175 results about "Image processing software" patented technology

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

The invention relates to the technical field of substation defect detection, in particular to a substation defect detection method and system and a storage medium. The method comprises the following steps: acquiring a substation equipment image by adopting real-time image acquisition equipment, and establishing an equipment image database; performing denoising and edge detection through image processing software to generate preprocessed image data; detecting an abnormal area of the substation equipment through feature extraction and texture analysis, and training a defect recognition model; after real-time image information is input into the model, an abnormal defect area of the transformer substation is recognized, and fault risk gradient deterioration is estimated; calculating a risk index based on a pre-estimation result, and if the risk index exceeds a set threshold value, triggering an early warning function, providing defect types and positions, and suggesting repair measures; according to the invention, the transformer substation defect detection method is optimized, so that the transformer substation defect identification is more accurate.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

The invention discloses a blasting vibration monitoring method and system based on vision and vibration sensors, and relates to the technical field of blasting vibration monitoring. An aerial vision monitoring device is arranged at a set height right above a blasting point, and a vibration sensor array is radially arranged around the blasting point; and the visual monitoring device and the vibration sensor array are in wireless communication connection with the blasting vibration analysis module based on the computer. Omnibearing monitoring of the blasting process is achieved by combining the aerial vision monitoring device and the ground vibration sensor array, ground vibration data can be captured, and the scattering condition of fragments generated by explosion can be observed. An image feature recognition algorithm is used for analyzing an image captured by a high-speed camera, and visual evidence is provided for understanding the explosion effect. Complex vibration data and visual feature changes can be converted into charts and schematic diagrams which are easy to understand through image processing software and a data visualization tool, and non-professionals can conveniently and rapidly grasp key information.

The present invention relates to a non-destructive evaluation method for internal pores of an additive manufacturing titanium alloy test bar. The reconstructed image is subjected to filtering and noise reduction processing by Avizo image processing software, and then interactive threshold segmentation is performed to obtain the test bar contour image, and the gray-scale image of the sample with closed internal holes is obtained; the gray-scale image is subtracted from the test bar contour image to obtain a gray-scale image containing only holes; by setting a gray-scale threshold greater than the standard deviation of the gray-scale of the sample material in the image, gray-scale difference operation is performed on the gray-scale image containing only holes to remove noise, and a binary image is obtained. The present invention proposes a method for detecting the internal porosity of an additive manufacturing titanium alloy test bar by using micro-focus industrial CT, which overcomes the disadvantage that conventional ray detection cannot detect the internal micro-defects of an additive manufacturing titanium alloy test bar, detects and counts the geometric characteristics of the pores, and realizes the non-destructive evaluation of the internal micro-defects of an additive manufacturing titanium alloy test bar.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

The invention belongs to the technical field of hydrogen sulfide detection, and discloses a batch quantification method for bacterial endogenous hydrogen sulfide yield. Materials (qualitative filter paper, a 96-well plate and a lead acetate solution) used in the method are cheap commercially available consumables, a used gel imaging system is also a laboratory basic instrument, and Fili imageJ is widely used free image processing software. Therefore, the method has the advantages of low cost, simplicity in operation, capability of quickly quantifying in batches and the like. Besides, membrane covering of the qualitative filter paper enables each pore of the 96-pore plate to be relatively closed, and meanwhile, different from a color developing agent directly added into the bacterial liquid, the measuring position is located above the bacterial liquid, so that accurate quantification is achieved, and growth and metabolism of bacteria are not affected at the same time. The method not only can realize accurate quantification, but also can detect the yield of hydrogen sulfide of different bacteria in batches, and is convenient to popularize and apply.

The invention belongs to the technical field of visual inspection, and particularly relates to an industrial defective product detection method and defective product detection device.The industrial defective product detection method comprises the steps of S1, image collection, S2, image preprocessing, after image collection, image preprocessing to improve image quality, S3, key features in images are extracted through a computer vision algorithm, and S4, defect recognition and classification. S5, decision making and judgment: classifying the products through a processing system according to the identified defects or abnormal characteristics, and judging whether the products are defective products, S6, outputting results, judging whether the products are qualified or unqualified, and finally outputting qualified or unqualified judgment results, and the system is connected with a production line, automatically sorts the defective products or prompts an operator to carry out manual intervention. According to an image sensor, a light source, image processing software and an analysis algorithm, the product appearance and defects are recognized and classified, and through the image obtaining and processing technology, whether the product meets the design standard or not is detected in real time, and the problems of surface defects, shape inconformity, size out-of-tolerance and the like are recognized.

The invention relates to a binding material single particle local spatial evolution analysis method, and belongs to the technical field of civil engineering binding material microstructure characterization. The method comprises the following steps: acquiring back scattering (BSE) and characteristic X-ray energy spectrum (EDS) images of a sample; selecting a target gel particle based on the BSE image and intercepting a local area; identifying the reaction edge of the target gel particle; performing equal-width stepped strip division inwards and outwards by taking the reaction boundary as a starting point, and storing the mask; carrying out image operation on adjacent masks to extract strips, and carrying out statistical analysis on gray feature and element feature changes of each strip; according to the method, surrounding phase interference is avoided through local analysis, whole-process analysis is realized by adopting unified image processing software, a programming basis is not needed, the technical threshold is reduced, the operation process is simplified, the uniformity of strip division and the reliability of an analysis result are ensured, and the method is suitable for large-scale popularization and application. And a simple, convenient and effective technical means is provided for revealing the reaction mechanism and quantitative reaction activity of the cementing material.

The invention discloses a full-automatic electrochemical luminescence detector based on a photodiode, and relates to an electrochemical luminescence detector, the full-automatic electrochemical luminescence detector comprises a shell, the shell is internally provided with an optical signal acquisition module, a small packaging circuit board, an ECL chip, a man-machine interaction module and a chip inlet and outlet device; a light current detection unit, an electrochemical reaction excitation unit and a microcontroller are arranged in the small packaging circuit board; wherein a test strip sample pad and a reaction area are arranged in the ECL chip. The photodiode used in the invention can make a quick response to the change of light intensity, which is far faster than the frame capturing speed of the camera, and the demand and complexity of subsequent data processing are reduced, so that the system is easier to realize automation. Compared with a camera, the photodiode is lower in hardware cost, does not need to use complex image processing software, and is suitable for household use. The detector is compact in structure, small and exquisite in appearance and convenient to use in a handheld mode and carry about.

The invention relates to the field of intelligent detection, and provides a slub yarn fabric process detection method and system based on computer vision, and the method comprises the steps: firstly obtaining a plurality of local grayscale images of a slub woven fabric through a digital image collection device, and then carrying out the feature-based global analysis of the images to generate a complete slub yarn fabric image; the method comprises the following steps of: firstly, acquiring an image of the slub yarn fabric, marking and positioning slubs in the image through image processing software, connecting adjacent slubs, recording position coordinates of a starting point and an ending point of each connected slub, and finally detecting key process parameters of the slub yarn fabric by using a specific slub parameter calculation method according to the coordinate data. Therefore, the method can better adapt to different fabric types and complex environmental conditions in detection, and is beneficial to improving the precision and reliability of bamboo joint parameter detection.

The invention provides a method for in-situ measurement of an internal stress state of an ultrathin film surface by using RHEED, and relates to the technical field of condensed state substance structure detection, and the method comprises the following steps: epitaxially growing an ultrathin film on a substrate by using film growth equipment; irradiating the ultrathin film by using an RHEED electron beam to obtain a diffraction pattern, and obtaining characteristic parameters of the diffraction pattern; obtaining the lattice constant of the ultrathin film through the characteristic parameters of the diffraction pattern; based on the lattice constant of the ultrathin film, the stress type and strain borne by the ultrathin film are determined. According to the method, the distance between diffraction fringes in a diffraction pattern is accurately extracted from a simple RHEED image, the lattice constant from the diffraction pattern is calculated, the stress state of the ultrathin film is accurately judged by comparing lattice constants in a stress-free state, existing equipment does not need to be greatly modified, and the method is simple and convenient to operate. The method can be realized only by using the existing RHEED electron beam and image processing software.

The invention discloses an embroidery positioning printing method based on machine vision, electronic equipment and a computer readable storage medium, and relates to the technical field of embroidery printing, basic data of a camera and a printer are obtained, the camera is connected to an upper computer, and if the camera is used for the first time, a calibration process is executed to complete starting point binding and distortion correction of the camera and the printer; selecting template mapping positioning or template deformation mapping positioning according to matched material characteristics, intercepting a printing area image as a template, and extracting feature points for positioning; positioning the logo image and the template map, and adjusting a local form into a logo template by using image processing software; finally, the logo template and material position information are transmitted into a program and mapped to a blank TIF image, the blank TIF image is transmitted into a printer to complete positioning printing after PRN processing, the steps of calibration parameter calculation, stretching and compression scale factor calculation, rotation angle adjustment and the like are involved, coordinate optimization, color calibration and anti-aliasing processing are further conducted on the mapped image, and accurate embroidery positioning printing can be achieved.

The invention provides a design method for checking dislocation between layers of a multilayer circuit board, which comprises the following steps of: designing an intelligent positioning identifier at a board corner of each layer, capturing an SPM high-definition image, transmitting the image to a central control system through a high-speed network, designing special image processing software to automatically identify the SPM, and extracting concentric circle and rectangular bar code information; the method comprises the steps of calculating relative position deviation between layers, preprocessing original image data, converting the original image data into structured offset data, establishing a real-time data analysis platform, generating a detailed interlayer offset report, setting a threshold value alarm mechanism, providing a visual interface to display the state and historical trend of a production line, and obtaining a real-time data analysis result based on real-time data analysis. A machine learning algorithm is adopted to predict an offset trend, subsequent process parameters are optimized, interlayer offset in a final finished product is reduced, a dynamic process control system is introduced, operation parameters of production equipment are automatically adjusted according to real-time feedback, and production stability and precision are ensured.

The invention discloses an OpenMC-based BNCT dose full-process automatic calculation output method, and particularly relates to the technical field of boron neutron capture therapy dose calculation, and the method comprises the steps: reading a DICOM-CT image, automatically completing HU value segmentation, material assignment and voxel grid modeling, and generating an OpenMC geometry and material input card; setting a neutron / photon source, an operation mode and a counting grid, and executing Monte Carlo transport calculation; an ICRP flux-dose conversion coefficient library is built in, and dose calculation is automatically completed; the dose field is written into an Rt dose file, and the Rt dose file can be directly imported into mature medical image processing software for visual evaluation and plan optimization. According to the method, end-to-end automation from the CT image to the clinical available dose file is achieved, manual intervention is not needed, the BNCT dose calculation efficiency, precision and standardization level are remarkably improved, and a reliable tool is provided for BNCT dose simulation research.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

The application relates to a scanning electron microscope measurement method for the thickness of a metal compound layer, which comprises the following steps: obtaining a cross section containing the compound layer by wire cutting, and polishing after inlaying; observing under a scanning electron microscope, selecting a copper-tin alloy compound layer to be measured, selecting a backscattering electron probe to obtain a composition contrast image, adjusting the image contrast so that the measured object and the matrix have obvious differences; selecting a magnification of 2500 times matching the thickness of the metal compound layer, obtaining a high-definition backscattering electron image at a scanning speed of 28 seconds / frame; and quantitatively and finely measuring the thickness of the metal compound layer by using ImageJ software. The advantages of the application are as follows: the metal compound layer is extracted by using the ImageJ image processing software, the area is calculated to obtain the average thickness of the film thickness measurement method, not only the accurate alloy layer thickness information is obtained, but also the standard deviation value of the measured object is obtained to evaluate the uniformity of the measured object; the measurement method improves the accuracy and can be applied to detection and analysis practices.

This invention provides a method for determining the carbon dioxide huff and puff mechanism in fractured reservoirs, belonging to the technical field of determining the carbon dioxide huff and puff mechanism in fractured reservoirs. This invention establishes a unified digital core by selecting outcrop cores to create cast thin sections and employing multi-scale fusion reconstruction technology. Topological connectivity is evaluated based on a seepage topological invariant fracture network connectivity evaluation algorithm. During well shut-in, a diffusion-convection hybrid encoding / decoding model is used to predict migration in real time, and the model learning rate is adjusted by a dynamic learning rate adjustment function. After well shut-in, a feedforward-feedback composite control strategy is used to gradually reduce back pressure to complete the production stage. The experiment ends after cleaning the chip with anhydrous ethanol. Finally, the degree of crude oil recovery is statistically analyzed using image processing software. This invention solves the technical problem of not being able to predict the migration process in fractures and matrix of fractured reservoirs in real time during well shut-in.

This invention provides a method for measuring pulsed laser parameters based on titanium nanofilms, belonging to the field of pulsed laser parameter measurement methods. The method first prepares titanium nanoparticle ink; then, a titanium deposition layer is prepared by inkjet printing or spin coating; finally, the titanium deposition layer is placed within the laser scanning range, a single-point or line scanning mode is set, and images of the sintered titanium region are recorded. The corresponding laser parameters are obtained through image processing software analysis. This method can intuitively, conveniently, and cost-effectively obtain key pulsed laser parameters, and can accurately obtain parameters such as spot size and repetition frequency.

The invention relates to the technical field of fiber reinforced resin-based composite materials, and particularly discloses a quantitative characterization method for the wettability of a unidirectional fiber reinforced resin-based prepreg. The method comprises the following steps: cooling a prepreg sample in a refrigerant until the temperature is lower than the glass-transition temperature of a resin matrix by 50 DEG C or above, shooting and imaging by adopting a microscope, identifying and calculating the areas of a resin infiltration area and a resin non-infiltration area through image processing software, and further calculating the infiltration degree of the prepreg. According to the method, the defect that the infiltration degree is judged according to experience in the prior art is overcome, and key parameter support is provided for research and development of the prepreg.

The invention discloses an in-situ detection method of active oxygen. The in-situ detection method comprises the following steps: attaching an active oxygen composite membrane prepared on the basis of a ratio-type fluorescent probe to a to-be-detected area to react with active oxygen; capturing a green light signal on the active oxygen composite film by using a digital camera equipped with a 520-540nm narrow-band filter to obtain a picture A; capturing a red light signal on the active oxygen composite film by using a digital camera equipped with a 640-660nm optical filter to obtain a picture B; performing digital processing on the picture A and the picture B by using image processing software, respectively acquiring a numerical value (G) of a green light channel acquired by the picture A and a numerical value (R) of a red light channel acquired by the picture B, and calculating relative fluorescence intensity (FI) as an active oxygen response value; and substituting the active oxygen response value (FI) into an active oxygen concentration quantitative standard curve to obtain the concentration of the in-situ active oxygen. According to the invention, the stability of a fluorescence signal can be improved, the problem of environmental disturbance is solved, and meanwhile, the spatial resolution and the soil universality are improved.

The invention relates to a method for quickly and accurately acquiring a radiation treatment irradiation field, which comprises the following steps of: (1) positioning a patient, and adjusting an irradiation angle and distance from an accelerator or a simulation positioning machine, a treatment bed or a positioning bed to an electronic wire; (2) the bearing supporting plate I or the bearing supporting plate II is installed on a small machine head of an accelerator or a simulation positioning machine; (3) turning on a field lamp of an accelerator or a simulation positioning machine, and connecting a wireless camera assembly with the bearing support plate I or the bearing support plate II; (4) ensuring that the position of the bearing plate enables the cross shape of the projection center of the beam lamp of the accelerator or the simulation positioning machine to coincide with the positioning cross shape above the outer part of the box type cover plate; (5) turning on a power supply and a switch of the wireless camera assembly; and (6) starting the handheld tablet personal computer and image processing software thereof, starting to receive an image of the skin electron beam irradiation field, tracing through a capacitance pen, automatically processing the image, and then sending the image to a wireless network printer for printing. The method is simple and efficient in operation process, and the size of the obtained electron beam irradiation field is accurate.

The invention discloses a picture processing method based on rapid batch photographing and printing, and relates to the technical field of image processing and intelligent equipment manufacturing, and the method comprises the following steps: S1, building a picture processing folder, and presetting a picture processing execution action; s2, performing picture shooting through a camera, and performing serial number coding according to picture shooting information; s3, according to the serial number codes of the pictures in the step S2, carrying out preset processing on the pictures by utilizing image processing software; and S5, after the picture processing is completed, sending the picture data to the printing equipment, and executing the processing action of the next picture at the same time. The picture processing action is performed in real time in the picture data sending process, and the data of the next picture is processed in the time period when the picture data is sent to the printer for printing, so that the photographing, picture processing and printing efficiency is improved, the load balance of equipment is realized, and the picture data is acquired according to the photographing time. And orderly processing of batch pictures and data transmission are realized.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

The invention relates to a conformity control installation (1a) for a manufacturing line of cast concrete segments comprising at least one mold (2) including a base (3) and side walls (4, 5) and means (30) for automated in-person and dimensional control of said mold (2) before the pouring of fluid concrete into it, said means comprising a movable digital image acquisition element (33) for extracting a plurality of predetermined control points, and a computer terminal (40) integrating image processing software that retrieves the plurality of captured points to generate a three-dimensional map of the inside of the mold in the form of a point cloud and then compares this map with a digital reference model in order to detect any geometric differences and indicate whether the mold conforms to said model. Figure for the abstract: Fig. 3

The present invention is a method for identifying the spatial distribution of microplastic-polluted waters based on remote sensing, specifically relating to the technical field of environmental monitoring. It solves the technical problems that it is difficult to analyze various characteristic data of microplastics through image processing software, and it is also difficult to comprehensively construct a model to output the comprehensive pollution degree value of waters, and there is a lack of a technology for combining the model prediction value with GIS technology to identify the spatial distribution. The method includes the following steps: extracting 70% of the sample data in the target waters for preprocessing; screening out the samples with the microplastic abundance not less than the average abundance of microplastics in the target waters; extracting characteristic data from the remote sensing image, including the total color adsorption ability degree, the total shape coverage ability degree, and the total water turbidity degree; using the characteristic data to construct a model to obtain the predicted value of the comprehensive pollution degree of waters; using GIS technology to generate the spatial distribution of the predicted value of the comprehensive pollution degree, and using different colors to represent different pollution degrees.

This invention relates to the field of building material ceramic performance testing technology, specifically a method and application for testing the wear resistance of glaze surfaces, comprising the following steps: S1, cutting out the glazed area as a sample, washing it, and drying it to constant weight; S2, pre-test photography: determining the measurement area on the sample, observing and photographing the measurement area using a microscope, and obtaining the initial dark area ratio η0 of the measurement area using image processing software; S3, grinding test; S4, sample post-treatment: after reaching the pre-adjusted rotation speed n, removing the sample, cleaning it, and drying it to constant weight; S5, post-test photography, obtaining the dark area ratio η of the measured area surface after grinding. n S6. Calculate the wear area ratio Δη of the measurement area, plot Δη against the grinding revolution number n, and take the lowest value among the grinding revolutions corresponding to the wear area ratio Δη reaching 33.3% or above as its wear resistance revolution number, so as to solve the problem that the current test of the wear resistance of glaze is difficult to quantify and has a large human error.

The invention belongs to the technical field of unconventional oil and gas development, and particularly relates to a gas-water-rock reaction and particle dissolution-migration in-situ visual quantitative determination method and device based on a micro-fluidic chip. The quantitative determination method comprises the following steps: firstly, designing a chip model containing a real rock core, wherein factors such as a strong heterogeneous structure of the compact conglomerate oil reservoir and strong difference of a pore throat structure are considered at the same time; then, the gas-water-rock reaction and the particle dissolution-migration process are recorded through an optical camera; and finally, analyzing contribution degrees of different minerals to a gas-water-rock reaction and judging different corrosion modes of the conglomerate by combining image processing software and a mathematical model. The method can be used for carrying out in-situ visual quantitative determination on gas-water-rock three-phase reaction, particle corrosion and a secondary migration process in the conglomerate reservoir under the conditions of oil reservoir temperature pressure and fluid chemistry.

The application discloses an integrated digital microfluidic plasmonic metasurface chip biological image detection system, and belongs to the field of microfluidic and metasurface biological image sensing. The system comprises a digital microfluidic chip, a plasmonic metasurface chip, a light source, a CMOS image sensor and a control circuit. The digital microfluidic chip is provided with a driving electrode array, a medium layer and a hydrophobic layer, and is used for constructing a liquid path and controlling droplets. The plasmonic metasurface chip is combined with the digital microfluidic chip to form a detection site, and is used for detecting biomolecules by using a plasmonic resonance effect. The light source is used for exciting plasmonic resonance. The CMOS image sensor is used for capturing images at the detection site. The control circuit is used for controlling electrodes of the digital microfluidic chip, and realizes construction of the liquid path and control of the droplets. The biomolecule solution to be detected can be accurately guided to the detection site of the plasmonic metasurface chip, the light source is used for exciting plasmonic resonance, and the CMOS image sensor is used for capturing images. Image intensity changes are analyzed by using image processing software, and a detection result of the biomolecules is obtained.