116 results about "Line fitting" patented technology

A straight line fitting method for image detection in a complex interference environment comprises the following steps: firstly, carrying out interference point deletion on a feature point set of an environment image, then carrying out multiple times of random sampling, forming a total point set by using associated points through distance operation, obtaining a plurality of straight line models through initial fitting, and carrying out linear fitting on the linear models; and then calculating an interior point proportion in the total point set according to the linear model, finally selecting the total point set with the maximum number of interior points, and continuously reducing a residual threshold in multiple iterative calculations to improve an interior point proportion threshold by dynamically adjusting a feedback mechanism of the residual threshold when the interior points are calculated. In the initial stage of iteration, more points can enter the model to ensure the diversity and robustness of the model, and the threshold value is gradually tightened along with the convergence of the model, so that the interior points conforming to the model are screened out more accurately. And finally, performing secondary sampling on the inner points and performing straight line fitting on an inner point set subjected to secondary sampling again to eliminate potential error inner points and further improve the fitting precision.

The invention relates to the technical field of power transmission lines of power systems, in particular to an adjustable anti-twist tension yoke plate. Through the unique design of the adjusting rod group, the extension and retraction amounts of the two tension-resistant hanging heads in the right-angle direction of the right-angle connecting rod can be synchronously adjusted, so that the relative angle between the two tension-resistant hanging heads can be continuously and accurately changed. Therefore, the yoke plate can flexibly adapt to complex actual working conditions such as different line steering angles and elevation differences, the universality of the yoke plate is greatly improved, and the application range of the yoke plate is greatly widened. Elastic constraint is applied to rotation of the triangular yoke plate through a constraint piece such as a hook spring or a spring abutting rod which is arranged between the tension-resistant hanging head and the triangular yoke plate. According to the design, the line can be allowed to slightly deflect in a reasonable range to release stress, excessive torsion or continuous single-side torsion caused by wind power and the like can be effectively inhibited, the problems such as wire torsional pendulum and uneven yoke plate stress caused by excessive torsion or continuous single-side torsion are fundamentally avoided, and the service life of the line hardware fitting and the wire is prolonged.

The invention relates to the technical field of hydrological data reorganization, in particular to a water level flow relation fitting method based on an LSM-OF model. The method comprises the following steps: performing regression analysis on actually measured flow by using a least square method (LSM), and selecting and matching an optimal polynomial fitting equation to predict a water level flow relation curve; linear fitting is carried out on the overall sample through an orthogonal function (OF) model, and a final curve is determined; then performing alignment precision inspection and three-item inspection of symbol, line adaptation and deviation; and finally verifying the extension curve through manual alignment and analyzing errors. The method combines the advantages of LSM and OF composite models, and improves the fitting precision and stability. The whole process can be automatically completed through a computer, manual subjective errors are avoided, the working efficiency is improved, the method is suitable for stable water level flow relation fitting of different hydrological stations, efficient and accurate technical support is provided for hydrological monitoring and hydraulic engineering decision making, and wide practicability and innovativeness are achieved.

The invention discloses a ship water gauge scale line fitting algorithm, and relates to the technical field of ship water gauge scale calculation, and the method comprises the steps: obtaining a ship water gauge region image through an image collection device to extract a measurement point coordinate, and building a mapping relation between a pixel position and a physical draft; a weighted least square method is adopted to perform nonlinear curve fitting, a weight coefficient is calculated based on a local neighborhood standard deviation, a polynomial order p is dynamically adjusted according to an adjusted decision coefficient, and the decision coefficient is iteratively optimized to improve the balance between amplitude and model complexity. And the system repeatedly corrects model parameters through a dynamic verification mechanism of the residual sum of squares and a preset threshold value, and finally an accurate water gauge scale fitting curve is generated. The method effectively solves the problems that traditional manual observation is prone to environmental interference and large in measurement error, high robustness is kept in a complex water area environment, and reliable data support can be provided for the fields of ship load evaluation, channel safety management and the like.

The invention discloses an airport pavement plate automatic synthesis method comprising the following steps: S1, using a deep learning model to identify an airport pavement image, and segmenting a pavement slab seam area; s2, extracting pavement slab seams through expansion, refinement and Hough transform modes, fitting corresponding line segments, and obtaining intersection point coordinates according to the fitted line segments; s3, after coordinates of all the intersection points are obtained, the intersection points are supplemented and corrected according to the distance relation; and S4, filtering the intersection points, and fitting the airport plate according to the filtered intersection points. The method comprises the following steps: firstly, extracting a mode of extracting intersection points of transverse and longitudinal slab joints according to a slab joint recognition result, extracting plate corner points, then performing completion according to an extracted corner point result, performing intersection point filtering after completion, and fitting an airport plate according to the filtered intersection points, so that the airport pavement plate fitted by adopting intersection point information is more accurate than a method of searching the intersection points through straight line fitting, and the accuracy of the airport pavement plate fitting is improved. The edge of the plate is better attached, and an airport management unit can conveniently and efficiently manage the airport pavement.

The invention relates to the technical field of wafer detection, and provides a wafer positioning method, device and equipment and a storage medium, the method carries out circle fitting and straight line fitting through a plurality of contour point coordinates, the more the contour point coordinates participating in fitting are, the higher the positioning precision is, and parameter verification and correction can be carried out through multi-contour point fitting of a circle or a straight line. The precision of the fitting circle and the fitting straight line is higher; meanwhile, the image range for collecting the coordinates of the contour points can be very small, so that the image pixel precision is higher, the fitted circle center coordinates and positioning edge straight lines are more accurate, and the positioning precision and accuracy of the target wafer are improved.

The invention discloses a railway track vertex cloud data extraction method and system based on deep learning. The method comprises the following steps: classifying track point cloud data by using a point cloud network enhanced multi-scale classification model to obtain a track key component point cloud classification data set; rail head point cloud data are extracted from the rail key component point cloud classification data set, center line fitting is carried out, a rail head center line is generated, and a reference point is selected on the rail head center line; a rolling window method is adopted, and a plurality of slices are generated along the rail head center line according to the reference points; and carrying out rail top point extraction on the plurality of slices to obtain a continuous rail top coordinate point set. The system comprises a data classification module, a rail head center line generation module, a slice generation module and a rail vertex extraction module. The rail top data extraction efficiency can be improved, the data accuracy and the rail safety are ensured, and scientific maintenance and management of the railway rail are facilitated.

The invention relates to the technical field of automatic driving, and discloses a lane line fitting method, device and equipment and a medium, and the method comprises the steps: obtaining a lane image; extracting a lane line graph with a preset length from the lane image; taking points from the lane line graph at equal intervals to obtain a plurality of lane line fitting point positions; fitting and calculating a current lane line equation by using the lane line fitting point; and controlling the vehicle to run based on the current lane line equation, returning to the step of acquiring the lane image when the vehicle runs to a preset position, and fitting the lane line equation of the next lane line with the preset length. On the basis of an original lane line fitting scheme, optimization is carried out only through the principle of distance estimation and equidistant point taking, under the condition that an algorithm and an architecture are not changed, the weight value of fitting lane line data at the far end is particularly ensured, the stability of a finally-calculated curve result is ensured, and the method is suitable for being applied to a vehicle. And the far-end error of the lane line fitting result is reduced.

The invention discloses a lane line fitting smoothing method, system and device and a storage medium. The method comprises the steps that multiple pieces of geometry node information in a planView field corresponding to a target road ID are read from a simulation high-precision map opendrive file; determining a plurality of simulation lane line coordinate points and a plurality of simulation yaw angles corresponding to the target road ID according to the plurality of pieces of geometer node information; processing the plurality of simulated lane line coordinate points and the plurality of simulated yaw angles through a fitting function to obtain a plurality of lane line fitting coordinate points and a plurality of fitting yaw angles; and realizing lane line fitting smoothness corresponding to the target road ID according to the plurality of lane line fitting coordinate points and the plurality of fitting yaw angles. According to the method, the purpose of smoothing the coordinate points of the lane lines of the high-precision map is achieved through the fitting function, and the problem of snakelike vehicles in the automatic driving simulation test process is solved.

The invention provides a ship draught load line identification method based on machine vision, which comprises the following steps of: (1) acquiring a ship shot image, (2) preprocessing the obtained images of a prow, a midship and a stern water gauge areas, expanding the midship water gauge areas, and obtaining the position of a load line through preprocessing and Hough circle detection; (3) carrying out water gauge character recognition on the pre-processed water gauge area image; (4) inputting the ship image into a key point detection model to detect ship waterline key points; (5) based on the ship waterline key points, performing line fitting by adopting a least square method to obtain a ship waterline; (6) respectively comparing ship waterlines of the bow, the middle and the stern with ship load identification positions, if the ship waterlines are higher than the ship load identification, judging that the ship is overloaded, and if the ship waterlines are lower than the load line, judging that the ship is not overloaded; (7) if it is judged that the ship is overloaded, draught values of a prow water gauge, a midship water gauge and a stern water gauge of the overloaded ship are calculated respectively.

The invention discloses a lane center line confirmation method for avoiding mistaken direction turning at an intersection in an intelligent navigation mode. According to the confirmation method, firstly, effectiveness and smoothness judgment is carried out on left and right side lane lines respectively, and a quantitative basis is provided for decision making; and then, based on a judgment result, according to a preset decision logic comprising four modes of double-side fitting, left-side single-side fitting, right-side single-side fitting and non-following line control, adaptively selecting a center line fitting mode. According to the technical scheme, the system can effectively screen and utilize reliable lane line information in a complex intersection environment, or give up line following in time when the lane line information is not suitable, so that the problem that a vehicle mistakenly turns the direction due to the fact that sensing information jumps or is wrong is fundamentally solved, and the driving safety of the vehicle is improved. And the transverse control safety and the system robustness during crossing are obviously improved.

This invention relates to the field of autonomous driving technology, and discloses a lane line fitting method, apparatus, electronic device, and storage medium. The method involves acquiring a lane line dataset at the current moment; this dataset includes the position of each sampling point among multiple sampling points located on the lane line; if the slope value of any two adjacent sampling points in the lane line dataset is greater than or equal to a first preset threshold, segmentation points are determined from the lane line dataset, and then a target lane line dataset is determined. Based on the target lane line dataset at the current moment, the vehicle motion state at the current moment, the vehicle running state at historical moments, and the predicted lane line state quantity at the current moment, an extended Kalman filter is performed to obtain the target lane line state quantity at the current moment; the target lane line at the current moment is determined based on the target lane line state quantity at the current moment. This invention provides a lane line fitting method with high accuracy and reliability in the fitting results.

The invention discloses a deflection calculation method and system for automatically identifying casing deformation, and relates to the technical field of engineering application. The method comprises the following steps: acquiring initial point cloud data of a sleeve, and preprocessing the initial point cloud data of the sleeve; constructing a casing deflection calculation model, wherein the casing deflection calculation model comprises a three-dimensional space straight line fitting module, a primary rotation module, a secondary rotation module, a deflection parameter adjustment module and a deflection calculation module; and performing casing deflection calculation on the preprocessed initial point cloud data of the casing by using a casing deflection calculation model, and outputting a calculation result. By means of the method and system, automatic recognition of the deformation end point and the datum reference point can be achieved in engineering casing deflection calculation, the casing deflection calculation efficiency is improved, the problem that point selection is difficult is solved, and input of manpower and material resources is reduced.

A processor-based compressed memory system includes a memory partitioning circuit for dividing a memory region into data regions with different priority levels. The system also includes a cache line selection circuit for selecting a first cache line from a high-priority data region and a second cache line from a low-priority data region. The system further includes a compression circuit for compressing the cache line to obtain a first compressed cache line and a second compressed cache line. The system also includes a cache line encapsulation circuit for encapsulating the compressed cache line such that the first compressed cache line is written to a first predetermined portion of the candidate compressed cache line, and the second cache line, or a portion of the second compressed cache line, is written to a second predetermined portion of the candidate compressed cache line. The first predetermined portion is larger than the second predetermined portion.

The application discloses a centrifuge linear distortion correction method based on WIA-FA wireless communication, and the PID mode is adopted to form a closed loop control by using a frequency converter speed regulation and a Hall sensor speed measurement in centrifugal equipment design. By further optimizing the algorithm, the influence of the linear distortion of the control link on the system is eliminated, the problem that the set value deviates from the actual value is solved, the simulation loop is corrected by implementing the broken line fitting mode, and the control precision and the control performance are effectively improved. When metering, analog calibration is changed into digital calibration, and operation becomes simple. The centrifuge is provided with a WIA-FA communication module, the WIA-FA communication module is used for connecting the centrifuge to a WIA-FA wireless network, working parameters and result records are transmitted through the WIA-FA wireless network, data security can be realized, and leakage of secret data is avoided.

The application is a visual SLAM image line segment extraction method based on approximate line segment merging. Firstly, the CannyLines algorithm is used to perform edge detection on the image to obtain all pixel chains. Then, the RANSAC algorithm is used to perform line fitting on each pixel chain to extract line segments in the image. Finally, approximate line segments in all line segments are judged and merged. For the new line segment after merging, if the angle difference between the new line segment and the long line segment before merging is within a reasonable range, the new line segment after merging is retained; otherwise, the new line segment after merging is not retained, and the two similar line segments before merging are reset to continue traversing the remaining line segments. The method uses the approximate line segment merging strategy to merge the broken short line segments into longer line segments, and merge the approximate line segments into one line segment, thereby reducing the short and redundant line segments, improving the feature matching accuracy in the visual SLAM process, and reducing the time consumption of feature matching.

The application discloses a kind of ship slotting V-type groove weld parameter extraction method and system, the method includes: using the statistical filtering method based on percentile to eliminate abnormal points, and based on neighborhood z coordinate range realizes positive side weld point cloud separation;Then for the geometric characteristics of two kinds of structures of blunt edge V-type weld and butt V-type weld, rectangular surface recognition algorithm and boundary detection algorithm are designed respectively, accurate separation and boundary positioning of groove point cloud are realized;Finally, the adaptive extraction of groove angle parameters is completed by fusing RANSAC straight line fitting and endpoint method.The application can be suitable for the above two kinds of structures simultaneously, can provide accurate groove geometric parameters for ship welding robot, effectively improve the automation welding level of ship and marine equipment.

The invention relates to a queuing order detection method and apparatus, an electronic device and a medium. The method comprises the steps of obtaining a real-time video of a team in a queuing process; identifying a figure image in each frame of image in the obtained real-time video by using the constructed deep learning neural network to obtain position information of all people in each frame of image; performing straight line fitting on the position information of the owner in each frame of image to obtain a team fitting straight line; acquiring the vertical distance between the position information of each person in each frame of image and the team fitting straight line; when the vertical distance between the personal position information and the fitting straight line in the team is out of the threshold range, an alarm is given out for reminding, and non-contact intelligent monitoring on the queuing order of the crowd is realized; the recognition accuracy of targets such as personnel is improved; through deep learning, when position information confirmation is carried out, identification is carried out through a deep learning neural network, a certain self-learning capability is possessed, and adaptability is stronger.

Embodiments of the present disclosure provide a method for calibrating a lawnmower, including: collecting a preset number of position data of the lawnmower moving relative to a charging station; performing straight line fitting using the preset number of position data; and determining, if the preset number of position data fits a straight line, an orientation of the charging station based on a slope of the fitted straight line. Accordingly, embodiments of the present disclosure may accurately determine the orientation of the charging station and has the advantages of high calibration accuracy and low calibration cost.

The application discloses a steel structure welding method, and relates to the technical field of 3D visual welding, and comprises the following steps: step S1, scanning point cloud data of a steel structure; step S2, based on the scanned data in step S1, a random sample consensus method is used to find a plane; step S3, according to a visual coordinate, a normal line of the plane obtained in step S2 is unified; step S4, a boundary between planes is calculated according to the plane obtained in step S2; step S5, a nearest neighbor algorithm is used to search for the nearest neighbor points of each two groups of boundaries in step S4, and a common boundary is formed; step S6, straight line fitting is performed on the common boundary obtained in step S5, and end points are extracted as welds; and step S7, path planning is performed based on a distance method. The welding method provided by the application automatically solves the plate plate welding problem in a steel structure, uses a 3D visual system to identify welds, automatically plans a welding path, saves labor cost, improves welding precision stability, and shortens a welding cycle.

The application relates to the technical field of automobiles and discloses a lane line fitting method, an electronic device and an automobile. The lane line fitting method comprises the following steps: acquiring image data; according to the order of point sets, calculating the average change rate of the slope and / or the approximate average curvature of every three adjacent points in the image data; according to the average change rate of the slope and / or the approximate average curvature, dividing the image data into a plurality of point sets to determine a plurality of line segments; performing polynomial fitting on the plurality of line segments to obtain a lane line corresponding to each line segment; after obtaining the lane line corresponding to each line segment, connecting every two adjacent line segments based on a Bezier curve to determine a lane line corresponding to the image data. According to the application, the point sets are divided into a plurality of line segments, the segments are polynomially fitted, and then the adjacent two line segments are connected based on the Bezier curve, so that the accuracy of lane line fitting can be improved, the smoothness of the lane curve can be ensured, and the display effect of the lane line can be improved.

The present application relates to a dimming method based on straight line fitting and curvature adjustment, including: obtaining a PWM configuration value, and dividing a plurality of fitting intervals based on its possible value range; judging the fitting interval in which the PWM configuration value is located based on the first part of the content; when the PWM configuration value is other than its maximum value and the fitting interval in which the PWM configuration value is located is the first fitting interval, obtaining a straight line fitting result based on the PWM configuration value and the fitting interval in which the PWM configuration value is located; the first fitting interval is an interval starting with the minimum value of the PWM configuration value; obtaining an initial value of the number of adjustment times based on the second part of the PWM configuration value; when the initial value of the number of adjustment times is not 0 and the fitting interval in which the PWM configuration value is located is a fitting interval other than the first fitting interval, performing a first stage adjustment on the straight line fitting result. The present application also relates to an electronic device.

Disclosed in the present invention are a lane line fitting method and apparatus, and a device and a storage medium. The lane line fitting method comprises: on the basis of vehicle pose information, acquiring a lane line profile point set in a vehicle body coordinate system; determining a second derivative of each lane line profile point on the basis of an arrangement sequence of lane line profile points in the lane line profile point set, and determining segmentation points in the lane line profile point set on the basis of second derivatives; fitting a curve between adjacent segmentation points as an initial lane line; and performing smoothing processing on initial lane lines to obtain a final lane line. The technical solution in the embodiments of the present invention improves the accuracy and smoothness of a fitted lane line.

The invention provides a passenger line positioning method and system based on multi-source position fusion, and the method comprises the steps: obtaining the driving positioning data of a passenger car in real time, constructing at least one driving curve based on the driving positioning data, the driving positioning data comprising data of a plurality of positioning modes, each driving curve corresponds to one positioning mode; extracting a railway line where the passenger car is located and position points on the driving curve, and constructing a position point set; performing line fitting based on the position point set to obtain a fitted line; in the driving process of the passenger car, whether the positioning signal is lost or not is judged in real time, if the positioning signal is lost, a predicted driving point is calculated based on the current fitting line, and after the positioning signal is received again, the position of the predicted driving point is corrected. According to the scheme, combined positioning of multiple positioning modes is realized, so that the positioning precision of the combined positioning system is improved, and a more reliable and more accurate solution is provided for train positioning in a complex environment.

The application provides a start-stop machine monitoring method and system based on multi-modal data fusion. A gray weighted straight line fitting method is used to obtain a first image start-stop machine result, and a video classification model is used for processing to obtain a second image start-stop machine result. An audio classification model is used to process audio information to obtain an audio start-stop machine result. A pulse signal is used to obtain speed information, and the speed information is used to obtain a speed start-stop machine result. The multiple start-stop machine results are fused according to weights to obtain a target device start-stop machine result. In the scheme, the start-stop machine result of the device is determined by using multi-modal data fusion, the defect that the accuracy of a single algorithm is not high is reduced, the monitoring is more timely and accurate, and predictive maintenance is facilitated.

The embodiment of the invention provides a degree detection method and system based on pressure gauge occlusion, and the method comprises the steps: carrying out the occlusion processing of an original image of a pressure gauge, and obtaining a processed image; performing dial scale and pointer segmentation on the processed image to obtain a first segmentation result; performing fusion processing of a plurality of dial regions on the first segmentation result to obtain a fused dial region; performing circle center fitting on the fused dial plate area to obtain a circle center position of the pressure gauge; performing pointer straight line fitting on the first segmentation result to obtain a pointer direction; and determining the scale number of the pressure gauge based on the pointer direction and the circle center position. According to the method, even if the pressure gauge is shielded and reflected, the scale number of the pressure gauge can still be identified with relatively high precision.

The application relates to the technical field of coplanarity detection, in particular to a nut post coplanarity detection method and a detection system, which comprises the following steps: analyzing the discrete characteristics of three-dimensional coordinate data and angle data of the same bit sequence on all circle threads to obtain discrete characteristic values of each bit sequence; obtaining the collinear deviation of each bit sequence based on the deviation generated by straight line fitting of the three-dimensional coordinate data of the same bit sequence on all circle threads; analyzing the deviation between the fitting straight line and the fitting curved surface corresponding to two adjacent bit sequences based on the difference and distribution between the collinear deviations of each adjacent bit sequence to obtain the trajectory continuity between each adjacent bit sequence; analyzing the distance change characteristics and rotation change characteristics between the three-dimensional coordinate data of the thread points of all adjacent bit sequences on all circle threads to obtain the thread coplanar stability of the nut post, and obtaining the coplanarity detection result of the nut post. The application aims to improve the accuracy of the coplanarity detection result of the nut post.

The invention discloses a table automatic identification and structured conversion method and device, and the method comprises the steps: extracting elements and element position information in a document page, and the elements comprise texts, lines and images; determining a table candidate area in the document page according to the text density, the line distribution and the image edge intensity of the document page; performing isolation processing on the images according to the overlapping degree of each image and the table candidate region and the image type; generating a table frame based on line fitting in the table candidate region, and performing merging cell detection based on the table frame to determine a logic relationship between cells; according to the logic relation of the cells, the positions of the texts and the positions of the images which are not isolated, the texts and the images are filled into the corresponding cells to generate structured table data, high-precision recognition and logic restoration of a complex table structure are achieved, interference elements can be intelligently distinguished and isolated, and the recognition efficiency is improved. And outputting structured table data with complete semantics and high quality.

The invention discloses a lane line fitting method. The method comprises the following steps: screening an original lane line point set to determine a first lane line point set; performing lane line fitting processing according to the first lane line point set to determine an initial fitting lane line; and performing compensation processing on the initial fitting lane line, determining a target lane line point set, and performing lane line fitting according to the target lane line point set. Thus, compensation processing is performed on the initial fitting lane line obtained through screening and fitting processing, the problems of line breakage and local missing possibly existing in the initial fitting lane line are reduced to a certain extent, and the completeness and continuity of the lane line are recovered by supplementing the missing lane line, so that the accuracy of the lane line is improved. The target lane line point set has time sequence continuity and space consistency to a certain extent, so that the requirements of vehicle path planning and driving control for high-quality lane line data in automatic driving are met to a certain extent, and the effectiveness of functions of an automatic driving system is guaranteed.

This invention provides a method and system for cargo positioning in an automated storage and retrieval system (AS / RS). The method includes acquiring point cloud data of stacked goods; preprocessing the point cloud data to obtain preprocessed point cloud data; performing iterative plane fitting on the preprocessed point cloud data to obtain a fitting plane; projecting the preprocessed point cloud data onto the fitting plane to obtain a projected point cloud; extracting edges from the projected point cloud to obtain point cloud edges; performing line fitting and matrix determination based on the point cloud edges to obtain a transformation matrix; and outputting the coordinates of the target cargo based on the transformation matrix and the projected point cloud. This invention effectively improves the processing efficiency and accuracy of point cloud data by performing a series of processing steps on the original point cloud data, while effectively capturing the edge information of the cargo, thus improving the accuracy of subsequent positioning and recognition. A coordinate system is then established based on the boundaries, and the size and pose information of the target cargo are determined through affine transformation.