87 results about "Color model" patented technology

The invention discloses a semiconductor photoelectric chip anomaly detection method and device and computing equipment, and the method comprises the steps: loading a first target chip image, based on a first color model, of a target semiconductor photoelectric chip, and converting the first target chip image into a second target chip image based on a second color model, the second color model comprises 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 collecting a feature vector of each target superpixel in the target chip superpixel image; predicting a plurality of target key areas in the target chip superpixel image by using the target visual large model; based on the feature vector of each target superpixel, generating a corresponding OCSVM model for each target key area; and performing anomaly detection on any target key area based on the OCSVM model corresponding to any target key area. According to the invention, accurate anomaly detection can be carried out on the single key area of the semiconductor photoelectric chip.

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.

This invention provides a method for detecting adhesive buildup on the surface of a running track, comprising: acquiring an HSV image corresponding to the running track to be tested; performing a first image processing on the HSV image to obtain a first intermediate image identifying a feature region; the feature region consisting of undifferentiated adhesive buildup areas and interference areas; performing a second image processing on the HSV image to obtain a second intermediate image identifying interference areas; and determining the target information of the adhesive buildup on the surface of the running track to be tested based on the first and second intermediate images. A running track surface adhesive buildup detection device, a computer device, and a storage medium are also provided. Using the HSV color model, and through relevant image processing on the HSV image, the target information of the adhesive buildup on the surface of the running track to be tested is finally determined; compared with manual visual inspection, this method can greatly improve detection efficiency, reduce labor costs, and accurately determine the target information such as the area of ​​the adhesive buildup on the surface.

The invention provides a novel back contact photovoltaic cell film color sorting method, and relates to the technical field of back contact photovoltaic cell film color sorting.The novel back contact photovoltaic cell film color sorting method comprises a test table top, a back contact photovoltaic cell is arranged on the upper surface of the test table top, and a first test positioning device is arranged at the upper left corner of the test table top; the upper right corner of the test table board is provided with a second test point, the lower left corner of the test table board is provided with a third test point, the lower right corner of the test table board is provided with a fourth test point, and the center of the test table board is provided with a fifth test point. According to the method, the lightness value (L), the red-green chroma value (a) and the yellow-green chroma value (b) of the battery piece are tested by the spectrum luminosity tester through the Lab color model and are compared with the film color standard value to calculate the color difference value, whether the battery piece has color difference or not can be accurately determined through the HSV color model and the lab color model, operation is easy, production line application is convenient, the situation that color difference pieces are mixed into bulk goods can be eradicated, and the production efficiency is improved. And the product quality is improved.

The present invention discloses a contactless automatic analysis method for the degree of eye redness, comprising the following steps: photographing a human eye from the front of the face, performing eye region detection and image preprocessing on the photographed image, performing scaling and preprocessing, and then using a U-Net++ model to detect the sclera region to obtain a binary image, performing an AND operation on the binary image and the scaled image to obtain a sclera region color map; performing image smoothing and adaptive histogram equalization to enhance image contrast, filtering the image enhancement image using a B-COSFIRE filter, and converting the image enhancement image into a LAB color model to obtain an image mask; finally, performing an AND operation on the filtered image and the image mask to obtain a bloodshot binary map; and calculating the number of non-zero pixels in the sclera region color map and the bloodshot binary map, respectively, and then performing a ratio calculation to obtain the eye redness ratio. The present invention provides a contactless automatic analysis method for the degree of eye redness, which has high adaptability and accuracy in automatic determination and can achieve intelligent auxiliary diagnosis of the degree of eye redness in patients.

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.

According to various embodiments, there is provided an operation method of an electronic device including: acquiring a plurality of images of a user, captured by an RGB camera of the electronic device, acquiring a specific area on a specific body part of the user from the plurality of images, generating a plurality of first data associated with an RGB color model on the specific area associated with the plurality of images, generating a plurality of second data associated with a YCrCb color model based on the plurality of first data, generating first time-series data associated with a green channel based on the plurality of first data; generating third time-series data based on combining the first time-series data and the second time-series data; and estimating a pulse of the user based on conversion of the third time-series data into a frequency domain.

The invention relates to the technical field of remote sensing observation, and discloses an image color uniformizing model training method and device and an image color uniformizing method and device, and the method comprises the steps: constructing a training sample library and a verification sample library for an initial image in an image set; the training sample library is used for training the multiple different initial models, and multiple initial uniform color models are obtained; combining the initial uniform color models in pairs to obtain a plurality of candidate uniform color combination models; samples in the verification sample library are input into the candidate uniform color combination models, output results of the candidate uniform color combination models are obtained, one initial uniform color model in the combination models obtains a first uniform color image, the other initial uniform color model obtains a second uniform color image, and the output results are the second uniform color image; and evaluating and selecting an output result of each candidate uniform color combination model. According to the invention, the problem that color uniformity between images at different positions cannot be processed because reference images at the same position need to be subjected to model training is solved.

The invention relates to a three-dimensional part color recovery method and device, equipment, a medium and a product. The method comprises the steps of obtaining an initial model file corresponding to a target part; recursive analysis processing is conducted on the initial model file, a topological shape set and a color set are obtained, and the color set comprises colors corresponding to all topological shapes in the topological shape set; obtaining a target assembly structure corresponding to the target part, and constructing a target shape combination based on the topological shape set and the target assembly structure; and performing color mapping processing on the target shape combination by using the color set and the target assembly structure to obtain a color model file corresponding to the target part. By adopting the method, the visualization accuracy can be improved.

The present invention discloses a method for dynamic recognition of handwritten mathematical formulas based on multimodal feature fusion, comprising the following steps: 1. encoding and converting the stroke trajectory sequence information contained in the data using the HSV color model to generate an HSV pseudo-color image, and then fusing the HSV pseudo-color image with the data binary image to obtain a temporal rich image; 2. extracting features from the temporal rich image and the stroke trajectory sequence using a convolutional neural network to obtain image features and stroke features, and enhancing the stroke features using the image features, and then fusing the image features with the enhanced stroke features to obtain multimodal features; 3. enhancing the input multimodal features using position encoding using a decoder, and then performing symbol prediction in combination with an attention mechanism and a multi-scale symbol counting module to generate a mathematical formula symbol sequence; and 4. designing rules to correct the generated mathematical formula symbol sequence. The present invention can improve the accuracy of easily confused character recognition.

The embodiment of the invention discloses an image labeling method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a target image which comprises a to-be-labeled skin disease region; inputting the target image into the trained segmentation model for processing, and outputting an initial segmentation region; the segmentation model is obtained based on sample image training of a marked skin disease area, the segmentation model comprises an encoder, a decoder and a Mama bridging module connected between the encoder and the decoder, and the Mama bridging module is used for performing multi-scale fusion on high-level semantic features and low-level detail features which are extracted by the encoder and have different scales; and performing color feature screening on the initial segmentation region based on an HSV color model to obtain a target region image.

The invention discloses a cross color suppression method and system for multi-color 3D printing. The cross color suppression method comprises the following steps: establishing a steady-state operation reference before material switching, executing a pre-switching withdrawing action, guiding a new material to be stably injected and fused with a residual melt, reconstructing a cooperative relationship between extrusion flow and a nozzle moving path, and implementing dynamic pressure balance regulation and control; according to the method, a local path fine tuning instruction adaptive to material characteristics is generated, progressive flow climbing is executed, state verification after switching is completed, and other systematized steps are carried out, so that accurate control over the material switching process is achieved; the color crossing phenomenon in multi-color 3D printing is effectively inhibited, the color boundary is clear and sharp, the mechanical performance of a transition area is uniform and stable, meanwhile, material waste and time delay caused by excessive pre-extrusion in a traditional method are avoided, the appearance quality and structural reliability of a multi-color printed piece are remarkably improved, and the application prospect is wide. And the method is particularly suitable for manufacturing requirements of high-precision color models and functionally graded materials.

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.

Embodiments of the present application disclose a light balance method and device, equipment and a storage medium. The L channel picture in the LAB color model of the acquired to-be-processed image is divided into two regions, and a first target picture and a second target picture are generated. The brightness values of the first target picture and the second target picture are calculated respectively to obtain a first brightness value and a second brightness value. According to the sizes of the first brightness value and the second brightness value, the brightness difference of the first target picture and the second target picture is calculated to generate a brightness difference picture. The brightness difference picture is merged with the to-be-processed image to obtain a target image with balanced light. The L channel picture representing brightness is divided into two regions, the brightness values of the two regions are compared, the brightness difference on the same image is obtained, and the brightness difference picture is generated. The to-be-processed picture is adjusted based on the brightness difference picture to obtain an image with uniform brightness, so that the image meets the standard and the waste piece rate of the photographing device is reduced.

The invention discloses a monocular vision bridge structure three-dimensional reconstruction method, which comprises the following steps: camera calibration: adopting a Zhang camera calibration method to shoot a plane calibration plate image, and resolving an internal parameter matrix K and an external parameter matrix M of a monocular camera; monocular depth and pose estimation: obtaining a bridge structure video shot by a monocular camera, processing video frames through a MonoViT model, and outputting a depth map and a camera pose of each frame; constructing a neural radiation field (NeRF) model fused with depth information: taking a 5D vector as an input, the 5D vector comprising three-dimensional space coordinates (x, y, z) and a visual angle direction (theta, phi), and outputting a density sigma and a color RGB through an MLP network; model training and three-dimensional reconstruction: taking the depth map, the camera pose and the corresponding video frame as training data, and optimizing NeRF model parameters through a total loss function; and after training is completed, inputting any visual angle parameter, synthesizing a new visual angle image through volume rendering, and realizing three-dimensional reconstruction of the bridge structure.

1. The name of the product under this design: Water Purifier (168 two-color model). 2. Purpose of this design product: used for purification of drinking water. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture. 5. The bottom view of this design product is a part that is difficult to see or cannot be seen when in use, so the bottom view is omitted.

This invention provides an image processing method that enables highly accurate acquisition of information about a subject from an image. [Solution] The image processing method includes an acquisition step of acquiring first information relating to the color of a subject, a first database of color models, and second information relating to ambient light; a determination step of determining the state of ambient light using the second information; and a modification step of changing at least one of the processing relating to the first information or the processing relating to the first database based on the determination result of the state of ambient light.

The invention belongs to the technical field of image recognition, and particularly relates to a garbage classification method and system based on image enhancement, and the method comprises the steps: carrying out the preprocessing of an obtained garbage image, and sampling a reference region block according to a local color variance, so as to extract a reference color model and a reference texture model; calculating a color consistency index, a texture homology index and a structure regularity index of each pixel point; determining a self-adaptive color weight and a self-adaptive texture weight according to a color statistical characteristic and a texture distribution characteristic in the reference region block; and based on the self-adaptive color weight, the self-adaptive texture weight and a preset structure weight, carrying out weighted fusion on the three indexes to generate a material authenticity map. According to the method, the enhancement effect on the complex stained junk image can be remarkably improved by fusing the multi-dimensional features and adopting the self-adaptive weight.

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.

The application discloses a stereoscopic forming method, a stereoscopic forming device and a storage medium, which mainly forms a current printing layer through solidification, then forms a pigment layer, solidifies the pigment layer to adhere to the current printing layer, forms a color model through superposition, realizes one-time printing of the color model, does not need to be colored separately, and is flexible in color. The main technical scheme of the application is as follows: a stereoscopic forming method, comprising the following steps: adding printing material to a construction window, the printing material being in a covering position of the construction window and corresponding to a current printing layer of a to-be-printed model, controlling a printing platform to be close to the construction window, so that the printing material is solidified on the printing platform to form the current printing layer of the to-be-printed model, controlling the printing platform to be away from the construction window, removing the printing material on the construction window, spraying a layer of pigment layer on the construction window, the pigment layer corresponding to the current printing layer, and controlling the printing platform to be close to the construction window, so that the pigment layer is solidified on the current printing layer. The application is mainly used for printing a model.

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.

Embodiments of the present disclosure disclose a three-dimensional reconstruction method, a color information acquisition method, an apparatus and a device, wherein the reconstruction method comprises: processing a pixel three-dimensional coordinate set of a pixel point set of a target object surface by using an SDF network to obtain an SDF value set of the pixel point set; processing the pixel three-dimensional coordinate set by using a neural feature network to obtain a neural feature map of the pixel point set; processing, by using a decoding network, based on the SDF value set, the neural feature map and a camera line-of-sight set, to obtain a color information set of the pixel point set; and determining a three-dimensional structure color model of the target object based on a three-dimensional structure model of the target object and the color information set. The embodiments of the present disclosure can realize real-time rendering of the three-dimensional structure model while ensuring a high-quality mesh, and obtain a three-dimensional structure color model of the target object with color information.

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.

The application discloses a kind of based on plane Gauss's color model construction method, system, device and medium, method includes the position parameter of initialization Gauss ball, depth order, shape attribute, color attribute and opacity;According to shape attribute, the shortest axis of Gauss ball is determined, and then flat loss is calculated;According to the shortest axis and observation direction, the local normal of Gauss ball is obtained and then normal alignment loss is calculated;According to opacity, sparsity loss is calculated;Gauss ball is colored and color loss is calculated, according to flat loss, normal alignment loss, sparsity loss and color loss, construct final loss function, and shape attribute, local normal, opacity and color attribute are updated by back propagation algorithm.The application improves normal estimation accuracy by flattening Gauss ball, and then improves the color quality, by combining color model, high-quality rendering of a variety of materials is realized, and can be widely applied in computer vision technical field.

This invention proposes a method and system for controlling the color gamut of a mobile phone screen. The method includes: collecting the spectral characteristics of ambient light and constructing a spectral matrix; constructing a dynamic reference color model based on the spectral matrix to generate a global color gamut adjustment matrix; dynamically adjusting the screen color gamut according to the global color gamut adjustment matrix; collecting the user's eye movement data in real time, constructing a gaze region, and performing regional color gamut optimization analysis by combining the gaze region with the dynamic reference color model; performing local compensation based on the optimization analysis results and the global color gamut to generate a final local color gamut matrix; reducing energy consumption in non-gaze regions and minimizing unnecessary color processing. This invention, by combining ambient spectral detection and eye-tracking technology, provides an intelligent and dynamic color gamut adaptive adjustment system, solving the shortcomings of existing technologies in terms of ambient light adaptability, color accuracy, and energy efficiency, and has significant innovation and practical value.

The application is suitable for the field of image technology, and provides a chart image processing method and device, electronic equipment and readable storage medium. The method comprises the following steps: acquiring a to-be-processed chart image; converting the color model of the to-be-processed chart image into an HSV color model to obtain a converted chart image; generating a chart mask of each water depth area according to the HSV color of each pixel point in the converted chart image; extracting the corresponding water area contour in the converted chart image according to the chart mask of each water depth area; determining the longitude and latitude information of the water area contour of each water depth area based on a coordinate registration model; and constructing the corresponding chart vector contour according to the longitude and latitude information of each water area contour and the attribute information of the to-be-processed chart image. The application can automatically process the chart image in the whole link and ensure the image processing quality.