675 results about "Color matching" patented technology

The invention relates to the field of intelligent interactive design, and particularly discloses a visual intelligent interactive design system which comprises a three-dimensional structure design module, an intelligent color matching module, a visual rendering module and an interactive feedback analysis module. The three-dimensional structure design module can process imported or custom a three-dimensional model, detect and repair topology errors and construct a three-dimensional scene basic framework; the intelligent color matching module generates a color matching scheme based on the instruction, a rule base or user preference and displays a comparison view; the visual rendering module renders a three-dimensional scene in real time, collects rendering pipeline load parameters and quality indexes, and analyzes balance points to adjust rendering parameters; and the interaction feedback analysis module records interaction data, marks over-limit nodes by comparing a standard and analyzes a root cause. According to the system, efficient three-dimensional scene construction, intelligent color matching, rendering optimization and interaction experience improvement are realized through multi-module cooperation, and the system is suitable for multi-field scenes needing visual intelligent interaction design.

The invention discloses a thematic charting processing method and system based on online data, and the method comprises the steps: carrying out the standardization processing of original data through a pre-established data processing flow, segmenting the original data into tile data, storing the tile data in a distributed storage system, and constructing a structured tile data set. And according to the structured tile data set, performing rendering processing by applying a color matching scheme, and generating a map service interface to provide a dynamic map data stream. The data is loaded to a browser end drawing environment through the map service interface, an initial drawing project file containing a drawing layout is generated, and the drawing layout comprises at least one map frame. And adding map element data into the initial cartographic engineering file and adjusting the position so as to update the cartographic engineering file. Therefore, according to the thematic charting processing method based on the online data, the data processing efficiency is improved, the cooperation threshold is reduced, and dynamic sharing is achieved.

The invention relates to the technical field of computer vision, and discloses a vehicle paint make-up color matching method based on computer vision, and the method comprises the steps: collecting a vehicle paint image in real time through an industrial camera, constructing a multi-dimensional color feature extraction system after preprocessing, and building a color feature database through a color space conversion technology; and positioning a target color card by combining a feature matching algorithm. Meanwhile, a historical paint make-up case information base is constructed, a multi-factor weight distribution model is established, an optimal matching scheme is solved by adopting an improved particle swarm optimization algorithm, and finally a result is output through an interactive verification platform and tracked and fed back. According to the method, multiple factors are comprehensively considered, the precision and efficiency of color matching are improved, and the method is suitable for paint make-up color matching of vehicles of different vehicle types, years and paint surface types and has high practicability and popularization value.

The invention relates to the technical field of data processing, and discloses a method for automatically generating a patchwork pattern based on an intelligent algorithm, and the method comprises the following steps: S1, user demand analysis: collecting and analyzing design demands, including color preference, style requirements, pattern complexity and other parameters, input by a user; s2, preparing a patchwork element data constructing the patchwork element database, wherein the patchwork element database comprises geometrical shapes, textures, color matching schemes and historical design cases; s3, generating a patchwork pattern: adopting a GAN deep learning model to generate a candidate patchwork pattern; s4, optimizing the pattern of the patchwork: optimizing and generating the pattern in combination with reinforcement learning; s5, performing image segmentation and optimization algorithm: through the image segmentation and optimization algorithm, ensuring seamless connection when the cloth splicing blocks are spliced, and adapting to actual cloth processing requirements; s6, editing a patchwork design scheme: generating a patchwork design scheme in an editable format for a user to preview and modify; and S7, outputting the patchwork pattern: outputting the final patchwork pattern.

The invention relates to the technical field of printing, and discloses a printing parameter optimization-based printing quality improvement method, which comprises the following steps of: constructing a multi-dimensional color characteristic model through spectral data; collecting illumination conditions and related parameters of an observation environment in real time through a spectrum sensor, and generating an environment parameter data set; establishing an observer personalized visual perception model through a color matching experiment, wherein the personalized visual perception model maps the physical stimulation into perception response; dynamically adjusting printing parameters based on the multi-dimensional color characteristic model, the environmental parameter data set and the personalized visual perception model; according to the method, printing output is monitored in real time and printing parameters are corrected in the printing process to minimize perceptual printing differences, so that environmental factors and individual visual perceptual differences can be comprehensively considered, the printing parameters can be optimized in real time, and the printing quality and the color rendition precision are improved.

The invention relates to the technical field of tire detection, in particular to a method for identifying abnormal vibration of a tire through color difference of an automobile tire tread, which comprises the following steps: generating a point cloud picture; generating a first tire surface height point cloud picture at the first rotating speed; generating a first visual point cloud picture and determining an abnormal vibration level; dividing detection intervals, wherein n detection point sets are configured in each detection interval; generating a second tire surface height point cloud picture at a second rotating speed; reducing the rotating speed of the tire at a preset rate, calculating a stability score, and judging whether the stability of the detection device meets requirements or not; and in response to the satisfaction, rendering the tire surface to generate a second visual point cloud picture, and determining an abnormal vibration level. According to the method, the height difference of the tire surface height at each detection point position is calculated, and the tire surface is rendered according to the height difference and the preset color matching mechanism, so that the vibration condition caused by the tire surface height can be intuitively and visually displayed.

The invention relates to the technical field of aluminum decorative strip coating, and discloses an aluminum decorative strip color coating optimization system based on automatic control, which comprises a material pretreatment layer, a coating control layer and a quality detection layer. The material pretreatment layer is used for treating the surface of the aluminum decorative strip through surface cleaning, base material activation, roughness detection and adhesive force test; the coating control layer realizes coating control by utilizing a color blending unit, a spraying robot cluster, a dynamic temperature control module and a distributed controller in combination with a real-time color matching algorithm and a self-adaptive path planning mechanism; and the quality detection layer adopts an image analysis technology and a deep learning algorithm to construct a coating quality feature model, and color difference detection, defect positioning and process parameter compensation decision are realized. According to the system, automation, precision and intellectualization of the aluminum decoration strip coating process are achieved, the coating quality and the production efficiency are improved, and the system is suitable for the field of aluminum decoration strip color coating.

Systems and methods for a sample database are provided, where the sample database is for matching a target coating. In one embodiment, the system comprises a sample database stored on a storage device. The sample database includes a sample coating formula and a sample image feature with at least one sample coating formula linked to at least one sample image feature. At least one sample image feature includes a spatial micro-color analysis that includes a value determined by a sample pixel feature difference between at least two sample pixels.

The invention provides a digital pathological section color calibration method and device, and the method comprises the following steps: obtaining a standard color image and an image to be subjected to color correction, and extracting the feature points of the standard color image and the feature points of the image to be subjected to color correction, matching the standard color image and the image to be subjected to color correction based on the feature points to obtain a standard color matching image and a matching image to be subjected to color correction; performing histogram color correction on the matching image to be subjected to color correction by taking a standard color matching image as a reference to obtain a first color correction image, and performing CCM color correction on the first color correction image by taking the standard color matching image as the reference to obtain a second color correction image, and performing gamma correction on the color of the second color correction image by taking a standard color matching image as a reference to obtain a color correction completed image. According to the scheme, all pixel information of the target image is fully utilized, the color correction process is quantified to eliminate artificial errors, and the efficiency and accuracy of color correction of the digital pathological image can be remarkably improved.

The invention relates to the technical field of building maintenance scheme optimization, and discloses a building maintenance scheme optimization method based on an intelligent algorithm, and the method specifically comprises the following steps: 1, interface optimization: after starting MATLAB software, loading a source code of building quality diagnosis system software named as a building doctor, and in a design view interface of the software, carrying out interface optimization on the source code of the building quality diagnosis system software; according to the method, the user interface of the software is ensured to be clearly viewed, then a'optimization 'button in the interface is optimized and adjusted, a'help' menu is newly added in the software interface, and visual elements such as the graphic size and color matching of the user interface are finely optimized and adjusted, so that the functionality of the software is enriched, and the user interface is more vivid. In addition, the friendliness and usability of the user interface are remarkably improved, smoother and more comfortable use experience is brought to the user, the visual and clear user interface is elaborately designed, and it is ensured that the user can easily understand and operate the platform and detect the particularity of the building.

The invention relates to the technical field of building design, in particular to an ancient building visual color matching method, which comprises the following steps of: 1, acquiring multi-source data; step 2, color feature extraction; 3, constructing a historical color knowledge base; step 4, constructing a color matching model; and step 5, performing three-dimensional visual rendering. According to the historic building visual color matching method, qualitative analysis of'regional culture-natural environment 'is converted into quantitative collection of multispectral images and three-dimensional point clouds, and spatial accurate positioning of color features is achieved; a standardized knowledge base containing historical periods and technologies is constructed, and the fragmentation problem of traditional color matching experience is solved; through physical realistic rendering, the method is expanded to color simulation of the ancient building under different climate conditions, and the recovery credibility is improved.

The invention relates to the technical field of clothing color matching, in particular to an intelligent recommendation method for clothing color matching, which comprises the following steps: S1, constructing a multi-modal user data intelligent acquisition feature project; s2, deep learning of clothing color semantic feature analysis; and S3, intelligently constructing and optimizing the personalized recommendation model. Multi-source data of a user is acquired in real time through a multi-modal data acquisition engine, feature extraction and engineering construction are performed by using a deep learning technology, a complete user portrait is formed, garment color features are analyzed by using an advanced image processing technology and a deep learning model, a color semantic network is constructed, a fashion trend is captured, and a user experience is improved. A mixed recommendation model based on a graph neural network and Transform is designed, distributed training is achieved through federated learning, a personalized recommendation result is generated in combination with a multi-objective optimization algorithm, a recommendation strategy is continuously optimized through reinforcement learning and an online feedback mechanism, and system security and user privacy protection are ensured by adopting a zero-trust architecture.

The invention provides an immersive naked-eye 3D visual impact display system with enhanced double-screen dynamic parallax, and relates to the technical field of 3D display, and the system provides a wide-angle and highly-vivid 3D visual effect for a user without wearing auxiliary equipment through a unique double-screen architecture design in combination with an advanced dynamic parallax control technology. The core of the system is a dynamic parallax adjustment algorithm, the dynamic parallax adjustment algorithm can track the sight line and head position changes of a user in real time, 3D image parallax on a screen is intelligently adjusted, and it is ensured that the user can obtain consistent and stable stereoscopic visual experience at different angles and positions. Besides, the system adopts a high-precision 3D modeling and rendering technology and is combined with a transparent OLED display screen, so that the sense of reality and the visual impact of the 3D model are further enhanced. Through color matching and texture mapping algorithms, the system also realizes seamless fusion between the foreground and the background, so that the whole picture is more natural and harmonious.

The utility model provides a color master barrel righting and positioning device and color matching equipment, and belongs to the technical field of batching equipment. The color master barrel righting and positioning device is applied to color mixing equipment and comprises a righting gripper assembly, a color master barrel righting and positioning assembly and a color master barrel righting and positioning assembly, the righting gripper assembly comprises a side wall and a gripper part fixed to the side wall, and a slope angle opening is formed in the end, away from the side wall, of the gripper part; the driving part is connected with the side wall and used for driving the side wall to stretch out and retract in the first direction, and when the side wall stretches out, the grabbing part abuts against a handle of a color master barrel located at the color master barrel in-place position on the color mixing equipment. And the color master barrel is straightened to a preset liquid outlet position under the limitation of a space formed by the slope angle opening. The color master barrel can be accurately straightened to the preset liquid outlet position under the condition that the stopping precision of the color master barrel is insufficient.

The invention provides an oral ceramic restoration optical prediction matching method and system based on deep learning, relates to the technical field of oral medicine, and solves the limitation problems that existing oral restoration is low in clinical colorimetric accuracy, depends on artificial experience, has medical technology communication information deviation and the like. The method comprises the following steps: acquiring spectral data of natural teeth, dentin, enamel and different types of ceramics, and calibrating the semi-permeability of enamel and ceramic samples by using an extinction coefficient; obtaining a ceramic-dentin complex and composite spectrum data thereof, constructing a multi-layer sensor model and completing training; and splicing the dentin spectral data and the ceramic spectral data into an initial input vector, splicing the initial input vector with the calibrated semi-permeable constraint vector, and inputting the spliced initial input vector into a multi-layer sensor model to obtain a model matching result. The intelligent model for automatically generating the natural tooth defect repair scheme is established based on the deep learning technology, the intelligent repair design and the visual repair effect are achieved, and clinical application is effectively guided.

The invention relates to the technical field of waste paper detection, in particular to an AI-based waste paper whole-process detection method and system, which comprises the following steps: collecting image side line extension angle statistics color matching identification, coding direction sequence comparison identification offset, positioning an infrared adjustment frequency generation instruction, and correlating serial number contrast data to generate a linked list. And extracting a difference value to judge that the overrun output is abnormal. According to the method, in image processing, abnormal paper parcels are compositely recognized through sideline interruption, break angle errors and color strip density, a multi-dimensional judgment mechanism is constructed in combination with source codes, in path tracking, a direction sequence is adopted to recognize an offset trend, infrared monitoring frequency is dynamically adjusted, and a high-risk area is focused; in the detection link, quality and moisture data are connected in series through paper package numbers, a time sequence contrast linked list is constructed, and potential deviations are screened by fusing difference floating and trend cross validation, so that anomaly identification precision, monitoring response rapidness and data tracking closed loop are realized.

The invention discloses a data processing method, a data processing device and electronic equipment, and the method comprises the steps: determining a target light effect mode matched with first audio and video data based on the first audio and video data; the first audio and video data comprises audio features and / or video features of the currently played content; based on a target emotion attribute associated with a target object, determining a target color matching mode matched with the target emotion attribute; the target emotion attribute is obtained based on image data and / or audio data corresponding to the target object; and fusing the target light effect mode and the target color matching mode to obtain corresponding display information.

The invention provides a three-dimensional image modeling method and device based on plane data, and the method comprises the steps: carrying out the full-color / multispectral band fusion, bit depth adjustment, thin cloud removal, image enhancement, stripe removal and light and color uniformity of a satellite surveying and mapping image, and achieving the real color recovery of the image; performing splicing preprocessing on the plurality of small orthographic satellite surveying and mapping images after real color recovery, performing image registration on the to-be-registered image and a reference image, performing image geometric correction on the registered image, and performing image mosaic processing on the plurality of images after image geometric correction to obtain a single large-scene image; and three-dimensional image matching, building mask extraction, three-dimensional building modeling and three-dimensional building post-processing are carried out on a single large scene image to obtain a three-dimensional digital surface model, and ground three-dimensional real image modeling is completed. By applying the technical scheme of the invention, the technical problem that the existing two-dimensional surveying and mapping data is difficult to meet the increasing application requirements of three-dimensional scenes is solved.

The invention provides a deep learning-based automatic toning system and method for a record. The method comprises the following steps of: determining a toning constraint condition of the record in visual constraints according to style similarity of shallow visual features between adjacent recorded image frames in the record and brightness difference between the adjacent recorded image frames; performing fuzzy correlation on the scene semantic elements of the narrative segments in the record through the cross correlation among the scene semantic features to obtain the element membership of the scene semantics in the narrative segments, and further determining the scene attention of different narrative segments in the record according to all the element membership; and according to the scene attention and the hue constraint conditions of the different narrative segments, determining the chroma reconstruction cost of the record in the toning process, and carrying out automatic toning processing on the record based on the chroma reconstruction cost. According to the scheme, the visual features and the semantic elements can be fused in the automatic toning process of the record, and toning coordination with narrative logic as the guide is achieved.

The invention discloses an art design intelligent color matching auxiliary system and method based on artificial intelligence, and relates to the field of art design. Comprising an image analysis module, and the image analysis module comprises a noise reduction preprocessing unit for carrying out noise suppression on an input image by adopting a bilateral filter and a semantic segmentation unit for analyzing an image semantic region and outputting a segmentation mask by using a DeepLabv3 + model; a color space conversion unit that inputs and converts the RGB image into a CIELAB space; a style feature extraction unit; a palette optimization module; and a rendering output module. According to the method, the four-dimensional statistical vector of the LAB color space is extracted, high-level features such as the quantized lightness centrality, the chroma discreteness and the distribution skewness are extracted, the problem of feature expression distortion of a traditional method is solved, the style loss function based on the Gram matrix is constructed, gradient descent optimization is combined, and it is ensured that the palette meets the aesthetic rule and style consistency at the same time.

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 relates to the technical field of management systems, in particular to an internet-based jacquard vamp production management method, which comprises the following steps of: deploying a photoelectric sensor to acquire needle position and color matching parameters, filtering vibration tension and beat signals to generate a process data stream, a proportion operation color block and a stroke extraction breakpoint are input into an offset model to generate an adjustment threshold, a multi-target decision distribution weight is combined with pattern complexity to generate a needle bed action priority, remaining needle positions and needed needle positions are judged to generate a control instruction packet, and an issuing controller obtains feedback coordinates to calculate deviation overrun to trigger a calibration command. According to the invention, a photoelectric sensor array is used for capturing needle position and color matching parameters, a noise algorithm is used for suppressing vibration and tension fluctuation, breakpoint coordinates are calculated and extracted, a needle position offset model is constructed, a multi-target algorithm is used for generating an action sequence, needle position and color block requirements are dynamically matched, an instruction is automatically generated, synchronization precision is improved, intervention is reduced, and shutdown is reduced. And self-matching control is enhanced, and closed-loop production control is realized.

The invention discloses a 3D printing method for realizing high color accuracy and real-time effect preview based on a pre-calculated material stacking scheme database, and belongs to the technical field of 3D printing. The core of the method is that a material stacking scheme database of the corresponding relation between printing result colors and material stacking schemes and printing effects is constructed in advance: after multiple basic semitransparent printing materials are arranged according to a specific rule, stacking printing is carried out through different sequences and combinations, and a physical color sample array is formed; after highlight interference is eliminated through a polaroid, color data of all samples are accurately collected, and a mapping relation is established between the color data and corresponding material stacking schemes and printing effects and stored in a database. When target color content is printed, the system queries the database through an efficient color matching algorithm, the optimal printing formula is rapidly obtained, meanwhile, the printing effect is accurately previewed through the real-time rendering technology, and the query efficiency of the algorithm is improved through the ordered arrangement structure of the database. And finally, the printer prints layer by layer according to the obtained stacking scheme, and a pattern effect with accurate colors is presented on the bottom surface of a finished product. According to the method, repeated calculation of a complex color model is avoided, and color printing which is high in color accuracy, low in cost, high in efficiency and compatible with various consumables is achieved through the experience database constructed at a time.

One or more embodiments of the present description provide a fabric fusion method and apparatus, and a product color matching method and apparatus. The fabric fusion method comprises: acquiring a standard fabric figure and a product style figure; fusing the product style figure and the standard fabric figure to obtain an intermediate effect figure; determining, as a fabric figure to undergo fusion, image content in the standard fabric figure for fusion with the product style figure; and fusing the intermediate effect figure and the fabric figure to undergo fusion to obtain a final effect figure.

A system for estimating the feed intake of dairy cows in feeding areas based on computer vision belongs to the technical field of estimating the feed intake of dairy cows in feeding areas. It aims to solve the problem that the existing feed intake estimation of dairy cows in feeding areas cannot meet the actual needs of pastures and the problem of inaccurate estimation. The present invention includes a data acquisition module for obtaining RGB images of the feed area before and after feeding dairy cows, a feed area segmentation module for processing and identifying the RGB images using an image segmentation model and extracting a mask image of the feed area; a data processing module for performing color matching on the mask images corresponding to before and after feeding dairy cows, obtaining the RGB images of the mask image area and then obtaining a difference image, and a total feed intake estimation module for estimating the total feed intake of the obtained difference image using a total feed intake estimation model.

The invention relates to an automobile seat quality multi-dimensional detection and identification method based on AI vision. Firstly, a shooting sequence is planned according to the orientation relation between a seat detection surface and a robot and the movement range of a mechanical arm, and efficient posture adjustment of an invisible surface is achieved in combination with rotation of a rotary disc; secondly, determining an optimal shooting angle based on the curvature of the detection surface, and calculating the minimum shooting times according to the area of the suture region and the view of the camera; an image is pre-collected before photographing, light supplement is dynamically triggered through gray analysis, light supplement colors are matched based on leather-sewing line color matching, and the light supplement brightness and angle are analyzed; and finally, splicing the acquired images into a panorama, comparing the panorama with a defect example library, identifying the defect types of broken lines and skew stitches, quantifying the severity and feeding back the severity. According to the invention, the problem of lack of special analysis of stitches in traditional detection is solved, the quality of the stitches is deeply analyzed, shooting and light supplementing schemes are optimized, and the image acquisition efficiency and detection precision are improved based on cooperation of multiple mechanical arms.

The invention relates to the technical field of data processing, and discloses a visual large-screen dynamic display method and system based on data driving, and the method comprises the steps: collecting business scene demand data, generating a display logic configuration instruction, and setting a display content type, a spatial layout and an interaction mode; the calling data interface is connected with a background storage system and obtains service data in real time through the data stream processing module; performing time sequence analysis, sliding window detection and association rule calculation on the data to obtain a freshness index, an abnormal fluctuation parameter and a coupling degree, and judging whether abnormal fusing is triggered or not; performing exception filtering and standardization on the processed data, mapping the processed data into a graph data structure, optimizing layout through the Fresnel's law, adjusting color matching through a color contrast algorithm, and generating a chart graph; and dynamically refreshing the interface by the rendering engine. According to the method, on-demand customization and dynamic adaptation are realized, and the influence of wrong data on the accuracy of a large screen is avoided.

The utility model provides a rotary drum type color mixing device for design, which comprises a base, a cylinder fixedly mounted on the base, six layers of sliding rails fixedly mounted on the outer wall of the cylinder, a sliding ring slidably mounted on the sliding rails, three pigment trays fixedly connected to the peripheral side of the sliding ring, and a color mixing tank and a cleaning tank arranged on the base around the cylinder, the top end of the cylinder is fixedly provided with a top plate, and the periphery of the top plate is fixedly provided with sector plates. The sliding ring is rotatably connected outside the cylinder, the paint plates are fixedly connected outside the sliding ring, the paint plates are installed in a stacked mode, the paint plates on the upper layer can seal the paint plates on the lower layer, the lifting rod is arranged in the cylinder, and the lifting rod ascends and descends to drive the limiting ball to move through the cross rod, so that limiting of the sliding ring is relieved, and the sliding ring on the upper layer is rotated. The sliding rings and the pigment plates are fixedly connected through the countersunk bolts, so that disassembly, assembly, cleaning or maintenance and replacement are facilitated.

The present application discloses a method and device for improving the efficiency of color matching engineering based on a large model, belonging to the technical field of vehicle color matching. The method includes: collecting color matching data; importing the vehicle data of the vehicle to be matched into the trained color matching model to obtain color matching suggestions; processing the vehicle model of the vehicle to be matched based on the color matching suggestions, vehicle data and color harmony algorithm to generate a second vehicle color matching model; processing the second vehicle color matching model based on the environment model to obtain the vehicle's exterior effect; processing the second vehicle color matching model based on light source data and in combination with a color physics algorithm to determine the vehicle's interior effect under different light source settings. The present application achieves the technical effect of improving the efficiency of vehicle color matching design through the above method.

The invention discloses a tea space color matching method, device and equipment based on user preferences and a storage medium, and relates to the technical field of intelligent design, and the tea space color matching method based on the user preferences comprises the following steps: obtaining a tea ceremony type label, a tea ware picture, a tea space intention picture, an artistic conception text description and other multi-modal data input by a user; analyzing and generating a tea culture semantic vector, and extracting key features in the image by using an improved convolutional neural network to generate an image feature vector; and then, fusing the two into a user preference vector through a multi-modal attention mechanism, and finally, calculating the similarity between the vector and a color matching scheme feature vector in a preset database, and determining a most matched target tea space color matching scheme. According to the method, the personalized color matching scheme conforming to tea space culture attributes can be generated according to user interests and preferences, and efficient and accurate personalized recommendation is realized.