255results about How to "Increase contrast" patented technology

The invention discloses a calibration method of a polarization focal plane imaging system and an imaging system, relates to the field of photoelectric imaging and remote sensing detection imaging, and solves the problems of low correction efficiency and difficulty in correcting a system with a changed polarization state in the conventional polarization error correction technology. According to the calibration method, a plurality of coding patterns and corresponding polarization modulation matrixes are obtained based on the collected uniform light field and serve as calibration results. The polarization error correction method comprises the steps of obtaining an observation intensity vector based on a target scene; a corresponding polarization modulation matrix is obtained based on the coding pattern according to a coding polarization modulation matrix lookup table, and then a down-sampling Stokes vector after polarization error correction is obtained; and completing the correction of the polarization error through an imaging reconstruction method. A polarization focal plane imaging system comprises an imaging lens, a DMD digital micromirror array coding module, a focal plane DoFP polarization detector and an imaging reconstruction module. The method is suitable for the fields of remote sensing detection, target identification, environment monitoring and the like.

The invention discloses a frequency modulation and wavelet sub-band guided double-domain collaborative Transformer X-ray image denoising method, which comprises the following steps of: acquiring a noise-containing digital ray original image and a corresponding clear reference image, and constructing a data set after preprocessing the noise-containing digital ray original image and the corresponding clear reference image; constructing a network model of a double-domain collaborative coding-decoding architecture; performing 3 * 3 deep convolution on an input image to extract shallow layer features; in the encoding stage, ETB and AFMB are alternately stacked to represent local and global information, a WB-LKED module is embedded to strengthen fine-grained features, and WDB executes down-sampling and transmits high-frequency features to a decoding end; in the decoding stage, the WUB recovers the resolution through double-path up-sampling, integrates the same-scale features of an encoder, enhances details by using high-frequency features, splices the features, then carries out ETB and AFMB refining, obtains output features through 3 * 3 deep convolution, and combines a global residual error connection optimization result; and training the model by using the data set, inputting a to-be-denoised image, and outputting a final result. According to the method, the problems of weak complex noise interference resistance, poor detail retention effect and limited CNR improvement can be solved.

The invention discloses an image fusion method based on a double-branch feature decoupling auto-encoder, and belongs to the field of computer vision and image processing. According to the method, for the problems of modal pollution and structural distortion in infrared and visible light image fusion, structural semantic information and high-frequency texture details of a source image are extracted respectively by constructing a content feature coding module and a detail feature coding module, and feature decoupling is achieved. And performing deep fusion on the decoupled features by using an adaptive feature weighting mechanism, and reconstructing a fused image with infrared target saliency and visible light detail definition through a shared decoder. According to the method, an end-to-end two-stage training strategy is adopted for optimization, complex prior or post-processing is not needed, the effects of improving the fused image contrast, edge preservation and target recognition performance are remarkable, and the method is suitable for the fields of weak light monitoring, intelligent perception, unmanned system navigation and the like.

The invention provides a wooden door three-dimensional model parameterization design and numerical control code generation method and system, and relates to the technical field of woodworking numerical control machining and computer vision. A multispectral imaging technology is adopted at a raw material feeding station to obtain a wood board surface multiband image, and a high-definition wood characteristic spectrum is generated through algorithm processing; establishing a mapping rule base of the atlas and numerical control parameters in combination with historical data; the map and the three-dimensional embossment model are superposed, and a tool path and cutting parameters are adaptively adjusted according to texture features to avoid defects and optimize along grains; and finally, numerical control codes matched with wood characteristics are generated, the rotating speed of the main shaft is adjusted according to the hardness, a numerical control machine tool is driven to complete high-precision wooden door machining, and precise numerical control machining based on wood surface characteristic intelligent recognition and self-adaptive adjustment can be achieved.

The application provides a training method and device of an image enhancement model, electronic equipment and a storage medium, and relates to the technical field of image processing. The method comprises the following steps: generating a low-illumination sample image corresponding to each normal-illumination sample image in an initial image data set according to the normal-illumination sample image, and generating a first training data set according to each normal-illumination sample image and the low-illumination sample image corresponding to the normal-illumination sample image; performing image mask extraction according to a target object in each normal-illumination sample image to obtain target mask information corresponding to each normal-illumination sample image; and training an image enhancement model according to the first training data set and the target mask information corresponding to each normal-illumination sample image. The method can improve the training efficiency and generalization performance of the image enhancement model and improve the enhancement effect of the image enhancement model on low-illumination images.

This invention discloses a multimodal super-resolution microscopy imaging system and method based on multifocal structured light illumination, belonging to the field of optical microscopy imaging technology. The system includes: a laser beam generation module for generating and controlling the spatial coherence of the illumination beam; a multifocal structured light excitation module, including a beam modulation device, which modulates the illumination beam into a multifocal structured light array and projects it onto the sample plane to excite the sample to generate interference scattering signals and / or fluorescence signals; an interference scattering signal detection module for detecting interference scattering signals; a fluorescence signal detection module for acquiring fluorescence signals; and a control system module electrically connected to the beam modulation device, the interference scattering signal detection module, and the fluorescence signal detection module, respectively, for controlling the generation of multifocal illumination and its synchronization with signal acquisition. This invention solves the problem that existing interference scattering microscopy techniques cannot simultaneously achieve high speed, high signal-to-noise ratio, and high-resolution imaging.

The application relates to a low-complexity adaptive beamforming method based on phase apodization cross-correlation, and belongs to the technical field of ultrasonic imaging. The method comprises the following steps: focusing and Hilbert transforming a sampling echo signal to obtain a complex echo signal; constructing multiple groups of amplitude apodization functions with different side lobe levels and peak response, weighting the echo signal, calculating and comparing the estimated variances of the apodized signals; constructing multiple groups of complementary phase apodization function pairs, phase apodizing the apodized signal with the minimum estimated variance, and calculating the real part similarity coefficient matrix of the phase-apodized signal pair; summing and averaging the multiple groups of thresholded similarity coefficient matrices and performing two-dimensional mean filtering; and multiplying the sum result of the apodized signal with the minimum variance estimation and the filtered similarity coefficient matrix to obtain the output of a beamformer and form an image. The application has the advantages of low calculation complexity, high robustness, etc., and can significantly improve the resolution and contrast of an ultrasonic image.

The invention discloses an anti-counterfeiting printed matter preparation and identification method and system based on halftone frequency compensation, and the method comprises the steps: determining the compensation frequency of an embedded texture needed to be embedded into an original digital image according to the frequency of macroscopic moire patterns induced when an input anti-counterfeiting printed matter is copied; designing an embedded texture based on halftone frequency compensation according to the compensation frequency, and generating a digital image hidden with the embedded texture; and outputting the digital image hidden with the embedded texture to a printing material through printing equipment to obtain an anti-counterfeiting printed matter. The invention aims to utilize the active induction mechanism of the moire to actively induce the moire characteristics excited in the frequency domain and the micro texture at the moment of imaging of the copy, the discrimination of the copy is converted from searching a weak signal to detecting significant interference, and the stability of anti-counterfeiting printed matter discrimination in the application scene of complex media and cross-brand equipment is improved.

The invention discloses a sea cucumber accurate fishing robot suitable for a shallow sea culture area, and relates to the technical field of aquaculture equipment.The sea cucumber accurate fishing robot comprises a rack, an equipment cabin, a collecting cabin, a power supply cabin and a plurality of propellers are installed on the rack, and a fishing mechanical arm matched with the collecting cabin is installed on the front side of the rack; a precise fishing framework is arranged in the equipment cabin, the precise fishing framework identifies the positions of sea cucumbers in the shallow sea culture area and controls the fishing mechanical arm to fish the sea cucumbers and then put the sea cucumbers into the collecting cabin, and a power supply unit is arranged in the power supply cabin to supply power to the precise fishing framework and the fishing mechanical arm. Through fusion perception, turbid water body image enhancement and accurate positioning, full-process autonomous accurate fishing of the sea cucumbers in the shallow sea high-turbidity environment is achieved, manual diving operation is replaced, the fishing efficiency and the product quality are greatly improved, and intelligent upgrading of the sea cucumber culture industry is promoted.

This invention relates to positive resist materials and a method for forming patterns. The objective of this invention is to provide a positive resist material and a method for forming patterns that exhibit controlled acid diffusion, superior resolution compared to known positive resist materials, smaller edge roughness and dimensional deviations, and better pattern shape after exposure. The solution to this objective is a positive resist material comprising a base polymer capped with a sulfonate salt containing a carboxylic acid anion attached to a thioether group.

The embodiment of the invention provides a blood vessel segmentation method, computing equipment, a computer storage medium and a computer program product. The blood vessel segmentation method comprises the following steps: acquiring original medical image data containing blood vessels; performing feature extraction on the original medical image data to generate image feature data; based on the image feature data, modifying a pixel intensity value of a pixel in the original medical image data to obtain first medical image data; performing edge detection on the first medical image data to obtain edge information of the blood vessel, and generating second medical image data containing a blood vessel boundary mask; and based on the blood vessel boundary mask, performing blood vessel segmentation on the second medical image data to obtain a target blood vessel image. The technical scheme provided by the embodiment of the invention can improve the accuracy of blood vessel segmentation.

The invention relates to the technical field of polymer dispersed liquid crystal, and discloses a perovskite quantum dot / polymer dispersed liquid crystal film and a preparation method thereof, and the method comprises the following steps: preparing a toluene solution of perovskite quantum dots, and adding dithiol as a ligand to carry out surface modification on the perovskite quantum dots to obtain a perovskite quantum dot / polymer dispersed liquid crystal film; cleaning by using a mixed solvent of toluene and ethyl acetate in a volume ratio of 1: 2-2: 1, and centrifuging to obtain surface-modified perovskite quantum dots; uniformly mixing the surface-modified perovskite quantum dots with an ultraviolet polymerizable monomer, a cross-linking agent, liquid crystal and an ultraviolet initiator, injecting the mixture into a liquid crystal box, and performing ultraviolet curing to obtain the perovskite quantum dot / polymer dispersed liquid crystal film. The perovskite quantum dot / polymer dispersed liquid crystal film with enhanced long-wave infrared emissivity, fluorescent pattern and information encryption, provided by the invention, has wide application prospects in liquid crystal display, intelligent glass, energy-saving building materials, automobile decoration and related fields.

This invention belongs to the field of QR code printing control technology, specifically disclosing a variable QR code printing control method. This method includes: importing order parameters containing QR code printing position, content type, and application scenario characteristics; real-time acquisition of the flatness and colorimetric features of the substrate surface; quantifying and generating integrity assurance coefficient and clarity maintenance coefficient based on flatness features and printing position; quantifying and generating color stability coefficient and readability maintenance coefficient based on colorimetric features; comparing and verifying each quality indicator with quality indicator thresholds dynamically generated based on order parameters; if verification passes, printing is executed; otherwise, printing parameters are dynamically adjusted before printing is executed. This invention, through multi-feature fusion and dynamic verification adjustment, significantly improves the printing quality, physical durability, and visual readability of QR codes in complex outdoor environments, and overall enhances the adaptability of the QR code printing process.

The utility model relates to the technical field of elevator call-out, and discloses an elevator call-out device which comprises a panel and an assembly hole, a circuit board is fixedly installed inside the panel, a first LED lamp bead is fixedly installed at the top end of the front end of the panel, and a second LED lamp bead is arranged at the bottom end of the first LED lamp bead. The elevator call-out device is provided with the panel and other parts; a traditional LED segment code display module is replaced with an LED and lampshade surface paste, and the LED segment code display module has the advantages of being low in material cost, free in shape and size, diversified in display content, light and thin in design, simplified in assembly, low in maintenance cost, optimized in uniformity, high in contrast ratio, diversified in color, reliable and expansible. The LED segment code display module can exceed a traditional segment code module in the aspects of cost, design freedom degree and function expansibility, is particularly suitable for product schemes pursuing differentiation and high cost performance, and solves the problem of improvement of the traditional LED segment code display module in the aspects of cost, design freedom degree and function expansibility.

A method for enhancing steel surface images based on a regional autonomous strategy belongs to the field of computer vision and image processing technology. The steps are as follows: 1. Image preprocessing: Acquire the original image of the steel surface and convert the input RGB color image to a grayscale image; 2. Defect region detection: Use the Canny edge detection algorithm to perform edge detection on the grayscale image and extract potential defect boundary information; 3. Regional CLAHE enhancement: Based on the region mask generated in step 2, perform contrast-limited adaptive histogram equalization on the defect region and the background region respectively, and set different enhancement parameters; 4. Median filtering; 5. Weighted image fusion: Perform weighted fusion processing on the enhanced image obtained in step 3 and the filtered image obtained in step 4 to obtain the final output image. This invention can improve the overall quality and defect identifiability of steel surface images through the above method.

The present invention provides a reversible thermochromic composition which exhibits black color upon coloration and colorless color upon discoloration, and has excellent light resistance, by using a fluoran derivative having a specific structure as an electron-donating chromogenic organic compound, and a reversible thermochromic microcapsule pigment containing the reversible thermochromic composition. The means for solving the problem is a reversible thermochromic composition comprising: (a) a fluoran derivative having a specific structure as an electron-donating chromogenic organic compound, (b) a compound having a specific structure as an electron-accepting compound, and (c) a reaction medium which allows the electron transfer reaction between the (a) component and the (b) component to occur reversibly in a specific temperature range, and a reversible thermochromic microcapsule pigment containing the reversible thermochromic composition.

This invention relates to the field of optical imaging technology, specifically providing an optical radar co-aperture off-axis imaging system, comprising: an off-axis mirror assembly, a frequency-splitting device, a radar transceiver system, and an optical imaging system. The frequency-splitting device is disposed in the rear optical path of the secondary mirror and is used to reflect light waves and transmit microwaves. The frequency-splitting device includes a frequency-selective surface, which comprises an FSS pattern layer and a bias line layer. The FSS pattern layer includes periodically arranged FSS units. Nonlinear capacitors are electrically connected to the FSS units. The bias line layer applies a voltage to the nonlinear capacitors according to the received microwave band. By changing the voltage applied to the nonlinear capacitors, the resonant frequency of the FSS units is tuned, thereby changing the microwave passband frequency of the frequency-splitting device. This invention not only achieves a reflective wave-transmitting microwave design but also solves the problem that transmitting only a single band of microwaves in microwave-transmitting and light-reflecting methods is difficult to adapt to different task requirements.

The application provides a detection system and a control method thereof, and relates to the technical field of semiconductor detection. The detection system comprises an illumination module and an imaging module arranged in sequence. A product to be detected is arranged between the illumination module and the imaging module. The illumination module and the imaging module respectively comprise a first time sequence diaphragm and a second time sequence diaphragm arranged in rotation. The first time sequence diaphragm is used for obliquely irradiating the product to be detected with illumination light generated by the illumination module. The second time sequence diaphragm is used for filtering or weakening low-frequency diffraction light from the product to be detected and retaining high-frequency diffraction light. The first time sequence diaphragm and the second time sequence diaphragm are synchronously arranged in time sequence, so that the illumination light incident on the product to be detected and the diffraction light from the product to be detected to the imaging module cross at an optical axis. The high-frequency diffraction light is prevented from being shielded while the 0th-order diffraction light is filtered. The final image is formed by fitting different images with reduced 0th-order diffraction light, the imaging effect is improved, the contrast of the system is improved, and high-pass filtering is realized.

The application provides a pre-processing method of to-be-compensated data, a picture compensation method and related equipment. The pre-processing method of to-be-compensated data comprises the following steps: acquiring first luminance data of a plurality of sub-pixels in a display panel when a to-be-compensated picture with a display gray scale less than or equal to a preset gray scale; determining first part sub-pixels and second part sub-pixels from the plurality of sub-pixels, adjusting the first luminance data of the first part sub-pixels to second luminance data, and adjusting the first luminance data of the second part sub-pixels to third luminance data; wherein the second luminance data is greater than the first luminance data, and the third luminance data is less than the first luminance data. By adopting the scheme of the application, more reasonable compensation data can be obtained when Mura compensation is performed, and a better compensation effect can be achieved.

This invention relates to a method and system for multiple planning and force adjustment of welding allowance in robotic machining. The invention includes real-time monitoring of weld allowance changes to obtain real-time actual weld allowance data; establishing a material removal rate model based on historical grinding data and material properties; wherein the historical grinding data includes the material removal amount of materials with different properties under different grinding parameters; the material removal rate model is used to predict the material removal amount based on the actual grinding force and material properties; the grinding parameters include grinding speed, grinding path, magnitude and direction of grinding force and / or the tilt angle of the grinding tool; when there is a deviation between the actual weld allowance data and the target allowance, the grinding parameters are dynamically adjusted based on the material removal rate model; future grinding needs are predicted based on the current grinding state, and the grinding parameters are adjusted in advance. This invention improves the consistency of welding allowance processing and grinding accuracy, and enhances grinding quality and efficiency.

The application relates to a facial tissue foreign matter detection device and relates to the technical field of facial tissue production. The device comprises a bottom plate, a connecting frame one, a first detection mechanism, a placing mechanism and a second detection mechanism. The application has the effect of improving foreign matter detection precision. The first detection mechanism comprises a fixed guide plate, a first adjusting mechanism, a second adjusting mechanism and a detection module one and other components. The edge of the facial tissue is specially detected by the detection module one, so that a detection blind area is avoided, and the horizontal height position of the detection module one is adjusted by the first adjusting mechanism and the second adjusting mechanism, so as to adapt to facial tissues with different sizes and thicknesses. The second detection mechanism comprises a fixed cylinder, a motor two, a linkage mechanism, a motor three and other components. Through mutual cooperation, the detection range of the detection module two can be expanded, illumination compensation is realized through an illumination module, no dead angle detection of the facial tissue can be realized, the adjustment is flexible, and the detection precision and efficiency are high.

This invention provides a method and system for accurate tumor segmentation in CT images, relating to the field of image processing technology. The method includes: determining the region to be identified in a CT image containing a tumor using an image segmentation model; determining the boundary line, center position, and nearest reference pixels of the region to be identified, along with their probability information; and then selecting correction pixels from the nearest reference pixels to obtain a correction region, thereby updating the trained image segmentation model. According to this invention, after obtaining the region to be identified in the CT image of each slice using the image segmentation model, the boundary line of the region to be identified can be mutually verified based on the nearest pixels on the boundary line and the pixels of adjacent slices. This allows for the selection of pixels that better represent the tumor edge from the nearest pixels on the boundary line, thereby achieving more accurate segmentation of the region containing the tumor.

The invention discloses a sensing probe assembly, a fluidic optical fiber sensing system and a preparation method, and relates to the cross technical field of optical fiber sensing technology and microfluidic detection. One free end of a single-mode optical fiber in the sensing probe assembly is fixed to the outer wall of a first square capillary tube through ultraviolet curing glue, and a second square capillary tube is coaxially or parallelly inserted into an inner cavity of the first square capillary tube. A uniform air gap is formed between the inner wall of the first square capillary tube and the outer wall of the second square capillary tube, a microfluid channel is formed in the middle of the second square capillary tube, and broadband light beams emitted from the single-mode optical fiber are vertically incident. The micro-fluidic chip sequentially penetrates through the ultraviolet curing adhesive, the upper wall of the first square capillary tube, the air gap and the upper wall of the second square capillary tube, enters the micro-fluidic channel filled with liquid to be detected, then penetrates through the lower wall of the second square capillary tube and finally reaches the lower wall of the first square capillary tube. The probe has the advantages of high detection sensitivity, strong light beam coupling stability and the like.

The invention provides a board card defect detection method and system based on image processing, and the method comprises the steps: collecting an original image of a to-be-detected board card, and sequentially carrying out the image preprocessing and image detail splitting of the original image, so as to obtain a background image and a detail image; performing first enhancement processing on the background image to obtain an enhanced background image, and performing second enhancement processing on the detail image to obtain an enhanced detail image; fusing the enhanced background image and the enhanced detail image to obtain a target enhanced image; performing iterative enhancement on the depth image based on the original image to obtain an enhanced depth image; the enhanced depth image and the target enhanced image are fused to obtain a final fused image, the final fused image is input into a defect detection model for defect detection, and a board card defect detection result is output, and the problems that in the prior art, detection precision is low, robustness is poor, and three-dimensional defects cannot be detected are effectively solved.

The invention relates to a voice-based self-service wine selling device and method for self-service wine taking. The voice-based self-service wine selling device comprises a wine storage cavity, a data acquisition module, a wine amount calculation module, a two-dimensional code generation module, a locking module and a display module, a wine cover is arranged at the top of the wine storage cavity, a wine outlet module is arranged at the position, close to the bottom, of the wine storage cavity, a wine outlet is formed in the wine outlet module, a wine taking module is arranged below the wine outlet, the data acquisition module and the wine amount calculation module are arranged in the wine cover, and the data acquisition module is connected with the wine amount calculation module. The wine amount calculation module is connected with the two-dimensional code generation module, the two-dimensional code generation module is connected with the locking module, the locking module is connected with the wine taking module, and the two-dimensional code generation module is connected with the display module. By means of the device, automatic wine taking is achieved, cost calculation is automatically conducted, and a user conducts the whole process from wine taking to payment in a self-service mode.

The present invention relates to liquid crystal (LC) mixtures or LC materials based on mixtures of polar compounds, the use thereof for optical, electro-optical and electronic purposes, in particular in LC displays, in particular in fringing field switching mode LC displays, to fringing field switching mode LC displays comprising said LC media, and to a method for producing said LC displays.

The invention relates to the field of computer-aided diagnosis, discloses a system for judging and recognizing the intestinal tract cleanliness level of an enteroscope patient, and aims to solve the problems that existing intestinal tract cleanliness evaluation is high in subjectivity, low in evaluation efficiency and lack of quantitative standards. The method comprises the following steps: acquiring and preprocessing enteroscopy image sequence data, and extracting multi-scale features; and the intestinal tract cleanliness is identified through a deep learning model, and a quantitative scoring report is generated. The system comprises an image data acquisition module, a preprocessing module, a multi-scale feature extraction module, a cleanliness identification and classification module and a report generation module. According to the technical scheme, evaluation objectivity, accuracy and efficiency can be improved, automation, standardization and high-precision quantification are achieved, and dependence on doctor experience is reduced.

This invention discloses a CPWC beamforming method based on adaptive parameter zero-subtraction imaging, applied to ultrasound imaging signal processing. It involves transmitting ultrasonic waves to a target object using an ultrasound array element module and acquiring the echo imaging signal dataset; calculating a time-delayed imaging dataset based on the echo imaging signal dataset using a delay processing module; calculating an adaptive offset parameter based on the time-delayed imaging dataset using a model combining the generalized coherence factor and the mean-standard deviation coefficient; and calculating the final imaging beamforming signal using a zero-subtraction imaging beamforming model based on the adaptive offset parameter and the time-delayed imaging dataset. This method effectively solves the contrast-resolution-speckle quality trade-off problem caused by fixed offset in zero-subtraction imaging, improving imaging quality, and is particularly suitable for high-frame-rate ultrasound CPWC imaging.

Embodiments of the present application provide a medical image synthesis device and method. The method comprises: obtaining a first medical image and a second medical image; registering the first medical image and the second medical image; determining first parameter values of each pixel position on the registered first medical image and second parameter values of each pixel position on the second medical image; multiplying the first parameter values and the second parameter values on the same pixel positions of the registered first medical image and the second medical image, and generating a synthesis image data according to the multiplication result. Therefore, the multiplication of the first parameter values and the second parameter values is equivalent to amplifying the difference of pixel values of the positions of normal tissue and lesion tissue, so that the contrast and resolution of the synthesis image are higher, thereby making the lesion area clearer and improving the lesion detection efficiency.

This invention relates to the field of data anomaly detection technology, and more particularly to a method and system for detecting data anomalies at voltage monitoring points in a distribution network. The method includes the following steps: acquiring voltage data from the voltage monitoring points of the distribution network according to a preset sampling frequency; removing zero-value and null-value data from the voltage dataset to obtain a first dataset to be detected; performing limit-crossing detection on the first dataset to be detected to obtain a limit-crossing value dataset; performing a first-level detection on the limit-crossing value dataset according to the quartile data spacing criterion, and removing data with abnormal detection results in the first-level detection to obtain a second dataset to be detected; performing a second-level detection on the second dataset to be detected according to the median deviation method to obtain a first anomaly dataset. This invention can remove interference items through a two-layer identification method, making the identification results more accurate and effectively solving the problem of inaccurate results in current data anomaly detection methods for voltage monitoring points in distribution networks.