440 results about "Ellipse" patented technology

The invention belongs to the field of cable eccentricity detection, and particularly relates to a cable eccentricity detection method and system based on X rays. The method comprises the following steps: calculating a gradient magnitude diagram and a gradient direction diagram through an X-ray image of a cable, screening a point with the local maximum gradient magnitude and low neighborhood divergence as a contour starting point, performing contour tracking to generate a contour point set, and selecting a next contour point based on a tangential prediction direction; performing ellipse fitting on the contour point set to obtain a geometric center, long and short axis parameters and a root-mean-square error of a fitting ellipse, dividing the fitting ellipse into an inner candidate ellipse and an outer candidate ellipse according to a long axis, and matching the inner candidate ellipse meeting the condition for each outer candidate ellipse; and screening out an outer candidate ellipse and an inner candidate ellipse which meet conditions from the candidate pairs, and calculating the eccentricity of the cable to be measured based on geometric center coordinates of the outer candidate ellipse and the inner candidate ellipse. According to the invention, the accuracy and reliability of cable eccentricity measurement results can be improved.

The invention belongs to the technical field of image data processing, and particularly relates to a quality detection method and system for metal pipe fitting forming, and the method comprises the steps: obtaining a plurality of groups of matched gap regions of a port edge image according to the gray scale difference of the neighborhood of each gap of the port edge image in a corresponding metal pipe fitting image; obtaining a suspected defect area of the port edge image according to curvature change of edge pixel points of the port edge image; acquiring similar arc segments of each suspected defect area according to the change of the distance from the arc segment on the ellipse of the metal pipe edge image to the ellipse center; obtaining the abnormal degree of each suspected defect region according to the deformation difference between the suspected defect region and the similar arc section and the gray difference between the suspected defect region and the corresponding suspected defect region of the same group of matched gap regions; and screening to obtain a final defect area. According to the invention, the accuracy of quality forming detection of the metal pipe fitting is improved.

The invention provides a non-training burr detection method and device for a cover plate inner hole, relates to the field of burr detection, and solves the technical problem of non-target area interference caused by incapability of effectively focusing on an inner hole area. The method comprises the following steps: acquiring a current frame image of a target cover plate, and storing the current frame image as a grey-scale map; performing threshold segmentation on the grey-scale map, and extracting a maximum outer contour region in the grey-scale map; and carrying out convex hull calculation, and removing a concave part in the maximum outer contour region to obtain a regular convex hull contour. And generating an optimal ellipse boundary through an ellipse fitting algorithm. And carrying out segmentation fitting to remove outliers to obtain a final ellipse boundary. And generating a binary mask based on the ellipse fitting region, extracting a pixel set of which the gray value is zero in the mask, and outputting a burr region. And calculating the total defect area, comparing the total defect area with a dynamically adjusted area threshold value, judging whether the cover plate is qualified or not, and feeding back a judgment result to the detection control system. The device is used in the burr detection process of the inner hole of the cover plate.

The invention discloses a composite phase metasurface and method for generating a tunable elliptical Airy beam. The composite phase metasurface comprises two coaxially stacked phase metasurfaces, each phase metasurface is rotatably arranged, the composite phase metasurface can modulate an original light beam into an elliptical Airy light beam, and the relative rotation angle of the two phase metasurfaces is changed by rotating at least one phase metasurface around a common axis. The focus position of the elliptical Airy beam can be adjusted; the two phase metasurfaces are a first phase metasurface and a second phase metasurface respectively, the first phase metasurface is located on one side of an original light beam and has a superposition phase of a cubic phase and the first phase, the second phase metasurface is located on one side of an elliptical Airy light beam and has a second phase, and the first phase and the second phase are complementary. According to the composite phase metasurface and the method, the elliptical Airy beam can be generated, and the track of the beam and the position of the focus in the longitudinal or transverse direction can be dynamically adjusted in real time.

The invention relates to the technical field of structural dynamic displacement measurement, and discloses a structural deformation monitoring method, device and equipment and a medium, and the method comprises the steps: converting a vibration video of a target structure into a plurality of frames of pictures, and building a normalized orthogonal projection model of a camera, ellipse fitting is carried out through multi-point local calibration, ellipse parameters are obtained, displacement correction parameters of a camera are calculated, feature points of a calibrated circular image are extracted after ellipse correction is carried out on the calibrated circular image, and information fusion is carried out on the feature points of different frames of images based on the correction parameters; measuring point dynamic tracking is carried out through feature point matching of the calibration circular images in different frames of pictures, dynamic displacement information of the measuring points corresponding to the calibration circular images is calculated, and the deformation condition of the target structure is monitored according to the dynamic displacement information. The method can simplify the camera calibration process, reduce the calibration difficulty, improve the measurement precision of dynamic displacement, and improve the accuracy and reliability of structural deformation monitoring.

The invention relates to a camera calibration method and system based on solid circle feature points, and belongs to the field of machine vision. The method comprises the following steps: firstly, acquiring a plurality of images of different poses of a calibration plate, then sorting a plurality of large solid circles on the calibration plate from large to small according to the circle center spacing between the large solid circles, and then calculating a first perspective projection transformation matrix according to the circle center coordinates of the sorted large solid circles and the center coordinates of an ellipse; and obtaining internal and external parameters of the to-be-calibrated camera according to the first projection transformation matrix so as to realize calibration of the to-be-calibrated camera. The feature points are obtained by using the sorted large solid circles, so that the point location quality and the matching accuracy are improved, and the precision of calibration parameters is remarkably improved.

The invention discloses a steel pipe diameter and out-of-roundness measuring method based on ellipse fitting. The method comprises the following steps: acquiring section contour data of a steel pipe; utilizing an improved ellipse fitting algorithm to obtain an optimal ellipse model and a corresponding local point; reconstructing steel pipe section contour measurement data through a linear interpolation algorithm; and the maximum diameter and the minimum diameter of the steel pipe are calculated by using the reconstructed steel pipe section contour measurement data, so that the out-of-roundness of the steel pipe is determined. On the basis of geometric distribution of data points and high efficiency of an improved ellipse fitting algorithm, steel pipe section contour measurement data can be accurately reconstructed; according to the improved ellipse fitting algorithm, the confocal hyperbolic distance is used for replacing the algebraic distance, the actual geometric distance from the steel pipe section contour data points to the fitting ellipse can be accurately reflected, the fitting ellipse better conforms to the actual section contour of the steel pipe, effective data points are obtained, and the fitting precision is improved. Noise points and outliers generated by a measuring instrument and the environment are eliminated, and the measuring precision is improved.

The present disclosure relates to a method and device for a camera calibration algorithm using an unbiased conic estimator considering distortion, and may be configured to calculate an ellipse in a normalized coordinate system from a circular pattern in a space, express a center of a distorted ellipse in a camera coordinate system as a linear combination of moments of the ellipse, and perform camera calibration from an image of the circular pattern using the center as a control point.

The invention discloses a target positioning and recognition method for high-precision photogrammetry of a jacket. The target positioning and recognition method for high-precision photogrammetry of the jacket comprises the following steps: obtaining a plurality of jacket images through photogrammetry; drawing a histogram of the image; determining imaging conditions; using a real-time target detection algorithm to coarsely detect a possible circular target area; ellipse detection under different imaging conditions; positioning a circle center; and decoding the coding mark. According to the target positioning and recognition method for high-precision photogrammetry of the jacket, high-precision measurement work of the deepwater ultra-large jacket can be effectively completed through the target positioning and recognition method, and the measurement precision of completion measurement of the deepwater ultra-large jacket is effectively improved.

The invention relates to a crack prediction method and device based on post-stack seismic orientation attribute difference, and the method comprises the steps: carrying out the guided filtering of original seismic data, and obtaining the filtering data; setting a plurality of azimuth angles, and respectively extracting a plurality of azimuth attribute data of the filtering data based on the plurality of azimuth angles; ellipse fitting is carried out on the multiple pieces of azimuth attribute data, and ellipse parameters are obtained; and fracture data are obtained through analysis according to the ellipse parameters. According to the method, the response characteristics of the crack can be captured from different directions, so that the distribution rule of the crack is more comprehensively described, and the crack prediction precision is remarkably improved.

The invention discloses a river water surface space-time image texture direction angle detection method based on a frequency spectrum adaptive mask. The method comprises the following steps: step 1, obtaining a space-time image on a velocity measurement line and an amplitude spectrum thereof by using an image method flow measurement system; 2, binarizing the amplitude spectrum based on a triangular threshold method, and extracting a highlight part in the amplitude spectrum; step 3, performing contour extraction and ellipse fitting on the binarization amplitude spectrum in the step 2 based on boundary tracking and a least square method to obtain an ellipse mask, and performing subsequent texture angle detection by using a minor semi-axis and a major semi-axis of the ellipse mask; step 4, based on an LSD straight line segment detection algorithm, constructing a direct current mask and applying the direct current mask to the amplitude spectrum to remove direct current influence; 5, based on the long semi-axis and the short semi-axis of the elliptical mask in the step 3, coarse-to-fine texture direction angle detection is carried out; and step 6, carrying out detection result validity identification based on the coarse positioning and fine positioning difference value. According to the method, the direct current noise in the space-time image amplitude spectrum can be eliminated, the self-adaptive value taking of the integral radius parameter is realized, the texture direction angle detection accuracy under various noise interferences is improved, and the detection result is effectively identified.

The invention relates to the technical field of image processing, in particular to a rubber ring contour burr detection method and system based on geometric transformation, and the method comprises the steps: obtaining a rubber ring image, and extracting the outer contour of a rubber ring and the contour of each burr in the rubber ring image; fitting the outer contour of the rubber ring by adopting a least square method to obtain an ellipse, and mapping the ellipse into a standard circle: carrying out bilinear interpolation resampling on the rubber ring image, and carrying out polar coordinate transformation on the rubber ring image by taking the circle center of the standard circle as an original point to generate an expanded image; generating a reconstructed image with enhanced burr features from the expanded image through wavelet transform, determining burr parameters of the reconstructed image, mapping the burr parameters back to a Cartesian coordinate system of the rubber ring image, and generating a detection result containing burr number, position and size information; according to the invention, the accuracy and robustness of tiny burr detection can be improved.

The invention discloses a product detection method and device, electronic equipment and a readable storage medium, which are applied to the technical field of image processing, and the method comprises the steps: extracting a plurality of product edge feature points from an image of a circular product, carrying out the fitting of the plurality of product edge feature points to obtain an ellipse, and carrying out the building of a standard circle through the ellipse, then, a perspective transformation matrix is constructed by using an ellipse and a standard circle, perspective transformation is carried out on the multiple product edge feature points and images respectively, non-standard circles presented by qualified circular products in the images due to camera shooting angle or product position inclination are corrected, complete visual angle correction is achieved, and the product quality is improved. And finally, based on the plurality of transformation feature points obtained by perspective transformation and the target image obtained by perspective transformation, carrying out qualification detection on the circular product, so that the over-detection rate can be reduced, and the detection efficiency and precision of the circular product can be improved.

The invention provides a non-contact steel pipe end face size measurement method and system, and the method comprises the steps: traversing recognized contour points on the basis of obtaining an image and recognizing the contour of the image, calculating the distance between the contour points, judging the contour points which are too far away from each other as burrs, eliminating the influence of the points, carrying out the ellipse fitting of the contour, and obtaining the size of the end face of a steel pipe. And parameters such as the inner diameter, the outer diameter and the roundness can be calculated according to an ellipse fitting result. According to the invention, based on the original image of the pipe end, the contour of the pipe end is identified by combining image edge detection and a graphic method, the position relation between contour points and the contour is calculated through a self-research algorithm, pipe end burrs are accurately positioned, and the influence of the burrs on the measured pipe end size is eliminated. The problems that a manual measurement method is insufficient in precision and high in maintenance cost are solved, the burr sensitivity is improved, and the effective pipe end size is accurately obtained.

The invention provides a gear peeling time-varying meshing stiffness prediction method and system based on a back propagation neural network, and the method comprises the steps: considering a tooth surface peeling fault based on a gear tooth bearing contact analysis method, and constructing a helical gear pair time-varying meshing stiffness calculation model; a real irregular tooth surface peeling area is fitted by adopting a least square ellipse fitting method to obtain an ellipse appearance representation, any peeling position is completely described through six key geometric parameters, the geometric parameters of the ellipse appearance are systematically traversed and fitted, and diversified peeling appearance samples are generated. Introducing a tooth profile deviation matrix corresponding to the peeling morphology sample into a tooth surface bearing contact analysis model, and constructing a training data set; and constructing a back propagation neural network model of multiple hidden layers, and performing end-to-end training by using the training data set, so that the back propagation neural network model learns a nonlinear mapping relationship from geometric parameters to a time-varying meshing stiffness curve, thereby predicting the time-varying meshing stiffness under any peeling morphology.

Methods, systems and apparatuses may provide for technology that determines a major axis length of an ellipse in texture space based on a transformation matrix associated with a circle in screen space, inverts the major axis length, determines a product between the inverted major axis length and a determinant of the transformation matrix, and determines a minor axis length based on a modulus of the product between the inverted major axis length and the determinant of the transformation matrix. In one example, the technology selects a level of detail in the texture space based on the major axis length, the minor axis length, a direction of the major axis length, and a direction of the minor axis length.

The invention discloses a method for simultaneously generating Skyrmion and Mobius ring topological states, which comprises the following steps of: constructing a Stokes parameter Skyrmion beam of any order by using left-hand circularly polarized light and right-hand circularly polarized light as orthogonal substrates; the order of the Skyrmion beam depends on the difference value of topological charges of orbital angular momentums carried by the left-handed component and the right-handed component. The Skyrmion beam is tightly focused, and a three-dimensional polarization ellipse can be generated in a focal field. Based on any axis of a three-dimensional polarization ellipse, a Mobius ring can be constructed around a point C of a focal field. Meanwhile, the Skyrmion topology state with the same order as the incident field can be constructed based on the Stokes parameter of the focal field. The torsion times of the Mobius ring in the focal field can be controlled by changing the order of the Skyrmion light beam. According to the invention, the generation of the focal field with the Skyrmion topology state and the Mobius ring topology state is realized, and the generation, annihilation and torsion times of the Mobius ring in the focal field can be controlled.

The invention discloses a linear management method and device for a fabricated bridge and a medium. The problem that an existing detection scheme depends on manual operation is solved. According to the method, firstly, rich image data are obtained through multi-angle shooting; then, the image is processed through a target detection and ellipse detection algorithm, and a target is recognized and positioned; thirdly, determining the pose of the camera and the three-dimensional coordinates of the mark points by using a five-point algorithm and triangulation; and finally, through space splicing and linear fitting, a linear result of the bridge is obtained, and the linear result can provide a construction or maintenance basis for the bridge in a construction process or a use process. According to the method, the linear features of the current state of the bridge can be efficiently calculated only by shooting the image data containing the target. The tedious process that an expensive total station needs to be carried to a permanent observation point for observation every time in a traditional method is avoided, and the monitoring efficiency and convenience are remarkably improved.

According to one or more embodiments of the present disclosure, an ellipse model may be applied to detection results included in ultrasonic sensor data (USS data) to identify one or more objects that may be indicated by the detection results. The identification of the objects may include determining the locations, shapes, and / or classifications of at least portions of the objects. For example, in some embodiments, the ellipse model may be applied to detection arcs indicated in USS data and corresponding to detection of an object using multiple ultrasonic sensors. In some embodiments, the application of the ellipse model may include fitting an ellipse to the detection arcs. The resulting ellipse and / or its corresponding ellipsoidal parameters may indicate one or more properties about the object.

The invention belongs to the technical field of scanning measurement, particularly relates to a cable outer diameter and ovality measurement method and system based on line laser contour scanning, and aims to solve the technical problem of low measurement precision caused by the fact that an existing algorithm is sensitive to noise, asymmetry of light strips and contour discrete points. The measurement method comprises the following steps: S1, performing anisotropic Gaussian filtering on a pixel according to a local tangential direction of a preliminary center line; s2, calculating a second derivative value and a third derivative value of the sub-pixel center point in the normal direction; s3, performing initial weighted least square ellipse fitting by using the corrected contour point set and the corresponding fitting weight to obtain parameters of an initial ellipse; and S4, based on the lengths of the long axis and the short axis of the fitting ellipse, calculating to obtain the outer diameter and the ellipticity of the cable. According to the measurement method, the interference of abnormal data points introduced by local flaws such as oil stains and scratches on the surface of the cable is eliminated, and the accuracy and the stability of a fitting result are improved.

The invention relates to a feeding table position registration method based on 3D vision, belongs to the technical field of position registration, and solves the problem of low precision of positioning compensation of a feeding table in the prior art. The method comprises the steps that at least three circular marks are arranged on a workpiece; after the feeding table is controlled to convey the workpiece to a designated position, an image of the workpiece at the current position is collected through the 3D camera to serve as a target image; acquiring a workpiece point cloud from the target image as a target point cloud based on ellipse fitting processing on the circular mark; matching the target point cloud with the reference point cloud to obtain translation deviation and rotation deviation between the current position and the specified position; the reference point cloud is a workpiece point cloud of a specified position collected under a template attitude; and based on the translation deviation and the rotation deviation, the feeding table is controlled to move to a designated position. By means of the method, the precision of positioning compensation of the feeding table can be effectively improved.

Embodiments are disclosed for determining a spin rate and axis of a ball using deep learning. In some embodiments, a method comprises: training a deep learning network on training images of spinning balls, each spinning ball having at least one feature point in a time series that forms a two-dimensional (2D) ellipse image in a 2D plane; capturing, with at least one camera, a series of images of a ball; predicting, with the trained deep learning network, spin measurements associated with the ball based on the series of images; determining a spin rate of the ball based on the spin measurements; determining coefficients of a 2D ellipse model based on the spin measurements and the spin rate; and determining, with the at least one processor, a spin axis of the ball in 3D space based on the 2D ellipse model and the spin rate.

The invention relates to the technical field of spacecraft navigation, and discloses a method for estimating the relative attitude of a failed spacecraft under the constraint of computing resources, and the method comprises the steps: carrying out the preprocessing of measurement data, obtaining the observation data of the relative attitude of a camera based on an ellipse recognition algorithm, and obtaining the measurement data of the relative attitude of a laser radar based on an iterative nearest point algorithm. Pseudo measurement factors are designed for the camera and the laser radar, and variational integral prediction factors are designed for attitude increments at adjacent moments of the failed spacecraft; factor graph optimization based on a moving window is carried out, and the relative attitude of the failed spacecraft is estimated; the momentum conservation characteristics of the failed spacecraft can be mined through a designed variational integral predictive factor, the constraint relation of attitude increments at adjacent moments is constructed, and the problem that the estimation precision of an existing scheme depends on high-frequency measurement input is solved; and low-frequency measurement data of the camera and the laser radar are fused through a built failure spacecraft full-state factor graph model, so that the relative pose estimation of the non-cooperative target under the low computing power load is realized.

The invention provides a method and a system for detecting winding centering deviation. The method comprises the following steps of: S1, constructing and training a centering deviation detection model; arranging lighting equipment and camera equipment, and acquiring images at intervals; s2, inputting the image into the middle deviation detection model, solving a circle center coordinate of an ellipse in the image, and further calculating a pixel deviation value; obtaining an actual offset distance according to the pixel deviation value; s3, the track of the ellipse is obtained, and drawing is carried out on the image; s4, whether the actual offset distance is larger than or equal to a threshold value or not is judged; if the result is yes, storing the current data, and sending out an early warning signal; and if not, storing the current data. According to the invention, high-precision detection is carried out on the centering height of the steel coil in a visual identification mode, the coil turning phenomenon is avoided, and the labor intensity of operators is reduced.

The invention discloses a round hole pose measurement method based on reprojection optimization. The method comprises the steps that a binocular camera is used for collecting two target images containing a round hole, then initial pose parameters of the round hole are obtained, then a projection ellipse of the round hole on the plane of the binocular camera is generated through re-projection, the ellipse is detected in combination with the edge, the updating step length of the pose parameters of the round hole is obtained after processing is conducted through an ellipse error and a cosine attenuation strategy, and the pose parameters of the round hole are obtained. And the pose parameter of the circular hole is iteratively updated to realize the measurement of the pose of the circular hole. According to the method, the circular hole space pose parameters serve as variables to be optimized, the projection ellipse of the circular hole on the plane of the binocular camera is generated, the error between the projection ellipse and the ellipse obtained through the ellipse detection algorithm is minimum, the ellipse detection result is fully utilized, the defect that the ellipse detection result cannot meet the binocular vision epipolar constraint is overcome, and the binocular vision epipolar constraint requirement is met. Meanwhile, a cosine attenuation strategy is combined to calculate a learning rate, so that a circular hole space pose parameter calculation result is quickly converged, and the measurement precision is improved.

The invention relates to an axis calibration method for a line structured light system, and belongs to the field of machine vision measurement, and the method comprises the steps: S1, a three-jaw chuck clamps a cylindrical calibration body with an ideal Lambert surface, and the axis of the cylindrical calibration body and the axis of the three-jaw chuck are kept coaxial; s2, completing the installation and calibration of the line structured light system; s3, scanning and recording each frame of contour point cloud and rotation angle of the cylindrical calibration body which rotates around the axis at a constant speed, and checking a coaxial relationship; s4, fitting the contour point cloud into an ellipse by using a structured light plane normal vector, and converting the ellipse into a perfect circle to obtain an initial value of an axis; and S5, splicing each frame of contour point cloud by using a Rodrigues formula, constructing a target function by combining the cylindrical geometric constraint and the variance of the distance distribution from the overall contour point cloud of the cylindrical calibration body to the axis, and iteratively optimizing the axis equation. The axis initial value acquisition method provides a reliable initial value for a subsequent optimization algorithm, and the objective function is iteratively solved through the optimization algorithm, so that the accuracy is improved.

The invention discloses a hole group axis parallelism error detection method and device and a storage medium, and relates to the field of structured light vision measurement. The method comprises the following steps: acquiring first point cloud data of a reference hole for positioning and acquiring second point cloud data of a detected hole to be detected by adopting a line laser and camera equipment; on the basis of the first point cloud data and the second point cloud data, ellipse centers corresponding to intersection lines of the reference hole and the measured hole are obtained through a fitting algorithm; calculating a reference axis according to the ellipse center of each intersection line of the reference hole; establishing an evaluation plane perpendicular to the reference axis according to the reference axis and the ellipse center of the measured hole; projecting the center of the ellipse of each intersection line of the measured hole to an evaluation plane to obtain a minimum containing circle containing all projection points; and measuring the diameter of the minimum containing circle, comparing the diameter with a preset parallelism tolerance, and judging whether the parallelism of the measured hole is qualified or not according to a comparison result. According to the invention, the efficiency of measuring the parallelism of the part is improved.

The invention relates to the technical field of intelligent monitoring, in particular to an old people behavior abnormity monitoring system based on thermal imaging, which comprises a processor and a memory, the processor executes a computer program stored in the memory so as to realize the following steps: according to a long axis included angle, a gravity center and an axial ratio of a minimum circumscribed ellipse of a target area on a to-be-judged image; and obtaining an included angle change representation value of a local window corresponding to the first suspected fall image, a gravity center shift degree corresponding to the to-be-judged image and an elliptical deformation degree corresponding to the to-be-judged image, and monitoring the fall behavior of the monitored object according to the included angle change representation value, the gravity center shift degree and the elliptical deformation degree. And the accuracy of monitoring the falling behavior of the monitored object can be improved.

The invention discloses a circular hole measurement method based on image feature recognition, a medium and a system. The method comprises the steps of S1, performing Gaussian filtering processing on an original image; s2, performing gray scale superposition projection through a sub-pixel circular boundary projection algorithm to generate a projection curve; s3, performing moving average filtering on the projection curve to generate a smooth curve; s4, performing differential operation based on the smooth curve to generate a differential curve; s5, screening an effective boundary feature point set on the differential curve; s6, for each extreme point in the effective boundary feature point set, calculating an adaptive threshold value in a neighborhood gray scale curve of the extreme point, and realizing sub-pixel-level positioning through gray scale straight line and smooth curve interpolation fitting; s7, generating an initial ellipse model from the sub-pixel feature points through a robustness ellipse fitting algorithm; and S8, iteratively optimizing a fitting result, removing abnormal points which deviate from the model and exceed a threshold value, and outputting an optimized ellipse parameter. The method has the advantages of high measurement precision and the like.

The invention belongs to but not limited to the technical field of tunnel engineering, and particularly relates to a segment roundness measurement method and system based on a two-dimensional laser radar, and the method comprises the steps: S1, obtaining the point cloud data of a tunnel pipe wall under a polar coordinate system through the laser radar; s2, performing random noise filtering on the point cloud data and converting the point cloud data into a Cartesian coordinate system; s3, useless point cloud data generated by sundries such as pipelines and tracks on the pipe wall are filtered out; and S4, projecting the point cloud data to a two-dimensional plane, carrying out ellipse fitting on the filtered point cloud data to fit an ellipse contour of the section of the tunnel, and calculating a long axis and a short axis of the ellipse contour according to an ellipse curve equation so as to calculate the roundness of the tunnel. According to the invention, the laser radar is installed on the segment assembling machine for scanning, the installation of a redundant scanning device is avoided, the influence of a dust environment and sundries on scanning data is avoided to the greatest extent through the annular rotation of the segment assembling machine, and the operability and robustness of the scanning method are greatly improved.