99 results about "Contour analysis" patented technology

The invention relates to a curved surface contour analysis method and related equipment for laser multi-axis linkage machining, and the method comprises the following steps: carrying out the curved surface reconstruction of a target curved surface workpiece based on a three-dimensional point cloud data set, and obtaining a digital curved surface model; performing shape analysis on the digital curved surface model to obtain a curved surface feature descriptor, and if the curved surface feature descriptor does not meet an expected geometric characteristic standard, performing spectral decomposition on the digital curved surface model based on the curved surface feature descriptor to obtain a contour feature spectrum; performing path planning on the contour characteristic spectrum based on a geodesic theory to obtain a processing track sequence; and performing kinematics solution on the processing track sequence to obtain linkage control parameters of each axis, and adjusting the linkage control parameters of each axis based on the expected geometric characteristic standard, thereby solving the technical problem that the processed curved surface workpiece cannot reach the expected geometric characteristic standard due to lack of an effective curved surface contour analysis method.

The invention relates to the technical field of machine vision, in particular to a precision part size automatic detection method and system based on machine vision, precision part images are collected through a high-precision industrial camera, part positioning is carried out, sub-pixel-level topological feature mapping is carried out on interested area images, and precision part size automatic detection is carried out. Comprising the steps of gray histogram equalization, gray morphological processing, edge detection and edge chain code tracking, construction of an edge point topological feature space, execution of sub-pixel subdivision, obtaining of an edge line through contour analysis of a feature distance and a feature angle, and double-constraint geometric reconstruction based on the edge line. The characteristic distance and the characteristic angle are used for rotation matrix conversion and geometric dimension calculation, a relation model of the geometric dimension and the actual dimension of the part is established, precise part dimension measurement is achieved through dynamic error analysis and compensation, the measurement precision is remarkably improved, the risk caused by unreliability of a single characteristic is effectively reduced, and the measurement accuracy is improved. And the measurement stability is improved.

The invention relates to the technical field of target detection, in particular to a search and rescue task-oriented unmanned aerial vehicle thermal imaging visual target detection method, which comprises the following steps of: acquiring multiple frames of thermal imaging images of an unmanned aerial vehicle, extracting regional thermal difference characteristics according to a window, marking a non-background region to generate a candidate set, and fitting and reconstructing a suspected thermal target contour. And analyzing the track and the thermal change rate, screening background interference, identifying jump abnormity, positioning the gravity center, and generating a target repositioning signal. According to the method, the heat value range and variance index sequence in the image area is constructed, the thermal anomaly area is judged in combination with the temperature baseline difference, background disturbance comparison is executed in combination with the direction vector of the coordinate trajectory in the multi-frame image and the thermal change parameter, the false detection probability caused by background noise is reduced, and the detection accuracy is improved. The target jump identification is carried out according to the inter-frame heat value and area change rate in linkage with the thermal isoline closure degree, the target discrimination accuracy in a shielding scene is improved, and the robustness of thermal target extraction in a complex search and rescue environment is integrally improved.

The invention provides an atmosphere furnace surge flask bubble monitoring system and method based on machine vision. The image acquisition module is used for acquiring a multi-dimensional video image in a target area, wherein the multi-dimensional video image comprises a motion state of bubbles in liquid, real-time data reading on an atmosphere furnace digital display controller and an accurate indication condition of a gas cylinder pressure reducing valve gas pressure pointer display area; the data processing unit carries out fine processing on the acquired video image; the characteristics of bubbles are highlighted; the boundary of the bubble is accurately determined; calculating the flow velocity of the bubbles by using an optical flow method, and obtaining an accurate result by analyzing the position change of the bubbles between adjacent frames; counting the number and size of bubbles based on contour analysis; and the analysis and alarm module performs correlation analysis on the bubble parameters and the environmental parameters, generates a relation curve, presets a threshold value, and triggers alarm when the parameters are abnormal. According to the invention, real-time dynamic detection and deep analysis of parameters of bubbles in the surge flask of the atmosphere furnace can be accurately realized.

The invention provides a camera offset detection method and system based on image segmentation, and belongs to the technical field of image processing, and the method comprises the steps: inputting a to-be-detected railway image into an image segmentation model, and obtaining a plurality of rail region contours; a target contour is determined from all the rail area contours, and the target contour is divided into a plurality of convex areas in the preset direction when it is judged that concave points exist in the target contour; determining a target area from all the convex areas, and performing straight line fitting on contour points in the target area to obtain a straight line to be detected; and when it is determined that the camera deviates based on a comparison result of the to-be-detected straight line and the reference straight line, alarm information of camera deviation is generated. According to the invention, through image segmentation and contour analysis, the rail boundary is accurately extracted and the camera offset is detected, so that the accuracy of camera offset detection is effectively improved.

The invention provides a calligraphy work automatic identification and evaluation method and system, and the method comprises the steps: collecting calligraphy pattern images of different calligraphers, fonts and styles, and forming a multi-dimensional labeling original data set; carrying out standardization processing on the acquired calligraphy images; extracting stroke-level manual statistical features by using edge detection and contour analysis based on the standardized sample, extracting high-dimensional deep features by using a convolutional neural network, and fusing to form a unified multi-dimensional style feature vector; and performing unsupervised clustering on the fusion feature vectors of all the samples, and establishing a high-dimensional style prototype library. Obtaining a multi-dimensional similarity vector of a newly input calligraphy image; performing semantic unification processing on the new sample; and performing real-time scoring output on the new sample by using the exclusive evaluation model. The method can efficiently and accurately identify and evaluate the calligraphy work, is high in adaptability, and can be widely applied to the fields of calligraphy teaching, calligraphy work evaluation, digital calligraphy management and the like.

The invention discloses an intelligent defect detection method and system for a stamping die, and the method comprises the steps: obtaining a stamping excess material image through preset azimuth parameters after a stamping process is completed, and the azimuth parameters comprise a collection angle and a space coordinate; dividing the stamping excess material image into a plurality of sub-region excess material images according to coordinate information of the positioning reference hole in the stamping excess material image; inputting each sub-regional excess material image into a perspective correction model, and outputting a sub-regional excess material image with a normalized size; and extracting local stamping contour features by using a contour analysis algorithm, and outputting a stamping deformation early warning signal by comparing geometric deviation values of the local stamping contour features and the standard stamping contour template and combining with a preset tolerance threshold interval. Real-time monitoring of the size and the burr problem of the stamping part is achieved through the plate excess materials, the detection precision and the production efficiency are remarkably improved, and manual intervention and the rejection rate are reduced.

The invention provides an AI vision-based coal cinder amount intelligent detection early warning method and system, and the method comprises the steps: synchronously collecting the surface feature information, thermal radiation feature and internal structure information of a slag hopper of a slag conveyor through a dual-spectrum camera, and obtaining a dual-spectrum image; pixel-level coal cinder segmentation is carried out on the double-spectrum image; based on the segmentation result, counting the pixel proportion of the coal cinder area, and converting the pixel proportion into the actual coal cinder total amount proportion; identifying the segmented coal cinder area by adopting connected domain analysis, dynamically adjusting a size judgment threshold value through contour analysis and geometric feature extraction in combination with the bearing capacity of the slag conveyor, and determining whether large coal cinder exists or not; when the actual coal cinder total amount proportion is larger than the preset threshold value or large coal cinder exists, the risk level is generated to trigger the multi-level early warning control action, the actual coal cinder total amount proportion and the large coal cinder are automatically recognized through double-spectrum fusion segmentation, and early warning is given out when abnormity occurs, so that the accuracy and the real-time performance of coal cinder amount detection are effectively improved.

The invention relates to the technical field of detection systems, in particular to a quartz sand impurity rapid detection system, which comprises an image processing unit for regularly shooting images on a conveyor belt and recording the images as logistics images, and determining a target area corresponding to each logistics image based on a coincident part; the impurity identification unit is used for identifying the material contour in the target area, analyzing the impurity type corresponding to the material contour, marking the material contour corresponding to the impurity as a target contour and determining the position of the target contour; the air injection control unit is used for analyzing and determining the air injection opportunity of each air injection blowing nozzle based on the position coordinates when the target contour is identified and marked in combination with the conveying speed of the conveying belt; and when the air injection opportunity corresponding to the target contour is output, analyzing the shape characteristics of the target contour to obtain a projection area and a thickness measurement value, and adjusting the air flow parameters of the air injection blowing nozzle in combination with the corresponding related impurity types. According to the invention, different types of impurities can be effectively distinguished and targeted elimination can be carried out.

The invention discloses an IC carrier plate residual film inspection method and system. The method comprises the following steps: acquiring a surface image of a to-be-detected IC carrier plate; preprocessing the surface image of the IC carrier plate to be detected to obtain a first detection image; performing contour analysis according to the first detection image to obtain a residual film contour; performing ellipse fitting according to the plastic film residue contour to obtain an edge curve; performing graying processing on the edge curve to obtain a gray histogram; performing analysis according to the gray level histogram to obtain a second detection image; carrying out pixel calculation according to the second detection image to obtain a detection image pixel; judging according to the pixels of the detection image, and if the pixels of the detection image are greater than the first pixel threshold value and less than the second pixel threshold value, judging that defects exist; and if the pixel of the detected image is greater than the second pixel threshold value, judging that a defect exists and carrying out re-sticking prompt. According to the method, the influence of ink and the color of the plastic package body on detection can be effectively eliminated, and the detection accuracy is improved.

The invention provides a microscopic image distortion correction and reconstruction method, system and device, and a storage medium, a preset multi-shape calibration glass slide comprising a regular grid glass slide, a concentric circle glass slide, an irregular curve glass slide and a multilayer depth glass slide; the method comprises the following steps: acquiring images of a multi-shape calibration glass slide under different visual fields, different multiplying powers and different focal planes through a microscope, quantifying geometric distortion and fuzzy characteristics of the images by combining edge detection, contour analysis and fuzzy measurement methods, and generating a distortion feature vector; constructing a point spread function model based on the distortion feature vector, and optimizing the point spread function model by using a convolutional neural network; and applying the optimized point spread function model to carry out deconvolution processing and geometric correction on the microscopic image, and finally obtaining a reconstructed clear image. According to the invention, geometric distortion and edge blur can be effectively corrected, and details and definition of the microscopic image can be recovered. The method has a wide application prospect in the fields of scientific research, clinical diagnosis and industrial detection.

The invention relates to a micro-channel plate surface shape automatic detection system and detection method, and the detection system is characterized in that a lead screw is arranged above a bearing platform, a quartz boat is nested on the lead screw, and the lead screw is connected with a motor; the quartz boat is provided with a clamping groove position for clamping a to-be-measured micro-channel plate, the rotary strip lamp is arranged on one side of the quartz boat and is used for irradiating the to-be-measured micro-channel plate to form projection, and the length of the rotary strip lamp is greater than the maximum size of the appearance of the to-be-measured micro-channel plate; the image acquisition and processing system is arranged on the other side of the quartz boat and is used for acquiring a projection image of the rotary strip-shaped lamp on the to-be-detected micro-channel plate and transmitting the image to the image processing system in real time; the image processing system realizes detection of deformation at different positions through color space transformation, binary analysis, contour analysis, line segment detection, gradient fitting-based accurate edge detection and projection deformation quantity deviation calculation. According to the invention, the detection efficiency and the detection precision are improved, and the micro deformation of the edges of various special-shaped micro-channel plates can be discriminated.

The invention discloses a workpiece contour projection extraction method and system based on ordered point cloud, and is applied to the technical field of three-dimensional precision measurement. The method comprises the following steps of obtaining high-precision ordered point cloud data of a target workpiece and performing preprocessing; geometric analysis is carried out through the three-dimensional visual point cloud model, and section parameters are defined; performing rapid gridding processing on the ordered point cloud data through an efficient triangulation algorithm; calculating to obtain an intersection discrete point set of the cross section and the triangular mesh; and establishing a section plane local coordinate system and implementing two-dimensional projection transformation to obtain the contour projection of the target workpiece. According to the method, high-precision, high-efficiency and automatic extraction of the section contour of the workpiece can be realized, the actual requirements of industrial field online detection and quality control are met, and the method can be applied to scenes such as part size detection, reverse engineering, quality control and contour analysis in industrial manufacturing.

The invention relates to the technical field of industrial big data, in particular to LED light bar dispensing quality detection equipment based on visual inspection, which comprises an image processing module, a contour analysis and judgment module and an edge division compensation module, converting the dispensing area image into a grayscale image by using an image processing algorithm, and separating a dispensing area from a background area by using a threshold segmentation method; the contour analysis and judgment module is used for judging whether the glue dispensing area has defects, less glue and more glue; the edge division compensation module adopts an edge division method to extract edge pixel points in the gray level image, if the edge pixel points in the dispensing area in the image processing module are different from the edge pixel points in the gray level image in coordinate, the edge pixel points in the dispensing area are adjusted, the image processing module provides basic segmentation, the contour analysis module realizes logic judgment, and the image processing module processes the edge pixel points in the gray level image. And the edge division compensation module corrects local errors.

Techniques are provided for implementing liquid tolerance for a touch device. A sensor array of the touch device is scanned to generate response signals. In response to a response signal exceeding a touch threshold, a signal profile analysis is performed. The signal profile analysis includes sorting the response signals according to ascending order of delta positions to generate sorted signals. An extended vector of the sorted signals is formed. The extended vector of the sorted signals is analyzed using a fitted curve. In response to a feature of the fitted curve satisfying a criteria, the response signal is reported as a touch event. In response to the feature not satisfying the criteria, the response signal is rejected as a false touch.

The utility model discloses a data acquisition device for contour analysis, which relates to the field of cable data acquisition and comprises a first acquisition part, a second acquisition part, a driving part, a supporting part and a communication module, the first acquisition part is used for acquiring diameter data of a circle of a cable to be detected, and the second acquisition part is used for acquiring contour data of a circle of the cable to be detected; the measuring positions of the first acquisition piece and the second acquisition piece are located on a first horizontal line, the driving piece is used for driving a to-be-measured cable to rotate by 360 degrees, the supporting piece is used for enabling the to-be-measured cable to be located on the first horizontal line all the time, and the communication module is used for uploading diameter data and contour data of a circle of the to-be-measured cable to the computer; the high-precision diameter instrument and the contourgraph are combined to measure the diameter data and the contour data of a circle of the cable to be measured respectively, and then the data are uploaded to the computer, so that the accurate contour of the circle of the cable to be measured can be analyzed, and the measurement precision of the contourgraph is improved.

A detector (110) for determining at least one material property of at least one object (112) is proposed. The detector (110) comprises: - at least one projector (116) configured to illuminate the object (112) with at least one illumination pattern (118) including a plurality of illumination features (120); - at least one first camera (122) having at least one first sensor element, the first sensor element having a matrix of first optical sensors, each first optical sensor having a photosensitive area, each first optical sensor designed to generate at least one sensor signal in response to illumination of the respective photosensitive area by a reflected light beam propagating from the object (112) to the first camera (122), the first camera (122) configured to capture at least one first reflected image comprising a plurality of first reflected features generated by the object (112) in response to illumination by the illumination features (120), the first camera (122) being arranged such that the first reflected image is captured in a first line of sight direction relative to the object (112); at least one second camera (124) having at least one second sensor element, the second sensor element having a matrix of second optical sensors, each second optical sensor having a photosensitive area, each second optical sensor designed to generate at least one sensor signal in response to illumination of the respective photosensitive area by a reflected light beam propagating from the object (112) to the second camera (124), the second camera (124) being configured to capture at least one second reflected image comprising a plurality of second reflected features generated by the object (112) in response to illumination by the illumination features (120), the second camera (124) being arranged such that the second reflected image is captured in a second line of sight direction relative to the object (112), the second camera being different from the first line of sight direction and the second line of sight direction; - at least one evaluation device (126) configured to evaluate the first and second reflected images, the evaluation comprising matching the first and second reflected features and determining combined material properties of the matched pair of first and second reflected features by analysis of their beam profiles; Equipped with.

This invention relates to the field of laser processing and automated control technology, and particularly to a laser heating system, including an equipment device and a control device. The equipment device includes a support platform, a transmission mechanism, a laser, and vision components. The control device includes image acquisition, contour analysis, error compensation, coordinate optimization, and pulse sending modules. The image acquisition module drives the vision component to acquire material images and transmits them to the contour analysis module; the contour analysis module calculates deformation parameters and sends them to the error compensation module; the error compensation module combines pre-stored mechanical errors to generate a compensation matrix and sends it to the coordinate optimization module; the coordinate optimization module calculates and outputs the target coordinates to the pulse sending module; the pulse sending module drives the laser component to move and commands it to emit light. This invention solves the positioning deviation caused by hardware errors and changes in material size, improving control accuracy.

The present invention discloses an automatic annotation method, device and storage medium, which can locate a first target object in unannotated image data according to a preset contour analysis model, determine an empty label corresponding to each first target object, quickly determine a target image in the unannotated image data according to the position information of the empty label, and can automatically annotate the target object corresponding to the single product image through feature point matching. The preset contour analysis model of the present invention is an identification model trained based on deep learning, and this identification model can well locate the first target object; based on the feature point matching between the single product image and the target object, automatic annotation is realized, so as to obtain annotation data, which can be used in the unsupervised assisted manual annotation of shop commodities, and can greatly save labor costs and time while improving the work efficiency of the detection task.

The invention discloses a limb protection position detection method and device, equipment and a medium, and the method comprises the steps: recognizing a dangerous region and limb protection in a monitoring video frame through a trained limb protection detection model; respectively extracting the contour of the dangerous area and the contour of the limb protection, and determining the shortest distance between the contour of the dangerous area and the contour of the limb protection; and determining whether the edge protection placement position is qualified or not according to the shortest distance. According to the method, accurate segmentation and classification of the edge protection and dangerous areas in the construction site are realized, the accuracy of safety monitoring is greatly improved, and meanwhile, the introduced contour analysis and distance calculation effectively assess whether the edge protection setting reaches the standard or not, so that the safety management level of the construction site is comprehensively improved.

The invention discloses a laser cutting path optimization method of laser cutting equipment, and relates to the technical field of cutting path optimization. According to the laser cutting path optimization method of the laser cutting equipment, geometric primitive data of a to-be-cut workpiece is obtained, contour analysis processing is carried out, and a contour geometric data set of the to-be-cut workpiece is extracted; cutting sequence planning processing is conducted on the contour geometric data set of the to-be-cut workpiece based on a genetic algorithm, and an initial cutting path of the to-be-cut workpiece is generated; multi-target collaborative optimization processing is conducted on the initial cutting path of the to-be-cut workpiece, and the optimized cutting path of the to-be-cut workpiece is obtained.According to the method, the optimized cutting path of the to-be-cut workpiece is verified, the optimized verification cutting path of the to-be-cut workpiece is generated, and therefore the machining efficiency is remarkably improved while the machining precision is guaranteed; therefore, the reliability of the cutting process is comprehensively improved.

A testing method and apparatus for unmanned aerial vehicle (UAV) production includes the following steps: S1, Operating condition construction: controlling the power system of the UAV under test to operate to a preset target speed range; S2, Multi-dimensional data synchronous acquisition: generating a synchronous trigger signal based on the real-time speed signal of the power system; using the synchronous trigger signal to control a strobe light source to illuminate the rotating parts, and acquiring a freeze-frame visual image of the rotating parts during the illumination; simultaneously, acquiring acoustic signals during the operation of the power system; S3, Feature extraction: performing contour analysis on the freeze-frame visual image to extract visual feature values ​​reflecting physical deformation; performing spectral analysis on the acoustic signal to extract acoustic signature feature values ​​reflecting the mechanical operating state; S4, Fusion judgment: inputting the visual feature values ​​and acoustic signature feature values ​​into a preset multimodal fusion model to calculate the comprehensive health index of the power system, and determining whether the product is qualified based on the comprehensive health index.

This invention relates to the field of safety monitoring technology, and more particularly to an intelligent monitoring system for highway tunnel construction safety. The system includes a data acquisition module, a contour analysis module, a feature fusion module, and a data compensation module. By acquiring images of the tunnel surface, dust concentration within the tunnel, and water vapor humidity, the system divides the tunnel into several sub-image regions. The system determines the unevenness and texture complexity of each sub-image region, calculates region-sensitive feature values, and uses the tunnel dust concentration and water vapor humidity, combined with the region-sensitive feature values, to determine whether each sub-image region meets preset conditions. The system also calculates data missing characterization values ​​to determine the modeling anomaly tendency of each sub-image region. Based on the modeling anomaly tendency and the data missing characterization values, the system determines the data acquisition method for each sub-image region. This invention improves the accuracy and efficiency of model building through comprehensive analysis, data acquisition, and compensation of the tunnel environment, thereby ensuring construction safety.

The invention discloses a metal wire rope image feature segmentation method, system and device, and relates to the technical field of metal wire rope defect segmentation, and the method comprises the following steps: collecting a wire rope image; analyzing an edge threshold value between the two strands of wire ropes based on the wire rope contours; analyzing and extracting contour edge intersection points based on the wire rope contour; analyzing an initial contour line of the wire rope image, and analyzing an initial boundary between the two strands of wire ropes based on the initial contour line; calibrating the initial boundary to obtain a final boundary, and dividing the wire rope image into different stranded rope areas based on the final boundary; extracting region features of the stranded rope region, analyzing a defect region, and segmenting specific defect points in the defect region; the metal wire rope defect segmentation method is used for solving the problem that the existing metal wire rope defect segmentation technology cannot ensure whether defect segmentation is effective and accurate due to the fact that the description of image features is not detailed enough and the division of regions is not accurate enough.

This invention relates to the field of visual inspection of label bonding quality, and discloses an intelligent inspection system for label bonding quality, comprising: a polarization excitation illumination module for projecting a circularly polarized light field onto a highly reflective curved substrate; a multi-dimensional polarization imaging module for capturing spatially interwoven polarization signals; a geometric contour analysis module for analyzing the geometric contour information of the substrate; a polarization state compensation matrix generation module for determining the local incident angle and generating a compensation matrix according to Fresnel's law of reflection; a polarization distortion correction module for correcting polarization distortion and outputting a full Stokes polarization vector flow; an interface stress field feature extraction module for extracting phase delay features; and a defect location and judgment module for identifying bubble or wrinkle defects. This invention utilizes phase delay features to characterize the surface deformation of the transparent label bonding interface, and combines this with a polarization state compensation mechanism to remove geometric interference from the curved surface, thereby achieving the identification of hidden bonding defects under highly reflective environments.

This invention provides a method and system for detecting minute defects in proton exchange membranes (PEMs) in fuel cells. The method includes acquiring an original image of the PEM to be detected, preprocessing the original image to obtain a preprocessed grayscale image, the preprocessing including at least grayscale conversion and resolution normalization, extracting full-image phase consistency features from the preprocessed grayscale image to generate a phase consistency feature map, wherein the phase consistency feature map characterizes the structural abrupt changes of pixels in the grayscale image, and then performing multi-scale residual enhancement processing based on the preprocessed grayscale image and the phase consistency feature map to generate a defect-enhanced image. Finally, adaptive threshold segmentation and contour analysis are performed on the defect-enhanced image to locate the defect region in the original image. This method can locate the defect region in the original image of the PEM, thus overcoming the problems in the prior art.

The invention discloses a glue path defect detection method based on deep learning and contour analysis, and the method comprises the following steps: obtaining a semantic segmentation mask of a glue path, processing the semantic segmentation mask through a morphological refinement algorithm, obtaining a skeleton image of the glue path, and carrying out the geometric feature fitting, calculating an intersection of the fitting geometric feature and a corresponding semantic segmentation mask connected domain as an initial mark, and performing watershed segmentation to obtain a glue path segmentation mask; morphologically refining the segmentation mask of each glue path to obtain a skeleton image of the embodiment of the glue path, searching an end point and a branch point of the skeleton image by using hit-miss transform to obtain a main skeleton of the glue path, and recording pixel coordinates of the main skeleton from the end point according to an eight-neighborhood sequence; calculating the width, length and track accuracy of the glue path; and processing the glue path segmentation mask, the main skeleton coordinate, the width, the length and the track accuracy, judging whether an abnormal value is generated or not, and realizing classification, positioning and grade quantification of glue path defects.

The invention provides a method and a device for detecting a moving object. The method comprises the following steps of: performing difference operation on two adjacent frames of images by adopting an inter-frame difference method to obtain a frame difference image; carrying out binarization processing and morphological processing on the frame difference image to obtain a binarization image; performing contour analysis processing on the binarized image to obtain the area of a contour circumscribed rectangular region of the moving object in the binarized image; dividing a contour external rectangular area in the binarized image into large block motion areas or small block motion areas, performing space-to-channel compression processing on the image corresponding to each large block motion area, and performing image splicing processing on the images corresponding to all the small block motion areas to respectively obtain images to be detected; and performing target detection by using the target detection model to obtain the center point position coordinates and category information of the moving object. According to the moving object detection method and device provided by the invention, the calculation amount of the target detection model can be reduced, and the moving object in a complex scene can be rapidly and accurately detected.

The invention provides a table tennis ball roundness detection system, an electronic device and a readable storage medium, and the method comprises the steps that a bottom light source is used for illuminating a table tennis ball, and light penetrates through the bottom of the table tennis ball and illuminates the whole surface of the table tennis ball. Through an image processing and contour analysis algorithm, an image of the table tennis ball under light source irradiation is captured and analyzed, and the contour of the table tennis ball is extracted from the processed image. And calculating the roundness index of the table tennis ball according to the contour information. The roundness detection is realized by comparing the difference between the contour and the ideal circle, and the calculated roundness index is used for evaluating whether the roundness of the table tennis meets the standard or not. The table tennis ball roundness detection system is full-automatic, improves the production efficiency, reduces manual intervention, and is suitable for large-scale production. External interference is solved through image processing optimization, and precision and stability are improved. And special equipment arrangement is combined with a high-resolution camera and a high-precision image processing algorithm, so that micron-sized measurement is realized, and the roundness qualification evaluation accuracy is improved.

The present invention relates to the field of remote control technology, and in particular to a scraper machine image recognition method based on image processing; the method is implemented by a data acquisition module, a camera module, a color feature analysis module, a texture feature analysis module, a contour analysis module, an image recognition output module and an intelligent management module; the color, texture and contour feature analysis of the scraper machine image are respectively performed by the color feature analysis module, the texture feature analysis module and the contour analysis module to output the scraper machine image recognition result, which can more comprehensively analyze the scraper machine image and improve the accuracy of the scraper machine image recognition result; the scraper machine is stopped by controlling the distance between the responsible employee and the scraper, which can avoid the responsible employee stopping the scraper machine in advance before reaching the position of the abnormal warning scraper, resulting in unreasonable downtime and further waste of production resources of the coal preparation plant; and the abnormal scraper machine can be repaired while maximally ensuring the working efficiency of the coal preparation plant.