1700 results about "Magnification" patented technology

The invention discloses a method, system and equipment for monitoring the running state of a solid state disk and a storage medium, and belongs to the technical field of monitoring the running state of the solid state disk, and the method comprises the following steps: S1, monitoring core indexes during running of different solid state disks, including a health degree index, a performance index and an environment and hardware index; field mapping tables are established for different models of solid state disks, and SMART attributes of different manufacturers are uniformly converted into self-defined indexes; the main control temperature, the writing speed, the reading error rate and the environment temperature are combined, and the temperature values of different areas of the NAND are predicted; and the temperature, the voltage and the write-in magnification are combined to correct the residual life of the solid state disk. According to the method, the SMART attribute indexes are unified, the NAND temperature is accurately predicted, and the service life is predicted in combination with multiple factors, so that the operation and maintenance efficiency of the solid state disk can be effectively improved, and a safety guarantee is provided for stable operation of the solid state disk.

A data-centric system for analyzing agricultural crops, consisting of: a data acquisition module configured to capture images of agricultural fields using cameras, unmanned aerial vehicles (UAVs) or sensors, with the sensors collecting data on soil moisture, temperature, light, humidity and pH; a data preprocessing module configured to: resize the acquired images to a standardized dimension suitable for input to a deep learning model; apply noise reduction using a Gaussian filter; improve image contrast through histogram equalization; and perform image magnification through rotation, reflection, and scaling transformations; a feature engineering module configured to extract the following features: color features, which include color histograms, mean, and standard deviation of color channels; texture features using Gray-Level Co-occurrence Matrix (GLCM) properties, which include contrast, dissimilarity, homogeneity, energy, angular moment (ASM), and correlation; shape features, which include contour area, perimeter, aspect ratio, and roundness; and other features, which include the green pixel ratio and edge density; a classification module configured to: implement deep learning-based classification models selected from the group consisting of Support Vector Machine (SVM), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), ResNet18, Random Forest (RF), SegNet, VGGNet, Naive Bayes (NBG), Decision Tree (DT), K-Nearest Neighbors (KNN), and DeepLab; detecting and classifying weed species in the images of agricultural fields; and diagnosing plant diseases based on the features extracted from the images of agricultural fields; an output module comprises a user interface configured to display the classification and recognition results; and a recommendation module configured to suggest treatment solutions for diagnosed plant diseases through the output module's user interface.

The invention discloses an electrostatic induction and optical imaging principle-fused online monitoring device and method for wear particles of a water-lubricated bearing, and belongs to the field of state monitoring of mechanical equipment. The device comprises a square insulation detection cavity, a detection electrode array, an electromagnetic shielding shell, a high-speed optical imaging module and a signal processing unit, the square insulation detection cavity is installed in a bearing lubrication water loop. The detection electrode array is fixed to the outer wall of the cavity and used for capturing electrostatic signals generated when the abrasion particles pass through. The electromagnetic shielding shell wraps the detection cavity and is grounded through a wire to eliminate environmental electromagnetic interference. The high-speed optical imaging module integrates a high-magnification microscope lens and a CMOS sensor, is coaxially mounted with the detection cavity, and obtains the morphology characteristics of the wear particles in real time; and the signal processing unit performs multi-modal data fusion analysis on the electrostatic signal and the optical image. Through cooperative detection of electrostatic induction and optical imaging, the monitoring precision and reliability of the wear particles of the water-lubricated bearing are remarkably improved.

The invention discloses a metallographic detection method and system based on image recognition, and belongs to the technical field of metallographic detection. The detection method comprises the following steps: image acquisition and preprocessing: acquiring a metal metallographic image by an optical microscope, performing median filtering and denoising, and extracting a grain boundary by adaptive binarization; and field-of-view and scale calibration: selecting a corresponding scale according to the shooting magnification. The multi-parameter automatic measurement comprises grain size analysis, grain size rating, second phase analysis and intelligent report generation, a report is automatically generated based on a preset template and comprises an original image, a binary image, measurement data and a histogram, and report fonts and layout can be adjusted in real time through a visual control. According to the detection method disclosed by the invention, the efficiency, the precision and the reliability of metallographic structure analysis of the metal material are remarkably improved through the full-process design of image acquisition standardization, preprocessing intellectualization, data analysis automation and report generation templating.

The invention discloses a method for measuring the particle size of metal powder by using a scanning electron microscope, which comprises the following steps: step 1, sample treatment: adhering a small conductive adhesive tape on a sample table, sprinkling metal powder on the adhered conductive adhesive tape, and purging to obtain the conductive adhesive tape adhered with the metal powder; step 2, parameter setting: setting acceleration voltage, working distance, diaphragm, image contrast, brightness, magnification times and scanning speed of a scanning electron microscope to observe the conductive adhesive tape adhered with the metal powder obtained in the step 1 to obtain an electronic image of metal powder particles; and processing and calculating the electronic image of the metal powder particles by using software to obtain the average particle size of the metal powder particles. According to the method disclosed by the invention, a solvent is not needed to disperse the sample, pollution of the solvent to the sample is effectively avoided, and the result is more accurate than that of directly measuring the particle size by using length software.

An audio processing method implemented by an electronic device includes entering a multi-channel video recording mode, detecting a shooting operation of a user, simultaneously recording, after detecting the shooting operation, a first video image and a second video image using a first camera and a second camera, and recording audio of a plurality of sound channels, where the audio includes panoramic audio, first audio corresponding to the first video image, and second audio corresponding to the second video image. The electronic device further records the first audio based on a feature value such as a zoom magnification corresponding to the first display area.

The invention relates to the technical field of pathological image analysis and mining, and particularly discloses an ovarian cancer subtype classification method based on prototype learning and multi-view deep embedding clustering, and the method comprises the following steps: S1, collecting a tissue pathological image of an ovarian cancer patient and a corresponding full-view digital pathological image; and S2, generating a multi-view data set. According to the ovarian cancer subtype classification method based on prototype learning and multi-view deep embedding clustering, the problem that in the prior art, patch-level labels are generally lacked in the field of multi-instance pathological images, so that many natural image processing methods cannot be applied to the field of pathological images is solved. A ResNet backbone network is used for extracting features of pathological images under the maximum magnification, a small number of pathology prototypes are introduced to guide deep embedded clustering through pathology expert priori knowledge, a pathology image spectrogram is introduced to serve as a reference view, and the accuracy and stability of clustering are enhanced.

The invention discloses a method for optimizing micro-crack segmentation based on deep learning and super-resolution reconstruction, and the method comprises the steps: cutting an image in real time, obtaining an image block which takes a component as a target main body, and synchronously recording a homography matrix for geometric mapping; selecting an amplification strategy to improve the resolution, and recording a scale mapping relation; inputting the enhanced image block into a double-flow network; adaptive fusion and reconstruction are carried out on the two branch features, and a high-resolution texture image is output; generating a geometrically corrected ortho-image, fusing the geometrically corrected ortho-image with original illumination information, and outputting a corrected image with a known pixel size; identifying cracks, spalling and honeycomb diseases in parallel; generating a unified defect confidence map; calculating real geometric parameters of the BIM in a BIM global coordinate system through coordinate back projection; and generating quantitative defect reports and maintenance suggestions. The method has the advantage that seamless connection between the detection result and the BIM global coordinates is realized.

The invention discloses a visual tracking image acquisition method and device, electronic equipment and a readable storage medium, relates to the technical field of robot inspection, and accurately establishes a mapping relation between an actual image coordinate and a camera coordinate through a camera checkerboard calibration algorithm to obtain an internal reference matrix and a distortion coefficient. A shooting holder is controlled to collect a large-range image containing an inspection target, and a visual tracking algorithm is used to identify the contour of the target. And calculating a target magnification factor and a holder fine tuning parameter based on the contour coordinate data, the internal reference matrix and the distortion coefficient. And rotating the holder according to the fine tuning parameters, accurately positioning the inspection target to the center of the global image, and executing image magnification operation according to the target magnification times to complete target image acquisition. Through cooperation of calibration data support, algorithm contour recognition and parameter driving adjustment, the collection effect of a target image is not affected by repeated positioning precision of the robot, it is ensured that the collected target image is centered and clearly amplified, and a high-quality image basis is provided for subsequent detection.

The invention relates to a cloth flaw detection method, device and equipment and a storage medium, and the method comprises the following steps: carrying out the multi-angle light source irradiation of the surface of cloth, obtaining a texture image, and carrying out the grid segmentation of the texture image into detection units; and extracting a gray value sequence of each unit, calculating an edge difference by using a gradient operator, generating a texture edge change curve to identify an abnormal wave crest, and determining a defect candidate region. And carrying out local amplification imaging based on the candidate region coordinates, and extracting defect shape feature parameters. The defect types are determined according to the parameters, quality grade division is performed on the cloth according to the parameters, and a quality grade report is finally generated, so that the technical problems of low defect identification precision and easy missing detection of fine defects caused by uneven illumination and texture interference in the existing cloth defect detection method are solved.

The invention discloses an unmanned aerial vehicle autonomous inspection system and method based on AI identification, the system comprises an unmanned aerial vehicle body carrying a high-power optical zoom lens, an edge computing device and a function module, and the autonomous inspection of a power distribution tower is realized by fusing front-end AI identification and edge computing technologies. A Yolo structure is adopted to construct a lightweight tower recognition model, a dynamic route planning module is combined to realize single-point reference route generation and three obstacle crossing modes, and real-time coordinate correction in an RTK-free environment is supported. The edge computing device integrates a semi-supervised learning engine and a multi-sensor data fusion module, meets miniaturization design, and supports breakpoint continuous flight control and precise landing. The method covers automatic route generation, visual tracking, zoom cooperative control and self-adaptive task scheduling, solves the problems that a traditional unmanned aerial vehicle depends on manual operation, the data quality is poor and the efficiency is low, realizes whole-course automation of tower inspection in a complex environment, and is high in inspection efficiency, and the picture definition reaches the pin level.

The invention relates to a head-up display device, a head-up display system and a vehicle. In one aspect, the head-up display device includes: a first image generation unit configured to emit first image light; the second image generation unit is provided with a first transflective surface, the second image generation unit is configured to emit second image light rays through the first transflective surface of the second image generation unit, and the first image light rays emitted by the first image generation unit and propagated to the second image generation unit are reflected through the first transflective surface of the second image generation unit; and a first imaging amplification unit configured to reflect the second image light emitted by the second image generation unit and propagated to the first imaging amplification unit and the first image light reflected by the second image generation unit and propagated to the first imaging amplification unit. According to the method and the device, virtual images of different distances can be formed to realize fusion of the virtual images and corresponding real scenes, so that the driving safety and the driving experience are improved.

The invention discloses a yarn uniformity analysis method based on image processing, and relates to the technical field of image data processing, and the method comprises the steps: employing a convolutional neural network model to carry out the deep learning analysis of the surface features of a yarn through a preliminary feature distribution diagram, carrying out the adaptive feature weighting processing of a complex texture region, and obtaining a feature distribution diagram; obtaining a more accurate third characteristic distribution diagram; if the characteristic values of some areas in the third characteristic distribution diagram exceed a preset abnormal threshold value, performing local amplification analysis on the areas, and further extracting fine defect boundaries in combination with an edge detection algorithm to obtain a defect candidate area set; and generating a visual analysis report according to the multi-dimensional evaluation data, visually presenting yarn uniformity distribution by applying a thermodynamic diagram technology, marking specific position information for a defect high-incidence area, and outputting a final detection analysis result. The problems of yarn image acquisition and defect detection under complex illumination can be effectively solved, and the accuracy and efficiency of yarn uniformity detection are improved.

The invention belongs to the field of tunnel boring machine internal equipment, and discloses a multi-degree-of-freedom large-magnification-ratio visual carrying motion protection platform suitable for a long and narrow space in a TBM (Tunnel Boring Machine), which comprises a guide rail, a loading platform, a horizontal telescopic mechanism, a rotating mechanism, a vertical telescopic mechanism, a visual protection system and a front-back swinging mechanism. According to the multi-degree-of-freedom large-magnification-ratio vision carrying motion protection platform, the flexibility and coverage range of TBM internal vision monitoring are improved, and the requirements of different monitoring positions can be met; through multi-degree-of-freedom motion and a large magnification ratio, comprehensive monitoring of a complex environment in the TBM is realized; the visual protection system effectively protects visual equipment, and durability and stability of the equipment are improved; the structure design is compact, deployment and operation in a long and narrow space in the TBM are suitable, and the space utilization rate is increased; and through automatic and intelligent design, the requirement of manual operation is reduced, the operation risk is reduced, and the working efficiency is improved.

A target object tracking method, a camera, and a computer-readable storage medium are provided. The camera includes a telephoto lens and a wide-angle lens. The camera captures a telephoto image by the telephoto lens, and captures a wide-angle image by the wide-angle lens. When a target object is detected in the wide-angle image, a first zoom magnification of the wide-angle image and a zoom magnification of switching lenses are obtained. The wide-angle image is digitally zoomed according to the first zoom magnification if the first zoom magnification is less than or equal to the zoom magnification of switching lenses. Otherwise, if the first zoom magnification is greater than the zoom magnification of switching lenses, the telephoto image is digitally zoomed to output a tracking image of the target object when the target object is detected in the telephoto image.

The invention relates to the technical field of dust concentration measurement, and particularly discloses a dust concentration intelligent detection device and method, the dust concentration intelligent detection device comprises a shell assembly, the shell assembly comprises a main shell, a ventilation pipe is arranged on one side of the main shell, a top shell is arranged above the ventilation pipe, a bottom shell is arranged below the ventilation pipe, and an air blowing assembly is arranged in the ventilation pipe; a rotating assembly is arranged in the main shell, an air blowing assembly is arranged outside the rotating assembly, a dust collection assembly is arranged on one side of the rotating assembly, and a measuring assembly is arranged on the bottom side of the air blowing assembly. And under the reflection of the oblique light source of the measuring assembly, by utilizing the sensitivity of light reflection, a descending minimal variable is converted into a moving huge variable after the light is reflected, so that the magnification observation of the weight is facilitated, and the accuracy of the experiment is improved.

A thickness-distribution measurement device includes a light source; a light detector; and a control device. The light source irradiates a region of an object being conveyed with light, the region extending in a width direction. The light detector detects emitted light that has transmitted through the object. The control device obtains information on a distribution of a relative thickness of the object in the width direction based on a detection result in the light detector. The light detector includes an image sensor and a lens array. The image sensor includes a plurality of pixels arranged in the width direction, and detects an intensity of the emitted light for each pixel. The lens array includes a plurality of lenses having an equal magnification and arranged along the width direction, and collects the emitted light and forms an image of the emitted light on the image sensor.

The utility model relates to a symmetrical double telecentric lens, and relates to the technical field of measurement and control instruments in accurate manufacturing. Comprising an incident lens group, an imaging lens group and a diaphragm. The diaphragm is arranged between the incident lens group and the imaging lens group, and the focal lengths of the incident lens group and the imaging lens group are the same; and the incident lens group and the imaging lens group at the two sides of the diaphragm are respectively provided with seven lenses with the same number. According to the invention, an object is imaged according to the object-image proportion of 1: 1 through a small number of lens groups, so that the vision is more visualized, the illusion of people or interpretation errors caused by image distortion due to an image magnification or reduction mode are reduced, the authenticity is improved, and people can easily distinguish detail features of the object on a large-target-surface sensor. The problems that the number of built-in lenses of an existing lens is large, the magnification and imaging stability are insufficient, and the requirement for high precision cannot be met are solved.

The utility model belongs to the technical field of optics, and particularly relates to a large-magnification infrared beam expanding and focusing lens, which comprises a first lens, a second lens, a third lens and a fourth lens which are sequentially arranged along the propagation direction of a light path, the total length of the large-magnification infrared beam expanding and focusing lens is 110mm, and the distance between the first lens and the second lens is 0mlt; l1lt; 2 mm; the distance between the second lens and the third lens is 23 mlt; l2lt; 25 mm; the distance between the third lens and the fourth lens is 52 mmlt; l3lt; 54mm, 54mm; the full field of view of the large-magnification infrared beam expanding and focusing lens is + / -0.1 degrees, the entrance pupil diameter is 60mm, and the exit pupil diameter is 7.5 mm. The total optical length of the lens is short, the number of the lenses is small, the lens has the 1550 nm wavelength signal transmitting and receiving functions at the same time, and the size and weight of an optical system are reduced; all the lenses adopt standard spherical lenses, so that the development and processing cost is reduced, and the processing, detection and adjustment difficulty of the lenses is reduced.

A cabinet including a cabinet box, at least one door coupled to the cabinet box to form a storage compartment and an accessory system comprising a track and an adjustable mirror, wherein the track is mounted to an inner surface of the at least one door and the adjustable mirror is configured to slidably engage the track.

To provide a zoo lens which has a large aperture ratio and a minimized total length, offers less shift in the center of gravity while zooming and focusing and quiet autofocusing, and is suitable for video shooting.SOLUTION: A zoom lens of the present invention consists of a first lens group G1 having negative refractive power, an intermediate lens group GM having positive refractive power as a whole, a rear lens group GR, and a final lens group GN arranged in order from the object side, the intermediate lens group GM consisting of three or more lens groups including a focusing lens group configured to move along an optical axis while focusing from infinity to a short distance, and the rear lens group consisting of one or more lens groups. When zooming from the wide-angle end to the telephoto end, distances between the lens groups change as the intermediate lens group GM moves toward the object side, increasing the distance between the intermediate lens group GM and the rear lens group GR. The first lens group G1 and the final lens gup GN are stationary while zooming and focusing.SELECTED DRAWING: Figure 1

A head-mounted device is provided that includes displays configured to display an image and to simultaneously display a magnifying window that presents a magnified portion of the image. The magnifying window lies in a magnification plane that is fixed relative to a user's head. One or more processors in the head-mounted device can be used to perform a first ray cast operation to identify an input point where a detected user input intersects the magnifying window, to obtain a remapped point from the input point, to compute a directional vector based on the remapped point and a reference point associated with the user's head, to obtain a shifted point by shifting the remapped point from the magnification plane to another plane parallel to the magnification plane, and to perform a second ray cast operation using the shifted point and the directional vector.

A variable magnification optical system consists of, in order from an object side, a front group, an intermediate group, and a subsequent group. The front group consists of two or fewer lens groups having a positive refractive power. The intermediate group consists of two or fewer lens groups having a negative refractive power. The subsequent group consists of a plurality of lens groups. A lens group of the subsequent group closest to the object side is a first subsequent lens group having a positive refractive power. Two or fewer focusing groups that move along an optical axis during focusing are disposed in the subsequent group. During magnification change, a lens group of the front group closest to the object side is fixed with respect to an image plane.

The invention discloses a semiconductor defect detection method and device, and the detection method comprises the steps: controlling the bright field illumination and the objective magnification, and obtaining the surface microstructure morphology of a to-be-detected sample; determining the process type of the sample to be detected based on the surface microstructure morphology, and automatically determining dark field illumination light intensity parameters of at least two groups of dark field light sources according to a preset mapping relation between the process type and the dark field illumination light intensity parameters; according to the tissue morphology of the sample, at least two dark field light sources with different incident angles are controlled to carry out dark field illumination on the sample to be detected from different directions, and scattered signal images corresponding to different dark field angles are obtained through at least two detectors respectively; and analyzing defect information of the to-be-detected sample based on the scattered signal images at the dark field angles. The detection method can be adaptive to defect detection of different process sheet types, can effectively improve the detection precision of defect diversity and directivity, improves the detection signal-to-noise ratio, and efficiently detects multiple different types of defects at the same time.

An information processing device configured to simultaneously display a plurality of frames indicating a plurality of zoom magnifications, respectively, in a camera on a display on which a through image is displayed.

The invention relates to the technical field of digital pathology acquisition, and discloses a digital pathology picture acquisition method. The method comprises the following steps: acquiring sample characteristic data such as thickness, dyeing degree and structural characteristics of a tissue sample to be detected, and determining initial image acquisition parameters including exposure time, image resolution and optical magnification; and meanwhile, environment condition data such as temperature, humidity and environment illumination intensity of a scanning environment are collected, so that whether the initial parameters are adjusted or not is judged. When adjustment is needed, collecting preliminary image data, extracting quality features including image definition, color accuracy and detail retention degree, calculating feature values, and comparing the feature values with historical image quality feature values in a historical database; and if the same characteristic value does not exist in the historical database, calculating the similarity, and adjusting the initial image acquisition parameters according to the comparison result or the similarity. According to the method, sample characteristics and environmental conditions are comprehensively considered, and the quality of the digital pathological picture is effectively improved.

The invention discloses an underwater measurement method based on a zoom camera and a laser diode, which adopts the zoom camera to measure a laser spot image and greatly expands the application scene of equipment. The lasers A, B and C are manufactured based on laser diodes, the linearity of power adjustment can be well guaranteed, and measurement errors caused by too bright or too dark laser spots in images shot by the camera can be effectively avoided. According to the underwater measurement method provided by the invention, not only can the distance of the target object be measured, but also the feature size of the target object can be measured; in the installation process of the underwater measurement device, an error measurement link of the installation position of the laser is added, and the error is fully considered when the feature size of the target object is measured, so that the measurement precision is improved. During calibration, the average value of the height of the triangle and the corresponding bottom edge ratio in the maximum magnification and minimum magnification states of the zoom camera is taken as an independent variable, so that the influence of magnification change on calibration precision is reduced.

The invention belongs to the technical field of infrared optics, and discloses a long-wave infrared continuous zooming microscope lens. The lens is provided with two lenses, namely a first lens and a second lens which are sequentially and coaxially arranged between an object plane and an image plane; the first lens is a meniscus positive lens of which the convex surface faces the image side, and the second lens is a meniscus positive lens of which the convex surface faces the image side; the first lens and the second lens can move between an object plane and an image plane so as to carry out high and low magnification switching. The long-wave infrared continuous zooming microscope lens can realize multi-magnification switching, and also has the characteristics of small number of lenses, large target surface and clear imaging; the working wave band is 8-12 [mu] m, the magnification factor is 0.2-0.6, the F number of the image space is 1.5, the number of pixels is 1280 * 1024, and the size of the pixels is 12 [mu] m.

The invention provides a method for correcting the layout of a photomask, and is applied to the technical field of semiconductors. According to the method and the device, a plurality of pixel graphs of which the interval lengths do not meet a preset range are screened out based on the interval lengths between adjacent pixel graphs, and then the key sizes of the screened pixel graphs are multiplied by N times according to different proportions, so that a plurality of first test photomasks are constructed; and then determining the optimal magnification ratio of the initial photomask based on the combination of the wafer data, the incremental limit suboptimal solution and the two-side clamping theorem, namely obtaining the target photomask, so that the unexpected effects are that the optimal magnification ratio of each pixel graph in the initial photomask can be rapidly determined only by using a small part of pixel graphs in the initial photomask, and the target photomask is obtained. The manufacturing efficiency and quality of the photomask and the space utilization rate of the photomask and the wafer are improved, and the manufacturing cost of the photomask is reduced.

The invention relates to the technical field of visual inspection in the optical module industry, and provides a method and a device applied to AOI (Automatic Optic Inspection). A low-magnification microscopic imaging module of the fixed shooting vision subsystem is controlled to carry out fixed shooting on a detection object on the object carrying platform to obtain a global image, and each flying shooting point position coordinate is positioned according to the global image; controlling a motion shaft to drive a flying shooting vision subsystem to move according to the coordinates of the flying shooting point positions, and performing flying shooting on the flying shooting point positions to obtain a plurality of local high-definition images; taking the global image as a background, and splicing the acquired multiple local high-definition images into a complete to-be-detected image; performing region cutting on the to-be-detected image according to the category of the to-be-detected object to obtain each region image; and judging the defect category of each regional image according to the defect characteristics, and generating a defect detection result. According to the method, the problem that the actual extraction of large-area defects is incomplete is solved, and the comprehensiveness and accuracy of detection are ensured.