16 results about "Color model" patented technology

One variation of a method for modeling a human body includes: driving a sensor block along a path above a platform occupied by a user and recording a sequence of depth images and color images, via the sensor block, at each capture position in a sequence of capture positions along the path; compiling the set of depth images into a low-density 3D model of the user and a high-density 3D model of the user; extracting a set of color patches, from the sequence of color images, corresponding to discrete regions on a surface of the low-density 3D model of the user; projecting the set of color patches onto the surface of the low-density 3D model to generate a 3D color model of the user; and extracting a value of a dimension, projected from the low-density 3D color model onto the high-density 3D model, from the high-density 3D model.

This application provides a method and system for processing surface defects on silicon wafers, an electronic device, a computer-readable storage medium, and a product. The processing method includes: acquiring image information, whereby the image information characterizes defect features on the silicon wafer surface, and the defect features characterize the peak and valley differences on the silicon wafer surface within a preset unit area; processing the image information to convert it into a surface feature model, where the surface feature model includes grayscale values ​​corresponding to the defect features, with different defect features corresponding to different grayscale values; coloring the surface feature model to generate a color model, where the color model includes a preset set of colors, with different colors corresponding to different grayscale values; and outputting defect identification results based on the color model. In this way, the nanometer-level peak and valley differences on the silicon wafer surface are transformed from discrete numerical values ​​into a visualized color model, thereby solving the problem of not being able to intuitively present defect features and improving the efficiency and accuracy of defect identification.

The application discloses an eye fundus image coloring method, a computer readable storage medium and an electronic device, relates to the technical field of medical image processing, and comprises the following steps: acquiring a gray eye fundus image of a patient with a diagnosis; inputting the gray eye fundus image as a lightness V channel into a pre-trained image coloring model to obtain a hue H channel and a saturation S channel corresponding to the lightness V channel output by the image coloring model; the image coloring model comprises an SPD downsampling module for performing a lossless downsampling operation; and performing color space conversion on the lightness V channel, the hue H channel and the saturation S channel after combination to obtain a color eye fundus image.

The application provides a color painting image reconstruction system and method based on brightness and saturation information matching, and relates to the field of color painting image reconstruction.The application comprises HSI color model conversion, Origin software fitting and reconstructed RGB image;the HSI color model conversion is to convert the measured different color RGB color space into HSI color space;the Origin software fitting is to import the HSI color space data into Origin software for data fitting;the reconstructed RGB image is to reconstruct the obtained HSI color space after fitting to obtain the RGB color image.Through the color painting image reconstruction system, the object color information is efficiently reconstructed, the spectral reflectance characteristics are accurately presented, and a scientific and reliable solution is provided for subsequent 3D object color reconstruction and artistic product digital copying.

Food contact materials with a color difference ΔE <20 from the L*a*b* coordinates to a color number starting with "5" of the RAL color chart according to the color model according to EN ISO 11664-4, to be determined according to DIN 5033 (1979), based on compositions containing at least one polyester or polystyrene and a colorant consisting of at least one blue anthraquinone dye and at least one ethylene oxide-propylene oxide block copolymer with a central propylene oxide unit between two ethylene oxide units, a molar mass determined from the OH number to be determined according to DIN / ISO 4629, in the range of 5500 to 7500 g / mol, a mass fraction of ethylene oxide units in the range of 45 to 55 wt.% and a flocculation point to be determined according to EN 1890 method B in the range of 70°C to 85°C.

Food contact materials with a color difference ΔE <20 from the L*a*b* coordinates to a color number starting with "3" of the RAL color chart according to the color model according to EN ISO 11664-4, to be determined according to DIN 5033 (1979), based on compositions containing at least one polyester or polystyrene and a colorant consisting of at least one red azo dye and at least one ethylene oxide-propylene oxide block copolymer with a central propylene oxide unit between two ethylene oxide units, a molar mass determined from the OH number to be determined according to DIN / ISO 4629, in the range of 5500 to 7500 g / mol, a mass fraction of ethylene oxide units in the range of 45 to 55 wt.% and a flocculation point to be determined according to EN 1890 method B in the range of 70°C to 85°C.

Embodiments of the present specification disclose a skeleton screen detection method and device, electronic equipment, medium and program product. The method comprises: obtaining a screenshot of a page to be detected; based on the screenshot of the page to be detected, extracting a target color model corresponding to the page to be detected; and based on the target color model, determining a target skeleton screen detection result corresponding to the page to be detected.

The present application relates to a kind of Mamba network scenic spot crowded people identification method, specifically to a kind of Mamba network scenic spot crowded people identification method based on LUV color model.The method includes the following steps:1, the original RGB image to be identified is converted into LUV image;2, LUV image is sequentially subjected to random cutting, random flip and random rotation, realizes data enhancement;3, the LUV image after data enhancement is divided into training set and test set, and constructs Mamba network;4, the LUV image in training set is input into Mamba network training, obtains the Mamba network of training;5, the LUV image in test set is input into the Mamba network of training and generates prediction frame, i.e. the density detection frame for indicating crowded area position.The present application can effectively reduce the influence of illumination variation on crowded people detection, improve robustness and accuracy in crowded people identification task, especially suitable for complex illumination environment under scenic spot scene.

Food contact materials with a color difference ΔE <20 from the L*a*b* coordinates to a color number starting with "4" of the RAL color chart according to the color model according to EN ISO 11664-4, to be determined according to DIN 5033 (1979), based on compositions containing at least one polyester or polystyrene and a colorant consisting of at least one violet anthraquinone dye and at least one ethylene oxide-propylene oxide block copolymer with a central propylene oxide unit between two ethylene oxide units, a molar mass determined from the OH number to be determined according to DIN / ISO 4629, in the range of 5500 to 7500 g / mol, a mass fraction of ethylene oxide units in the range of 45 to 55 wt.% and a flocculation point to be determined according to EN 1890 method B in the range of 70°C to 85°C.

Food contact materials with a color difference ΔE <20 from the L*a*b* coordinates to a color number starting with "2" of the RAL color chart according to the color model according to EN ISO 11664-4, to be determined according to DIN 5033 (1979), based on compositions containing at least one polyester or polystyrene and a colorant consisting of at least one orange methine dye and at least one ethylene oxide-propylene oxide block copolymer with a central propylene oxide unit between two ethylene oxide units, a molar mass determined from the OH number to be determined according to DIN / ISO 4629, in the range of 5500 to 7500 g / mol, a mass fraction of ethylene oxide units in the range of 45 to 55 wt.% and a flocculation point to be determined according to EN 1890 method B in the range of 70°C to 85°C.

This invention discloses a method, apparatus, and computing device for anomaly detection in semiconductor optoelectronic chips. The method includes: loading a first target chip image based on a first color model and converting it into a second target chip image based on a second color model, the second color model including a red channel, a saturation channel, and a brightness channel; performing superpixel segmentation on the second target chip image to obtain a target chip superpixel image, and acquiring the feature vector of each target superpixel in the target chip superpixel image; predicting multiple target key regions in the target chip superpixel image using a target visual large model; generating a corresponding OCSVM model for each target key region based on the feature vectors of each target superpixel; and performing anomaly detection on any target key region based on the OCSVM model corresponding to any target key region. This invention can perform accurate anomaly detection on a single key region of a semiconductor optoelectronic chip.

The application discloses a video coloring model construction method, a video coloring method, equipment and a medium, and the method comprises the following steps: sampling key frames from a grayscale video sequence; extracting scene description text and generating a color reference image; constructing a basic video generation model, introducing a main branch with parameter freezing and a control branch with parameter training; constructing a composite visual sequence and setting a time sequence mask sequence; extracting spatio-temporal control features in the control branch, and injecting the main branch with residual superposition; introducing an alignment loss function to train the control branch, extracting deep target semantic features of the color reference image, mapping the intermediate features denoised by the main branch to a semantic space; setting a loss function to jointly construct a total training target and minimize, iteratively optimizing specified parameters to obtain a video coloring model, and performing a video coloring operation. The application can effectively decouple single-frame content color editing and long-sequence time sequence color propagation, and improve the color fidelity and dynamic time sequence consistency of the generated video.

The application discloses a kind of well mine based on three-dimensional Gaussian sputtering dynamic three-dimensional scene reconstruction method, through multimodal perception degradation modeling and compensation, unified processing structural degradation, environmental degradation and sensor failure, combined with time compensation, multi-source fusion and IMU alignment ensure data stability.Construct dynamic target and static environment decoupling three-dimensional Gaussian model, adopt local coordinate system modeling and time sequence posture tracking to realize continuous geometric expression, and be optimized by re-projection error and motion smoothness constraint jointly.Innovatively, neural network is used to predict Gaussian color, multi-scale features, dynamic mask and feature sampling are fused, and spherical harmonic function is replaced to realize high-precision color modeling under dynamic lighting.Compared with traditional methods, the application breaks through the dependence of static scene and high-quality data, reduces complexity through "global motion + local correction" posture modeling, improves the real-time performance and engineering applicability of dynamic scene reconstruction, and supports intelligent application of well mine.

The application discloses a face recognition processing method and device, and relates to the field of biometric recognition technology in the field of artificial intelligence. A specific embodiment of the method comprises the following steps: receiving an original face image collected by a face collection interface, inputting the original face image into a preset color model to obtain a hue value and a brightness value of each pixel point; determining a pixel point set whose hue value is located in a preset hue range and whose brightness value is located in a preset brightness range, obtaining a skin color region in the original face image, and performing auditing processing on the skin color region; through auditing, calling a preset face detection model to identify whether a face in the original face image is complete, and in response to an identification result that the face is complete, transmitting the original face image to a face recognition interface for processing. The embodiment adds a face image evaluation link, and the face image is sent to a face library for recognition processing after evaluation, so that the face library recognition success rate is increased, and the user face payment experience is improved.