158 results about "Color gradient" patented technology

A high-fidelity three-dimensional reconstruction method for a specular reflection plane comprises the steps of decomposing pixel colors into diffuse reflection and specular reflection components based on a 3D Gaussian sphere, introducing a dynamic reflection ratio parameter and a spherical harmonic function coefficient to respectively represent two reflection characteristics, and simulating light multi-reflection behaviors through weight fusion of cumulative projection and a reflection ratio map. Secondly, in combination with monocular inverse depth calibration, depth smoothing constraint of color gradient weighting and edge mutual exclusion loss, geometric consistency is enhanced, and artifacts are suppressed; a progressive multi-resolution training strategy is further adopted, low resolution is gradually optimized to complete resolution, reflection parameters are activated in stages, 3D Gaussian sphere overgrowth and floating artifacts are inhibited, and efficiency and precision are balanced. According to the method, the reconstruction fidelity of the specular reflection scene is remarkably improved while the real-time rendering advantage of the 3DGS is reserved, and the method is suitable for the high-precision modeling fields of virtual reality, augmented reality and the like.

The invention discloses an image processing method applied to printed matter surface color difference detection, which relates to the technical field of image processing, and comprises the following steps: acquiring a digital image of a printed matter to be detected, performing illumination non-uniformity correction, and converting the corrected digital image into a CIELAB color space; performing region segmentation on the digital image based on double constraint conditions of color gradient and texture boundary to generate a detection region graph; feature parameters are extracted based on the detection area graph, and a feature data set is generated; establishing a dynamic reference model by utilizing process parameters and material characteristics of the printed matter; and calculating the distance between the feature data set and the dynamic reference model, identifying color difference regions and generating color difference scores, and screening and grading the color difference regions according to the color difference scores. According to the method, a multi-layer image pyramid and homomorphic filtering combined illumination correction technology is adopted, and an adaptive weight fusion mechanism based on image features is introduced, so that the illumination nonuniformity is effectively eliminated while the definition of printing details is kept.

The invention discloses an energy consumption management platform based on big data, and belongs to the technical field of energy consumption management, and the platform specifically comprises a building level energy consumption tracking module which collects energy consumption data of different levels of a building in real time, binds energy consumption equipment with a building space, maps sub-item energy consumption equipment to corresponding level nodes according to physical positions, and transmits the energy consumption data to the building level energy consumption tracking module; constructing an energy consumption flow direction topological graph according to a total-score table relation; the visual energy consumption display module is used for dynamically generating a multi-level energy consumption distribution thermodynamic diagram according to the topological graph, setting different color gradients according to the energy consumption loss rate, calculating a loss rate threshold value by means of a dynamic threshold value algorithm in combination with historical and environmental data, and marking abnormal nodes if the loss rate threshold value is exceeded; and the energy consumption repair positioning module is used for generating a diagnosis report containing fault equipment positioning and energy consumption waste reasons based on the historical monitoring data and the user operation log of the corresponding energy consumption equipment after detecting the abnormal node.

The invention relates to the technical field of lung perfusion, in particular to an AI-based lung perfusion evaluation system, which comprises an image quality screening module, a blood vessel positioning analysis module, a blood flow velocity measurement module, a blood vessel anomaly analysis module and an anomaly response module, and is characterized in that the image quality screening module monitors the pixel density of an image and the variation amplitude of color gradient. According to the method, through real-time image definition evaluation and screening, the image selection process is optimized, it is ensured that all the images used for analysis reach the high-quality standard, the gray level change and the edge contour of the blood vessel are automatically calculated, the potential lesion area is accurately positioned and marked, more detailed blood vessel structure analysis is provided, and the accuracy of blood vessel analysis is improved. In addition, the system can rapidly analyze the speed deviation of the blood vessel segment, timely identify the abnormal blood flow, effectively improve the judgment speed of diseases such as pulmonary embolism or pulmonary hypertension, enhance the efficiency of coping with emergency medical conditions through automatic abnormal detection and recording, improve the accuracy and speed of judgment, and support more effective clinical decisions.

The invention discloses a WebGL-based mass data particle system rendering method and device, and belongs to the technical field of computer graphic processing. The method comprises the following steps: firstly, selecting the type of a particle emitter according to scene requirements, then constructing a primitive object based on points or quadrangles, and configuring three-dimensional coordinates and texture parameters; aggregation rendering is carried out on a single-frame primitive array through a WebGL vertex shader and a fragment shader, and the drawing calling frequency is reduced; the method comprises the steps of dynamically adjusting particle attributes, including position compensation, color gradient and explicit-implicit control, determining a rendering form and playing time of an animation according to requirements of an actual application scene, and supporting fine configuration of a single particle, including texture animation, dynamic scaling and rotation parameters. When a large amount of data is processed, on the premise of ensuring the rendering quality, the rendering efficiency can be remarkably improved, the consumption of a memory and GPU resources can be reduced, the response time of the system can be optimized, and meanwhile, the interaction experience of a user can be improved.

The invention relates to the technical field of light control, and discloses a creative and creative light color gradient control method and system, and the method comprises the steps: carrying out the preprocessing of the spatial position information of audiences, generating an audience position sequence, calculating the moving speed, the steering angle and the region density in real time, and generating a light adjustment signal in combination with a preset threshold value; mapping the RGB values to an HSL space to generate an initial color parameter set; adjusting a brightness weight, a hue weight and a saturation weight based on the moving speed, the steering angle and the area density, and updating a color parameter set; generating a gradient sequence through smooth interpolation; sending a control instruction by using a low-delay protocol and monitoring a delay value; and calculating a comprehensive evaluation value according to the rendering effect, iteratively adjusting the weight if the comprehensive evaluation value exceeds the limit, and regenerating a light control instruction. According to the invention, through the technical means of real-time calculation, dynamic weight adjustment, low-delay transmission, deviation feedback and the like, a light control instruction with smooth gradual change is generated, and accurate control of light color gradual change is realized.

The invention relates to the technical field of engineering plastic detection, and particularly discloses an aging detection and evaluation method and system suitable for nylon 6 in a marine environment, the system comprises nylon 6 as a core layer, an aging response color-changing material as a surface layer and a middle layer located between the core layer and the surface layer; the thickness of the middle layer is 200-250 [mu] m, and the composite conductive film is transferred to the position 0.2 mm below the surface of the nylon 6 component in a hot pressing mode; the thickness of the surface layer is 0-200 microns and is realized by spraying an aging response color-changing material solution. By integrating the specially designed aging response color-changing material and the conductive film into the nylon 6 matrix, real-time, visual and efficient detection of the aging process is realized. According to the method, the problem that equipment such as a traditional optical fiber spectrometer is complex and expensive is solved, the convenience of field detection is greatly improved through double signal output of color gradient indication and simple electronic reading, and a brand new technical solution is provided for life prediction and preventive maintenance of nylon 6 components in ocean engineering.

The invention discloses a liquid chromatographic peak intelligent analysis method and system based on deep learning, and relates to the technical field of data processing. The method comprises the following steps: constructing a chromatographic peak intelligent analysis network based on deep learning, and training the network by using a sample chromatogram until convergence; inputting a to-be-analyzed chromatographic signal into the chromatographic peak intelligent analysis network, and evaluating the reliability of a prediction result based on the probability distribution of the key physical parameters output by the chromatographic peak intelligent analysis network to obtain a result confidence coefficient; dynamically adjusting the number and composition of the sample chromatograms based on the result confidence and a preset confidence threshold, and continuously updating the chromatographic peak intelligent analysis network; and recording an attention mechanism of the chromatographic peak intelligent analysis network as a weight fraction allocated to each data point, mapping the weight fractions back to a time sequence of an original chromatographic signal, carrying out visualization through a color gradient, and superposing the weight fractions on an original chromatographic curve in a semitransparent layer form to generate a chromatographic peak thermodynamic diagram. According to the invention, the efficiency and precision of liquid chromatography analysis are effectively improved.

The invention relates to the technical field of image analysis, in particular to a data visualization pathological diagram analysis system which comprises a pathological image noise reduction and enhancement module, a lesion area judgment module, a local texture and global structure fusion module, a self-adaptive multi-scale segmentation module and an error correction and optimization module. According to the method, by analyzing color channels, cell structure edge features and background noise distribution in the pathological image, accurately screening noise and optimizing image filtering, the image quality is effectively enhanced, the noise is reduced, the recognition accuracy of a lesion area is improved, and the recognition accuracy of the lesion area is improved in combination with cell nucleus gradient information and tissue edge distribution. The accuracy is further improved by using gray statistics and cell density, region division is weighted and optimized through the contrast and entropy of lesion tissues, the segmentation accuracy is ensured, the image segmentation scale is accurately adjusted in combination with the cell density and color gradient information, errors are reduced, accurate segmentation of lesion regions is ensured, and the accuracy of image segmentation is improved. And finally, the precision and reliability of overall image analysis are improved.

The invention discloses an unmanned aerial vehicle formation dynamic light control method and related components. The method comprises the following steps: taking a geometric center of an unmanned aerial vehicle formation in a three-dimensional space as a reference origin; constructing a corresponding orthogonal basis according to a specified scanning direction, and defining a plane formed by the orthogonal basis as a dynamic plane where a scanning effect is located; converting the position projection of the unmanned aerial vehicle in the three-dimensional space into a polar coordinate angle on the dynamic plane; calculating the absolute scanning angle of each light beam according to the animation time axis length, the preset number of light beams and the total number of scanning turns; calculating the final illumination intensity of each unmanned aerial vehicle after being influenced by all the light beams, and performing interpolation according to a preset color gradient to obtain a final light color; and assigning the final light color to a light material attribute corresponding to the unmanned aerial vehicle, and inserting a key frame on an animation time axis to generate a dynamic light animation sequence. According to the invention, the multi-beam dynamic scanning effect of the unmanned aerial vehicle formation in the three-dimensional space is realized, and the spatial stereoscopic impression of light performance is improved.

The invention provides a cyanide generation and absorption efficiency monitoring method based on double-color indicator gradient change, and belongs to the technical field of cyanide monitoring, the absorption process is visually reflected through the double-color indicator gradient change, the absorption efficiency can be rapidly judged through color change without a complex instrument, the operation is simple and convenient, and the cost is low. And gradient color development and spectral analysis are combined, so that the detection limit can reach a mu g / L level, the trace detection requirement is met, and the absorption condition of the low-concentration cyanide can be accurately monitored. Through real-time change of the color gradient, the concentration distribution and the reaction process of the cyanide in the absorption process can be dynamically reflected, real-time data support is provided for industrial process control and environmental emergency monitoring, expensive detection equipment is not needed, the reagent cost is low, and the method is suitable for large-scale popularization and application.

The invention discloses a shoulder joint rehabilitation action image recognition and real-time posture correction feedback method and system, and belongs to the technical field of medical image processing and computer vision, and the method comprises the steps: collecting a rehabilitation training image frame sequence through an RGB camera; inputting the image into a human body analysis model, extracting skeleton key point coordinates and calculating a joint angle sequence; constructing the skeleton key points into a space-time diagram structure, and inputting the space-time diagram structure into a space-time diagram convolutional network for action classification and recognition; aligning and comparing the actual joint angle with the standard action template by adopting a dynamic time warping algorithm to calculate a deviation vector and an action compliance score; a standard posture skeleton line and an angle deviation indicating arrow are overlaid and rendered on an image, the compliance degree of each joint is displayed in a color gradient mode, an action compliance degree score and personalized correction suggestions are output, the error posture recognition accuracy is larger than 92%, the feedback delay is smaller than 100 ms, and the technical problem that home rehabilitation lacks professional action guidance is solved.

The invention provides a traditional Chinese medicine decoction piece quality evaluation method based on big data, and relates to the technical field of data processing, and the method comprises the steps: extracting texture direction consistency data from texture dense region detection points of a central region, and extracting structural symmetry data from wrinkle region detection points; comparing the color gradient change data with a preset standard color gradient threshold to generate a first difference index, comparing the texture direction consistency data with a historical qualified batch texture direction distribution range to generate a second difference index, and comparing the structural symmetry data with a pharmacopoeia form standard to generate a third difference index; and calculating a quality evaluation value based on the first difference index, the second difference index and the third difference index in combination with the initial quality deviation risk value, and obtaining a quality grade judgment result of the traditional Chinese medicine decoction pieces according to an interval matching relationship between the quality evaluation value and a preset risk threshold. According to the invention, the evaluation accuracy can be improved.

The invention provides a dynamic feature contribution degree-based color textile fabric image retrieval method. Innovation and improvement are carried out aiming at single feature limitation and fixed weight fusion defects existing in a traditional retrieval technology. Color, texture and shape features are separated through a multi-modal feature decoupling technology, and coupling interference between the features is eliminated; a dynamic contribution degree quantification mechanism is innovatively constructed, gradient back propagation is used for calculating the contribution proportion of features to retrieval results in real time, and weight self-adaptive adjustment is achieved. According to the method, the problem of retrieval deviation caused by complex characteristics such as color gradient and blending structure difference of the colored spun yarn fabric is solved in a breakthrough mode, weight distribution can be intelligently matched according to inquired image characteristics (for example, the color gradient fabric focuses on color characteristics, and the jacquard fabric focuses on shape edges), and the retrieval result better fits human visual perception. According to the technical scheme, the image retrieval precision of complex fabrics in the textile industry is effectively improved, and an intelligent solution is provided for production process data association.

The invention discloses a GIS-BIM-based in-service road disease section marking cooperation platform and method, and the method comprises the steps: constructing an EBS structure tree model, importing the EBS structure tree model into a GIS system to form a GIS-BIM platform, and transmitting a to-be-inspected line and a stake number coordinate table to an unmanned plane; the unmanned aerial vehicle inspects and shoots a long picture and matches a stake number label, and the server cuts the picture and identifies disease features; and the GIS-BIM platform maps the disease pictures to the corresponding BIM model segments, and deletes the maps if no disease pictures are inspected again. The stake mark coordinate table is generated according to stake mark progressive increase, disease recognition adopts a convolutional neural network model, and color gradient distinguishing is performed according to severity. The platform integrates EBS and WBS dual-core structure trees, realizes full-period collaboration through stake mark interval dynamic mapping, improves the disease marking efficiency and precision, and realizes full-process digital operation and full-period automatic collaboration.

The invention discloses a line sequence automatic detection algorithm based on machine vision and an implementation method thereof, and belongs to the technical field of machine vision and image processing. Aiming at the problems of low efficiency and poor accuracy of traditional manual detection of a multi-core cable, the invention provides the following technical scheme: preprocessing a collected cable image, and enhancing the image by adopting adaptive histogram equalization of an LAB color space; determining a scanning band at the center of the image and converting the scanning band to an HSV color space; the comprehensive value of the HSV color gradient is calculated, the peak value is detected by adopting an adaptive threshold value, and the boundary of each wire core is accurately positioned; establishing an HSV (hue, saturation and value) feature library containing 10 standard colors, and realizing color matching through weighted distance measurement; and an automatic detection mode and a manual assistance mode are provided. According to the method, the detection accuracy reaches 95% or above, the processing time of a single image is shorter than 1 second, the technical problems of automatic color recognition and sorting detection of the multi-core cable are effectively solved, and the method can be widely applied to cable production quality control.

The invention discloses a mulberry twig clamping and positioning method and system, belongs to the technical field of intelligent mulberry leaf picking equipment, and aims to solve the technical problems that an existing RGB camera is easily interfered by illumination, and picking damage is caused due to the fact that a demarcation point of a tender branch and an old branch is difficult to accurately recognize. According to the method and system, 500-600 nm visible light and 750-900 nm near-infrared band images are synchronously collected through a multispectral imaging device, HSV color space parameters are extracted, and a color gradient model is established; by analyzing the gradient change rate of the hue value H and the saturation degree S and combining the curvature change rate and the near-infrared reflectivity difference value, the transition boundary of the tender and old branches is accurately judged, and the three-dimensional coordinates of the clamping datum point are generated by dynamically shifting 5-15 mm towards the side of the tender branches. According to the scheme, the limitation of single hue detection is broken through, the xylem recognition capability is enhanced by utilizing multispectral information, the clamping accuracy is improved, the method is suitable for automatic operation of a top-remaining picking mode in large-scale silkworm and mulberry planting, the picking efficiency can be effectively improved, and branch damage can be reduced.

The invention discloses an image processing method and device, a nonvolatile storage medium and computer equipment. The method comprises the following steps: acquiring an initial image; determining initial color values corresponding to a plurality of pixel points in the initial image; calculating target color gradient values corresponding to the plurality of pixel points based on the initial color value; based on the smoothing function and the target color gradient value, adjusting initial color values corresponding to the plurality of pixel points to obtain first color values corresponding to the plurality of pixel points; adjusting the first color values based on a Gaussian function and the first color values corresponding to the adjacent pixel points corresponding to the plurality of pixel points to obtain second color values corresponding to the plurality of pixel points; based on the second color values corresponding to the multiple pixel points, the initial image is adjusted, a target image is obtained, and the target image is the initial image in the simulated colored lead style. According to the invention, the technical problems of difficulty in batch production and low efficiency due to dependence on manual design of an image with a color lead effect at present are solved.

The application discloses a method for improving printing ink color matching based on control of base color gradient, which comprises the following steps: (1) obtaining a base color ink series ladder ruler; (2) obtaining reflectivity coefficients of the base color ink series ladder ruler; (3) selecting the reflectivity coefficients that can be used to calculate the absorption and scattering coefficient ratio of the base color ink; (4) calculating the absorption and scattering coefficient ratio of the base color ink; and (5) formula calculation. The application increases the control of the reflectivity coefficients of the base color ink mixed with the diluent in the formula model, selects all the reflectivity coefficients that can be used to calculate the absorption and scattering coefficient ratio of the base color ink yellow, improves the accuracy of the absorption and scattering coefficient ratio of the base color ink, improves the stability and accuracy of the difference between the predicted target spectrum and the target spectrum, and has important significance for the development and application of the ink automatic color matching system.

Disclosed are systems and methods for a computerized framework for automated ceramic inkjet printing in dental restoration manufacturing. The disclosed ceramic inkjet mesh printing for dental restorations combines precision digital control with ceramic materials to create highly accurate and aesthetically pleasing dental prosthetics. The disclosed mechanisms utilize specialized printheads designed to deposit precise amounts of ceramic materials onto dental substrates, enabling the creation of detailed color gradients and natural-looking surfaces that closely mimic natural teeth.

The application provides a compressor aerodynamic stability prediction method and device, the method comprising color space conversion on an initial flow field cloud image of the compressor to obtain a target flow field cloud image, wherein the target flow field cloud image comprises at least two color channels; for any pixel point in the target flow field cloud image, the gradient amplitude of the pixel point on different color channels is calculated, and a color gradient map is generated according to the gradient amplitudes of multiple pixel points; based on a preset threshold and the gradient amplitudes, the color attribute of each pixel point in the color gradient map is adjusted to obtain a color mask image; the connected region of a target color in the color mask image is determined as a target region of a shock wave, a main flow and a leakage flow interface; based on the distance between the target interface region and the blade leading edge of the compressor, a stability prediction result is generated, wherein the stability prediction result represents that the compressor is in an unstable or stable state.

The invention relates to a desktop type high-resolution multi-dimensional optical image intelligent analysis method and device, and belongs to the technical field of optical image analysis. The method comprises the following steps: controlling an imaging device and an integrated desktop objective table through a host, performing synchronous image acquisition on a sample on the objective table, and generating an original multi-dimensional image set; generating a single-frame two-dimensional light and shadow mapping graph through a parallax fusion algorithm, and simulating the three-dimensional morphology characteristics of the sample through gray scale and color gradient change; outputting the dynamic light and shadow mapping graph to a desktop display screen in real time, and loading an interactive light source simulation engine; simulating an illumination effect on the dynamic light and shadow mapping graph in real time; the visual saliency of target features is improved by automatically configuring light source parameters; and according to the optimized rendering result, topological structure features and optical features of the sample are extracted, and a quantitative analysis report is generated. The full-process automation and intelligentization of optical images from multidirectional and multi-view collection to deep analysis and quantitative report generation are realized.

Disclosed are systems and methods of a decision intelligence (DI)-based computerized framework that automatically and / or dynamically implements a color algorithm for performing staining and glazing dental restorations. The framework operates by leveraging determined color variations through AI / ML-based analysis that generate detailed color maps, which can be translated into precise printing instructions controlling the mixture and layering of dental-grade glazing materials. A printing system can employ multiple print heads with varying base colors and opacity levels to create microscopic color gradients and translucency effects matching natural tooth enamel. The disclosed automated processing applies personalized color patterns in microscopically thin layers, ensuring consistent glaze thickness while replicating regional variations across the tooth surface. Such approach eliminates manual glazing variability while achieving superior customization compared to traditional pre-set patterns, resulting in dental restorations that integrate seamlessly with existing teeth.

The application discloses a kind of gradient color cover plate glass silk screen printing systems, belong to glass production technical field.Its technical scheme is: including glass conveying unit one, silk screen printing machine, glass conveying unit two, gradient heating unit, glass conveying unit three, cleaning machine and coating machine arranged in sequence.The application gradually changes by controlling the gradient input amount of oxygen along the color gradient direction, and further precisely controls the temperature of each region, finally prepares the gradient color cover plate glass, and the color CMYK value can be changed between 0,0,0,0 and 71,63,60,12;After placing in the environment of temperature 85 DEG C, humidity 85%RH for 48h, the glass color is stable and does not change.

This invention discloses a simulation method, apparatus, medium, and device for flip chip underfill, relating to the field of flip chip underfill simulation technology. The invention simulates the flip chip underfill process within a computational domain divided into two meshes in a flow plane perpendicular to the depth direction using a color gradient lattice Boltzmann model. A color function clearly distinguishes between the wetting phase (filler adhesive) and the non-wetting phase (air) to dynamically track the two-phase interface. When simulating the flow field changes during the self-absorption process of flip chip underfill, the average curvature of the interface in the depth direction and the average frictional force of the upper and lower solid walls of the flip chip are introduced to determine the force applied at the two-phase fluid interface, thus reflecting three-dimensional physical effects. While maintaining near-two-dimensional computational costs, this invention significantly improves the accuracy of flip chip underfill simulation and can quickly predict the entire flip chip underfill process at a lower cost.

The invention provides a system (2.41,81) for controlling an array (281) of light sources (11-19) to render color gradient light (231,232,271), the array (281) comprising at least four individually controllable light sources. The system (2,41,81) comprising an input interface (3,43,83,89) configured to obtain at least four gradient stop colors (C1,C2,C3,C4) and a gradient contrast option; a processor (5,45,85) configured to (i) receive the at least four 5 gradient stop colors and the gradient contrast option from the input interface, (ii) determine color contrasts (CC12,CC13,CC14,CC23,CC24,CC34) between pairs (C1-C2, C1-C3,C1- C4,C2-C3,C2-C4,C3-C4) of the at least four gradient stop colors, (iii) determine a gradient stop color sequence of the at least four gradient stop colors based on the determined color contrasts and the gradient contrast option, (iv) determine a mapping of the at least four 10 gradient stop colors onto at least four light sources of the array of light sources based on the gradient stop color sequence, and a control interface (6,44,84) configured to control the array of light sources to render the gradient stop colors on the at least four light sources.

The invention discloses a method for manufacturing color gradient of mobile phone rear cover glass based on a composite salt bath ion exchange coloring technology. According to the preparation method, by designing a specific composite salt bath formula, an innovative workpiece loading mode and precise process control, an ion concentration gradient is formed on the surface of the glass through ion exchange, so that the gradient color effect which is soft in transition, rich in color and high in binding force is prepared through a one-step method; and the glass naturally forms an ion concentration gradient at the interface of the fused salt and the air, so that the steps of adjusting and converting for multiple times in the traditional process are omitted. The production process is simplified, the processing time of a single product can be shortened, and the overall production efficiency is improved; and meanwhile, the equipment investment and the consumption of consumables are reduced, the manufacturing cost is effectively reduced, and the method is more suitable for large-scale industrial production.

The invention relates to a method for characterizing the size of an irregular proppant-fiber cluster unit in a slit, and the method comprises the steps: S1, carrying out a proppant-fiber mixed conveying physical model experiment, obtaining an experiment image, carrying out the preprocessing and threshold segmentation of the experiment image, focusing on a region of interest (ROI), and obtaining a proppant-fiber cluster unit size; dividing the pixel value of the image into continuous intervals according to a preset threshold parameter, and generating a multi-category segmentation mask; s2, performing multi-scale morphological operation on the segmented masks, removing small noise cluster units and filling internal holes of the cluster units; s3, identifying each connected region in the image, counting the area of the connected region, and dividing cluster units according to a preset level; and S4, performing color gradient rendering, contour labeling and area numerical value labeling on the cluster units of different levels to enhance the visual discrimination, and outputting an image. According to the experimental image processing method provided by the invention, the information of each cluster unit can be more intuitively obtained, and the action mechanism of the proppant-fiber cluster unit can be clearly known.

The invention relates to the technical field of light control, in particular to a skin visual detection control method based on a silicon substrate multi-primary-color LED lamp. According to the method, the original skin image is continuously acquired, the local window is divided, and the similarity of the structure direction field and the color gradient field of the local texture is combined, so that the high-resolution recognition of the skin texture state is realized, and the recognition precision of the facial detail abnormity is enhanced. By setting the fuzzy judgment interval and quantifying the membership degree, a multi-dimensional recognition system for different abnormal types such as color spots, redness and swelling, dry decrustation, acnes and comedos is established, and the sensitivity and adaptability of skin abnormality judgment are remarkably improved. In a color response interference identification process, an inter-class variance is introduced to calculate a response difference between a red channel and a yellow channel, so that the influence of a color overlapping region is effectively eliminated, and the effectiveness and independence of extracting a gray region are ensured. And further extracting an effective gray area in the non-interference area.

The present application provides a model coloring method, apparatus, device, medium, and program product. Among them, the method includes: obtaining a color gradient map corresponding to the current game scene and a texture map of the virtual model, and coloring the surface of the virtual model according to the texture map and the color gradient map. In this technical solution, by setting color gradient maps corresponding to different game scenes, when the virtual model is in different game scenes, the corresponding color gradient map can be obtained and combined with the texture map of the virtual model to color the virtual model, which can make the virtual model not only rely on the texture map for coloring, thereby improving the flexibility of virtual model coloring.