51 results about "Brightness gradient" patented technology

The invention discloses an edge spraying compensation control method based on intelligent visual feedback. The method comprises the following steps: performing space scanning on a to-be-sprayed workpiece to obtain spraying image data, and establishing a space corresponding relation between a spray gun motion coordinate and a workpiece surface coordinate; registering the real-time spraying image by using the corresponding relation, identifying a geometric boundary line, brightness gradient change and a coating adhesion area of the edge of the workpiece, and generating edge feature data; according to the difference between the edge feature data and the target spraying image, the spraying coverage deviation and the boundary overlapping error are calculated, the coating thickness change trend, the optical density change rate and the boundary direction offset are extracted, and the spraying gun posture adjustment amount, the spraying distance correction amount, the spraying pressure correction amount and the path speed correction amount are generated; the angle, the spraying distance, the pressure and the movement speed of the spray gun are dynamically adjusted according to the parameters; according to the method, real-time visual feedback and self-adaptive compensation control in the spraying process are achieved, and the uniformity and consistency of the coating on the edge of the workpiece are effectively improved.

The invention relates to the field of defect detection, in particular to a wallpaper defect detection method and system based on machine vision. The method comprises the following steps: analyzing acquired to-be-detected wallpaper image data to obtain regional texture variance, edge density and brightness gradient indexes, and generating a scale image layer set; extracting salient edge points in each scale image and generating an edge anchor point set; analyzing the scale image layer set and the edge anchor point set to obtain a texture difference index, and generating a texture feature map set according to the edge anchor point set; processing the texture feature map set to generate a texture significance distribution map; based on the texture significance distribution diagram, main direction distribution is extracted, a direction residual error model is constructed, and a residual error diagram and a direction difference distribution diagram are generated; and establishing a region scoring matrix, and generating a wallpaper defect credibility distribution map and a defect classification image output set on the basis of the region scoring matrix. The wallpaper defect detection precision can be improved.

The invention relates to the technical field of visual control, in particular to a picture defect test equipment control system and method, and the system comprises a difference tensor construction module, a space-time constraint construction module, a strain response judgment module, a coupling focusing mapping module and a boundary stability evaluation module. According to the method, the multi-dimensional difference incidence relation is constructed by extracting the pixel gray difference value, the brightness gradient and the chrominance phase angle, and fine brightness fluctuation and color shift in a picture can be captured. The superposition of the time-space change rate enables the dynamic performance of image defects to be distinguished, and continuous and transient anomalies can be effectively recognized. And in combination with tensor strain ratio and difference amplitude analysis, an abnormal region can be adaptively recognized, and neglect of a traditional method on a complex scene is avoided. The weighted aggregation of the local energy response improves the stability of the defect boundary, ensures the accurate positioning and judgment consistency of the image defect, and significantly improves the reliability and accuracy of the detection result especially in dynamic change and complex illumination environments.

The invention relates to the technical field of computer vision, in particular to an image target detection system and method based on deep learning, and the system comprises a dynamic feature alignment unit, a motion blur compensation unit and a feature fusion control unit. A dynamic feature alignment unit generates spatial deformation parameters through a deformable convolutional layer and an offset prediction sub-network, resamples a shallow high-resolution feature map, and realizes deep and shallow feature space alignment, and a motion blur compensation unit generates a motion vector based on brightness gradient field difference, constructs a mask and weights a suppression blur region, so as to realize deep and shallow feature space alignment. The feature fusion control unit analyzes local entropy and target size distribution, dynamically distributes feature weights and feeds back and optimizes offset parameters, a closed-loop learning loop is formed by the method, and the problems of inaccurate feature alignment, fuzzy interference and poor scene adaptation are solved.

The invention discloses an image super-resolution edge reconstruction method based on morphology and coverage rate perception. The method comprises the following steps: dividing an image into an edge region and a non-edge region based on depth and brightness information; anti-aliasing edge detail recovery is realized through coverage rate perceived depth mode classification and a table look-up filter; generating direction features by using the brightness gradient and keeping details through a table look-up filter; and combining the reconstruction results of the current frame and the historical frame to ensure the image stability in a dynamic scene. The invention also provides an image super-resolution edge reconstruction system. According to the method provided by the invention, the quality of an object edge and a newly appearing pixel region can be remarkably improved, sawtooth artifacts are effectively inhibited, and relatively high time stability is kept in a dynamic scene, so that the requirements of real-time rendering and visual enhancement application are met.

The invention relates to the technical field of road recognition, in particular to a road pavement abrasion state digital evaluation method and system, and the method comprises the following steps: extracting the brightness and texture features of pavement partitions, recognizing synchronous anomalies, generating a candidate set, screening connectivity and brightness anomaly partitions, analyzing the gray scale and the structure, screening out an abnormal region, and evaluating the abrasion state of a road pavement. And evaluating a stress deviation calibration abrasion grade, and outputting a pavement repair linkage adjustment data table. According to the method, the brightness change and the texture track fluctuation are synchronously analyzed on the time axis, dynamic capture of the abrasion area is achieved, the consistency of the brightness gradient direction and the texture fitting vector and boundary connectivity judgment are combined, the recognition accuracy and coherence are improved, non-abrasion interference is eliminated, and the recognition accuracy is improved. In combination with a stress distribution trend and an original flatness curve deviation condition, an abrasion grade is accurately calibrated, a coverage range is reasonably adjusted in a repair priority sequence, abrasion identification precision and grading reliability are improved, and repair response pertinence and resource allocation rationality are enhanced.

The invention provides a panel lamp light spot uniformity detection method and system and electronic equipment, and the method comprises the steps: analyzing the non-uniform characteristics of brightness gradient distribution according to the intensity and range information of a light spot region, carrying out the image processing of a projection image region, carrying out the quantitative evaluation of the brightness uniformity of a screen, and determining the specific region and degree data of the non-uniform brightness; if the dynamic influence range of the light interference exceeds a preset threshold value, meeting room layout adjustment and equipment position change are determined according to a light interference distribution diagram and equipment configuration parameters, the adjusted light distribution mode change is identified, and the detection priority is determined; according to the detection priority and the brightness deviation index, a brightness compensation method is adopted to carry out local correction on the specific area with the uneven brightness, and corrected brightness distribution data are obtained; and identifying the image definition index and the color rendition degree index after the brightness distribution is corrected, obtaining an area coverage proportion for clearly presenting the information, and judging whether the projection display effect reaches a preset definition standard value or not.

The invention discloses a lens smudginess monitoring method, computer equipment and a storage medium, and relates to the technical field of image processing, and the method comprises the steps: controlling an image collection device to shoot a plurality of images with different exposure degrees, and forming an image sequence from overexposure to underexposure; processing the image sequence, and respectively extracting a smudginess feature based on pixel brightness variance, a smudginess feature based on block brightness gradient change and a smudginess feature based on frequency domain enhancement; and fusing the extracted multiple smudginess features to generate smudginess area information. By collecting a multi-exposure image sequence and respectively extracting pixel brightness variance, block brightness gradient change and frequency domain enhancement features, light transmission abnormity, local response abnormity and edge texture features of a dirty area in exposure change are effectively captured, multi-dimensional features are fused, the accuracy, sensitivity and robustness of recognition of various pollutants are improved, and the recognition accuracy, sensitivity and robustness of various pollutants are improved. The problem of misjudgment of single-frame detection in a complex environment is solved, and reliable and comprehensive monitoring of lens smudginess is realized.

The invention discloses a multi-view camera splicing monitoring system based on a sky target, and relates to the technical field of visual intelligence. The multi-view camera splicing monitoring system based on the sky target comprises the following steps: a multi-view data acquisition module used for acquiring multiple types of data sets and carrying out time alignment and dimensionless normalization; the target detection and luminosity reference construction module is used for carrying out sky target detection and standard color block analysis and constructing a multi-view luminosity reference library; the deviation estimation and mapping construction module is used for constructing a cross-camera global luminosity mapping model; the adaptive control and real-time correction module is used for regional luminosity correction and illumination change detection; and the panoramic stitching and evaluation feedback module is used for constructing a joint area luminosity consistency evaluation index. According to the method, the multi-view splicing brightness color consistency and the target detection robustness under complex illumination are effectively improved, and the problems of seam brightness gradient and difficult color cast elimination caused by independent automatic exposure and white balance are solved.

The present application relates to computer vision and three-dimensional reconstruction technical field, disclose a kind of based on image recognition's building decoration component three-dimensional modeling method, method includes the following steps: receiving near-axis active illumination image sequence, solving camera pose and equivalent point light source trajectory;Inverse projection two-dimensional foreground mask generates maximum base envelope grid;Combining brightness gradient and texture high-frequency edge tensor field removes false shadow, extract effective sweep shadow mask;Tracking shadow residual optical flow displacement and combining light source trajectory analysis absolute depth, generate local three-dimensional point cloud;Surface reconstruction is executed to point cloud and opening plugging constructs negative space primitive entity grid;Extract the Laplace curvature energy of interface to generate normal shrinkage constraint, control entity grid after shrinkage and envelope grid execute Boolean difference set operation output model.The present application extracts absolute depth in featureless recessed area, and eliminates the boundary interference and distortion of grid Boolean operation.

The utility model discloses a projection device, a projection module and a vehicle. The projection device comprises a plurality of local projection single channels arranged in an array; each local projection single channel is provided with a mask unit, the mask unit of each local projection single channel is provided with a local pattern block for light to pass through, each local pattern block is a part of a preset overall pattern, two or more local pattern blocks form the overall pattern, and the projection device is configured to respond to a light source component arranged on the light incident side. And an integral image corresponding to the integral pattern is formed on the light emitting side. Local blocks in different local projection single channels are respectively a part of a preset overall pattern, that is, the overall pattern is composed of at least two local blocks, and the intensity of light energy which can pass through different local blocks can be freely and flexibly regulated and controlled. Therefore, the overall image which is finally projected and superposed on the ground can easily present the image effects of partition brightness change and brightness gradual change, and the effects of emphasizing display information, increasing interactivity or increasing the sense of science and technology and advanced sense of projection are achieved.

The invention provides a heavy calcium carbonate packaging quality detection method based on visual inspection, and relates to the technical field of heavy calcium carbonate packaging quality detection.The method comprises the steps that a low-dust detection angle and a high-dust detection angle are calculated according to the radian angle range of a packaging bag; the method comprises the following steps: acquiring pixel difference matrixes of in-bag areas of two images with high and low dust detection angles, performing shadow and brightness gradient identification on the in-bag areas according to the pixel difference matrixes, dividing brightness areas, and calculating the identification thickness of dust in each area according to the brightness of each brightness area, the method comprises the following steps: acquiring environmental parameters of a package detection area, calculating the thickness, position and quantity of different brightness areas of a bag-in-bag area, calculating a quality evaluation value of the bag-in-bag area, establishing a visual detection model, calculating a quality evaluation value of a bag end area, calculating a package quality score according to the quality evaluation value of the bag-in-bag area, and identifying the package quality.

The application discloses an aluminum veneer engraving path automatic correction method and system based on positioning image feedback, and particularly relates to the technical field of digital program control path correction, and is used for solving the problem that the path correction method includes the protective film pseudo edge into the space transformation calculation, resulting in the deviation of the corrected path from the real contour of the aluminum veneer; the positioning image containing the protective film state of the aluminum veneer surface is acquired, and the boundary features are extracted; the plate material contour in the original tool path data is called to match each boundary feature with the predetermined cutting contour to determine the candidate pseudo features; the brightness gradient asymmetry is calculated along the normal direction of the boundary feature to identify the protective film tearing pseudo edge; the process feature point coordinates are called to review the protective film tearing pseudo edge; after the protective film tearing pseudo edge determined in the pseudo edge judgment and the candidate pseudo features are removed, the remaining boundary features form a trusted boundary feature set; and only the trusted boundary feature set is used as a constraint to calculate the space transformation relationship and to perform overall transformation on the original tool path data.

The present application relates to lightning arrester intelligent monitoring technical field, specifically to a kind of lightning arrester lightning fracture risk intelligent monitoring system, system includes collecting lightning arrester tension electric field displacement disturbance data and rearranging section according to time, screening multi-source disturbance node and locating paragraph position, according to node number matching unmanned aerial vehicle continuous navigation section, extract corresponding image analysis brightness gradient and texture change, combine image and paragraph number cross relationship output lightning fracture risk section number.The present application is through the time series reorganization of tension, electric field, displacement disturbance data and paragraph number, constructs continuous disturbance structure, selects trigger node by the relationship of multiple physical quantity change, matches planning path according to node paragraph, compresses the range of inspection, identifies fracture suspect point by image gradient and texture change, combines the cross relationship of coordinate and outputs risk number section, enhances the coverage and traceability of risk identification.

The invention discloses a digital ink-jet printing color analysis method and system based on image processing, and relates to the technical field of printing color analysis. According to the method, a multi-angle fabric image is obtained, the brightness gradient is calculated, the reflectivity is measured, and surface scattering distribution is deconstructed by combining an initial absorption baseline; then, according to the law of conservation of energy, utilizing reflectivity and scattering distribution to iteratively update an absorption baseline, and dynamically stripping the absorption and scattering coefficients of the fabric; and finally, inputting the dynamic coefficient as a bottom layer parameter into a Coubella-Miscang model to reversely solve the target spectral reflectivity, and matching an optimal ratio in an ink ratio database, so that high-precision color prediction which does not need manual intervention and adapts to various complex fabrics is achieved, the matching degree of printing colors and design intentions is improved, and the printing quality is improved. The problems that in the prior art, correction coefficients and simple linear hypotheses are set depending on artificial experience, color prediction adaptability is poor in the face of complex fabric, and automatic high-precision real color matching cannot be achieved are solved.

The invention provides a brightness adjusting method, electronic equipment, a storage medium and a computer program product. The method comprises the following steps: for each image frame in an HDR video, determining a brightness gradient value corresponding to each pixel of the image frame; the brightness gradient value is used for reflecting the brightness change of the pixel value of the pixel and the adjacent pixel value; obtaining a battery SOC coefficient of a device used for displaying the image frame; determining a brightness adjustment coefficient of the image frame based on the brightness gradient value corresponding to each pixel of the image frame and the battery SOC coefficient; and adjusting the brightness of the image frame based on the brightness adjustment coefficient. According to the invention, the display quality of the image frame after brightness adjustment can be improved.

The invention discloses a driving mode judgment method and system based on computer vision, and relates to the technical field of driving mode judgment, and the method comprises the following steps: extracting a static image frame, and dynamically adjusting the frame extraction frequency; carrying out local contrast self-adaptive adjustment on the image frame to obtain an enhanced image; extracting and fusing a brightness gradient and texture distribution based on multi-level visual feature analysis to generate a unified feature vector; inputting the unified feature vector into an intelligent discrimination model for navigation picture recognition and outputting a result with confidence; and carrying out dynamic weighted updating on the confidence of the continuous frames based on time sequence attenuation and a sliding window mechanism. Through computer vision identification and time sequence regulation and control, intelligent identification and dynamic release of the navigation picture by the vehicle-mounted terminal are realized, interruption caused by error limit is avoided, navigation continuity and driving safety are guaranteed, and identification accuracy and response sensitivity are kept in stable and sudden change scenes through an adaptive adjustment mechanism, so that the navigation effect is improved. And the intelligence and user experience of the vehicle-mounted system are improved.

The present application relates to the technical field of defect detection, in particular to an electronic component defect visual detection system and method, the system comprising an image illumination control module, a defect boundary identification module, a confidence level calculation module, a result level classification module and a structure repetition elimination module.In the present application, the edge gray value and the inside pixel gray value of the packaging pin and the soldering point area are extracted, and the brightness gradient change trend is calculated, to realize dynamic adaptation of image illumination control, improve the clear identification of defect contour, build a defect intensity index sequence, and combine historical fluctuation interval difference to complete dynamic adjustment of the confidence interval, so that the defect level evaluation has stable distinguishing ability, compare the defect intensity value with the upper and lower limits of the confidence interval, combine the label attribution logic to form a clear distribution layer, match the boundary contour with the gray texture feature to realize structure repetition elimination between defects of the same level, and improve the independence and annotation accuracy of the detection layer.

The invention discloses a mobile robot pallet identification method based on computer vision, and relates to the technical field of robot visual perception, and the method comprises the steps: obtaining external parameters from a camera to a robot base, collecting a color image and a depth image, carrying out the distortion removal and alignment processing, fitting a ground plane based on the depth image to generate a near-earth mask, and carrying out the recognition of a mobile robot pallet. Constructing a structure dimension candidate region by combining a depth gradient and a brightness gradient, extracting an effective structure, weighting and solving a pallet center pose and a pose covariance, further calculating a docking deviation, and constructing an error uncertainty domain to complete docking judgment; structural recognition accuracy is improved through spatial constraint and multi-source information fusion, pose estimation stability is enhanced through observation quality weighting and uncertainty quantification, conservative evaluation of docking risks is achieved, and docking safety and reliability are improved.

The application discloses a satellite remote sensing data collection and preprocessing method and system, and relates to the technical field of satellite navigation. The method specifically comprises the following steps: collecting remote sensing images of a semiarid region through a satellite, analyzing pixel radiation and brightness gradient to identify bare land water features, constructing a leading atlas, extracting a boundary and registering to generate a standard structure, combining a climate model to correct to generate a reflectivity layer, transferring instructions when parameters are insufficient, reconstructing a queue by using a shortest algorithm to complete radiation calibration, atmospheric correction and geometric registration, and forming a preprocessing layer set. In the application, multi-band division is combined with radiation gradient calculation to enhance the separation degree of ground objects, boundary feature extraction and geometric registration are used to eliminate imaging distortion, a dynamic radiation model is fused with climate parameters to correct reflectivity, a double-threshold value is monitored to optimize a transmission strategy and avoid interruption, a priority algorithm is used to reconstruct a queue to reduce data delay, multi-level quality control is used to cooperatively process to form standard data, and the temporal and spatial reliability and application value are improved.

This invention discloses an optical compensation method and display device for OLED display modules. The method includes a calibration stage and a display stage. Calibration stage: Input a test image to obtain pixel grayscale distribution; collect actual brightness distribution using an optical sensor to extract brightness gradient features; input the features into a lightweight fully connected neural network, which sequentially includes a feature encoding layer, a gradient direction perception layer, and a classification decision layer, outputting the region structure type; select a target compensation weight kernel based on the region type, calculate the neighborhood dependency compensation intensity using weighted averages, adjust the base compensation value to obtain the final compensation value, and store it. Display stage: Directly read the stored final compensation value and superimpose it into the driving data. This invention identifies the spatial structure of Mura based on actual brightness distribution, effectively improving brightness non-uniformity while maintaining edge sharpness. The model is lightweight, suitable for hardware integration and deployment, and can significantly improve the image quality and yield of OLED display modules.

The application discloses a control system of a six-degree-of-freedom hydraulic mechanical arm for dismounting and mounting a cylinder, relates to the technical field of cylinder dismounting and mounting, and is characterized in that a multi-angle polarized light source is configured at a light jump area on the surface of the cylinder, a brightness gradient sequence is established, a multi-exposure time chain is constructed, the light intensity is controlled in time, the reflection area is formed into a continuous light level, spot energy diffusion is performed to form a continuous texture transition zone, a pose feature track is extracted, a motion edge is generated by combining light intensity variation to identify an optical flow clue, a visual guide channel is constructed according to the clue, a hydraulic actuator is driven to perform pose fine adjustment, and synchronous compensation and pressure regulation of the alignment process are realized. The application realizes the continuous transition of the light on the surface of the cylinder through the multi-angle polarized light and the multi-exposure time chain, improves the imaging accuracy and the texture recognition stability, and realizes the pose fine adjustment and the pressure balance control by combining the optical flow guide, so that the hydraulic mechanical arm can complete adaptive assembly in a reflection interference environment, and the dismounting and mounting accuracy and safety are significantly improved.

The invention discloses an image forgery positioning system based on a bimodal vision Mangbar network, which relates to the technical field of image forgery positioning and comprises a model construction unit and a forgery positioning unit. The model construction unit is used for preprocessing the to-be-detected image and acquiring an RGB modal image and a corresponding brightness gradient modal image; respectively carrying out feature extraction to obtain RGB features and corresponding brightness gradient features, carrying out fusion to obtain fusion features, and carrying out decoding through a decoder to obtain prediction maps of all stages; and the forgery positioning unit is used for receiving the prediction map of each stage, obtaining a final prediction map by adopting a voting mechanism, setting a confidence coefficient threshold value, judging an area of which the pixel value is greater than the confidence coefficient threshold value as a forgery area, superposing the final prediction map subjected to morphological operation processing with an original input image, and outputting a visual positioning result. According to the method, RGB and brightness gradient bimodal features are combined, and the positioning precision of weak-trace and high-fusion-degree forged areas is greatly improved.

The application discloses an explainable attribution method and system based on a star atlas semantic segmentation model, a device and a storage medium, and belongs to the technical field of deep space exploration image processing. The star atlas image is subjected to gray processing and gradient calculation, and the image is divided into super-pixel regions based on a gradient minimum strategy; a regional-level topological structure diagram is constructed, and node links are established based on spatial adjacency and brightness gradient similarity; the structural importance of each region is calculated, a center point of a mask is sampled, a directional elliptical Gaussian perturbation mask set is generated according to a gradient main direction angle; the perturbation mask is applied to the original image, and a semantic segmentation model is input to calculate a saliency score; and saliency information is propagated in the topological structure diagram based on a graph attention mechanism, and a structural saliency explanation diagram is constructed. Through regional division and topological propagation of terrain perception, model explanation of spatial continuity and terrain consistency is realized, and the technical problems that a traditional method ignores the physical characteristics of terrain structure and lacks a propagation path description are solved.

The invention relates to the technical field of defect detection, in particular to an electronic component defect visual detection system and method, and the system comprises an image illumination regulation and control module, a defect boundary recognition module, a confidence level calculation module, a result level classification module and a structure repetition resolution module. According to the method, the edge gray values and the inner side pixel gray values of the packaging pins and the welding spot areas are extracted, and the brightness gradient change trend is calculated, so that dynamic adaptation of image illumination regulation and control is realized, and the clear recognition degree of defect contours is improved; dynamic adjustment of a confidence interval is completed by constructing a defect intensity index sequence and combining historical fluctuation interval differences, so that defect grade evaluation has stable distinguishing ability, and a clear distribution diagram layer is formed by comparing the upper and lower limit relation of a defect intensity value and the confidence interval and combining label attribution logic; and structure repetition resolution between defect areas of the same level is realized through a boundary contour and gray level texture feature matching result, and the independence and marking accuracy of a detection layer are improved.

The invention relates to the technical field of image data processing, and discloses an image data adaptive enhancement method in a high-speed rail platform end complex environment, which comprises the following steps: acquiring an environment image and extracting a brightness component, and executing spatial sampling to construct a brightness distribution matrix; calculating a brightness gradient vector of a sampling node to determine a spatial weighting coefficient; performing spatial filtering on the preliminary mapping gain by using a spatial weighting coefficient, generating a weight component, and realizing gain correction; calculating a brightness change rate to determine a time sequence smooth step length, executing time sequence constraint adjustment on a mapping function control parameter, and determining a collaborative mapping function; according to the method, the slicing feeling caused by a strong-directivity light source is eliminated and video flicker is suppressed through spatial weight correlation and time sequence smooth constraint, and the track edge topological features are locked while noise is filtered out.

The application relates to the technical field of visual control, in particular to a picture defect test equipment control system and method, and the system comprises a difference tensor construction module, a space-time constraint construction module, a strain response judgment module, a coupling focusing mapping module and a boundary stability evaluation module.In the application, a multi-dimensional difference correlation relationship is constructed by extracting pixel gray difference, brightness gradient and chrominance phase angle, and subtle brightness fluctuation and color deviation in a picture can be captured.The superposition of space-time change rates can distinguish the dynamic performance of picture defects, and can effectively identify persistent and transient abnormalities.Combining tensor strain ratio and difference amplitude analysis, abnormal areas can be adaptively identified, and the neglect of traditional methods for complex scenes is avoided.The weighted aggregation of local energy response improves the stability of the defect boundary, ensures the accurate positioning and consistency of the picture defect, and significantly improves the reliability and accuracy of the detection result, especially under dynamic changes and complex lighting environments.

The application discloses a paperboard warping degree detection method and device, and relates to the technical field of paperboard surface flatness detection.The paperboard warping degree detection method comprises the following steps of image acquisition, image preprocessing, reflection feature extraction, edge detection, morphological operation, contour analysis and warping degree calculation; the image acquisition is performed by means of a light source and a camera located above the paperboard to be detected to acquire image information of the paperboard; the image preprocessing is performed by converting the acquired image information into a gray-scale image, removing noise and then performing histogram equalization to enhance contrast; the reflection feature extraction is performed by calculating the brightness gradient in the horizontal and vertical directions to obtain a reflection change intensity map, and then performing binarization processing to obtain a reflection feature map; the edge detection is performed by adopting a Canny algorithm to extract a basic edge, and then performing a morphological closing operation on the reflection feature map, and then performing a bit or operation on the basic edge to obtain an enhanced edge; and the morphological operation is performed by performing corrosion operations on the enhanced edge by using different structure elements in sequence to obtain an optimized edge image.

The application discloses a kind of based on computer vision's mobile robot pallet identification method, it is related to robot vision perception technical field, including, obtain camera inside participate camera to robot base external parameter, collect color image and depth image and carry out distortion removal and alignment processing, generate near-ground mask based on depth image fitting ground plane, construct structure dimension candidate area in combination with depth gradient and brightness gradient, extract effective structure and weightedly solve pallet center pose and pose covariance, further calculate docking deviation and construct error uncertainty domain to complete docking determination;Through space constraint and multi-source information fusion, improve the accuracy of structure identification, through observation quality weighting and uncertainty quantification, enhance the stability of pose estimation, and realize the conservative evaluation of docking risk, improve the safety and reliability of docking.

The invention relates to the technical field of holder control, in particular to an intelligent following shot method based on an optical flow method and target behavior prediction. The method comprises the following steps that a moving target image sequence continuously collected by a pan-tilt camera is obtained, pixel displacement is calculated for adjacent frames of images to form an optical flow field, and the optical flow field comprises the optical flow vector of each pixel point in a target area; analyzing motion disturbance structure characteristics of a target area in the optical flow field; constructing a motion state vector according to the motion disturbance structure features, and recognizing a sudden stop starting state, a turning state and an illumination sudden change state of the target through the motion state vector; and generating a pan-tilt control presetting instruction according to the sudden stop starting state, the turning state and the illumination sudden change state. According to the method, through analysis of the divergence value, the turning characteristic value and the brightness gradient inner product value, accurate identification of the comprehensive motion state of the target is realized, and the reliability of following shot decision is improved.