72 results about "Contour matching" patented technology

Disclosed in the present invention is a salient contour matching-based method for target measurement in a severe imaging environment. The method specifically comprises: (1) acquiring a binocular image of a target; (2) establishing a global-local joint constraint-based background light estimation model, and removing a scattering effect of a medium in an imaging environment to obtain a restored left eye image and a restored right eye image; (3) learning an original image, and on the basis of a residual between a network reconstructed image and the original image, obtaining target localization prediction maps of the left eye image and the right eye image; and (4) respectively extracting contour lines of the target in the left eye image and the right eye image, constructing feature matching descriptors of contour points, performing stereo matching on the two sets of contour lines by minimizing matching cost, and performing three-dimensional reconstruction on the contour lines in light of calibrated intrinsic and extrinsic parameters to complete the measurement of a key size. According to the present invention, the key sizes of different targets in a severe environment can be accurately measured, thereby providing an effective solution for the problem of measuring the sizes of targets in a severe environment.

The invention belongs to the technical field of super high-rise building three-dimensional reconstruction, and particularly relates to a multi-source data fusion super high-rise building group live-action three-dimensional model construction method. According to the method, an initial three-dimensional model is generated through a series of processing such as aerial triangulation encryption and triangulation network construction based on multi-source image data, in the process of recognizing a fuzzy region and performing data supplementary collection, regions with texture loss and structure distortion in the initial three-dimensional model can be positioned, supplementary collection requirements are determined according to characteristics of different regions and a preset threshold value, and the recognition accuracy of the initial three-dimensional model is improved. The method comprises the following steps of: performing oblique photography on an unmanned aerial vehicle to acquire data in a supplementary manner, fusing the data with original data, extracting a building structure contour, matching high-resolution texture data, performing texture binding and processing and the like to form a building monomer model, and performing spatial position and texture fusion on the building monomer model and a process three-dimensional model to generate a regional three-dimensional live-action model. And finally, splicing and fusing the three-dimensional live-action models of all the areas to form a complete super high-rise building group live-action three-dimensional model.

The invention provides a culture symbol transmission method and system based on Sichuan opera facial makeup art patterns, and particularly relates to the field of facial makeup digital transmission. According to the method, multi-level modeling of a Sichuan opera facial makeup pattern from a pixel layer to a component layer and then to a semantic layer is realized by fusing image processing, component contour matching, image structure modeling and an image neural network technology; according to the method, main and auxiliary color block areas and component information in an image can be automatically identified and structurally stored, a spatial semantic relationship of the image is learned through a graph neural network, a structural semantic code is output, and finally a multi-dimensional cultural label index capable of being filed, clustered and classified is generated; the method effectively overcomes the limitation that in the prior art, only stays at an image level and is lack of structure and semantic modeling, enables the Sichuan opera facial makeup pattern to have machine-readable component structure representation and semantic feature representation, and lays a foundation for cultural inheritance and intelligent propagation.

The invention relates to the technical field of image recognition, in particular to a radiotherapy target volume recognition method based on a large language model, and the method comprises the following steps: collecting a radiotherapy target image and historical data, converting the target image into a grayscale image, separating a background, extracting a target plane contour, and cutting a target plaque image based on the contour. Texture analysis is carried out to generate target texture features, texture and contour information is combined, the pathological state of the target is speculated, a preset large language model is utilized to calculate the feature similarity between the pathological state of the target and historical data, a historical radiotherapy target set with similar pathological states is matched, and data with consistent historical contours are screened through contour matching. And corresponding radiotherapy parameters and volume information are extracted, and identification and analysis of precise radiotherapy target parameters are realized. According to the method, the automation level and the intelligent degree of target volume recognition are improved, the manual intervention requirement is reduced, and the recognition efficiency and accuracy are improved.

The invention discloses a logistics warehouse cargo storage method and system and a storage medium, relates to the field of logistics warehouse cargo storage, realizes intelligent warehouse management through multi-module cooperation, remarkably improves inventory monitoring and cargo scheduling efficiency, and improves the cargo scheduling efficiency based on video image recognition and contour matching technologies in combination with database information. Accurate inventory data is generated in real time, unregistered goods are effectively identified, manual inventory errors are reduced, goods flow indexes are quantified through a dynamic time decay model, and goods turnover rules are accurately reflected by combining weighted analysis of carrying proportion and quantity, so that data support is provided for scheduling decision making. Multi-dimensional factors such as environmental parameters, transportation distance and storage capacity are integrated, a callout-storage staged optimization model is established, environmental adaptability, storage safety and scheduling rationality are organically combined, manual intervention is reduced, the warehouse turnover efficiency is improved, the storage cost is reduced, and a full-process closed-loop intelligent warehouse management system is formed.

The invention relates to the technical field of image recognition, and discloses a lightweight system applied to label printing defect recognition. According to the system, the position of a target in a label printing image is recognized and a result is extracted by combining edge detection and a contour matching algorithm in a preprocessing stage, then, in order to improve the feature extraction efficiency and reduce the consumption of computing resources, a C-D-Conv module is constructed by using a mobile inverted residual bottleneck block, and the feature extraction efficiency is improved. In order to improve global information capture and local feature enhancement capability in image processing, an LA-LC-LM module mainly composed of self-attention, local convolution and MLP is constructed, in order to help a model to better process preliminarily extracted image low-level features in the later period, a dual-path collaborative hybrid attention mechanism DHAM is embedded in a network, and the algorithm is applied to image processing. According to the system provided by the invention, the Top-1 Acc and Param on a self-made data set Code-10 respectively reach 99.25% and 3.595 M, and the Top-1 accuracy on a public data set NEU-CLS-64 and the Top-1 accuracy on a reconstructed data set DAGM2007 * respectively reach 97.79% and 85.42%.

A computer-implemented, in particular user-guided, method for selecting a photographic image (F) for use in production control, wherein the method comprises the following steps: a) Receiving from a multitude of input images (E1,...,En) specifying an object to be captured (30) in a multitude of lighting settings, wherein the lighting settings are specified by different configurations of an RGB-W lighting unit (20) and include a white image (E0); b) Selecting at least one candidate recording (K1,...,Km) from the initial recordings (E1,...,En) based on a first selection criterion; c) Defining a template image section (A0) within the white image (E0); d) Generating at least one target image section (A1,...,Am) in the at least one candidate image (K1,...,Km) that corresponds to the template image section (A0); e) Applying at least one image processing algorithm, in particular contour recognition, blob analysis, region analysis, code analysis or model matching, with a first set of parameters and / or parameter values ​​to the at least one target image section (A1,...,Am) to generate processed candidate images (K'1,...,K'm); f) Selecting at least one preselection recording (V1,...,Vk) from the set of processed candidate recordings (K'1,...,K'm) based on a second selection criterion; g) Check whether a pre-selection recording (V1,...,Vk) exists that meets a final screening criterion and, if so, select such a pre-selection recording (V1,...,Vk) as the final recording (F); otherwise h) Repeating steps e) to g), wherein the at least one preselection recording (V1,...,Vk) is used as the at least one candidate recording (K1,...,Km) and in step e) a second set of parameters and / or parameter values, in particular specified by a user, is used;wherein at least one of the selection criteria depends on an evaluation result of at least one image analysis algorithm, namely contour recognition, wherein a collection of reference images is used for the evaluation of the at least one selection criterion, wherein contours are extracted from object edges of the reference images during contour recognition and stored as reference contours, which are searched for in the multitude of input images, wherein the method further comprises calculating a value that indicates a match with a reference contour and wherein, if the value exceeds a threshold, the area under consideration is regarded as a match, wherein an image is rated as good if a predefined number of matches are found and wherein the image is selected as at least one candidate image if the image is rated as good.

The embodiment of the invention discloses a texture image generation method and device, computer equipment and a storage medium, and belongs to the technical field of computers. According to the method, the texture image matched with the category and contour of the three-dimensional model can be quickly generated based on the grid data of the three-dimensional model, and an art engineer does not need to manually draw and generate the texture image, so that the generation efficiency of the texture image is greatly improved. The texture image is matched with the three-dimensional model in category and contour, so that the texture image can be ensured to be attached to the surface of the three-dimensional model, and the quality of the texture image is ensured.

The application discloses a kind of high-precision vector map automatic generation method, mainly according to laser point cloud intensity, geometric structure feature extraction lane marking, through ground filtering, ground, non-ground point cloud is segmented;Adopt block grating to convert three-dimensional point cloud into two-dimensional projection image;Using image filtering, edge extraction operator, dynamic adaptive threshold segmentation, morphological analysis and other processing extraction road marking pixel, based on point cloud image mapping relationship extraction marking point cloud;Using the point cloud contour matching method based on knowledge template library carries out marking classification.Based on deep learning convolutional neural network, road sign detection classification is carried out to road image, and the point cloud region of interest is established by image point cloud fusion;Using clustering screening candidate point cloud, based on principal component analysis carries out local projection, based on knowledge template library point cloud matching extraction traffic sign;Finally, based on GPS data, calibration, parameter fitting, vectorization, data association are carried out, and the construction of high-precision vector map is completed.

The application relates to the technical field of image detection, and discloses a scale-invariant contour matching method and device based on machine vision and a storage medium, the method comprising the following steps: extracting a target contour from a template and a query image and detecting key points; constructing a multi-scale contour context descriptor for each key point, the descriptor being composed of chord length ratios and chord angle features under multi-scale in a local neighborhood; performing feature matching, estimating scale and rotation transformation parameters according to chord length ratios and chord angles of a matched descriptor pair, and combining key point coordinates to calculate a translation parameter to generate a similarity transformation hypothesis; clustering all hypotheses as points in a high-dimensional parameter space to obtain candidate instances; for each candidate instance, fitting an accurate similarity transformation model and eliminating false matching by using a random sample consensus algorithm through matched point pairs associated with the candidate instance, and outputting final positioning parameters of a target object. The application realizes efficient, accurate and scale- and rotation-invariant contour matching.

The invention relates to the technical field of metal powder processing, in particular to an interface interlocking waveform generation method and system for an additive manufacturing technology. The method comprises the steps of obtaining multi-material model data; layering and slicing the model data to obtain a plurality of slice layers and corresponding base material contours and filling material contours; in each slice layer, a reference contour is determined from the filling material contours, and coincident contours matched with the reference contour are screened out from the base material contours to form coincident contour pairs; selecting a matrix material contour as a target contour; the target contour is processed according to set waveform parameters, and an interlocking contour with a periodic waveform structure is generated; and reversing the direction of the interlocking contour to obtain the interlocking contour of the filling material matched with the interlocking contour. According to the method, the interface shape is conveniently and flexibly regulated and controlled, and the multi-material interface bonding quality and the design and manufacturing efficiency are improved.

This invention relates to the field of metal powder processing technology, and more particularly to a method and system for generating interlocking waveforms at interfaces for additive manufacturing technology. The method includes acquiring multi-material model data; slicing the model data into layers to obtain multiple slices and corresponding matrix material and filler material contours; within each slice, determining a reference contour from the filler material contours and selecting overlapping contours from the matrix material contours that match the reference contours to form overlapping contour pairs; selecting the matrix material contour as the target contour; processing the target contour according to set waveform parameters to generate interlocking contours with a periodic waveform structure; and reversing the direction of the interlocking contours to obtain the interlocking contours of the filler material that match the interlocking contours. This method enables convenient and flexible control of the interface shape, improving the bonding quality of multi-material interfaces and design and manufacturing efficiency.

The application discloses a kind of automobile workpiece quality detection methods based on weighted profile matching, first based on 3D laser profiler sample data acquisition, through adaptive profile modeling algorithm to the profile data after intercepting correction is graphically trained and reverse analysis, construct with process tolerance compatibility dynamic standard profile model;Second, design bimodal weight evaluation function, calculate the optimal distance of each point of the measured profile and standard profile, combine the weighted deviation of profile mutation area and the cumulative deviation of gradual change area with mutation sensitive factor Differentiated analysis, convert distance into confidence score by nonlinear mapping, realize the intelligent quantitative evaluation of edge covering quality.It can be applied to the online detection of automobile workpiece edge covering quality such as car door, engine cover and other body coverings, and provides an intelligent quality control solution with high precision and high efficiency for automobile manufacturing.

This application provides an automatic object annotation method, apparatus, electronic device, and storage medium. The method involves acquiring a first image to be annotated, containing markers and objects to be annotated; identifying markers in the first image to obtain target marker information; determining the target 3D model corresponding to the target marker information according to a pre-set correspondence between the marker information and the object's 3D model; performing contour matching on the first image to be annotated based on the target 3D model to determine the position information of the objects to be annotated in the first image; and annotating the objects to be annotated in the first image according to the position information of the objects to be annotated. This achieves automatic object annotation, reducing image annotation costs and increasing annotation efficiency.

The application discloses a visual-based contact type measuring robot adaptive measuring point relative guiding method, which comprises a 2D visual-based product image contour matching method, realizes 4-degree-of-freedom measuring point guiding of plane translation, rotation and height scaling, and is suitable for contact type six-axis cooperative measuring robot measuring point guiding measurement of products with local features; the method comprises the following steps: teaching contact type six-axis cooperative measuring robot measuring points of a product to be measured; determining a teaching 2D measuring pose, obtaining a product multi-scale contour image template under the teaching 2D measuring pose and a multi-scale image of the current product, and performing contour matching of corresponding scale levels; based on the contour matching result, calculating a first pose deviation under the teaching 2D measuring pose, transforming the first pose deviation to all teaching point positions of the teaching 2D, performing pose transformation, performing iterative updating on all measuring point positions, and obtaining all updated first measuring point poses. The application better realizes adaptive contact type measuring point measurement of products.

The application discloses a subtractive process planning method, device and equipment and a storage medium. The method comprises the following steps: acquiring contour information of each layer of a structure to be subtracted; acquiring a topological relationship between all contours contained in each layer; and identifying a corresponding relationship between contours of different layers to perform contour matching search. The contour matching search comprises finding two or more contours between different layers to establish a connection, so that the connection conforms to a structural feature of an STL model. The method is simple to operate, requires a small number of parameters input by a user, and can reduce the operation difficulty of the user. Meanwhile, NC code generation is rapid and accurate. In addition, the method is easy to integrate with a system, is used for rapidly and accurately generating subtractive process code of composite additive and subtractive machining, and controls accurate execution of a subtractive process.

The invention discloses an image processing-based sorting and nesting analysis method, which comprises the following steps of: S1, drawing a part contour diagram according to a nesting file, extracting part contour points and establishing a mapping relationship between part names and the contour points; s2, extracting a closed curve, determining a nesting relation, and collecting the closed curve into a part contour set; s3, establishing a mapping relation between part names and contours through contour matching; s4, the minimum enclosing rectangle of the part is calculated, and a center coordinate and a rotation angle are obtained; s5, based on the tooling magnetic column layout, generating a gray scale increasing magnetic column distribution projection drawing; s6, the magnetic column distribution projection drawing serves as a mask to be overlaid on part filling, and the opening and closing radius of the tooling is dynamically adjusted till the number of magnetized magnetic columns meets the requirement or reaches the minimum radius; and S7, optimizing a magnetic distribution calculation process based on asynchronous programming. According to the invention, the magnetic matching calculation of more than 95% of parts can be automatically completed, and high-precision, high-efficiency and high-compatibility automatic sorting is realized.

This application belongs to the field of visual inspection technology for laser processing equipment, specifically disclosing a method and apparatus for detecting nozzles in a laser cutting head. The method includes: acquiring an image of the nozzle end face and an image of the optical core for the laser cutting head nozzle; based on the nozzle end face image, sequentially performing image preprocessing, nozzle outer contour matching, nozzle inner hole contour matching, and circle lookup to obtain the position of the nozzle inner circle center and the roundness detection result of the nozzle inner circle; wherein, the nozzle inner hole contour matching is performed under the constraint of the nozzle outer contour matching result; based on the optical core image, sequentially performing image preprocessing, optical core region segmentation, and circle lookup to obtain the position of the optical core center; wherein, the circle lookup is performed under the constraint of the optical core region segmentation; and based on the position of the nozzle inner circle center and the optical core center position, determining the nozzle optical core concentricity detection result. This application enables efficient and comprehensive detection of laser cutting head nozzles.

The invention provides a scatter diagram generation method based on an object contour diagram, and belongs to the technical field of graphic processing, and the method comprises the steps: contour preprocessing: carrying out the smooth denoising processing of a contour diagram, carrying out the Gaussian blurring of the contour diagram, converting the contour diagram into a binary image, extracting a contour set of a connected region in the binary image, and carrying out the Gaussian blurring of the contour image; calculating the surrounding area of each contour and carrying out noise filtering; uniform sampling and initial scatter point generation: constructing a pixel point set, and calculating a maximum distance and a minimum distance of sampling; and scatter-contour matching optimization: traversing the contour line and the scatter set, and eliminating interference scatters to obtain a final scatter diagram of the object contour. Through the methods of uniform sampling, contour point matching, repeated point de-duplication and the like, a specified number of uniformly distributed scatter points can be quickly generated for a contour map. According to the method, the defect of scatter point generation in the current method is overcome, model training is not needed, generalization is high, and the method can be widely used in profile diagrams of various graphs.

This application discloses a binocular pupil recognition method based on high-brightness reflection point anchoring and contour matching, belonging to the field of automatic pupil recognition technology. It solves the problem of low pupil recognition accuracy in the prior art under complex conditions such as eyelash occlusion, corner shadows, and partial eyelid occlusion. The method includes: first, locating high-brightness reflection points in the left and right images of the binocular system and using them as stable spatial anchor points; then, determining an adaptive segmentation threshold in the monocular view; dynamically delineating the region of interest (ROI) centered on the centroid coordinates of the high-brightness reflection points and performing binary segmentation; identifying a preliminary set of contours and filtering them based on multiple features such as contour size, area, aspect ratio, and relative positional relationship with the anchor points to obtain a reliable set of candidate contours; finally, matching the candidate contours in the left and right views and selecting the optimal pupil contour pair, thereby achieving accurate and robust pupil localization in the binocular view.

The invention provides a cross-layer post-cast strip compliance automatic inspection method based on column reference, and particularly relates to a tool for inspecting dislocation spacing of post-cast strips of adjacent floors. The invention aims to solve the standard requirement that whether the position dislocation of the special-shaped bending post-cast strip of the adjacent floors exceeds the distance of a span beam cannot be accurately and quickly checked in the prior art. The defect that a traditional method cannot deal with a complex post-cast strip scene due to the adoption of a simple distance threshold value is overcome. The invention creatively provides an innovative scheme based on three-dimensional contour matching and column reference geometric containment detection, and establishes a detection mechanism taking a column as a space reference object by realizing millimeter-level accurate contour extraction of the post-cast strip in any shape. A column reference geometric containment detection method is used for checking whether a gap area formed by dislocation of the outlines of the upper and lower layers of post-cast strips contains a structural column or not, whether dislocation of the cross-layer post-cast strip exceeds a beam span range or not is judged, and an automatic and high-precision detection scheme is provided.

This invention relates to the field of public safety technology and discloses a method, system, robot, and medium for preventing drowning in robots. The method includes: acquiring single-beam sonar ranging data, binocular images, and robot pose data; initially screening stationary candidate targets, performing visual confirmation using binocular images, and detecting the target to be confirmed; performing geometric contour matching between the contour of the target to be confirmed and a pre-stored contour model, using an improved YOLO detection model to identify the visual features of the target to be confirmed, determining whether it is in a continuously stationary state based on the robot pose data, and recording the duration of continuous stationary state; generating a drowning prevention warning signal to issue a drowning prevention warning. This invention accurately identifies the target to be confirmed from the morphological and visual feature levels by using geometric contour matching and detection models, respectively, and provides a quantitative standard for drowning prevention warning by combining whether the target to be confirmed is in a continuously stationary state and the duration of continuous stationary state, thereby improving the efficiency of drowning prevention warning.

The invention relates to a millimeter-wave-based local amplification display device and a control method, and the method comprises the steps: obtaining three-dimensional point cloud data of a human head through the scanning of a millimeter-wave radar, extracting the contour features of the human head, calculating and generating a circular frame parameter matched with the contour of the human head, and carrying out the overlapping display of a circular frame on a display module according to the circular frame parameter. The circular frame is used for defining the boundary of the local amplification area; performing real-time image processing on the picture in the selected area of the circular frame through the FPGA chip; by applying the method, the aiming precision and the game winning rate can be improved, the global view field can be kept, the'tunnel view field 'effect can be avoided, meanwhile, self-adaptive personalized adaptation is carried out according to the shape of the head of each person, the comfort can be effectively improved, operation is convenient and fast, and fine adjustment is supported; in addition, the scheme is based on hardware-level real-time processing, low delay and high smoothness are achieved, and jamming or smear caused by processing delay is avoided; and the game fairness can be maintained through the non-intrusive design.

The invention relates to the technical field of image processing, and discloses a complex background image contour matching method based on a physical contour feature point template, and the method comprises the steps: firstly converting physical contour data into contour image coordinate data according to an image pixel equivalent, and generating a template image; gradient information is extracted through an image pyramid model and a Scharr filter, candidate feature points are screened in combination with non-maximum suppression, and feature point uniform sampling is achieved through a grid statistical method; rotating and scaling the sampled feature point set based on preset parameters to generate a multi-angle and multi-scale template set; traversing the template by adopting a sliding window method and carrying out similarity calculation on the template and the to-be-matched image; and finally, obtaining a matched contour center point through center point offset compensation. The method improves the matching efficiency on the premise of guaranteeing the completeness of feature information, effectively resists complex background and illumination change interference, solves the problem of positioning offset caused by irregular contour rotation, and has the advantages of high robustness and high precision.

The invention relates to the technical field of contour recognition, in particular to a fast contour recognition method under a complex background, and the method comprises the steps: carrying out the contour recognition training under the complex background through employing a sample image, and collecting contour attribute data, so as to determine a plurality of first clear contour segments; determining a standard contour frame based on the performance parameters of the plurality of first clear contour segments; collecting contour attribute data of the image of the target detection area, and determining a plurality of second clear contour segments so as to determine a plurality of contour matching segments; determining whether to trigger quick matching or not based on the proportion of the contour matching section; determining the adjustment amount of the contour recognition optimization parameter based on the plurality of second clear contour segments; and processing the image of the target detection area by using the adjusted contour recognition optimization parameters, and obtaining a plurality of second clear contour segments again to determine whether to trigger rapid matching. According to the invention, the efficiency and accuracy of rapid contour recognition under a complex background are improved.

The present application relates to the technical field of image processing, and discloses a contour extraction method, a retrieval library establishment method, a contour matching method and a system thereof. The contour extraction method comprises: for each preset contour feature in a plurality of preset contour features, determining a contour feature quantity of the each preset contour feature within each preset step length on the contour; and for each preset contour feature in the plurality of preset contour features, recording a corresponding relationship between the preset step length and the contour feature quantity. The present application can realize high recall of similar contours through high-precision house type contour matching.

The application discloses a defect detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a transmission image and a reflection image; inputting the transmission image and the reflection image into an image contour extraction model respectively to obtain contour images of the transmission image and the reflection image; wherein the image contour extraction model is trained in advance by using multiple transmission images, reflection images and contour images of the transmission images and the reflection images; matching the generated contour images of the transmission image and the reflection image to obtain contour matching coordinate points; matching the transmission image and the reflection image based on the contour matching coordinate points; adding pixel values of all pixel points on the transmission image and the reflection image to obtain a synthesis image; and comparing the pixel values of all pixel points on the synthesis image with a threshold value to determine defect pixel points and position coordinates of the defect pixel points.

The invention discloses a drainage wire clamp contour matching point cloud filtering method and system based on combination with deep learning, and relates to the technical field of point cloud filtering, and the method comprises the steps: recognizing the contour of a target object through contour matching and point cloud filtering technologies; performing dynamic filtering based on non-uniformly distributed noise, and complementing according to sparse region information; and learning feature representation of the point cloud by using a deep learning model and carrying out filtering operation. According to the drainage wire clamp contour matching point cloud filtering method based on deep learning provided by the invention, the accuracy of target object recognition is improved through a contour matching algorithm, the system has stronger adaptability to non-uniformly distributed noise points through a dynamic filtering mechanism, a sparse region is effectively processed through an information completion algorithm, and the accuracy of target object recognition is improved. The integrity of the point cloud data is improved, and efficient filtering processing of the point cloud data is realized by introducing a contour matching algorithm, a dynamic filtering mechanism and an information completion algorithm.

The present application relates to the technical field of contour recognition, and particularly relates to a fast contour recognition method in a complex background, contour recognition training in the complex background is performed using sample images, contour attribute data is collected to determine a plurality of first clear contour segments; a standard contour frame is determined based on performance parameters of the plurality of first clear contour segments; contour attribute data of an image of a target detection region is collected, a plurality of second clear contour segments are determined to determine a plurality of contour matching segments; whether to trigger fast matching is determined based on a proportion of the contour matching segments; an adjustment amount of contour recognition optimization parameters is determined based on the plurality of second clear contour segments; the image of the target detection region is processed using the adjusted contour recognition optimization parameters, the plurality of second clear contour segments are reacquired to determine whether to trigger fast matching. The present application improves the efficiency and accuracy of fast contour recognition in a complex background.