21 results about "Grey scale" patented technology

The invention discloses a question and answer system knowledge base shunting method based on a weighted polling algorithm, and belongs to the technical field of artificial intelligence retrieval enhancement generation. In order to overcome the defects of a single knowledge base architecture of a traditional RAG system in the aspects of multi-source knowledge management, gray updating and load balancing, a cluster architecture comprising a main knowledge base, an auxiliary knowledge base and a test knowledge base is constructed, and intelligent flow distribution is achieved through a flow distribution controller. The system adopts a multi-dimensional weight calculation model, fuses a user role coefficient, a knowledge base state coefficient and a performance coefficient, and dynamically calculates the weight of each knowledge base according to a weight calculation formula; using a weighted polling algorithm to accurately distribute user requests; and automatically adjusting the weight of the knowledge base in the gray scale test period. The vector retrieval module converts questions into vectors to retrieve in a target library, and a result fusion engine resolves multi-library answer conflicts through weighted voting. After the method is applied, the update failure rate of the knowledge base is reduced from 25% to 5%, the question and answer accuracy is improved by 22%, and the response speed is improved by 40%.

The invention discloses an experimental animal intracerebral target accurate injection system and method based on artificial intelligence and ultrasonic guidance, and relates to the technical field of target injection, the system comprises an ultrasonic probe for emitting ultrasonic waves, receiving experimental animal craniocerebral echo signals and outputting radio frequency signal data; the image processing module is used for executing time gain compensation and beam forming on the radio frequency signal data and outputting gray scale image data and blood flow image data; the artificial intelligence reasoning module is used for inputting the gray-scale image data and the blood flow image data into a convolutional neural network model and outputting corresponding coordinates; the path planning unit is used for generating an entry point coordinate, an angle parameter and a depth parameter through an optimization algorithm; the puncture guide frame adjusts the spatial position of the puncture needle according to the angle parameter and the depth parameter; and the needle point tracking unit is used for calculating a deviation value between the needle point coordinate and a preset track and generating an early warning signal. The problem of inaccurate positioning caused by individual difference in a traditional method is fundamentally solved.

A mail signature verification system employs a software that is configured to remove pixels of a digital photograph taken of a signature through an opaque security window. The mail piece can be signed and then the signature is covered with the signature cover having a security window therein. The signature reading station of a mail processing machine compresses the security window against a press plate and illuminates the signature with a light element while taking the digital photograph. The software then analyzes the digital photograph to remove pixels having a grey scale value below an upper grey scale threshold and remove pixels above a lower grey scale threshold, thereby rendering a signature with these darkest of pixels over the lightest of pixels.

The disclosure provides a gamma adjustment method, a computer readable storage medium and a computer program product. The gamma adjustment method comprises the following steps: obtaining a model of a to-be-tested module, determining a target model corresponding to the model and an error probability density distribution function according to the model, the target model being used to represent a mapping relationship between a gamma register value and a target influence factor, and the error probability density distribution function being used to represent an error distribution between a predicted gamma register value output by the target model and an actual gamma register value; obtaining a target influence factor value when the to-be-tested module displays a target gray scale picture, and inputting the target influence factor value into the target model to obtain a first gamma register value; detecting whether a display picture of the to-be-tested module meets a requirement when the to-be-tested module performs gamma adjustment by using the first gamma register value; and when the display picture does not meet the requirement, adjusting the first gamma register value by using the error probability density distribution function until the display picture meets the requirement.

The application discloses a kind of based on RIS model and QoS constraint MU-MISO system energy efficiency optimization method, comprising: constructing RIS assisted channel model;According to RIS assisted channel model, actual discrete RIS power consumption model is constructed;System total power consumption model is constructed;The joint optimization problem with system weighted energy efficiency maximization as target and meeting quality of service constraint and maximum transmit power constraint is constructed;Optimize beamforming matrix using improved gradient descent algorithm;Optimize the genetic algorithm of grey scale coding discrete phase shift matrix;Judge whether the joint optimization problem converges, if convergence, then output the optimal solution obtained at present, obtain maximum energy efficiency, optimal phase shift matrix and RIS phase configuration;Otherwise, re-iterative optimization beamforming matrix and discrete phase shift matrix, until the joint optimization problem converges or reaches maximum iteration number.The application significantly improves system energy efficiency while ensuring user QoS by jointly optimizing beam matrix and RIS phase configuration.

The application belongs to the technical field of medical information processing, and discloses a kind of intelligent versioning construction, grey scale updating and batch repair method of medical equipment report analysis template, creates an independent analysis template object for each report format of each kind of specialized medical equipment, and all template objects are stored in central template library in versioned form and indexed;When a new format report that cannot be parsed or optimization of existing templates is required, start the dynamic updating process;When it is found that there is a parsing logic error in a published template version, start the repair process;And deploy intelligent scheduling, fault tolerance and recovery mechanism and anti-repetition processing mechanism, etc.The application not only realizes the standardization, versioning construction and centralized storage of analysis templates, but also realizes the grey scale release and hot update of templates, and automatically locates and batch repairs historical data based on template version number, forming a complete management closed loop of template testing, release, monitoring and rollback.

A system (7) is a mobile electronic device, for example a smartphone, and includes a ToF device (1), an image sensor (5), and circuitry (6). The ToF device (1) includes an illuminator (2) to emit light spots (11) to a scene (9) which includes an object (10), a ToF camera module (3) to obtain ToF data of the scene (9), and a controller (4) to control the ToF device (1) to perform a ToF measurement to obtain the ToF data. The ToF device (1) preferably uses one or more macropixels which are configured according to light spots (11) or light patterns emitted by the illuminator associated with the macropixel. The image sensor (5) captures a color image of the scene (9) to obtain RGB or grey scale image data. The position and orientation of the image sensor (5) and the ToF camera module (3) against each other is fixed and calibrated. The circuitry (6) segments the image to obtain image segments. The ToF device (1) preferably detects peaks in the macropixel histograms and calculates, for each macropixel histogram, the distances for the peaks. The ToF device (1) outputs the ToF data including one or more macropixel histograms corresponding to the configured one or more macropixels to the circuitry (6) which then processes the one or more micropixel histograms. The circuitry (6) matches the calculated distances with the image segments. A machine learning algorithm, preferably a trained neural network, may be used to match the distance information with the image segments.

A method, apparatus, device, and medium for compensating brightness. The method includes: arranging a plurality of first anchor points and at least one fixed anchor point in a display area of a display panel; dividing the display area of the display panel into a plurality of adjustment areas each including at least one of the first anchor points, and determining a first compensation gain for each of the adjustment areas under a grey scale image to be compensated; determining a second compensation gain corresponding to the first anchor point according to a brightness value corresponding to the first anchor point, a brightness value corresponding to the fixed anchor point, and the first compensation gain of the adjustment area to which the first anchor point belongs; and performing brightness compensation on a pixel corresponding to the first anchor point according to the second compensation gain.

The application relates to an engineering view proportion and size checking method and device, computer equipment and a storage medium, which comprises the following steps: S1, obtaining an engineering view picture to be compared; S2, performing gray scale processing on the picture; S3, performing black-and-white binary processing on the picture on the basis of the gray scale image; S4, traversing each row and column pixel point of the black-and-white binary picture, obtaining the pixel width and the pixel height of the picture, and the ratio of the pixel width to the pixel height; S5, comparing with the judgment basis, judging whether the size and the proportion are distorted, and outputting the judgment result. The application can compare and judge the corresponding proportion and size of multiple engineering view pictures, ensure that the proportion parameters of the views remain the same, so that the views can correctly express the original design. The operation process is simple, the automation of the engineering view proportion and size checking is realized, the accuracy and the efficiency of the checking are improved, and therefore the overall quality of the engineering design is improved.

A method and electronic device for evaluating local contrast are disclosed, relating to the field of image measurement technology. The electronic device acquires a first image, which is an image captured on a test chart based on first shooting parameters under a first test environment. The test chart includes a grayscale chart. The electronic device then determines first data corresponding to each adjacent gray block in the grayscale chart; the first data characterizes the brightness difference between the corresponding adjacent gray blocks in the first image. Furthermore, the electronic device determines a first quantization parameter based on the difference between the first data and the second data corresponding to each group of adjacent gray blocks; the second data characterizes the theoretical brightness difference between adjacent gray blocks; and the first quantization parameter is used to evaluate the local contrast of the first image. By using a quantization method with the electronic device to evaluate local contrast, the interference of subjective perception is avoided, improving the objectivity and accuracy of the evaluation.

The invention relates to the technical field of airborne meteorological radar detection, and discloses an airborne meteorological radar terrain mode reflection intensity compensation display method, which comprises the following steps of: removing noise and abnormal echoes in a signal through a preprocessing step, and ensuring the accuracy and reliability of a radar echo signal; the accuracy of the radar echo intensity is gradually improved through the steps of distance compensation, lower visual angle compensation and antenna gain compensation; under the condition of considering the influence of topographic factors on radar echoes, the radar echo intensity can reflect topographic features more truly by adopting incident angle compensation. And finally, the processed radar echo intensity is quantized to a gray scale range, and pseudo color setting is carried out. Through the above steps, accurate compensation and display of the radar echo intensity in the terrain mode of the airborne meteorological radar are realized, the accuracy of calculation of the radar echo intensity is improved, the display mode of the radar is optimized, the details of the terrain contour are enhanced, and the recognition capability of a pilot on a typical region is improved.

This invention provides a method for digitally identifying anomalies in semiconductor test pieces during material / fault analysis, comprising the following steps: S1: Passive VC mode inspection of the semiconductor test piece using a scanning electron microscope (SEM) to obtain a SEM PVC image; S2: Preparing a layout diagram of the original semiconductor test piece design on the metal contact layer; S3: Data processing of the SEM PVC image and the layout diagram; S4: Fault analysis. This invention utilizes digital processing to obtain SEM PVC images, analyze grayscale values, and automatically compare them with the original design layout diagram, marking discrepancies with prominent red asterisks to easily identify the location of faulty transistors. The judgment method is intuitive, with accuracy and correctness far exceeding that of human visual image recognition, avoiding errors in human judgment, accurately identifying the brightness of different transistors, improving the yield of material / fault analysis, and effectively enhancing the quality and success rate of material / fault analysis.

A system and method for denoising a grey scale image of a pattern on a substrate, including: scanning a gaussian beam consecutively across scanlines extending along an x direction, wherein the scan lines are disposed adjacent to each other in a y direction within a predetermined region of the pattern, obtaining waveforms from secondary electrons and backscattered electrons reflected from the scanned pattern; converting the waveforms into a grey scale image, and applying a gaussian weighted distribution for each of the scan lines of the grey scale image and the neighboring scan lines of the grey scale image to account for the impact of the neighboring scan lines to each scan line.

A processing method for enhancing the image quality of an image, more particularly a digital medical grey scale image, that comprises the steps of a) decomposing an original image into multiple detail images at different resolution levels and / or orientations, b) processing the detail images to obtain processed detail images, c) computing a result image by applying a reconstruction algorithm to the processed detail images, said reconstruction algorithm being such that if it were applied to the detail images without processing, then said original image or a close approximation thereof would be obtained, the processing of the detail images comprises the steps of: d) calculating at least one conjugate detail image, and e) computing at least one value of the processed detail images as a function of said conjugate detail image and said detail images.

The application discloses a kind of based on dot matrix code micro perturbation anti-fake method and system, it is related to information coding field, comprising: by gathering anti-fake object information to generate binary dot matrix image, extract initial seed and store in database after SM4 algorithm encryption and associate object identification;Original image is enlarged and divided into checkerboard, to generate random perturbation parameter with encryption seed, the dot matrix in specified grid is controlled in direction, amplitude and is adjusted with grey scale, and generates the anti-fake dot matrix containing secret micro perturbation;According to material, select corresponding process coding and solidification, extract the code in image and micro perturbation characteristics when verifying, compare with database encryption record.This application has the advantages that: based on dot matrix code micro perturbation anti-fake method adapts to a variety of materials and scene, generates unique micro perturbation seed by SM4 encryption, realizes hidden difficult-to-copy perturbation characteristics, combined with core coding and micro perturbation characteristics double check, realize accurate anti-fake and whole-process closed loop, practicality and security are outstanding.

The invention discloses a release film production detection method and system, and relates to the field of release film performance detection. Comprising a hardware entity terminal and a software control platform. The microscopic thickness change of silicone oil coating can be clearly captured through high-resolution imaging, the detection sensitivity is ensured, and in addition, the optical contrast ratio of uneven coating is enhanced by adopting a double-light-source scheme (white light and ultraviolet light); 5-degree inclined installation avoids mirror reflection interference and ensures stable image quality; and objective and quantitative defect judgment is realized through FFT (Fast Fourier Transform) frequency domain analysis and a high-frequency energy ratio threshold value in an algorithm level. And in the judgment process, noise suppression (Gaussian filtering) retains key textures, so that misjudgment is avoided. Edge interference is eliminated through ROI extraction, and the analysis accuracy is improved. The influence of uneven illumination is eliminated through gray normalization, and the robustness of the algorithm is enhanced. The problems that in the prior art, a direct detection method or an indirect detection method is not timely in feedback and cannot directly correspond to the coating amount due to interference of various factors are solved.

This invention relates to a grayscale printing control method for thermal printers and a thermal printer itself. The grayscale printing control method includes: Step 1, sending the dot line data to be printed to the thermal print head; Step 2, latching the dot line data, outputting a heating enable signal to heat the valid heating points corresponding to the valid dot data in the dot line data, and starting a timer; Step 3, removing the valid dot data of the first gray level from the dot line data, setting the initial value of j to 1, updating the dot line data, and sending it to the thermal print head again; Step 4, when the heating timer expires, re-latching the dot line data, re-outputting the heating enable signal to heat the valid heating points corresponding to the valid dot data in the dot line data; Step 5, determining if j equals j. If yes, the process ends; otherwise, incrementing the value by 1 and updating the j value, then returning to Step 3. This method precisely controls the heating energy of the heating points, ultimately improving the printing effect of the thermal printer on grayscale data.

The invention provides a Gamma correction method and system based on a genetic algorithm, and the method comprises the steps: S1, collecting individual parameters, and generating a gray-scale curve; s2, preliminarily optimizing the gray scale curve to obtain a preliminary optimization result; and S3, performing iterative optimization through a genetic algorithm to obtain a final optimization result. The invention provides a multi-objective collaborative optimization framework based on a genetic algorithm, carries out global optimization on digital driving parameters, and aims to synchronously improve the linear response precision of a gray-scale curve through an optimization algorithm.

The invention relates to the technical field of medical imaging and signal processing, in particular to an automatic real-time envelope line drawing method of ultrasonic equipment in a PW mode and the ultrasonic equipment. RF data are collected through an ultrasonic probe, and log compression and baseline translation processing are carried out to form gray scale data; calculating mathematical expectation and variance of noise through a noise evaluation module; a boundary calculation module obtains a boundary for each frame of image data to separate an upper envelope line and a lower envelope line; the signal extraction module extracts a signal main body part and removes noise; the envelope line calculation module determines edge points of an envelope line through accumulation and calculation, and a continuous and smooth envelope line is generated through quadratic curve fitting and a least square method. According to the scheme, the envelope line drawing precision and stability are effectively improved, noise interference is removed, efficient and real-time envelope line drawing is achieved, and reliable technical support is provided for ultrasonic equipment.

The invention relates to the technical field of ultrasonic diagnosis, in particular to an abdominal ultrasonic multi-modal image fusion analysis system which comprises a multi-modal space alignment module, an anatomical semantic structuring module, a multi-modal feature fusion and visualization module, a multi-parameter quantitative analysis module, a qualitative evaluation matrix construction module and an intelligent report generation module. By taking the gray-scale ultrasound image sequence of the target abdominal region as a space reference, aligning the elastography and ultrasound contrast sequences to obtain a multi-modal image set; mapping an anatomical structure, tissue hardness and blood perfusion information in the image set to a standard anatomical map to generate structured data; associating and visually coding the tissue hardness distribution information and the blood perfusion dynamic information to obtain a fused image; feature parameters of the fused image are analyzed and compared with a clinical threshold value to obtain quantitative parameters, and a qualitative evaluation matrix is constructed; summarizing qualitative evaluation indexes, quantitative parameters and structured description data to generate an analysis report; the efficiency of abdominal ultrasonic diagnosis analysis can be improved.