image of workpiece to be inspected, obtain initial target frame by target detection network, segment workpiece image to obtain pixel mask and contour, calculate the minimum area of contour as size reference frame as circumscribed quadrilateral;Based on the matching relationship between the actual feature points in the reference frame and the preset template, calculate the homography matrix to correct the perspective distortion, get the corrected contour and the standard size frame;Sample along the normal direction of each side of the standard size frame to get edge point set, fit high-precision edge with random sampling consistency algorithm and calculate the proportion of in-point, if the proportion does not meet the standard, increase the sampling density and re-fit, compare the fitted workpiece size with the planned size, and construct the machining deviation state matrix;Combine historical deviation matrix and compensation parameters to update the transfer matrix of machining process online, generate compensation parameters through current deviation matrix and send to unit controller.

The application discloses a kind of based on machine vision's patch type infrared receiving head appearance detection method and system, belong to computer vision detection field.Method includes: through bottom collimating backlight source irradiation to be measured receiving head, utilize the image of two telecentric cameras of symmetrical arrangement Synchronous acquisition pin;Sub-pixel level feature positioning is carried out to image and rejects reflection false feature point;Based on binocular vision principle, reconstruct the three-dimensional space coordinates of pin end;Adopt lowest multipoint method to construct reference plane, calculate the vertical distance of each pin to reference plane as coplanarity deviation;Deviation and tolerance threshold are compared, and output determination signal.System includes object table, bottom collimating backlight source, double-side telecentric camera, hardware level synchronous trigger unit, image processing and three-dimensional reconstruction unit, coplanarity evaluation and determination unit.The application can high-precision measurement pin coplanarity, eliminate perspective distortion and stray light interference, suitable for on-line full inspection on automatic production line.

The application discloses a visible light and laser radar aerial survey target, and relates to the field of aerial surveying and mapping, which comprises a transparent box body, a composite corner reflector and an adjustable supporting mechanism. A visible light image control pattern is arranged on the top plate of the transparent box body, and the geometric center of the visible light image control pattern is coaxially locked with the geometric center of the composite corner reflector with multiple symmetrical corner reflection units in the box. Regardless of the change of the ground slope and the angle of the box body, there is no relative displacement, and the systematic registration error caused by the center misalignment due to the two-time layout of the separated target is completely eliminated from the physical structure. The box body is adjusted to be absolutely horizontal through the adjustable supporting mechanism, the visible light image control pattern is guaranteed to be perpendicular to the unmanned aerial vehicle aerial photography optical axis without perspective distortion, the laser signal capture rate is improved through the configuration of the composite corner reflector comprising multiple symmetrical corner reflection units, and the aerial survey precision in mountainous areas is significantly improved.

The invention provides a control method and system of grabbing equipment and the grabbing equipment. The control method of the grabbing equipment comprises the steps that an original image of a cloth bearing device used for bearing cloth to be grabbed is obtained; correcting a target monitoring area in the original image into a rectangular shape through perspective transformation processing to obtain a to-be-processed image; identifying a target grabbing position of to-be-grabbed cloth in the to-be-processed image, wherein the to-be-grabbed cloth is located in the target monitoring area; and controlling the grabbing equipment to grab the target grabbing position of the to-be-grabbed cloth. Distortion of an original image is corrected through perspective transformation, a target monitoring area is corrected to be in a regular rectangular shape, the processed image can accurately reflect the actual position and shape of cloth, and interference of perspective distortion on cloth position measurement is effectively eliminated. And the target grabbing position of the to-be-grabbed cloth is recognized based on the corrected to-be-processed image, and the grabbing device is controlled to grab the target grabbing position, so that the accuracy of cloth grabbing control is improved.

The invention discloses a liquid level optical precision measurement method and system based on multi-depth reference characteristics, and belongs to the field of non-contact industrial measurement. The method comprises: taking an image including a luminescent liquid level, a container opening as a first reference feature, and at least one second reference feature located below the container and having a known size, from diagonally above the container; acquiring reference information such as the real size of each reference feature; based on the real size of each reference feature and the pixel size of each reference feature in the image, constructing a core effective scale conversion relation related to depth; and finally, the liquid level height is accurately solved by using the relation. According to the method, the concept of multi-depth reference is introduced, the problems of perspective distortion and scale uncertainty of a traditional single-reference-object vision method under the strabismus condition are fundamentally solved, and non-contact high-precision measurement of the liquid level is achieved.

The invention relates to the technical field of computer vision nondestructive testing, and discloses a concrete crack nondestructive testing quantitative analysis method based on a convolutional neural network. The method comprises the following steps: firstly, carrying out definition screening on a video stream, and generating a semantic mutual exclusion mask covering a crack region by utilizing semantic segmentation and morphological expansion; removing non-coplanar interference feature points in the crack region under the constraint of a mask, resolving a homography matrix only based on the feature points of the background region, and generating an orthoimage without perspective distortion; and finally, calculating the sub-pixel physical width of the crack in combination with the camera physical distance obtained by homography matrix decomposition and a direction adaptive Zernike moment positioning algorithm. According to the method, interference of crack textures on plane parameter calculation is eliminated through semantic constraint, geometric distortion caused by oblique shooting is corrected through virtual orthographic projection, and high-precision crack width quantitative detection can be achieved without external distance measuring equipment.

Systems, methods, and computer program product embodiments for an image correction system are disclosed herein. Embodiments operate by receiving an image of a physical object including graphics data with undefined perspective distortion. It is determined that an image transformation is to be performed on the received image. The image is provided to a neural network configured to generate a plurality of transformation parameters corresponding to the perspective distortion. The neural network is trained on a training dataset, the training dataset comprising: a first image set comprising an object having graphic data similar to the received image in a readable direction; and a second image set having a known perspective transformation. Image transformation is performed on the received image based on the values for the plurality of transformation parameters to generate a corrected image having graphic data oriented within a readable threshold.

The invention provides a field core box corner extraction and perspective distortion correction method based on multi-scale Retinex fusion. The field core box corner extraction and perspective distortion correction method comprises the following steps: S1, preprocessing a core box image based on anisotropic diffusion and multi-scale Retinex fusion; s2, core box angular point extraction based on topological constraint Shii-Tomasi and graph cut optimization interaction; s3, perspective correction based on thin plate spline transformation and Markov random field fusion; and S4, performing correction result precision verification and closed-loop feedback based on Hough transform straight line fitting and geometric moment invariant fusion. According to the method, accurate extraction of core box angular points and efficient distortion correction of images are realized, and meanwhile, full-dimension precision verification of correction results, adaptive migration of processing parameters of batch images and lightweight field deployment of algorithms are completed.

The application discloses a kind of pose closed loop planning system and method based on PLC six visual quality inspection, it is related to industrial robot quality inspection technical field, including: visual perception module, for obtaining RGB-D image;Pose closed loop control module, for receiving RGB-D image and output 6D pose data;Motion planning module, for generating double-arm motion trajectory;Flip optimization module, for generating optimal flip sorting set;Sorting execution module, for completing sorting and discharging action according to quality inspection result and control instruction;Robot controller, for data interaction and issue control instruction.The application does not need to rely on artificial flip or multiple fixtures, reduce the failure rate caused by incoming material position deviation etc., through double-arm alternate operation and Monte Carlo optimization flip sorting, realize PLC device six automatic continuous detection, with the combination of coarse positioning, fine positioning of double RGB-D camera, combined with the output 6D pose data of deep learning pose estimation model, effectively avoid perspective distortion and miss detection, false detection.

The application discloses an intelligent file digitization processing method and system, and the method comprises the following steps: synchronously scanning paper files through a multispectral line array scanner, and collecting file image data in a visible light band and a near-infrared band respectively; correcting non-uniform illumination and perspective distortion of the file image data, and generating a geometrically and coloristically standardized double-channel fusion file image; outputting structured layout description information containing a text area, a table area, a signature area and an illustration area based on the double-channel fusion file image; generating a preliminary file information graph according to the structured layout description information; and finally outputting a fully-structured digital file object meeting archiving standards based on the file information graph and a preset file metadata specification. By using the embodiment of the application, a fully-structured digital file object can be automatically and high-faithfully generated, and the accuracy, completeness and knowledge level of digitization processing are improved.

The invention belongs to the technical field of intelligent automobile lighting, and particularly relates to a dynamic glare suppression method and system based on multi-automobile cooperative perception, a vehicle and a computer readable storage medium. According to the method, a glare sensitivity distribution diagram which is sent by an opposite vehicle and based on the visual angle of the vehicle is received through V2X vehicle wireless communication, vehicle-vehicle information sharing is achieved, and the sensing limitation of a single vehicle is broken through; constructing a human eye glare sensitivity model based on the CIE standard, converting the physical brightness into subjective glare perception to generate a smooth weight map, and performing curve and ramp dynamic geometric compensation on the map to eliminate perspective distortion; and finally, generating a pixel-level dimming instruction by using the multi-agent depth deterministic strategy gradient network in combination with the lighting requirement of the vehicle, and driving the pixelated headlight to execute accurate brightness adjustment. According to the method, the problems of multi-vehicle meeting game conflicts, rough control strategies and failure of complex road conditions are effectively solved, and collaborative and accurate glare suppression and remarkable improvement of subjective comfort are achieved.

The application provides an image processing method and device, electronic equipment and computer readable storage medium. The electronic equipment determines the arrangement of multiple portraits in a group image to be processed. If the arrangement of multiple portraits in the group image is neat, the correction strength of a correction model is reduced, and the multiple portraits are corrected according to the adjusted correction model. The correction model is used to adjust the projection mode of the image to reduce the perspective distortion of the image. The neat arrangement indicates that the distance between the arrangement position of the multiple portraits and the reference line is within a preset range. The above method can reduce the perspective distortion of the image to be processed, and can avoid the phenomenon that the portrait arrangement queue is obviously curved due to the excessive correction strength. By reducing the correction strength, the problem of image imbalance caused by the small size of the edge face and the magnification of the center face in the corrected image can be avoided, and the display effect of the image is improved.

The invention discloses a card and document image processing method, system and device and a medium, and relates to the technical field of image processing. Aiming at the problems of perspective distortion, inclined rotation and incorrect direction of a card image, the method comprises the following steps: acquiring a card or document image, and preprocessing the card or document image to generate a standard image; constructing a lightweight multi-task model comprising a lightweight convolutional neural network backbone, a corner regression network branch and a direction classification network branch, and training the lightweight multi-task model; a multi-scale shared feature map is extracted through a lightweight convolutional neural network backbone, then two-dimensional coordinates of four corners are output through a corner regression network branch, and an image direction category is output through a direction classification network branch; constructing a perspective transformation matrix by using the two-dimensional coordinates of the four angular points, and performing perspective distortion correction on the original image; and rotating and outputting the corrected image according to the direction category. According to the invention, the image processing efficiency and accuracy can be improved.

This invention discloses a method, system, and terminal device for displaying a 3D geographic information system based on multiple screens, relating to the field of 3D display technology. The method includes: acquiring 3D geographic information data; constructing a 3D geographic scene in a 3D rendering engine; determining the observer's viewpoint within a physical space, which is enclosed by multiple planar display screens forming a multi-screen display; deploying a corresponding number of virtual cameras facing the corresponding screens, with the observer's viewpoint as the origin; configuring the cameras in a physical trapezoidal combination based on the physical size and position of the screens relative to the observer and calculating the asymmetric view frustum projection matrix; allocating rendering tasks to pre-built distributed rendering cluster nodes, and controlling the synchronous output of each camera's image to the corresponding screen through a hardware synchronization mechanism. This invention achieves naked-eye stereoscopic display on multiple screens, eliminates perspective distortion at screen junctions, ensures seamless synchronization of multi-screen images without tearing, and enhances the immersiveness and accuracy of 3D geographic information display.

The invention discloses an intelligent detection system for waterproof roll lap joint quality based on deep learning, and relates to the technical field of waterproof roll lap joint quality detection.The intelligent detection system is characterized in that an area acquisition module is arranged, and after detection personnel complete image data shooting on any waterproof roll lap joint area in a target area, a detection result is obtained; the image processing module is used for receiving and collecting the image data, the image auditing module is used for pre-auditing any image data, and images with unqualified shooting heights and inclination angles are screened out in advance in the pre-auditing process, so that low-quality image data with serious perspective distortion are reduced from the source; therefore, a subsequent quality evaluation platform does not need to execute large-scale matrix operation, pixel coordinate mapping calibration and other complex preprocessing operations on a large number of distorted images, the requirement for platform computing power resources is greatly reduced, and the hardware configuration cost and operation energy consumption of a detection system are effectively reduced; and meanwhile, the evaluation result delay caused by complex processing is avoided, and the response efficiency of the detection service is improved.

The application discloses a kind of viewgraph generation methods of cross-modal fusion and multi-frequency coding under ultra-low orbit scene, solve the ultra-low orbit scene of aircraft target, based on the generation of view condition and single picture three-dimensional reconstruction method of priori diffusion, because of insufficient condition information fusion ability, radiation or illumination representation is limited and cross-view geometric constraint is insufficient, it is difficult to obtain the problem that visual coherence and geometric consistency of new view image with texture details under large range of view and scale change simultaneously;The application effectively captures the multi-order angle information of direction distribution to the perception coding of light direction vector, then encodes the position of light starting coordinate, finally encodes the pose of camera pose parameter, can depict the influence of relative attitude on depth perception and perspective distortion in image generation process;The above three encoding results are used in the decoding stage of latent diffusion model, effectively improve the geometric consistency of detail recovery under new view.

The invention belongs to the technical field of medical braided tube measurement, and particularly relates to a medical braided tube parameter measurement method and system based on machine vision. According to the medical braided tube parameter measurement method based on machine vision, a dome integral light and polaroid fused illumination scheme is designed, an air suspension rotary table supporting structure is combined, multiple reflection and flexible deformation of metal are effectively restrained, and a stable imaging basis is provided for measurement; a skeleton optimization algorithm based on dual-threshold RDP simplification and geometric constraint connection significantly improves the recovery rate and topology integrity of the fractured grid; according to a linear density calculation model based on parallel measurement line intersection point multi-verification and perspective transformation analysis, non-contact, high-precision and unbiased linear density measurement is realized by dynamically generating measurement lines, counting effective intersection points and combining coefficients to compensate perspective distortion; a complex multi-dimensional parameter measurement problem is converted into a unified sub-pixel visual detection problem, automatic detection of linear density, wire diameter, outer diameter and defects is synchronously realized in single imaging, the detection efficiency and consistency are greatly improved, and a reliable technical means is provided for precise quality control of medical instruments.