10 results about "Edge tracking" patented technology

The invention relates to the technical field of display screen detection, in particular to a multi-spectral imaging-based display screen pixel-level defect dynamic detection method, which comprises the following steps of: acquiring high-resolution images of a plurality of fixed wavebands during dynamic display of a display screen by adopting a multi-waveband parallel imaging mode; filtering edge tracking and fuzzy region interpolation compensation are carried out, dynamic threshold updating is adopted, and a single physical pixel is segmented in a dynamic scene; extracting three types of multi-dimensional features of multi-band light intensity, band association and space-time dynamic of pixels, identifying and classifying pixel-level defects of the display screen by adopting multi-band cross validation, and outputting identification and classification data; through the above mode, the dynamic adaptation and segmentation precision is improved, and the large-scale production quality management and control requirements of high-resolution and high-refresh-rate display screens are met.

This invention relates to the field of display screen inspection technology, specifically to a dynamic detection method for pixel-level defects in display screens based on multispectral imaging. The method includes the following steps: employing multi-band parallel imaging to acquire high-resolution images of multiple fixed bands during dynamic display; performing filtered edge tracking and blurred region interpolation compensation, and using dynamic threshold updates to segment individual physical pixels in dynamic scenes; extracting three multi-dimensional features of pixels—multi-band light intensity, band correlation, and spatiotemporal dynamics—and using multi-band cross-validation to identify and classify pixel-level defects in the display screen, outputting the identification and classification data; through the above methods, dynamic adaptation and segmentation accuracy are improved, meeting the quality control requirements of large-scale production of high-resolution, high-refresh-rate display screens.

This invention provides a multi-target tracking method and system for special steel production processes using edge-cloud collaboration, belonging to the field of industrial intelligent manufacturing. The method deploys a multi-target tracking model at the edge of the special steel production line and a multimodal inference model in the cloud. Real-time production data is collected and input into the multi-target tracking model, outputting initial tracking results. Based on the initial tracking results, a scenario complexity index is calculated, and then it is determined whether the scenario meets stability conditions. If it does, the initial tracking result is output as the edge tracking result; otherwise, the cloud-based multimodal inference model performs multimodal inference based on the data uploaded from the edge side to obtain the cloud tracking result. The edge side fuses the edge and cloud tracking results to obtain and maintain the multi-target tracking trajectory. The cloud uses knowledge distillation to train a copy of the multi-target tracking model and distributes it to the edge side to update the model. This invention improves the accuracy and precision of multi-target tracking in special steel production processes.

A high-resolution remote sensing image edge repairing method based on tracking, first, a deep convolutional neural network is designed according to the remote sensing edge detection task, samples are made and edge detection model and edge tracking model are trained; the remote sensing image is input into the edge detection model to extract the ground feature edge, so as to obtain the ground feature edge intensity map. The remote sensing image and the random starting point file are input into the edge tracking model to iteratively generate the edge tracking graph, and for the discontinuous ground feature edge, the edge detection result and the edge tracking result are fused to automatically determine the edge width and complete the edge. The method completes the broken line repairing work through the topological information provided by the edge tracking algorithm for the discontinuous edge part in the prediction result of the edge detection algorithm, and simultaneously uses the edge binary graph to assist in connecting the broken edge tracking graph, or creates an edge in the position where the edge does not exist to complete the edge tracking graph. The method can improve the edge extraction accuracy and efficiency, and improve the accuracy of the edge tracking model.

This invention relates to an edge detection and tracking method. The edge detection stage includes color grayscale conversion, Gaussian filtering, generation of gradient magnitude matrix, generation of gradient magnitude histogram and calculation of threshold. The edge tracking stage includes initial point selection, edge concatenation, removal of redundant points, and edge verification. The input to this invention is a color photograph image, and the output is a set of contour line information contained in the image. It is particularly suitable for real-time algorithms in embedded hardware development and can be applied to practical scenarios such as educational robots, pattern recognition, and autonomous driving.

The application discloses a card ticket image segmentation method, device, equipment and program product, and is used for solving the problems of inaccurate edge positioning, poor adaptability and error accumulation in a complex scene. The scheme comprises the following steps: determining an edge starting point of a target card ticket image. Starting from the edge starting point, performing multiple rounds of edge tracking on the target card ticket image to determine an edge path; wherein each round of edge tracking comprises the following steps: taking a current edge point as a center, intercepting a local image in the target card ticket image, and generating a current state vector based on the local image; inputting the current state vector into a first intelligent agent to predict multiple candidate positions of a next edge point; inputting the current state vector into a second intelligent agent to predict an offset direction from the current edge point to the next edge point; and determining the next edge point based on the offset direction and the multiple candidate positions determined in the current round. A segmentation mask is constructed based on the determined edge path, and the target card ticket image is segmented based on the segmentation mask.

Techniques and systems are provided for edge detection is provided. The process can include obtaining a depth information and location information for a point detected in an obtained image; predicting a pose for the point based on the depth information, location information, and information about movement of a device; determining a search range and a search direction based on the location information and predicted pose; performing normalized cross correlation (NCC) matching between pixels of the obtained image based on the determined search range and search direction to identify an edge; and outputting a location of the edge.

The application relates to the polyester tow twist detection technical field and discloses a polyester tow twist detector, which comprises a fixing frame, a conveying mechanism, a first electric push rod and a limiting mechanism. The conveying mechanism is provided with two groups and is symmetrically arranged in the fixing frame. The polyester tow twist detector is provided with a camera and a limiting mechanism. The camera cooperates with an image processor to realize edge tracking of the tow. Compared with traditional visual interpretation, the detection error of the untwisting angle is reduced, and the detection repeatability is improved. The light supplement lamp ensures stable images within the illumination range, avoids environmental light interference, and integrates a pressure sensor. When the first electric push rod and the second electric push rod push down the two groups of sleeves, the limiting plates and the limiting blocks at the ends of the two groups of sliding rods contact the tow, and the pressure sensor monitors the pressure value in real time. The controller dynamically adjusts the stroke of the first electric push rod and the second electric push rod, so that the clamping force is stabilized in a proper range, and the tow is prevented from being damaged.

Techniques for identifying and eliminating overlaps of characters in an image that are to be processed for character recognition involve selecting a line of contours within the image, generating a line boundary around the line, identifying respective starting edgepoints on each edge of a contour that intersects the line boundary, and tracing a section of the contour by following each edge of the contour until a stopping point indicating an end to the tracing of the section of the contour is reached. The stopping point may comprise a determination that either (i) an end of the section of the contour is reached, or (ii) the section of the contour comprises a first sub-contour, and an intersection between the first sub-contour and a second sub-contour is reached. Based on the determination, the tracing of the section of the contour is completed, and the traced section is deleted from the image.

Techniques for identifying and eliminating overlaps of characters in an image that are to be processed for character recognition involve selecting a line of contours within the image, generating a line boundary around the line, identifying respective starting edgepoints on each edge of a contour that intersects the line boundary, and tracing a section of the contour by following each edge of the contour until a stopping point indicating an end to the tracing of the section of the contour is reached. The stopping point may comprise a determination that either (i) an end of the section of the contour is reached, or (ii) the section of the contour comprises a first sub-contour, and an intersection between the first sub-contour and a second sub-contour is reached. Based on the determination, the tracing of the section of the contour is completed, and the traced section is deleted from the image.