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1022 results about "Color space" patented technology

A color space is a specific organization of colors. In combination with physical device profiling, it allows for reproducible representations of color, in both analog and digital representations. A color space may be arbitrary, with particular colors assigned to a set of physical color swatches and corresponding assigned color names or numbers such as with the Pantone collection, or structured mathematically as with the NCS System, Adobe RGB and sRGB. A "color model" is an abstract mathematical model describing the way colors can be represented as tuples of numbers (e.g. triples in RGB or quadruples in CMYK); however, a color model with no associated mapping function to an absolute color space is a more or less arbitrary color system with no connection to any globally understood system of color interpretation. Adding a specific mapping function between a color model and a reference color space establishes within the reference color space a definite "footprint", known as a gamut, and for a given color model this defines a color space. For example, Adobe RGB and sRGB are two different absolute color spaces, both based on the RGB color model. When defining a color space, the usual reference standard is the CIELAB or CIEXYZ color spaces, which were specifically designed to encompass all colors the average human can see.

Wafer probe trace accurate detection method based on deep learning

The invention discloses a wafer probe mark accurate detection method based on deep learning, and belongs to the field of wafer probe mark detection, and the method comprises the steps: constructing a pin mark image denoising preprocessing network, employing a small target feature protection and enhancement strategy based on HSV color space and local contrast joint adjustment, and carrying out the recognition of a small target feature; denoising and contrast optimization are carried out on the needle mark image; a multi-scene training sample is generated through mosaic splicing and mix fusion; a dense small target enhancement module is introduced into the backbone network to enhance needle mark feature expression, and a multi-scale feature fusion module is arranged in the neck network to extract full-scale features; and establishing an anchor frame optimization system adaptive to the minimum needle mark target, and adopting an optimizer and learning rate collaborative optimization training strategy to realize model adaptive convergence. According to the method, high-precision detection and robust identification of the wafer probe mark can be realized under a complex background, and the detection accuracy and stability are remarkably improved.
Owner:WUXI UNIV

Orientation sensitive target detection method based on sub-aperture color image saturation characteristics

The invention discloses an SAR image orientation sensitive target detection method based on sub-aperture image saturation characteristics, and belongs to the technical field of synthetic aperture radar image target detection. The azimuth sensitive target detection is realized through the following steps: 1) sub-aperture image generation: dividing an azimuth frequency spectrum into a plurality of sub-bands, and generating a plurality of sub-aperture images through inverse Fourier transform; 2) color synthesis and feature extraction: allocating different hues to each sub-aperture image by using an HSV color space, synthesizing an RGB color image, converting the RGB color image to the HSV color space, and extracting a saturation channel in the RGB color space as an azimuth sensitivity feature map; and 3) target detection: carrying out threshold segmentation on the saturation feature map, and identifying a pixel region with a high saturation value, namely, an orientation sensitive target. According to the method, the color saturation change caused by the scattering difference of the target in different sub-apertures is utilized, effective detection of azimuth sensitive targets such as artificial buildings and vehicles is achieved, and the method has the advantages of being simple in calculation and high in robustness.
Owner:NANJING UNIV OF SCI & TECH

Slide fastener slider, and slide fastener

A slide fastener slider, includes: a slider body; a puller, and a lock pin. The lock pin is made of a stainless steel material. A black oxide film is formed on a surface of the lock pin. The surface of the lock pin has brightness L* satisfying 31.70≤L*≤35.90, and a* of a value satisfying −0.708≤a*≤1.929, the brightness L′ and the a* of the value according to definitions in a CIELAB color space defined in JIS Z8781-4 (2013).
Owner:YKK CORP

Low-light environment image adaptive enhancement method based on unmanned aerial vehicle inspection

The invention belongs to the technical field of image processing, and particularly discloses a low-light environment image adaptive enhancement method based on unmanned aerial vehicle inspection, which comprises the following steps: preprocessing a low-light RGB image shot by an unmanned aerial vehicle; the preprocessed low-light RGB image is converted to an HSV color space, and brightness and color components are obtained through separation; performing dual-channel attention mechanism processing: respectively optimizing brightness and color components by adopting a brightness branch and a color branch; wherein the brightness branch enhances the dark part contrast through a convolutional network, and the color branch suppresses a color channel with significant noise based on a channel attention mechanism; and reconstructing the optimized color and brightness components into an HSV color space, and converting the HSV color space into an RGB image format to realize brightness enhancement and color denoising. The problems of overexposure, color distortion, excessive noisy points and the like existing in the image shot by the unmanned aerial vehicle camera in the low-light environment in the prior art can be effectively solved, and the image quality under the night or weak light condition is improved.
Owner:XIAN JIAOYUAN ENERGY TECH CO LTD +1

Method and device for detecting color reducibility of mobile phone camera and medium

The invention discloses a method and device for detecting color reducibility of a mobile phone camera and a medium, and relates to the technical field of image quality detection.The method comprises the steps that after geometric alignment is conducted on a color card image set, color block areas are divided, and a cross-light-source color block observation matrix is obtained through color block feature extraction; converting the cross-light-source color block observation matrix into a target color space coordinate, and performing illumination correction to obtain a cross-light-source color coordinate matrix; inputting the cross-light-source color coordinate matrix into a deep learning model, outputting a color block level high-dimensional color embedding matrix, and obtaining a high-dimensional color embedding vector set corresponding to the tested mobile phone camera in combination with an attention weight; calculating a color reducibility error index based on the high-dimensional color embedding vector set in combination with the standard reference library; and performing qualification judgment according to the color reducibility error index to generate a qualification detection conclusion. According to the invention, a stable and reliable technical basis is provided for camera quality detection under a multi-light-source imaging condition.
Owner:AGIS INTELLIGENT SYST (SHENZHEN) CO LTD

Video content enhancement method for low-light environment

The invention provides a video content enhancement method for a low-illumination environment, and the method comprises the steps: achieving the data preprocessing based on an original low-illumination video frame sequence through frame synchronization, color space conversion and local brightness analysis, generating a noise sensitivity thermodynamic diagram through multi-feature unsupervised learning, and constructing a noise perception gating mechanism through the combination of affine transformation. Dynamic modulation of the characteristic channel is realized; in the multi-scale network structure, a channel attention module is used for carrying out layer-by-layer self-adaptive adjustment on a noise sensitive area; a basic illumination image and an edge enhancement image are generated through double-branch decoding, and then weighted fusion is carried out in combination with a noise thermodynamic diagram, so that brightness balance and detail enhancement are realized; a noise smoothing regular term is introduced during end-to-end training, so that the network achieves dynamic balance between an enhancement effect and noise control.
Owner:GUANGZHOU CHENXI NETWORK TECH CO LTD

Image optimization in mobile capture and editing applications

HDR color patches are sampled throughout an HDR color space parameterized by a parameter. Reference SDR color patches, input HDR color patches and reference HDR color patches are generated from the sampled HDR color patches. An optimization algorithm is executed to generate an optimized forward reshaping mapping and an optimized backward reshaping mapping. The optimized forward reshaping mapping is used to forward reshape input HDR images into forward reshaped SDR images, whereas the optimized backward reshaping mapping is used to backward reshape the forward reshaped SDR images into backward reshaped HDR images.
Owner:DOLBY LABORATORIES LICENSING CORP

Photovoltaic sand and dust identification method based on color space fusion and lightweight learning

The invention relates to a photovoltaic sand and dust identification method based on color space fusion and lightweight learning, and the method comprises the following steps: S1, obtaining image data of a photovoltaic module, detecting a module region in an image, and obtaining a mask image of the module region; s2, extracting an ROI image of the photovoltaic module, and performing geometric correction processing; s3, converting the ROI image from an RGB color space to an HSV color space; s4, respectively carrying out threshold setting on the H, S and V three-channel images based on the HSV color space; s5, fusing threshold setting results of the H, S and V channels, generating a final sand and dust pollution mask pattern, and completing sand and dust region identification; and S6, calculating the sand-dust covering proportion of the polluted area on the surface of the component, and dividing pollution grades according to the sand-dust covering proportion. According to the invention, the dust area on the surface of the photovoltaic module can be accurately extracted under different illumination conditions, standardized quantitative evaluation of the pollution degree is realized, and the method is suitable for intelligent cleaning management and remote operation and maintenance scheduling scenes of a photovoltaic system.
Owner:LANZHOU JIAOTONG UNIV

Realtime facial sentiment analysis for metahuman response

A system and method for real-time facial and sentiment detection using a computing system. The system includes a video input module that receives real-time video input from various sources such as webcams, security cameras, and smartphone cameras. The video frames are pre-processed by adjusting the resolution, converting color spaces, and isolating the foreground from the background. A facial detection module employs a convolutional neural network to identify and localize human facial regions within the video frames. Geometric and appearance features are extracted from the localized facial regions by a feature extraction module. A sentiment classification module classifies the extracted features to determine sentiments using a deep learning model. The system also includes a module for API integration, enabling third-party applications to utilize the sentiment recognition results.
Owner:BACON CHANTAL +1

Self-adaptive low-illumination image enhancement method and device and storage medium

The invention discloses a self-adaptive low-illumination image enhancement method and device and a storage medium, which are used for stably outputting a high-quality image under various complex conditions. The method comprises the steps of generating an adaptive key parameter set through a preset mapping function based on brightness features; processing the brightness channel through a combined filtering strategy and carrying out adaptive weighted fusion to obtain an irradiation component; converting the brightness channel and the irradiation component to a logarithm domain and performing operation to obtain an initial reflection component; performing linear stretching processing on the initial reflection component to obtain an enhanced reflection component; performing nonlinear gamma correction processing on the irradiation component to obtain a corrected irradiation component; converting the enhanced reflection component back to a linear domain, and performing operation with the corrected irradiation component to obtain an enhanced brightness channel; and recombining the enhanced brightness channel with the original hue channel and saturation channel in the HSV color space, and converting back to the RGB format to obtain an enhanced image.
Owner:SHENZHEN SEICHITECH TECHN CO LTD

Intestinal stoma mucous membrane state evaluation system based on color comparison

The invention relates to the technical field of medical image processing, in particular to an enterostomy mucous membrane state evaluation system based on color comparison, which comprises a multi-modal data acquisition module used for acquiring and analyzing a mucous membrane image sequence, ambient light characteristics and basic physiological data and generating acquisition data records with aligned timestamps; and the individualized benchmark modeling module is used for establishing a patient specific color reference benchmark through HSL color space analysis on the basis of the collected data records and the preoperative physiological indexes, and generating an initial adaptive color gamut threshold model. According to the method, the specific initial color reference is established for each patient, and the sliding window algorithm is combined to continuously monitor the color gamut drift so as to dynamically update the reference, so that accurate self-adaption to individual physiological differences of the patients and postoperative slow recovery changes is realized, and therefore, the objectivity and accuracy of evaluation are greatly improved; the problem of misjudgment caused by individual differences or normal evolution of physiological states in a traditional fixed threshold value method is effectively avoided.
Owner:SHANTOU CENT HOSPITAL

Method for identifying looseness of bolts at bottom of maglev train based on deep learning

The invention provides a maglev train bottom bolt looseness identification method based on deep learning. The method comprises the following steps: acquiring a bottom image of a maglev train by adopting imaging equipment, and carrying out bolt target detection on an image in a bottom image data set through an improved YOLOv8 network to obtain a bolt image; performing classification processing on the bolt image through a lightweight network RepViT fused with a lightweight ViT design principle; color space conversion, image binaryzation, morphological processing and connected domain screening processing are carried out on the bolt image to extract an anti-loosening line, and whether the vehicle bottom bolt in the bolt image is loosened or not is judged based on the bolt anti-loosening line according to loosening characteristics of different types of bolts under multiple visual angles. According to the method, the detection precision is improved by means of improving a target detection network structure, refining bolt loosening characteristics, providing adaptive detection methods for different types of bolts and the like; by designing a lightweight classification network mode, the calculation amount and time consumption are reduced, and the detection efficiency is improved.
Owner:BEIJING JIAOTONG UNIV

Intelligent osteosarcoma image recognition and classification method and system based on image recognition model

The invention relates to the technical field of image recognition, in particular to an osteosarcoma image intelligent recognition and classification method and system based on an image recognition model. The method comprises the following steps: collecting a tumor image and carrying out multi-sequence disturbance equilibrium enhancement to generate an enhanced block tumor image, then obtaining a color standardized image through color space transformation remapping, then extracting a tumor region image and carrying out contrast inversion processing, reconstructing a tumor feature image, and finally, carrying out multi-sequence disturbance equilibrium enhancement on the tumor feature image. Based on a preset image recognition model, tumor edge features are recognized, the edge rule degree is determined, preliminary classification is carried out, a benign tumor image is obtained, surrounding metabolite signal features of the benign tumor image are analyzed, a benign reference group is formed through combination, metabolism state comparison is carried out on tumor feature images, and metabolism difference data are generated. And performing category correction according to the metabolic state mapping data so as to identify the osteosarcoma category. According to the invention, intelligent analysis of tumor features is realized, the image processing flow is optimized, and the processing efficiency is improved.
Owner:NANHUA HOSPITAL AFFILIATED TO UNIV OF SOUTH CHINA

Method and system for predicting combustion state of rotary furnace based on flame image

The invention belongs to the technical field of image analysis and processing, and particularly relates to a flame image-based rotary furnace combustion state prediction method and system. The method comprises the following steps: acquiring a video image sequence of flames in the rotary furnace, and converting each frame of image into a YUV color space; calculating a combustion contribution degree based on the brightness component and the chromaticity component, and screening out a core flame pixel set; taking the combustion contribution degree as a weight, calculating a weighted covariance matrix, determining a confidence ellipse according to the eigenvalue and eigenvector of the matrix, taking the center of the confidence ellipse as a weighted centroid, determining a rotation angle by the eigenvector, and making the length of long and short semi-axes in direct proportion to the square root of the eigenvalue; extracting the area, eccentricity rate, rotation angle and center position of the confidence ellipse as combustion state feature vectors at the current moment; and inputting a time sequence formed by the combustion state feature vectors at the multiple moments into a pre-trained hidden Markov model, and outputting the combustion state of the rotary furnace. According to the invention, the accuracy and anti-interference capability of combustion state prediction are improved.
Owner:YIXING HOTTEEN ENVIRONMENTAL PROTECTION ENG

Printing color closed-loop control system based on spectral analysis

InactiveCN121442046AImage analysis2D-image generationScreentoneLoop control
The invention discloses a printing color closed-loop control system based on spectral analysis, and relates to the technical field of computer processing, and the system comprises the following steps: S01, collecting the spectral reflectivity data of a plurality of key color blocks on a printed matter measurement and control strip in real time through an online high-speed spectrometer at the frequency of not less than 100 color blocks per second; s02, constructing a color prediction model, wherein the model receives the spectral reflectivity data and outputs absorption scattering characteristics, the spectral transmittance of ink and dot expansion, trapping and overprinting effects in the printing process; s03, setting a dynamic tolerance threshold value delta Et based on a chromatic aberration formula according to the color precision requirement of the printed matter, and judging the absorption and scattering characteristics, the spectral transmittance of the ink and a grading tolerance interval in which the dot expansion, trapping and overprinting effects in the printing process are consistent with visual perception; and S04, converting the spectral reflectivity data acquired in real time into a CIELAB color space irrelevant to equipment, and comparing the spectral reflectivity data with a preset standard color target value. According to the method, the problems of different standards and color drift caused by artificial experience difference and visual fatigue are solved.
Owner:HANGZHOU DEKA DECORATION NEW MATERIAL CO LTD

Image quality optimization method based on multi-scale feature decoupling and dynamic fusion

The invention discloses an image quality optimization method and system based on multi-scale feature decoupling and dynamic fusion, and the method comprises the steps: carrying out the multi-scale decomposition of an input degraded image, and extracting the feature components of illumination-color, texture-noise and edge-structure; illumination normalization and color fidelity enhancement are realized through illumination estimation and color space transformation; the base layer and the detail layer are separated through edge preserving filtering, and self-adaptive contrast enhancement and noise suppression are carried out on the detail layer; extracting edge information by using a multi-directional gradient operator, and strengthening significant structural features through nonlinear mapping; constructing a lightweight weight learning network, and generating a spatial self-adaptive dynamic fusion weight map according to the multi-scale features; executing progressive three-level fusion according to the dynamic weight, and reconstructing to obtain a high-quality image; according to the method, the image is decomposed into feature components with different physical meanings, targeted optimization and adaptive fusion are carried out, and more accurate and robust image quality improvement is realized.
Owner:HENAN INST OF ENG +1

Image fusion enhancement method for multi-signal-source liquid crystal splicing screen

PendingCN121190321AImage enhancementStatic indicating devicesPattern recognitionVirtual coordinate systems
The invention discloses an image fusion enhancement method for a multi-signal-source liquid crystal splicing screen, and relates to the technical field of large-screen display control, and the method comprises the steps: building a virtual coordinate system taking a physical gap as a reference at an input end, carrying out the decoding, time synchronization and unified mapping of a multi-source heterogeneous signal, converting the multi-source heterogeneous signal into a unified color space, and carrying out the image fusion enhancement of the multi-signal-source liquid crystal splicing screen. The display consistency of different signal sources is ensured; then, a compensation model based on a brightness attenuation function is introduced into the splicing boundary area, edge pixel brightness is subjected to self-adaptive correction, and brightness unevenness caused by physical gaps is relieved; calculating the content complexity based on the row-level gradient magnitude in the fusion screen area, dynamically constructing a content-sensitive fusion weight, and carrying out weighted fusion on the images on the two sides to generate a transition image frame; and through joint output of the transition image frame and the original side image frame, visual seamless connection of the splicing gap area is realized. Therefore, the integral continuity and visual experience of tiled display are effectively improved while the image detail fidelity is ensured.
Owner:SHENZHEN XINGWEI OPTOELECTRONICS TECHNOLOGY CO LTD

Image quality evaluation method and device, electronic equipment and storage medium

The embodiment of the invention discloses an image quality evaluation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a to-be-processed image, and converting the to-be-processed image into a target color space to obtain a to-be-used image; wherein the to-be-processed image is an image acquired based on fusion of a plurality of sensors; determining a brightness mean value corresponding to the to-be-used image, and converting the to-be-used image into a frequency domain space to obtain frequency domain data corresponding to the to-be-used image; determining image texture attributes according to the frequency domain data; determining a target evaluation result of the to-be-processed image according to the image texture attribute and the brightness mean value; wherein the target evaluation result is used for representing the credibility of the image collected by the image sensor in the current environment. Through the technical scheme of the embodiment of the invention, image quality evaluation for non-single indexes can be realized, and the image quality evaluation efficiency and accuracy are improved.
Owner:CHINA FAW CO LTD

Fluorescence detection test paper visualization system and method based on deep learning

The invention relates to the technical field of water quality detection, and provides a fluorescence detection test paper visualization system and method based on deep learning, and the method comprises the steps: detecting a fluorescence detection test paper image obtained through shooting through a target detection network, and obtaining a test paper main body region, a colorimetric block region and a test paper key angular point coordinate; performing homographic perspective transformation on the main body area of the test paper according to the key angular point coordinates of the test paper, generating a test paper standard view after perspective correction, performing color space standardization correction, generating a mixed deep learning model, and outputting a fluorescence intensity concentration predicted value of the target detection area; generating an interpretable thermodynamic diagram based on the intermediate features of the mixed deep learning model; according to the method, shooting deviation is eliminated through multi-stage image correction, the fluorescence intensity is accurately quantified by fusing CNN and Transform models, the result credibility is improved in combination with a thermodynamic diagram, and the detection automation is comprehensively improved.
Owner:BAICHENG NORMAL UNIV

Underwater image enhancement method combining multi-color space and multi-scale

The invention provides an underwater image enhancement method combining multiple color spaces and multiple scales, and belongs to the technical field of image enhancement and deep learning. The method comprises the following steps: processing an underwater image through a color processing channel to obtain color fusion features; processing the underwater image through a scale processing channel to obtain scale fusion features; and fusing the color fusion feature and the scale fusion feature of the underwater image to obtain an enhanced image. According to the method, a multi-color space and multi-scale coordinated double-coding enhancement network is adopted, different color spaces are coded through parallel residual errors in multi-color space coding, and the limitation of a single-color space method on color cast correction, color distortion processing and contrast difference is effectively solved by decoupling color and brightness information. In multi-scale coding, hierarchical feature extraction and cross-scale information complementation are adopted to capture details and texture features of an image on different scales, and blurring and detail loss at different depths can be effectively processed.
Owner:DALIAN UNIV

Solder paste three-dimensional detection parameter automatic configuration method and system based on Gerber file

The invention relates to the technical field of parameter automatic configuration, and discloses a solder paste three-dimensional detection parameter automatic configuration method and system based on a Gerber file, and the method comprises the steps: analyzing a bonding pad attribute data set of the Gerber file, and building detection frame coordinate data under an equipment coordinate system; a Mark point image is collected and converted to an HSV color space, and a Mark point matching contour template is created; based on the Mark point matching contour template, substrate, solder paste and silk-screen area images are collected, and a color segmentation parameter set is calculated; generating a grouping allowable value configuration table according to the bonding pad attribute data set; the camera is controlled to collect the RGB image set of each bonding pad, the solder paste contour is extracted, the mass center offset is calculated, and the detection frame configuration file is output. According to the method, automatic generation and accurate positioning of the detection frame are achieved, accumulative errors are effectively compensated, and the position deviation of the detection frame is reduced.
Owner:SHENZHEN ZHENHUAXING INTELLIGENT TECH CO LTD

Intelligent welding visual identification robot cooperative control system for steel tube tower assembly

The invention relates to the technical field of image analysis, in particular to a steel tube tower assembly intelligent welding visual identification robot cooperative control system, which comprises a groove surface pollutant identification module, a groove surface pollutant identification module, a linear polarization component calculation module and a control module, meanwhile, the original light intensity image is converted into a CIELAB color space, an a channel value is extracted, the polarization degree value of each pixel point is fused with the corresponding a channel value, and a pollutant pixel mask is established. According to the method, in the image analysis process, the multi-angle polarization image is introduced and the color channel value is fused, so that precise recognition of a tiny pollution area is achieved, and the space sensing capacity of groove pollutants in a complex welding environment is enhanced; the space coordinates of the pollutant area and the welding seam edge are compared and screened point by point, the overlapped part of the pollutant area and the welding path is positioned, and the pertinence and accuracy of pollution interference identification are improved.
Owner:QINGDAOHAOMAIQILIN STEEL STRUCTURE CO LTD

HVI color space-based shadow removal method and system, terminal and storage medium

The invention relates to the technical field of image processing, and discloses an HVI color space-based shadow removal method and system, a terminal and a storage medium, and the method comprises the steps: obtaining an RGB input image, converting the RGB input image to an HVI color space, and carrying out the decoupling of the RGB input image to obtain HV branch information and I branch information; designing a double-branch network structure, extracting color features in HV branch information by using an HV branch in the double-branch network structure, and extracting brightness features in I branch information by using an I branch in the double-branch network structure; fusing the color features and the brightness features by using an attention mechanism to obtain fusion information; and performing brightness adjustment and color correction on the fusion information to obtain an HVI component, mapping the HVI component back to an HVI color space, converting the HVI component into an RGB image, and outputting a shadow-free image. According to the method, the HVI color space and the double-branch architecture are introduced, so that the robustness and the accuracy of image shadow removal can be remarkably improved.
Owner:GUANGDONG LAB OF ARTIFICIAL INTELLIGENCE & DIGITAL ECONOMY (SZ)

Pier crack detection method based on improved YOLOv8n

The invention discloses a bridge pier crack detection method based on improved YOLOv8n. Firstly, a collected image is subjected to preprocessing such as color space conversion, contrast enhancement and geometric correction; then constructing a detection model taking YOLOv8n as a baseline, embedding a channel attention mechanism in a backbone network of the detection model, and replacing an original path aggregation network with an adaptive weighted feature pyramid network; then crack prediction is performed by using the improved model, and bounding box regression is performed by using a loss function based on a minimum distance between vertexes of a prediction frame and a real frame; and finally, pixel-level segmentation is carried out on the detection area, a sub-pixel-level edge contour is extracted, and the physical width of the crack is calculated. The method improves the precision and robustness of crack detection, and is suitable for bridge structure health monitoring.
Owner:CHONGQING SHOUXUN TECH CO LTD

Coal slime flotation dosing data processing method and system

The invention discloses a coal slime flotation dosing data processing method and system. The method comprises the steps that a continuous image sequence of surface foam of a flotation cell is collected, and X fluorescence detection signals are collected; converting the continuous image sequence from an RGB color space to an HSL color space; the change rate of the single foam surface area along with time is calculated to track the foam fusion behavior, and an overall foam merging rate index is obtained; calculating the foam viscosity according to the integral foam merging rate index and the diameter distribution of the foam; calculating the foam ash content and the foam water loading rate according to the fluorescence intensity and the total fluorescence signal in the X fluorescence detection signal; constructing a multi-modal feature vector; according to the multi-modal feature vector, feature extraction is carried out through a neural network, and a foam quality comprehensive score and a foam change trend are obtained; aiming at inaccurate extraction of coal slime flotation froth features in the prior art, the stability and the product quality of the flotation process are improved through combination of visible light image features and X fluorescence chemical indexes and the like.
Owner:北京长河数智科技有限责任公司 +1

Homomorphic filtering-CLAHE remote sensing image enhancement method based on integration strategy multi-target particle swarm optimization

The invention relates to the technical field of remote sensing image processing, in particular to a homomorphic filtering-CLAHE remote sensing image enhancement method based on integration strategy multi-target particle swarm optimization, which comprises the following steps: acquiring remote sensing image data, and preprocessing the remote sensing image data; converting the preprocessed remote sensing image into an HSV color space, and extracting a V component in the HSV color space; constructing a frequency domain-spatial domain hybrid enhancement framework of homomorphic filtering and contrast-limited adaptive histogram equalization, and performing enhancement processing on a V-channel component by using the framework; constructing an integrated strategy multi-target particle swarm optimization algorithm; constructing a four-target fitness function including structural similarity, average gradient, information entropy and gray variance, and guiding particles to search in the direction of optimizing a plurality of key image quality indexes at the same time by using the function so as to realize optimal selection of remote sensing image enhancement parameters; the method can effectively enhance the definition and structural integrity of the terrain texture in the remote sensing image of the complex mountainous area.
Owner:SOUTHWEST FORESTRY UNIVERSITY +1

Construction method and system of universal digital twin asset data model for multi-source heterogeneous data exchange and sharing

The invention discloses a method and system for constructing a universal digital twin asset data model for multi-source heterogeneous data exchange and sharing, and belongs to the technical field of digital twin. The method comprises the following steps: obtaining three-dimensional data structures and three-dimensional data indexes of different geometric forms in a digital twin model, the spatial topological relation between the three-dimensional data structures is identified; converting texture map information of the three-dimensional data structure into a unified format, normalizing coordinates of the texture map information, and unifying vertex coloring information of the three-dimensional data structure to a standard color space; and performing material analysis and description on different material characteristics of the digital twin model, dynamically calling node objects corresponding to the different material characteristics to obtain real material information, and finally dynamically outputting to obtain a general three-dimensional data model. According to the invention, the problem that a unified digital twin floor scene is difficult to generate due to different sources and structures of current model data can be solved.
Owner:SHAANXI NORMAL UNIV

Abnormal defect detection method for terminal welding

The invention discloses a terminal welding abnormal defect detection method, and relates to the technical field of image data processing, and the method comprises the following steps: carrying out the image collection through a multi-light-source image collection module, and obtaining a single-light-source image and a uniform-light-source image; calculating through a single light source image to obtain a reflectivity image, and obtaining a reflection grey-scale map through bilateral filtering and nonlinear transformation of an enhanced kernel function; fourier transform is carried out on the reflection grey-scale map, and a frequency domain interest map is obtained through mean filtering and subtraction; performing feature extraction through binary matrix sampling and a conditional probability model to obtain a two-dimensional interest graph; carrying out two times of pixel point screening and maximum value suppression on the reflection grey-scale map to obtain a texture interest map; carrying out HSV color space conversion on the uniform light source image, and calculating through Gaussian filtering and a normal form distance model to obtain a color interest graph; and obtaining a defect feature map through weighted fusion, carrying out threshold segmentation on the defect feature map, marking defects, and completing identification of the terminal welding defects.
Owner:NANTONG RUITAI ELECTRONICS

Method for quickly acquiring leaf shape parameters

The invention provides a leaf shape parameter rapid acquisition method, and the method comprises the steps: obtaining a to-be-recognized image, carrying out the color conversion of the to-be-recognized image, and determining a conversion image of the to-be-recognized image in a surface color system; performing image segmentation in the converted image based on the brightness channel to obtain a first reference image; performing perspective transformation based on the first reference image to obtain a second reference image; performing color conversion on the second reference image, and determining a third reference image of the second reference image in the HSV color space; and performing leaf segmentation based on the third reference image, and determining leaf shape parameters in the to-be-identified image. According to the method, the leaf shape parameters are determined by identifying the to-be-identified image with the leaf, and the leaf shape parameters can be determined under the conditions of low resource occupation and low delay.
Owner:PEKING UNIV SHENZHEN GRADUATE SCHOOL

Illumination adaptive image preprocessing method and system for monocular Gaussian sputtering SLAM

The invention discloses an illumination adaptive image preprocessing method and system for monocular Gaussian sputtering SLAM, and belongs to the technical field of computer vision and robots. Aiming at the problem that the front end of the existing SLAM system depends on a luminosity consistency hypothesis, and positioning drift and mapping artifacts are easy to generate under intense illumination fluctuation, the method decouples a processing flow into a global dimension and a local dimension. In a CIELAB color space, smooth correction of global exposure is realized through a continuous interpolation algorithm, a multi-factor joint constraint mechanism is introduced to adaptively calculate a dynamic threshold value of local contrast enhancement, and intermediate-frequency edge information is directionally improved in combination with a Gaussian difference sharpening technology. According to the method, the robustness of the system is enhanced in an illumination abrupt change and extremely dark environment, the SLAM positioning precision is remarkably improved, the image rendering capability is improved when 3D Gaussian sputtering is used for scene reconstruction, and suspended noisy points and geometric cavities in a map are effectively eliminated.
Owner:WUHAN UNIV