476 results about "Color data" patented technology

The invention discloses a composite optical detection method and system for metal surface corrosion, and the method comprises the steps: employing a line scanning camera and a spectrum confocal sensor to carry out the synchronous data collection through a time-space registration method, obtaining the RGB image data of a to-be-detected metal surface through the line scanning camera, i.e., color data, and obtaining the color data of the to-be-detected metal surface; acquiring point cloud data, namely morphology data, of the metal surface to be detected by using a spectral confocal sensor; carrying out multi-modal data fusion on the RGB data and the point cloud data; a data fusion result is optimized by introducing a confidence coefficient weight; a double-threshold segmentation method of a color threshold and a depth threshold is adopted, and a corrosion area in an optimized data fusion result is preliminarily identified; performing morphological post-processing on the preliminary recognition result through opening operation and closing operation to generate a final recognition result; and carrying out quantitative evaluation on the corrosion area by utilizing a final identification result. The method provided by the invention can realize a rapid and accurate detection process.

The invention discloses an intelligent management system and method applied to clothing flexible customization, and relates to the technical field of clothing intelligent manufacturing, and the system comprises a multi-source color data acquisition module, a color space preprocessing module, a dynamic color space mapping module, an edge real-time calibration module, an equipment state monitoring module and a full-process data closed-loop module. Wherein the multi-source color data acquisition module constructs a cross-device color reference library, the color space preprocessing module standardizes color data and unifies a color gamut, the dynamic color space mapping module generates and optimizes a dynamic conversion matrix, and the edge real-time calibration module updates device parameters in combination with fabric characteristics. The equipment state monitoring module constructs a correlation model to analyze the equipment state and color deviation, and the full-process data closed-loop module stores data through a block chain and optimizes an algorithm. The system realizes a complete process from fabric color data acquisition, cross-device mapping calibration, device state monitoring to full-process data closed-loop management through cooperation of the modules.

The invention relates to the technical field of intelligent lighting control, and discloses a light color shift control method and system, and the method comprises the following steps: S1, receiving target color data and shift parameters through a user interaction interface; s2, acquiring an environment color temperature Tamb by using an environment light sensor, and monitoring an LED module junction temperature Tled through a PT1000 type temperature sensor; s3, calculating a color compensation parameter based on the offset parameter in the step S1 and the sensor data in the step S2; and S4, generating a PWM driving signal through an improved HSV-RGB bidirectional conversion model. By receiving the target color data and the offset parameters and collecting the environmental color temperature and the LED module junction temperature data, basic input and real-time state information are provided for color compensation calculation, so that the system can dynamically adjust the color parameters in combination with user requirements and environmental equipment states, and the pertinence and environmental adaptability of color control are improved.

The invention discloses an elastic material hydrofoil fluid-solid coupling cavitation erosion forecasting method based on a potential energy theory, and belongs to the field of computational fluid mechanics and cavitation. The implementation method comprises the following steps: simulating the cavitation of the hydrofoil made of the elastic material by using a tight coupling algorithm to obtain the pressure and steam volume fraction distribution of the surface of the hydrofoil; a steam volume fraction distribution based on pressure; constructing an erosion index correction factor F for representing the bending torsional deformation degree of the elastic material hydrofoil to correct the cavitation erosion index represented by the pressure wave power density; the cavitation erosion indexes larger than a threshold value are screened out, and the final cavitation erosion risk index is a quotient after superposition of the cavitation erosion indexes; the corrected cavitation erosion index data are interpolated into RGB color data, the data serve as a geometric structure model of a fourth-dimensional mapping elastic material hydrofoil, and the corrected cavitation erosion index numerical value is represented through color change. The corrected cavitation erosion index can more accurately forecast a cavitation erosion risk part on the surface of the hydrofoil made of the elastic material.

The invention discloses an automatic grading control system and method for royal jelly, and belongs to the technical field of bee product processing automation. According to the system, color data, moisture data and HDA content data of royal jelly samples are synchronously obtained through a data acquisition module, and a control module performs normalization processing on multi-modal data, constructs a grading model based on a gradient lifting decision tree to generate a grade judgment result and dynamically generates sorting execution parameters. The execution module drives an execution mechanism to complete automatic sorting and packaging, and a man-machine interaction interface supports classification process visualization and parameter real-time adjustment. The method can be widely applied to an automatic grading assembly line of a royal jelly production enterprise, the grading efficiency and accuracy are remarkably improved, the product quality consistency is guaranteed, and data support is provided for subsequent quality tracing.

The invention relates to a computer vision technology, and discloses a laying hen health condition monitoring method and system based on a cockscomb form, and the method comprises the steps: collecting laying hen cockscomb images according to a preset time interval, and forming an image sequence; and carrying out gravity center identification on each image in the sequence, obtaining gravity center sequence data and analyzing gravity center offset. If the center-of-gravity offset exceeds a preset threshold value, color identification is directly carried out on the current image to obtain color data, and if the center-of-gravity offset does not exceed the preset threshold value, the form variation of the cockscomb edge area in the image sequence is analyzed. When the form variation is greater than a preset threshold value, judging that the laying hen is healthy; and if not, returning to execute the color identification step. And finally, performing disease judgment according to the color data to obtain a judgment result. The laying hen health condition monitoring efficiency can be improved.

The invention discloses a self-adaptive parameter calibration camera module automatic debugging system, and relates to the technical field of camera debugging, a parameter calibration module sets a physical parameter threshold value based on the specification of a camera module, then a calibration board is used for geometric and optical parameter calibration, and boundary conditions of the camera module are generated; the self-adaptive debugging module detects environmental parameters of a shooting environment in real time and dynamically adjusts imaging parameters of each camera, the multi-camera coordination module performs exposure coordination across the cameras, adopts global white balance mapping, performs curve alignment according to color temperature response curves of the cameras, and combines a machine learning algorithm to obtain a multi-camera color temperature response curve; and color style matching is carried out on the color data of the multiple cameras, and shooting parameters are adjusted when the multiple cameras are switched. According to the debugging system, a layered debugging framework is combined with environment adaptive optimization and cross-camera parameter coordination, so that an automatic and multi-camera cooperative high-precision parameter calibration process is realized, and the consistency and stability of a camera module are improved.

This invention provides a method and system for inspecting wall decoration, relating to the field of building inspection technology. The method includes acquiring wall decoration data using a laser level and camera equipment, the data including height, level, and image information; sending the data to a wall flatness model for flatness calculation to obtain flatness error data; performing edge calculation based on the flatness error data and decoration data to obtain crack data, including location and shape information; analyzing the data using a data analysis model to obtain smoothness and color data; and finally, sending the flatness error data, crack data, smoothness, and color data to a qualification analysis model for analysis to obtain the wall decoration inspection result. This invention achieves a comprehensive assessment of wall decoration quality through the analysis and detection of multiple data sources, accurately determining whether a wall is qualified, and is characterized by high efficiency, accuracy, and a high degree of automation.

The invention is suitable for the technical field of aircraft obstacle avoidance, and particularly relates to an aircraft obstacle avoidance control method and system, and the method comprises the steps: delimiting a flight region of an aircraft, collecting the stereoscopic optical remote sensing data of the flight region, drawing an obstacle recognition graph, marking the position of an obstacle, and configuring the color of the obstacle. Wherein one obstacle at least corresponds to one color, calculating the height of each obstacle, and marking the height in the obstacle identification graph; and segmenting the height into a plurality of layers, and creating branch nodes and leaf nodes. By constructing the obstacle avoidance tree, the color data of all obstacles can be visually displayed, and the color image can be quickly verified, so that the flight safety is greatly improved while the normal flight of the aircraft is ensured, the suspicious obstacles on the flight path can be verified by extracting the RGB values, the flight path planning is optimized, and the flight path planning efficiency is improved. And the flight safety is further improved.

The invention provides projection equipment and a projection method. The projection equipment comprises a projection module, a driving circuit and a controller. The projection module is used for emitting an image beam according to the display data to form a projection picture. The display data includes first color data corresponding to the first color. The driving circuit is coupled to a light source of the projection module. The light sources include first light sources corresponding to a first color. The driving circuit is used for providing a first driving signal to control the luminance of the first light source. The controller is coupled to the driving circuit. The controller is used for receiving the display data and adjusting the first driving signal according to the first color data. According to the projection equipment and the projection method provided by the invention, the power consumption of the projection equipment can be reduced.

The invention provides a yarn color prediction method and system based on multi-modal learning, and belongs to the technical field of textile printing and dyeing, and the method comprises the steps: firstly, comprehensively collecting blended cotton fiber data, process parameters, fiber color data, yarn appearance images and color data in yarn production, and carrying out the alignment, cleaning and normalization preprocessing of the data; then, a color prediction network composed of a feature extraction module, a compensation fusion module and an output module is constructed, after main modal feature extraction and preliminary prediction are completed through 1D-CNN, auxiliary modal features are extracted with the help of VGG16, and correlation is calculated through the compensation fusion module to achieve compensation for preliminary prediction; and finally, selecting a CIEDE2000 chromatic aberration formula as a loss function, and optimizing model parameters in combination with an Adam optimizer. According to the method, by means of fusion of multi-modal data, a unique fusion compensation strategy and a self-adaptive complementary fusion mechanism, the precision, accuracy and stability of yarn color prediction are remarkably improved, and a more reliable technical scheme is provided for color prediction of colored spun yarns in the textile printing and dyeing industry.

The invention discloses a GPU shader rendering computer implementation method of a finite element result. The method comprises the steps that a static three-dimensional grid is adopted as a rendering geometry; the 32-bit floating point type scalar data corresponding to the vertexes are subjected to lossless coding at a CPU end to obtain four-channel 8-bit RGBA vertex color attributes; during data updating, lightweight vertex color data are only transmitted to the GPU; hardware interpolation is carried out on the encoded color attributes by using a GPU rasterizer; and finally, in the fragment shader, decoding the interpolation result of each pixel to reconstruct a scalar value, and mapping the scalar value into a final color. According to the method, the bottleneck of topological calculation of a CPU end and transmission of massive geometric data to the GPU is avoided, the calculation load is transferred to the GPU in a large scale for parallel processing, the rendering efficiency is remarkably improved, and high-frame-rate dynamic visualization of a finite element result is realized.

The invention discloses an intelligent interaction method and system based on ink-jet printing color recommendation, and relates to the technical field of color management, and the method comprises the steps: obtaining brightness value data of a fabric image and a printing template image; quantifying the glossiness of the surface of the fabric based on the change of the lightness values among the fabric images; quantizing texture complexity of the fabric surface based on distribution of lightness values between pixel points on each fabric image; correcting the color data of the printing template image to obtain corrected target color data; calculating theoretical spectral reflectance corresponding to the mixed ink in different proportions to obtain predicted color data of the mixed ink; the predicted color with the minimum color difference with the target color is matched, and a corresponding optimal ink matching parameter is obtained; according to the method, the glossiness and texture complexity of the fabric are quantified, a traditional color prediction model is corrected, the problem of deviation between the real object color and the screen color can be solved, and high-precision prediction and recommendation of the ink-jet color are achieved.

The invention relates to the field of data analysis, in particular to a publication color adaptive optimization method based on printing color deviation, which comprises the following steps: identifying color data of a publication to extract color block distribution characteristics of the publication; evaluating a printing deviation interference characterization value of the publication based on the color block distribution characteristics in combination with a color number corresponding to a plurality of color blocks of the publication so as to mark the publication; according to the marking result, color printing of the publication is analyzed; according to the method, color data identification and feature extraction, printing deviation interference evaluation and marking, color fusion color block analysis, printing condition judgment and parameter adjustment are carried out on the publications, and then the color fusion color blocks meet the standard printing conditions or not according to the printing level characterization parameters, and the color printing of the corresponding publications is adjusted according to the color data identification and feature extraction, the printing deviation interference evaluation and marking, the color fusion color block analysis and the printing condition judgment and parameter adjustment. And on the premise of adapting to a complex color scene, the printing quality of the publication is precisely regulated and controlled, and the printing precision and the color rendition degree of the publication are improved.

The invention discloses a high-power LED color output control system and method, and belongs to the technical field of LED control. After first color data of an LED light color developing image and second color data of an LED irradiation area image are obtained, the first color data are compared with first expected color data to obtain a first deviation result; comparing the first color data with the second expected color data to obtain a second deviation result, comparing the first color data with the second color data to obtain a third deviation result, carrying out primary correction on the first expected color data according to the second deviation result and the third deviation result, and then carrying out secondary correction according to the first deviation result to obtain a correction result; the corrected first expected color data are obtained, the corrected first expected color data are used as setting parameters of the LED equipment, and the accuracy of the color output effect is improved.

Disclosed is an imaging system with image sensor and processor(s). The image sensor has a plurality of photo-sensitive cells and a colour filter array. The processor(s) is configured to read out unprocessed colour data from those photo-sensitive cells that correspond to the colour filters of the at least three different colours; generate coarse depth data by processing data read out from at least one of: those photo-sensitive cells that correspond to the colour filters that allow the at least one infrared wavelength to pass through the PDAF photo-sensitive cells; perform interpolation and demosaicking on the unprocessed colour data and the coarse depth data, using at least one neural network, to generate a full-resolution colour data and a full-resolution depth data; and reproject the full-resolution colour data from a given camera pose to a given eye pose of a user, by utilising the full-resolution depth data.

A method includes obtaining, using at least one imaging sensor, an image frame. The method also includes mapping, using at least one processing device, the image frame to a mesh including multiple vertices. The method further includes performing, using the at least one processing device, noise reduction to determine color data of pixels located on the vertices of the mesh. Performing the noise reduction includes using a denoising filter to denoise the image frame. The method also includes determining, using the at least one processing device, color data of remaining pixels not located on the vertices of the mesh based on the determined color data of the pixels located on the vertices to generate a denoised image. In addition, the method includes performing, using the at least one processing device, image enhancement of the denoised image to enhance at least part of the denoised image and generate an enhanced image.

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.

The invention belongs to the technical field of production control, and particularly relates to a wearable / attachable ammonia colorimetric sensor, a preparation method and leakage risk monitoring application thereof. The invention discloses an adhesive and stretchable ammonia colorimetric sensor. The sensor is deposited on a non-woven fabric through electrostatic spinning of polylactic acid (PLA) based on bromocresol green (BCG). The feature color data is extracted by combining a deep learning semantic segmentation algorithm, and the data is converted into a CIE L * a * b * color space, so that colors are analyzed and compared more accurately. The conversion from color data to gas concentration is realized by adopting a deep neural network, and the system has a low-power-consumption, wearable / attachable and visual ammonia gas leakage real-time monitoring function.

The invention relates to the technical field of novel ink, and provides a spot color separation method and system for ink recovery. The method comprises the following steps: acquiring an RGB image of a printing recovery product; pixel segmentation is carried out on the image, and color and coordinate data of pixels are marked; performing region clustering according to the color data to obtain a plurality of recovery regions; identifying coordinates of the recovery area, and controlling the recovery device to dissolve and separate the ink in the target area to obtain mixed ink; and constructing a spot color adjustment module, and blending the mixed ink with the ground color ink to obtain the spot color ink. The technical problems that in a traditional ink recycling technology, due to the fact that different color areas cannot be accurately separated, the recycled novel ink is low in purity and cannot be directly recycled are solved, high-precision color area segmentation is achieved through multi-stage clustering, local dissolution and a special hue and process are combined, and the efficiency is improved. And the purity of the recovered novel ink and the direct reuse rate of the novel ink are improved.

A method implements masked text processing for information processing with documents. The method involves receiving a document page as an image including text image data. The method further involves extracting text unit data and text location data from the image corresponding to the text image data using an optical character recognition (OCR) engine. The method further involves generating mask data for the text unit data with color data based on text type data. The method further involves producing a masked image by replacing the text image data with the mask data using the color data with the location data in the image. The method further involves transmitting the masked image to a machine learning model to execute a downstream task.

A tiled display screen (100), a tiled display system and a grayscale compensation method, belonging to the technical field of display. The tiled display screen (100) comprises a plurality of mutually-tiled display modules (10). Each display module (10) comprises a data acquisition device (101), a display driver board (TCOM) and a display screen (105). Each display driver board (TCOM) comprises a processing unit (102), a controller (104) and a memory (103); the data acquisition device (101) is configured to acquire actually measured color data in a corresponding target color space when the display screen (105) is illuminated with a preset initial grayscale, and send the actually measured color data to the processing unit (102); the processing unit (102) is configured to determine, on the basis of the actually measured color data and predefined target color data in the target color space corresponding to the preset initial grayscale, color compensation data under the preset initial grayscale, and send the color compensation data to the memory (103) for storage; and the controller (104) is configured to retrieve the color compensation data from the memory (103) in response to a power-on startup signal, and control the display screen (105) to display images on the basis of the color compensation data.

A human posture judgment method and a mobile machine using the method are applied to the technical field of human posture judgment. The posture of a human body is detected by the following steps: obtaining a ranging image by a ranging camera; detecting a plurality of key points in an estimated skeleton of a human body in color data of the ranging image, and calculating positions of the detected key points based on depth data of the ranging image; selecting a feature map from a group of predefined feature maps based on the detected key points in a group of predefined key points; obtaining two features of the human body corresponding to the selected feature map based on the positions of the detected key points; and determining the posture of the human body according to the two features in the selected feature map.

The invention relates to efficient color conversion using multiple lookup tables. Disclosed are systems and techniques for efficient color conversion. The techniques include receiving a first lookup table (LUT), a corresponding first range, a second LUT, and a corresponding second range. The first range is smaller than the second range. The techniques include receiving first color data of a first color space from a first computer system component. The techniques include, in response to determining that the first color data is within a first range corresponding to the first LUT, converting the first color data of the first color space to second color data of a second color space using the first LUT. The techniques include providing second color data of a second color space to a second computer system component.

The present invention discloses an automated debugging system for camera modules with adaptive parameter calibration, which relates to the field of camera debugging technology. The parameter calibration module sets physical parameter thresholds based on the specifications of the camera module, and then uses a calibration plate to calibrate the geometric and optical parameters to generate the boundary conditions of the camera module. The adaptive debugging module detects the environmental parameters of the shooting environment in real time and dynamically adjusts the imaging parameters of each camera. The multi-camera coordination module coordinates exposure across cameras and uses global white balance mapping to align curves according to the color temperature response curves of multiple cameras. Combined with a machine learning algorithm, the color data of multiple cameras is matched with color styles, and the camera parameters are adjusted when multiple cameras are switched. The debugging system adopts a layered debugging architecture combined with environmental adaptive optimization and cross-camera parameter coordination to achieve an automated, multi-camera collaborative high-precision parameter calibration process, thereby improving the consistency and stability of the camera module.

The application discloses a kind of spatial intelligence three-dimensional reconstruction method and system based on cross-scale topological consistency, it is related to spatial intelligence field, solve the problem that existing spatial intelligence three-dimensional reconstruction technology exists three-dimensional reconstruction effect is not good, including steps S1: acquisition area plan image is carried out to modeling region space marking, obtain modeling region plan image, to target modeling region preliminary creation three-dimensional model, obtain target region preliminary three-dimensional model, step S2: target region preliminary three-dimensional model is verified with target modeling region scene geometry topological, according to the topological element repair of target region preliminary three-dimensional model according to verification result, obtain target region repair three-dimensional model, step S3: according to the real-time color data of target modeling region corresponding to target region preliminary three-dimensional model is carried out real-time color restoration, obtain spatial region three-dimensional reconstruction model, the application improves the structural integrity and geometric accuracy of three-dimensional model under complex scene.

The application discloses a display device color self-adjusting system and method for a matching-free color analyzer, a measurement data picture on a panel of the color analyzer is acquired through a camera of an intelligent display device, and the intelligent display device parses measurement values from the panel picture through deep learning according to the picture; then, the recognized display parameter data is compared with standard color data, and the intelligent display device is controlled to modulate standard color data that does not meet the standard, and the production adjustment data is saved in the intelligent display device. The application is not affected by whether the color analyzer and the display device can be matched and connected, application scenarios are expanded, stability is improved, and research and development investment is saved.

A method for producing a plate-shaped three-dimensional object (10, 20, 30), the method comprising: an image preparation step (S10) for creating color image data (P1) containing a colored three-dimensional pattern; a gray scaling step (S20) for gray scaling the color image data (P1) created in the image preparation step (S10) to obtain grayscale image data (P2), wherein the gray scaling step (S20) comprises a brightness adjusting step for adjusting the brightness of at least one of the color image data (P1) and the grayscale image data (P2); a three-dimensional data generation step (S30) for generating three-dimensional data based on a gradation of the grayscale image data (P2) obtained in the grayscale step (S20); a three-dimensional color data generation step (S40) for generating three-dimensional color data (M2) by performing texture mapping on the three-dimensional data (M1) generated in the three-dimensional data generation step (S30) using the color image data (P1) prepared in the image preparation step (S10) as a texture; and a molding step (S50) for molding the plate-shaped three-dimensional object (10, 20, 30) by a full-color 3D printer based on the three-dimensional color data (M2) generated in the three-dimensional color data generation step (S40).

The present invention is to introduce a computer-implemented, web-based stereoscopic acuity computation and stereo eye color accuracy assessment to test for what colors patients are deficient in as seen through the real world in pictures rather than just for color by itself. The pictures are taken with a camera or similar electronic device use. The eye color accuracy exam utilizes caffeine products. The computation takes color characteristics of a target color where they are inputted, identified matched, and processed in a way as to expose a visual deficiency of the target color selected from a color database and color chart based upon color characteristics of the target color to be matched, processed, and visually stereoscopically displayed thus enabling comparison of the alternate color(s) with the target color. The computation uses gamma correction, color thresholding, alpha composing, opacity ratios and eye color accuracy assessment from a patient to provide a result.

To provide a printing system that can suppress a color of a medium from changing hue of an image, while suppressing white ink from being used.SOLUTION: A printing system comprises a discharge part that discharges color ink and white ink to a medium, and a control part that controls the discharge part. The printing system obtains image data, information on colors of the medium and information on a density of white ink. The control part calculates a masking ratio of the medium on the basis of the information on colors of the medium and the density of the while ink, calculates adhesion amounts of white ink that are necessary for masking the medium on the basis of the calculated masking ratio, reads out an image parameter describe below in the image data, performs threshold determination of the read image parameter, and adjusts the adhesion amounts of white ink on the basis of the determined result. One or more image parameters are selected from adhesion amounts of color ink and color data that can be measured with a measurement instrument.SELECTED DRAWING: Figure 1