20 results about "Edge detector" patented technology

A photodetection device according to the present disclosure includes a plurality of light-receiving sections that each generates a pulse signal including a pulse corresponding to a result of light reception, a plurality of edge detectors that each generates a detection signal by detecting an edge of the pulse in the pulse signal generated by a corresponding light-receiving section, and an adder that generates a detection value indicating number of the pulses on the basis of a plurality of the detection signals. The edge detectors each include a first latch circuit that generates a first signal by latching the pulse signal on the basis of a first clock signal, a second latch circuit that generates a second signal by latching the first signal on the basis of a second clock signal that is an inverted signal of the first clock signal, a combination circuit that generates a third signal on the basis of the pulse signal, the first signal, and the second signal, and a third latch circuit that generates the detection signal by latching the third signal on the basis of the first clock signal.

A computer-implemented image processing method is provided. The computer-implemented image processing method includes: obtaining a pair of training samples, the pair including a training image with a first sharpness and a reference image with a second sharpness greater than the first sharpness, wherein at least a portion of the training image and at least a portion of the reference image in the same pair have the same content; inputting the training image into an image enhancement convolutional neural network to generate a training enhancement image; inputting the training enhancement image into an edge detector; generating a plurality of first edge maps by the edge detector; inputting the reference image into the edge detector; generating a plurality of second edge maps by the edge detector; and adjusting parameters in the image enhancement convolutional neural network to minimize at least one or more of the first and second losses.

The invention provides a non-contact air suspension ultrathin wafer turning device, which comprises a machine body, two clamping jaws, an edge detector, a displacement sensor and a control system, and is characterized in that the two clamping jaws can move relative to the machine body, each clamping jaw is provided with a crack for placing a wafer, and the edge detector is arranged in the crack; a plurality of air holes for spraying air towards the wafer are formed in the crack, so that an air film is formed on the outer side of the wafer to enable the wafer to suspend in the crack, the edge detector is arranged in the crack and used for monitoring the real-time position of the edge of the wafer, the displacement sensor is used for detecting the position state of the wafer, and the control system controls the clamping jaw to rotate when the clamping jaw turns over. And calculating execution air pressure based on data of the edge detector and the displacement sensor so as to adjust air film pressure distribution, so that the wafer is kept at a preset position. According to the non-contact air suspension ultrathin wafer turning device provided by the embodiment of the invention, in the wafer turning process, the pollution risk and physical damage of the wafer can be reduced.

The invention belongs to the technical field of building construction, relates to a ceramic tile seam beautifying method and an automatic ceramic tile seam beautifying robot, and aims to solve the problems that manual seam beautifying depends on experience, the efficiency is low, the cost is high, and the quality is unstable. The method comprises the following steps: positioning and moving equipment (a center detector is aligned with a tile gap, and an edge detector detects an obstacle avoidance area in real time); automatically pasting a film (releasing the film by a film storage roller, attaching the film by a film pasting roller, pressing the film by a film pressing roller and exposing the gap by a film cutting ring cutter, and cutting the film by a film cutter); and automatically gluing and scraping glue (lifting to drive a glue gun to inject glue. The robot comprises a moving trolley, a follow-up film pasting mechanism and a gluing mechanism, the moving trolley comprises a detection device and a multi-wheel walking device, the follow-up film pasting mechanism and the gluing mechanism are arranged, full-automatic seam beautifying can be achieved, manpower is reduced, and efficiency and quality are improved.

The application discloses an image internal occlusion relationship prediction method and system based on edge information guidance. The method comprises two parts of an edge detector and an occlusion relationship predictor, and comprises the following steps: inputting an image through an edge detector composed of an image segmentation module, a plurality of pooling Transformer modules and a deconvolution module to generate an edge detection graph; then in the occlusion relationship predictor, the edge detection graph acts on the image element features generated by the edge detector through an edge information guidance module; then the new image element features are sequentially optimized through a plurality of pooling Transformer modules; and finally, a last deconvolution module adjusts and enlarges the finally obtained image element features in resolution, and outputs an occlusion relationship graph. The application first proposes a new method of guiding feature calculation by the generated edge detection graph and directly generating an occlusion relationship graph. Compared with other existing methods, the application has less calculation amount and better prediction effect.

The invention discloses a multi-information progressive fusion image colorization method based on a deep convolutional neural network. The method is composed of five core modules: an input module is responsible for receiving an original image and carrying out preprocessing operations such as graying and normalization; the feature extraction module is actually a VGG network and is responsible for extracting multi-level features of the image; the multi-information fusion module adopts a channel attention mechanism to collaboratively fuse gray features, edge features extracted by a Canny edge detector and semantic features extracted by a DeepLabv3 + semantic segmentation network; the progressive colorization generation and optimization module comprises a plurality of U-Net sub-networks, and realizes colorization image generation from coarse to fine through a staged generation strategy in combination with joint optimization of L1 loss, perception loss and adversarial loss; and the output module carries out reverse normalization processing on the result. According to the method, the problems of color distortion and detail loss in the prior art are effectively solved, the color image with accurate color, rich details and vivid vision can still be generated in a complex scene, and the method can be widely applied to the fields of old film color restoration, medical image enhancement and the like.

Automatic target evaluation system for bullet holes, comprising a camera unit, a computing unit and image analysis software, wherein the camera unit continuously records images of a target and the computing unit is designed to extract contours and edges using a Canny edge detector, to perform a circle approximation using area boundaries and to identify possible bullet holes.

The application provides a train wheel position monitoring method, device and system, which can accurately measure the position of the train wheel by periodically using a stereo camera and a thermal imager, and automatically display the measurement image, thereby significantly improving the accuracy and robustness of the measurement. When an image selection instruction is received, the system automatically marks the image to be measured and the train wheel to be measured in the image, then processes the image through an edge detector to extract the vertical edge of the train wheel, and further uses an iterative algorithm to accurately extract the horizontal coordinate of the edge white point. The arc angle between the horizontal center of the image and the edge white point is calculated to determine the width of the train wheel, and the offset is compared with a preset template to determine whether the train wheel is displaced. This method not only reduces the dependence on camera settings, improves the operation efficiency, and reduces the implementation and operation cost, but also meets the strict requirements of the railway transportation system for high safety and high efficiency, and has great popularization value.

The application discloses a method capable of storing different magnifications and automatically setting boundary strength, adopts a projection system, and comprises a workbench, an objective lens, a projection screen, a frontmost mirror and a last mirror; the objective lens comprises a mounting seat and a lens; a plurality of sensing elements are arranged on the mounting seat, the sensing elements are connected with an edge trigger controller, a trigger element is arranged on the lens, and the trigger element automatically triggers the corresponding sensing element after the lens is mounted on the mounting seat, so that the edge trigger controller automatically distinguishes the magnification of the lens, a plurality of different magnifications are preset and stored, and corresponding boundary strengths are respectively set; during operation, the corresponding boundary strengths are automatically adjusted according to the lens with different magnifications, manual setting is not needed, the setting magnification is avoided to be forgotten, and the edge detector is used in combination to automatically enable the edge detector to perform edge detection by using different threshold values according to different magnifications, so that the precision and convenience are considered.

The application relates to the technical field of object recognition, and discloses an image recognition detection method and system based on weak supervision learning, which comprises the following steps: S1, generating initial pseudo labels of a to-be-detected image through point annotation, an edge detector and a self-adaptive flood filling algorithm; S2, constructing a point supervision salient object detection model based on a visual converter; S3, performing the first round of training on the point supervision salient object detection model to obtain a final salient map; and S4, suppressing non-salient objects of the final salient map, performing the second round of training on the point supervision salient object detection model, and completing the recognition of the image. The application solves the problem that the existing image recognition detection technology can only cover part of an image, cannot ignore invalid objects, leads to low efficiency, and has the characteristics of strong supervision capability.

The present invention provides a low-power receiver for MIPI C-PHY, comprising: an oscillator, a delay cell calibration, an edge detection and pulse generator, and a sampler & wire state decoder. The delay cell calibration is connected to the oscillator signal and receives the frequency signal generated by the oscillator. The edge detection and pulse generator is signal-connected to the delay cell calibration and is used to receive signals transmitted by the MIPI C-PHY. The sampler and wire state decoder is signal-connected to the edge detection and pulse generator and is used to receive signals transmitted by the MIPI C-PHY and output a decoding result. The invention utilizes the known oscillator pulse width (OSC clock high period width, i.e., the duration of the high level of the pulse signal), which is the delay time of one delay cell. After passing through the delay cell calibration circuit, the number of delay cells within the selected oscillator OSC cycle time can be determined. With the known data rate, a selection code is sent to the same delay cell in the edge detector to obtain the delay time for edge pulse generation. The edge pulse is sent to the sampler for data sampling, and after sampling, the state of the decoding action is determined.

A metrology system for determining a characteristic of a structure on a substrate. The metrology system comprises an illumination source to output radiation to an objective. The objective is configured to direct radiation toward the structure on the substrate and direct radiation diffracted from the structure toward a detector. The detector comprises an event based camera to detect changes in intensity of radiation incident on the event based camera, and outputs an event data stream conveying the detected events. The detector comprises an edge detector o receive the event data stream and to output movement detection data representing a movement of the structure on the substrate relative to the objective or camera. The detector comprises a processor to receive the output movement detection data and determine the characteristic of the structure on the substrate based on the movement detection data and 0 properties of the structure on the substrate.

The invention discloses a large model auxiliary damage detection system and method based on verification prompt and reflux distillation, and belongs to the field of machine vision and industrial detection. The system comprises an edge detector, an adaptive verification distributor, a verification prompt generator, a cloud verifier, a reflux distillation module and a resource and physical monitoring subsystem. Preliminarily detecting an output result, uncertainty and characteristics at the edge end; the distributor is combined with uncertainty, physical parameters and resource states to trigger a cloud rechecking and uploading mode; generating a compressed structured verification prompt data packet during triggering; the cloud rechecks through a large model and integrates physical consistency verification; the reflux distillation module utilizes cloud feedback to finely adjust the edge model; and the monitoring subsystem dynamically adjusts the strategy. The verification prompt compression enables the single-time uploading data volume to be reduced; the detection accuracy is improved through end-cloud cooperation and physical verification, and false positive is inhibited; the adaptive strategy balances the delay cost and the accuracy of key events; and the edge model is continuously and adaptively optimized through reflux distillation.

The invention relates to a well logging technology, and discloses a multilayer stratum inversion method of a while-drilling electromagnetic edge detector, which comprises two stages of offline training and online inversion. In the offline stage, firstly, multiple stratigraphic structure types are constructed, and training samples are generated; performing feature enhancement and reconstruction on the forward modeling original response vector of the sample to improve the data dimension and sensitivity; then, for each stratum type, training through a supervised descent method to obtain a special gradient optimization set; in the online stage, the same feature reconstruction is carried out on the original response measured in real time, the stratum type to which the original response belongs is intelligently judged, and the matched gradient optimization set is automatically called to carry out rapid iterative inversion. Dynamic attenuation regularization and geological prior constraint are fused in inversion iteration, noise is effectively suppressed, and stability and geological rationality are guaranteed. According to the method, rapid, accurate and stable inversion of a complex multi-layer stratum is realized, and the reliability of geosteering while drilling is remarkably improved.

This invention discloses a design method and a metalens device for monolithic dual-mode edge detection, belonging to the field of optical edge detection technology. When used in conjunction with a linear polarizer, this device can achieve isotropic two-dimensional and directionally adjustable one-dimensional edge detection according to the polarization state of the incident light. The phase distribution of the nanoarray in the device in the x and y polarization directions is the bright-field imaging phase and the phase difference between the phases, respectively. Each nanounit rotates counterclockwise with its lattice center as the rotation center. The rotation angle relative to the initial posture (when the angle between its major axis and the x-axis is 0° or 90°) is half the angle between the line connecting the lattice center and the origin of the x-y coordinate system and the x-axis. Based on this, this invention can achieve edge detection imaging with a wide working bandwidth, high edge detection resolution, and convenient mode switching without the need for other imaging devices.

The application provides a polarization-independent BIC metal super surface optical edge detection device and a design method, the method shows a simple and easy-to-process metal super surface, the device can realize high-quality polarization-independent two-dimensional optical edge detection with high numerical aperture and high efficiency. The design scheme provided by the method takes silicon dioxide as a substrate and C4 symmetric L-shaped aluminum metal patch as a basic unit, adjusts and controls the spatial dispersion of BIC by fine-tuning the perturbation parameters of the super surface, and realizes the polarization-independent second-order spatial differential operation. The design scheme works at a frequency of 0.6718 THz, the numerical aperture (NA) can be as high as 0.56, the peak efficiency can be as high as 36%, and the high-quality edge detection performance can be maintained. The work can realize compact, low-power and ultrafast optical edge detection, and shows great potential in various applications such as optical imaging and computer vision.

The application discloses a kind of edge enhancement and distribution equalization's remote sensing stereoscopic image feature matching method, corresponding multi-scale space image of reference image and image to be registered is constructed, and each scale space image is filtered with unbiased ratio UDR edge detector, to obtain the final multi-scale space image;Search the extreme point in the final multi-scale space image, the extreme point obtained is candidate feature point, then using non-maximum suppression algorithm to the candidate feature point is handled uniformly, feature point extraction is completed;With feature point as center, four different concentric circle regions of different sizes are selected from different scale images to construct multi-scale feature descriptor, calculate multi-scale feature descriptor vector, then using nearest neighbor distance ratio algorithm to obtain initial feature matching point pair, then using random sample consensus algorithm to delete the abnormal point in initial feature matching point pair, complete reference image and image to be registered feature point registration.

The invention discloses a self-adaptive product layout probe testing device, and relates to the field of probe testing, the self-adaptive product layout probe testing device comprises a base, a workbench and a wafer bearing table, the top of the workbench is symmetrically provided with probe carrying assemblies on the wafer bearing table, and the probe carrying assemblies can be adjusted in multiple directions. A probe carrying assembly is arranged on the workbench, an edge detector three-dimensional seat is connected to the output end of the probe carrying assembly, a probe body is borne on the edge detector three-dimensional seat, a visual moving assembly is arranged on the workbench, a visual detection module body is connected to the visual moving assembly, and a wafer bearing table moving assembly is arranged at the top of the workbench. The test requirements of line loops with different sizes in a product layout can be met by adjusting the probes through the single-side double probes, and the probes are matched with the Z-axis precision fine tuning table through the X-axis probe linear motor and the Y-axis probe linear motor, so that the test of different product layouts is met, and the overall compatibility is improved.

This invention belongs to the field of image processing technology. It proposes an adaptive multi-stage non-edge pruning method and system for image edge detection. In multiple stages of the Transformer encoder, edge probability maps are generated based on the features of each stage, and these maps are binarized using an adaptive threshold for each stage to obtain a pruning decision mask. The masks from each stage are accumulated along the network depth to form a consistent cumulative pruning mask, which is used to retain only key edge image patches and remove redundant non-edge regions during self-attention computation. After encoding, the multi-stage features, restored to their original length, are input into a streamlined edge detector. The final edge prediction map is generated through lightweight linear projection and multi-scale fusion. This detector uses the image encoder as its backbone, removes the original cue decoder, has a simple structure, and is highly coordinated with the pruning mechanism. It significantly reduces computational complexity while effectively maintaining edge detection accuracy, making it suitable for resource-constrained edge computing scenarios.

The invention provides a multi-angle detection device for a pressure pipeline. The multi-angle detection device structurally comprises a bottom plate, an end positioning body, a top plate, a driving motor, a bracket and a control end, on the basis of supporting plates arranged on the side edge of the support and the edge of the bottom plate, a moving body of an edge detector in a sliding rail is combined with a parallel block to drive an air cylinder, a hydraulic rod, an extrusion block and a pressure detection body to move up and down; then a hydraulic system of a cylinder is combined to drive a hydraulic rod to extend out, so that an extrusion block performs pressure detection on the edge of the pressure pipeline, and meanwhile, a pressure detection body transmits measured data to a control end position to complete edge detection; therefore, the situation that the detection area is missing and the detection comprehensiveness of the detection device is reduced due to the fact that the pipeline edges cannot be detected in place can be avoided, the pipeline edges can be detected one by one through the up-down adjusting effect, and the detection integrity is improved.