90 results about "Background subtraction" patented technology

The invention discloses an invading object detection method and device applied to a perimeter security system, and relates to the technical field of invading object detection.According to the invading object detection method and device, a background model is dynamically updated by combining adaptive background modeling with time sequence analysis, background stability is kept in dynamic environments such as illumination variation and leaf shaking, and the invading object detection efficiency is improved. Different types of background changes are distinguished through a Gaussian mixture model, and the coexistence condition of long-term static background and short-time dynamic change can be adapted; in the target detection stage, a front-and-back frame difference method and a background subtraction method are combined, a moving target is extracted by utilizing complementary characteristics of the two methods, in the target classification and behavior analysis stage, spatial morphological characteristics of the target are extracted, the motion trend of the target is analyzed and predicted in combination with a time sequence, and track prediction is performed by adopting Kalman filtering. Even if the target is shielded for a short time or moves slowly, the tracking stability can still be kept.

The invention is suitable for the technical field of artificial intelligence, and provides a TOF camera hardware-based personnel falling intelligent monitoring method and system, and the method comprises the following steps: collecting three-dimensional point cloud data of a monitoring region through a ToF area-array camera, carrying out the data preprocessing and background subtraction of the three-dimensional point cloud data, and obtaining the point cloud data of a human body; personnel existence detection and personnel static detection are carried out based on the three-dimensional point cloud data; performing posture recognition, performing normalization conversion on the human body point cloud data to obtain a human body depth map, and performing posture detection on key points of the human body depth map to obtain human body key point data; and predicting the human body key point data based on the trained LSTM model to obtain a person posture state, and when the person posture state is that the person falls down, generating early warning information. The method is wide in application range and suitable for personnel falling detection in public areas and private spaces, the point cloud data only comprises the attitude key points of the personnel, and personnel falling reasons can be known under the condition that privacy is not invaded.

The invention relates to the technical field of ocean structure monitoring, in particular to a method for monitoring the scouring degree of a pile foundation of an offshore wind power station through bubble tracing, which comprises the following steps of: 1, constructing a bubble feature data acquiring an underwater image, manually segmenting and selecting key bubbles, extracting contour features of the key bubbles and expressing the contour features by vectors, a Zernike moment is used for grouping according to shapes, and a bubble feature database is constructed; and 2, identifying underwater bubbles: obtaining an underwater background image, constructing a dynamic background, obtaining an image containing suspended particles, extracting a foreground main body through a background subtraction method, comparing contour features of the foreground main body with a bubble feature database, and screening out the bubbles. By introducing an innovative method combining image recognition, feature modeling and physical inversion, the key problems of bubble misjudgment, track loss, inaccurate flow velocity and the like in a traditional bubble tracing technology are effectively solved, and high-precision, low-cost and automatic monitoring of the scouring process of the offshore wind power pile foundation is achieved.

The invention provides a gesture recognition method and system for screen flying interaction, and relates to the technical field of gesture recognition, and the method comprises the steps: processing video data through employing a background subtraction algorithm, and obtaining a foreground region in the video data; extracting a foreground region in the video data by adopting human body posture estimation to obtain a hand key point set of each human body; constructing a hand skeleton model by adopting forward kinematics according to the hand key point set of each human body; utilizing the hand skeleton model to simulate the movement of a hand, and extracting a gesture area and an actual space position of each human body; according to the gesture area and the actual space position of each human body, by combining distance measurement and a collision detection algorithm, whether the gestures of different users are spatially overlapped and crossed or not is judged, the independent gestures and the interactive gestures of the users are distinguished, the problem of misjudgment of a conventional gesture recognition method in the gesture overlapping and crossing state is avoided, and the user experience is improved. Therefore, the accuracy of gesture recognition is improved.

The invention discloses a method for detecting SF6 gas leakage of GIS equipment. The method comprises the following steps: acquiring field images of the GIS equipment in real time through optical gas imaging equipment; a target detection algorithm based on a YOLOv8 model is adopted to identify and position the contour of the GIS equipment; identifying a potential SF6 gas leakage area through a background subtraction method and differential calculation; performing reverse tracking on the optical flow field of the SF6 gas leakage area through a streamline integral method, and determining a leakage point of the SF6 gas and a spatial position coordinate of the leakage point; determining the specific position of the leakage point by judging whether the leakage point is located at the edge of the contour of the GIS equipment and performing area expansion detection by taking the leakage point as the center; and dynamically marking and visually displaying the position of the leakage point in the constructed GIS equipment three-dimensional point cloud model. The method effectively solves the technical problems that in a traditional method, the positioning precision is low, the anti-interference capacity is weak, and the leakage position cannot be visually displayed, and safety monitoring of GIS equipment is achieved.

The embodiment of the invention provides an actor recognition method, system and device based on ViT gait analysis and a medium, and belongs to the technical field of gait recognition. The method comprises the following steps: acquiring behavior video data of a target object; performing background subtraction processing on the behavior video data to obtain a binary image of the gait of the target object; inputting the binary image into a feature analysis model, wherein feature analysis is constructed and formed based on Transform; performing attitude feature extraction through a double-path parallel multi-head attention module of the feature analysis model, fitting a feature weight of the attitude feature through a feature average fusion module, and outputting an embedded feature vector; and comparing the embedded feature vector with a preset feature vector, and identifying the identity of the target object according to a comparison result. The embodiment of the invention aims to improve the accuracy of performing actor identity recognition through gaits.

An inspection method performed by a computer for inspecting a display panel includes: obtaining an anomalous portion image that includes an anomalous portion of a pixel region of the display panel, the anomalous portion being acquired by performing image processing using a background subtraction method on an inspection image of the pixel region; generating, using a trained generative model, a label image from the anomalous portion image by converting a region indicating the anomalous portion into a region of a color corresponding to a fault mode of the anomalous portion; and determining, based on the color of the region in the label image, whether the fault mode of the anomalous portion has a possibility of being a seepage defect in which light is not emitted due to deterioration of a functional layer in the pixel region. The fault mode includes the seepage defect and a dark-dot defect.

The invention relates to an aero-engine tail jet infrared image background hierarchical differential elimination method, belongs to the technical field of infrared test data processing, and solves the technical problems that background elimination is tedious in processing flow, poor in experimental environment adaptability and difficult to consider both calculation speed and precision. The method comprises the steps of converting an infrared thermogram into a relative energy diagram, setting algorithm parameters, solving an energy difference sequence D, searching a background cut-off layer, removing discrete interference points of the background cut-off layer and obtaining a pure target image. The method is used for infrared stealth performance optimization and evaluation.

The invention discloses a video analysis-based early warning and monitoring method for children hyperactivity behavior and a storage medium, and the method comprises the steps: firstly, guaranteeing the comprehensive monitoring of children behaviors through employing a multi-channel video collection device, and providing a sufficient continuous data source for subsequent analysis; furthermore, the quality of monitoring data is ensured through the use of image noise reduction and segmentation technologies, and accurate motion features are effectively extracted through the combination of an optical flow algorithm and a background subtraction algorithm; further, the movement behaviors of the children are comprehensively analyzed by calculating behavior parameters such as movement amplitude, movement direction change and continuous movement time, and potential behavior abnormity is revealed; the multi-dimensional behavior feature vector obtained through behavior parameter analysis is compared with the standard template, the behavior type of the child is automatically recognized, early-stage symptoms of abnormal behaviors such as hyperactivity and the like are found in time, and a basis for early diagnosis and intervention is provided for behavior problems such as hyperactivity and the like of the child.

The present invention discloses a method and system for identifying interactive behaviors of people in post office scenes, belonging to the field of video analysis technology. The method utilizes background subtraction to determine if abnormal behavior is triggered in the unpacking area, then captures a video stream. The captured video stream image is input into a pre-trained UNet network model to extract the box and human hands in the foreground. Feature descriptors for the box and human hands are constructed by combining depth and visible light information to determine the interactive relationships between people. Finally, a pre-trained SVM classifier is used to generate a judgment result, achieving accurate recognition of interactive behaviors in post office scenes. The method has a strong inhibitory effect on complex background interference, a high recognition accuracy rate for unpacking and visual inspection behaviors, and excellent robustness. It can meet the supervision requirements of express delivery stations for staff, and contributes to improving the automation and modernization level of intelligent video surveillance systems.

The invention relates to the technical field of environment monitoring, in particular to an internet-of-things-based breeding environment monitoring system for pond turtles, and the system comprises a turtle movement trajectory tracking module which is used for collecting real-time images of an incubator, comparing pixel differences among continuous image frames to carry out background subtraction, and recognizing a moving foreground target. According to the method, the pixel differences between image frames are continuously compared, the geometric center point of the moving target is calculated, continuous recording of the moving tracks of the water tortoise individuals in the cultivation box is achieved, the moving area is gridded, the occurrence probability is calculated by counting the frequency that coordinates fall into all units, an objective data basis is provided for environment optimization, and the method is suitable for large-scale popularization and application. Meanwhile, multiple groups of temperature sensors are arranged at key positions such as a spawning area and a drying platform, multiple paths of environment sensing redundant numerical values are obtained, the state range is predicted according to a water body thermal inertia model, multiple paths of readings are updated and calibrated, deviation data are effectively recognized and eliminated, and the reliability of environment monitoring data and the fault tolerance of the system are improved.

The invention discloses a fan non-stop routing inspection blade tip triggering method, which comprises the following steps: S1, an unmanned aerial vehicle executes a fixed route to reach a blade tip waypoint, a single-point laser radar is adopted to measure and calculate the spatial pose of a fan blade in real time, whether the unmanned aerial vehicle triggers photographing within a preset time is judged, and if not, the unmanned aerial vehicle stops routing inspection; if so, calling a leaf tip perception compensation algorithm to calculate a new leaf tip photographing waypoint; s2, through a blade tip sensing compensation algorithm, realizing stable tracking and picture locking of the pan-tilt camera on the blade tip of the fan, and obtaining an image of the fan at a horizontal position through a background difference method; s3, calculating the proportion of the blade in the picture, and calculating the distance from the current waypoint position to the blade tip in the horizontal direction by combining the internal reference of the pan-tilt camera and the inspection distance; and S4, the unmanned aerial vehicle is controlled to fly to the new blade tip waypoint, and blade image capturing is executed. According to the scheme provided by the invention, a closed-loop mechanism is formed through the single-point radar, the compensation algorithm, the background difference and the waypoint offset calculation process, and accurate acquisition of the blade tip area image is completed for accurately calculating the target point again.

Image sensor, which includes the following: a pixel array including multiple pixels configured and functional to detect light from a scene, wherein the scene includes an object to be detected and a background image, wherein each pixel of the multiple pixels is configured to generate a new voltage signal in response to the intensity of light received by the pixel; a memory for storing digital values ​​corresponding to a predetermined voltage bandwidth around a prior voltage signal R of at least some of the multiple pixels corresponding to the light detected from the background image, wherein the voltage bandwidth defines a positive delta voltage +Δ and a negative delta voltage -Δ relative to the background voltage signal R; a sample-and-hold or track-and-hold module capable of sampling the new voltage signal corresponding to one of the several pixels selected; a digital-to-analog converter that generates a reference voltage R+Δ or R-Δ from the digital values ​​stored in the memory; a comparator that receives the new voltage signal sample value from the hold module and receives one of the reference voltages R+Δ or R-Δ for the selected pixel to compare it with the voltage signal sample value, wherein the comparator is configured to produce a high-voltage output signal if the voltage signal sample value is greater than the reference voltages R+Δ or R-Δ, and to produce a low- or zero-voltage output if the voltage signal sample value is less than the reference voltages R+Δ or R-Δ; a two-bit register containing a most significant bit (MSB) and a least significant bit (LSB), wherein the two-bit register provides a two-bit output signal; and a logic module that receives the voltage output from the comparator, wherein the logic module is configured and functional as follows: Selecting the reference voltage R+Δ to be supplied to the comparator, and setting the MSB to a logic "0" in response to a low-voltage output signal from the comparator or to a logic "1" in response to a high-voltage output signal from the comparator; and then Selecting the reference voltage R-Δ to be supplied to the comparator and setting the LSB to a logic "0" in response to a low-voltage output signal from the comparator or to a logic "1" in response to a high-voltage output signal from the comparator; a background subtraction module configured and functional to receive the two-bit output signal from the two-bit register for the selected pixel and, based on the two-bit output signal, to identify the selected pixel as detecting light from a scene that is different from the light detected by the same pixel in the background image; and a processing module for generating an output image that includes the selected pixel identified by the background subtraction module.

The invention provides a method and system for measuring the side deformation degree and the girdling depth of a capacitor, and relates to the technical field of intelligent quality inspection, and the method comprises the steps: carrying out the background subtraction and image binarization of a side image of the capacitor, so as to obtain a binary image of the capacitor; carrying out segmented detection on the capacitance binary image by adopting a slope and curvature combined mode to obtain wave crest information and wave trough information of a side surface deformation area and a girdling area; and performing side deformation degree measurement according to the wave crest information and the wave trough information of the side deformation area, and performing girdling depth measurement according to the wave crest information and the wave trough information of the girdling area so as to obtain a side deformation degree measurement result and a girdling depth measurement result. The side deformation degree and the girdling depth of the capacitor are measured based on the machine vision technology, and the problems that the side deformation degree and the girdling depth of an existing capacitor are high in measurement cost and poor in measurement precision are solved.

The invention discloses a fire fighting access occupation detection method based on multi-target tracking. According to the method, firstly, foreground targets are extracted through background subtraction and morphological processing, and then an independent life cycle management mechanism is established for each target by adopting a multi-target tracking algorithm based on intersection-to-parallel ratio IOU matching. By calculating the continuous existence time of the target and combining the spatial relationship between the target position and the preset no-parking area, the intelligent judgment that the alarm is triggered only when the continuous parking of the target in the area exceeds the set threshold value is realized. According to the method, the problem that the false alarm rate of a traditional area intrusion detection system is high is effectively solved, instant passing and illegal occupation behaviors can be accurately distinguished, and the accuracy and practicability of fire fighting access occupation detection are remarkably improved.

The present invention discloses a method for detecting the three-dimensional position of a target based on dual cameras and lasers, belonging to the field of position detection technology, and comprising the following steps: determining a coordinate system, adjusting the positions of a horizontal camera and a vertical camera, processing object occlusion relationships, determining the three-dimensional coordinates of the object, and detecting target motion. By providing two cameras and a laser rangefinder, the present invention utilizes the laser rangefinder, the computing modules within the horizontal camera, and the vertical camera to accurately calculate the coordinates of an object. The obtained coordinates are more accurate than those of previous technologies. Furthermore, when multiple objects are present within the detection area, the occlusion relationships between the objects can be determined. Background subtraction can also be used to determine whether the target object is in motion. The method has the functions of multi-target detection and tracking, greatly improving efficiency and better completing intelligent monitoring tasks.

The application discloses an infrared gas imaging detection method based on a filter array, and relates to the technical field of gas analysis. The method comprises the following steps: setting a filter unit array on a single infrared camera focal plane to determine the corresponding relationship between each filter channel and a pixel; determining a characteristic channel with strong absorption and weak absorption to other gases for each target gas, and constructing a channel-gas response matrix; dividing infrared radiation into multiple bands by using the array, collecting original multi-channel images on the same imaging surface, and deconstructing each channel image; calculating the normalized absorption of each channel after background subtraction and normalization, and combining the normalized absorption into an observation vector; performing multi-gas unmixing by using a non-negative least square method according to the response matrix, solving the component images of at least two target gases, and outputting the types, positions and distribution ranges of the target gases. The application can simultaneously separate the spatial distribution of at least two target gases, eliminate parallax and registration errors, and improve the accuracy and stability of multi-gas detection.

This invention discloses an adaptive adjustment method and system for a virtual environment, relating to the field of virtual reality technology. The method includes: performing background subtraction processing on a target image sequence when a user is experiencing a virtual environment; extracting detailed features from the target image sequence, and identifying key points using target anchor boxes based on the detailed feature information; determining the coordinates of three-dimensional key points based on the target key point information for user action behavior analysis; extracting a user eye image sequence from the target image sequence to determine eyeball image information, and analyzing the gaze direction based on the eyeball image information; analyzing the user's attention focus using image brightness distribution based on the gaze direction information; and adjusting elements of the virtual environment based on the user's action behavior information and user attention focus information. This invention enables more fine-grained virtual environment adjustment, improving the quality and naturalness of the user's immersive experience in the virtual environment.

The present invention is a motion target detection method based on the fusion of data distribution differences and multi-scale features. It combines a fast background subtraction algorithm with a foreground segmentation algorithm to perform motion target detection, so as to achieve the effect of not only finding the motion target but also accurately segmenting it. The present invention first uses the frame difference method and background subtraction method to detect the motion target, preliminarily extracts the motion features, and then uses a multi-scale foreground extraction network to perform foreground extraction. Finally, the feature results of the two are subjected to IOU calculation to obtain a binary mask of the motion target. Secondly, the present invention improves the multi-scale foreground extraction network, adds a channel attention mechanism to its decoder, and enables it to assign different weights to different channels of the feature map, remove the fused features and noise, and obtain a cleaner foreground. The method of the present invention was experimented on the mainstream dataset CDNet2014 for motion target detection. The results show that the algorithm can accurately detect moving targets in various scenarios and has good comprehensive performance.

The invention discloses a fixed scene real-time target counting system based on example driving, and the system comprises a cross-modal interaction module which receives a visual frame selection example and a natural language instruction to generate a unified example feature vector, and a lightweight feature extraction module which extracts a fixed scene image multi-scale feature map based on a post-distillation lightweight DINO backbone network. The space-time correlation processing module filters static interference and focuses on a dynamic target through an optical flow method and a background subtraction algorithm by utilizing the background constant characteristic of a fixed scene, and the real-time density map generation module normalizes a strategy for a priori optimization density map; and the edge computing optimization module performs edge device optimization deployment to reduce the computing power consumption and the storage demand of the embedded device. The method has the beneficial effects that multi-modal input processing, lightweight efficient feature extraction, accurate space-time target tracking, real-time density map generation counting and low-power optimization of edge equipment are realized, and the real-time performance, the accuracy and the deployment flexibility of the system are improved.

The present invention discloses an infrared thermal wave nondestructive testing system, comprising a testing table, a thermal excitation module, a thermal imaging device, a component to be tested, a computer, a time relay and a synchronous trigger; the thermal excitation module, the thermal imaging device and the component to be tested are respectively arranged on the testing table; the component to be tested is located on one side of the testing table, and the thermal excitation module and the thermal imaging device are located on the other side of the testing table; the thermal imaging device is facing the component to be tested; the excitation end of the thermal excitation module is aligned with the component to be tested; the computer is connected to the thermal excitation module via a time relay. The present invention also discloses an infrared thermal wave nondestructive testing method. The beneficial effects of the present invention are: through continuous excitation of the thermal excitation module, deeper defects can be effectively detected; and through the background subtraction-principal component analysis algorithm, the noise signal caused by the uneven surface of the component to be tested can be effectively eliminated, thereby improving the accuracy of quantitative detection of defect area.

The invention discloses an inland waterway traffic complexity evaluation method based on a radar sequence image, belongs to the technical field of intelligent monitoring of inland waterways, and aims to solve the problems of poor traffic situation perception real-time performance, low ship detection precision and insufficient dynamic interaction quantification in the prior art. Radar noise is removed through background subtraction and a gray region threshold value, a target and a background are separated, and accurate ship detection is achieved; kalman filtering and a Hungary algorithm are adopted to construct a continuous motion trail, an Euclidean distance cost function is utilized to distribute identification numbers, and the problem of number jump in shielding and dense scenes is solved; integrating relative distance, encounter angle and trend dynamic information, and quantifying ship interaction strength through a nonlinear function; and constructing an undirected weighted graph model, and realizing traffic complexity visual evaluation based on the symmetry of the adjacent matrix. According to the method, high-risk ship pairs can be marked in real time, accurate data support is provided for collision avoidance decision making and channel scheduling, and channel traffic management efficiency and safety are remarkably improved.

The present application belongs to the field of computer vision, and particularly relates to a video anomaly detection method, system and device based on scene classification. The steps of the present application method are as follows: step S1, performing gray processing on original video frames, using background subtraction method and frame difference method to extract foreground targets, and extracting pixel features through Double-Canny algorithm; step S2, using a pre-trained model to detect the number of people in the video frames and generate a heat map of the video frames; step S3, using K-means clustering algorithm to classify scenes of the video frames, and dividing the video frames into two categories of dense scenes and sparse scenes; and step S4, using an anomaly detection module to respectively perform anomaly detection on the dense scenes and the sparse scenes. The present application can select different network structures for anomaly detection according to scenes with different crowd densities, is better applied to complex real scenes, and achieves better anomaly behavior detection effect.

The present invention proposes a system and method for remote agent supervision of parking lots, aiming to improve the efficiency and safety of parking lot management through remote monitoring and automation technology. The system mainly includes image acquisition equipment, a remote agent center, a background subtraction module, a motion feature extraction module and anomaly detection module. The data processing module uses background subtraction and optical flow methods to pre-process image data to extract foreground and motion features, and combines anomaly detection algorithms to detect abnormal behavior and fire. The remote agent center receives and analyzes the processed data through the network, and combines deep learning algorithms to monitor and warn abnormal behaviors in real time, while providing remote emergency response suggestions to facilitate managers to take timely action. Through deep learning technology, the system achieves efficient abnormal behavior detection and emergency response, improving the safety and management efficiency of parking lots.

This invention discloses a visualization measurement method for solid-liquid phase change of electrically controlled solid propellants based on image recognition. The method is implemented using an electrode clamping device and includes synchronous control of image acquisition and laser illumination, background subtraction combined with adaptive threshold binarization, application of regional constraints and morphological image processing, extraction and tracking of phase change interface features, and statistical analysis of target parameters. This method enables continuous and intuitive optical observation of the solid-liquid phase change process, achieving high-fidelity visualization of the phase change process before combustion. Through the synergistic effect of laser directional illumination and image recognition algorithms, it effectively distinguishes the solid region, liquid molten region, and suspended particle region of the propellant. Candidate motion regions are segmented using background subtraction combined with adaptive threshold binarization, reducing light interference caused by laser illumination. This achieves effective identification and interface extraction of the main solid-liquid phase change region and weak phase change region, improving the accuracy of phase change morphology characterization.

The invention discloses a non-contact vital sign recognition and detection system, which relates to the technical field of vital sign monitoring, and comprises a time-sharing echo acquisition module for acquiring echo signals and constructing an original data matrix; the phase processing module is used for executing background subtraction and phase extraction processing on the original data matrix and resolving a phase signal; the vital sign separation module is used for processing the phase signal and generating a breathing waveform; the breathing event judgment module is used for converting the breathing waveform into a physical displacement waveform, and judging and generating an apnea early warning signal; the radar dynamic scheduling module is used for generating a radar switching instruction according to the calculated target position; and the power compensation module obtains the signal quality parameter and generates a power adjustment instruction. According to the invention, through cooperation of double radars and dynamic scheduling, global blind-area-free continuous monitoring is realized, obstacles can be penetrated and breath and heartbeat can be accurately separated by using an advanced signal processing method, and low power consumption and high environmental adaptability are realized while high precision is ensured.

The present invention discloses a radon measurement method based on time-stamped background subtraction, comprising: if there is a previous measurement, then at the end of the previous measurement, the average count per second value before background subtraction and the end time are recorded; otherwise, the average count per second value before background subtraction is recorded as 0, and the end time is the start time of the current measurement; after the current measurement starts, the time is recorded in seconds, and the background count to be subtracted at each time is calculated; after the current measurement ends, the background count to be subtracted calculated at each second of the current measurement is added to obtain a total background count; the total background count of the previous step is subtracted from the total count of the current measurement to obtain a total count after subtraction; the total count after subtraction is divided by the number of seconds of the measurement time, and multiplied by the efficiency coefficient calibrated by the instrument to obtain the actual radon concentration after subtraction. The present invention can directly perform the next measurement in the case of decay interference from the previous measurement, thereby restoring the true result, eliminating the purification waiting time, and improving work efficiency.

The present application discloses a method, device, and medium for detecting moving targets based on a feature mask and a YOLO model. The method comprises: performing image scaling on continuous frame images according to an image scaling algorithm to obtain a target continuous frame image; performing background extraction on the target continuous frame image according to a background subtraction algorithm to obtain a foreground image; obtaining a YOLO model including a feature mask generation module and a moving target detection module; inputting the foreground image into the feature mask generation module for image processing to obtain a target foreground feature mask; inputting the target foreground feature mask and the target continuous frame image into the moving target detection module for target detection to obtain a moving target detection result. The present application performs moving target detection on continuous frame images based on the foreground feature mask and the YOLO model, so that the background area of ​​the continuous frame image is masked out, and only the foreground area participates in the neural network operation, thereby improving the computing speed of the neural network running on the hardware terminal performing the moving target detection operation.

According to the automobile hub classification method and system based on machine vision provided by the invention, the working rhythm of a structural light source is designed, an industrial camera collects a plurality of images, a background subtraction method is utilized to obtain common features, namely a spoke window feature region, of a hub, the hub images are subjected to normalization processing, and a hub region is detected and positioned by utilizing a Hough circle; the area of the circular region of the hub is converted into a rectangle through polar coordinate transformation, and then multi-dimensional feature extraction and classification matching are carried out on a non-spoke window region. Multi-dimensional features including color, diameter, spoke number, spoke width, center hole number, gray level co-occurrence matrix and the like are extracted, and classification decision is carried out by adopting a hierarchical matching strategy. Hub geometric measurement, classification identification and template library self-updating can be realized. And requirements of high reliability, simple integration and the like of industrial vision are met.

The invention discloses a machine vision-based sundry road occupation detection method. The method comprises the following steps of: acquiring and preprocessing data; dual-mode differential detection: running a template differential channel and a background subtraction channel in parallel, calculating an absolute difference value between a current frame and a reference template by the template differential channel, and performing binarization processing and morphological closed operation to obtain a newly added static target area; the background subtraction channel dynamically models a background based on an MOG2 algorithm and separates a moving target; removing all pixels overlapped with the dynamic target mask in the newly added static target area through matrix subtraction operation, and outputting a static abnormal target image; target analysis; target tracking; and decision output. According to the embodiment, high accuracy can be achieved in various environments, the method can effectively distinguish temporary articles from illegal lane occupation, real-time alarm is supported, an efficient solution is provided for intelligent security and protection, and the method is suitable for intelligent supervision requirements of factories, fire fighting accesses and other scenes.