132 results about "Color model" patented technology

The invention provides a mobile phone screen color gamut control method and system, and the method comprises the steps: collecting the spectral characteristics of ambient light, and constructing a spectrum matrix; constructing a dynamic reference color model based on the spectrum matrix to generate a global color gamut adjustment matrix, and dynamically adjusting the screen color gamut according to the global color gamut adjustment matrix; collecting eye movement data of a user in real time, constructing a fixation area, and performing area color gamut optimization analysis on the fixation area in combination with the dynamic reference color model; according to an optimization analysis result, local compensation is carried out in combination with the global color gamut, and a final local color gamut matrix is generated; the energy consumption of the non-gazing area is reduced, and unnecessary color processing is reduced. The invention provides an intelligent and dynamic color gamut self-adaptive adjusting system by combining environment spectrum detection and eye movement tracking technologies, overcomes the defects of the prior art in the aspects of environment light adaptability, color accuracy and energy efficiency, and has remarkable innovativeness and practical value.

The invention discloses a handwritten mathematical formula dynamic recognition method based on multi-modal feature fusion, which comprises the following steps of: 1, performing code conversion on stroke track sequence information contained in data by adopting an HSV color model to generate an HSV pseudo-color image, and fusing the HSV pseudo-color image with a data binary image to obtain a time sequence rich image; 2, feature extraction is performed on the time sequence rich image and the stroke track sequence through a convolutional neural network, image features and stroke features are obtained, the stroke features are enhanced by using the image features, and multi-modal features are obtained after the image features and the enhanced stroke features are fused; step 3, enhancing the input multi-modal features by adopting position coding through a decoder, and 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, and correcting the generated mathematical formula symbol sequence. According to the invention, the recognition accuracy of confusable characters can be improved.

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.

Disclosed here is a method of matching color and appearance of coatings containing at least one effect pigment. The method involves: obtaining, for a coating sample, sample color image data having pixel-specific color model properties; generating a characterizing histogram for the sample color image data, wherein the characterizing histogram represents an appearance feature descriptor of the coating sample; creating a sample histogram vector from the characterizing histogram; retrieving a specimen histogram vector for a candidate coating specimen; and calculating a cosine similarity value from the sample histogram vector and the specimen histogram vector, wherein the cosine similarity value indicates how well the candidate coating specimen matches the coating sample to be matched.

Disclosed here is a method of matching color and appearance of coatings containing at least one effect pigment. The method involves: obtaining, for a coating sample to be matched, sample color image data having pixel-specific color model properties; creating local binary patterns based on the pixel-specific color model properties; generating a binary pattern histogram for the local binary patterns, wherein the binary pattern histogram arranges the local binary patterns into N distinct bins to obtain N bin counts, and wherein the binary pattern histogram represents an appearance feature descriptor of the coating sample to be matched; and utilizing the binary pattern histogram for comparison against a previously generated binary pattern histogram that serves as an appearance feature descriptor of a candidate coating specimen.

Embodiments of the present description provide a matting parameter determining method, an image processing method, a device, and a storage medium. The method comprises: obtaining an image to be matted and value ranges of channels of background color of said image under a specified color model; and optimizing a pre-constructed objective optimization function on the basis of said image and the value ranges to obtain an optimized value of a matting parameter of said image, wherein the variable of the objective optimization function is the matting parameter, and the optimization objective of the objective optimization function comprises one or more of the following: minimizing the number of misclassified pixel points during classification of pixel points in said image into a foreground area and a background area based on the matting parameter, minimizing the number of pixel points belonging to a transition area between the foreground area and the background area in said image, and minimizing the accumulated value of the probabilities of the pixel points in the transition area. In this way, the matting parameter can be automatically and accurately determined.

The invention discloses a manufacturing method, device and equipment of an insect simulation model, and relates to the field of model manufacturing. The method comprises the following steps: firstly, acquiring a rotary scanning image of an insect sample, and performing three-dimensional reconstruction on the scanning image to obtain a three-dimensional digital gray model of the insect sample; carrying out limb separation, posture adjustment and recombination on the three-dimensional digital gray model of the insect sample to obtain a recombined three-dimensional digital gray model; carrying out local reconstruction and restoration on the recombined three-dimensional digital gray model to obtain a restored three-dimensional digital gray model; rendering and coloring the repaired three-dimensional digital gray model to obtain a three-dimensional digital color model of the insect sample; and carrying out amplification and color 3D printing on the three-dimensional digital color model to print the insect simulation model. The large-size insect simulation model manufactured by the method is high in precision and detail reduction degree, the production speed and the model stability are improved, and the service time of the model is prolonged.

The invention discloses a color matching method based on a COLORO color system. The color matching method is specifically implemented according to the following steps: step 1, constructing a COLORO hue-hue basic model; according to the method, the COLORO hue-hue perceptual model is built, the reliability and precision of building of an existing color model are effectively improved, color selection is carried out, color screening and target confirmation of a product color scheme are well achieved, the color matching quantification efficiency is improved, and the objectivity and scientificity of color matching design are improved; the method has good accuracy, and solves the problems of large workload and low efficiency when a costume designer carries out color matching according to an existing color system.

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 present invention relates to the technical field of image processing, and in particular to a method and system for analyzing the flame of a hydrogen chloride synthesis furnace, including using a flame sensor to determine whether there is a flame in the hydrogen chloride synthesis furnace; collecting a flame video and obtaining a flame image by frame division; performing color detection on the obtained image under the RGB and HSI mixed color models to obtain a flame pixel point distribution matrix and obtain a preliminary image containing a suspected flame area; performing grayscale processing on the preliminary image containing the suspected flame area, using PSO search for global optimization, and substituting the global optimal solution back into the K-means clustering algorithm to perform clustering on the image; multiplying the matrix of the preliminary image containing the suspected flame area by the matrix of the flame image after clustering to obtain the final flame area; adjusting the gas concentration according to the RGB mean value and color temperature of the final flame area. The present invention solves the problem of poor control quality of manually observing the flame color.

The invention discloses a three-dimensional model processing method and device, equipment and a storage medium, and belongs to the technical field of model rendering. The method comprises the following steps: obtaining a model structure of a three-dimensional model, view angle images of an expected texture of the three-dimensional model under n view angles and confidence weights of a vertex in the three-dimensional model under the n view angles, wherein the confidence weight corresponding to a first view angle in the n view angles is in negative correlation with the offset degree of the vertex observed under the first view angle; taking the confidence weights under the n visual angles as color weights of visual angle images under the n visual angles, and performing texture baking on a model structure of the three-dimensional model based on the visual angle images under the n visual angles to obtain a three-dimensional color model; obtaining an observation image of the three-dimensional color model under n visual angles, and correcting the visual angle image according to the difference between the observation image and the visual angle image to obtain a corrected visual angle image; and performing texture baking on the model structure of the three-dimensional model based on the corrected visual angle image to obtain a corrected color model.

An embodiment of the present application provides a method, device, and storage medium for rendering a scene in an oil painting style. In this method, for a three-dimensional scene to be processed, the positions of the outlining lines in each scene element model are determined; according to the positions of the outlining lines, each scene element model is outlined and colored to obtain a three-dimensional scene containing the outlining lines; in the three-dimensional scene containing the outlining lines, according to the texture coordinates of each pixel in the three-dimensional scene, the scene color of the three-dimensional scene is blurred to obtain an oil painting stylized scene. This method depicts the outlines of each original scene color model through edge detection and outlining coloring, and realizes the scene color with an oil painting texture through blurring processing, and can complete the conversion to the oil painting style without re-designing and modeling, greatly improving the scene rendering efficiency and enhancing the scene scalability.

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.

Systems, methods, and apparatuses can store digital image data that is related to an image, or a series of images, commonly visualized as video. These systems, methods, and apparatuses can store the digital image data as unprocessed digital image data in a raw image format that includes color information, for example, luminance and / or chrominance color components of YUV color model and / or red, green, and / or blue color components of a red, green, blue (RGB) color model to provide some examples, for each pixel of the image. These systems, methods, and apparatuses can stripe the digital image data into multiple blocks of image data and can, thereafter, partitions the multiple blocks of image data into multiple blocks of pixel data. These systems, methods, and apparatuses can distribute the multiple blocks of pixel data across multiple memory modules that can operate in parallel to improve read and / or write performance.

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.

A camera includes an infrared thermal sensor, a processor, and an interface module is disclosed. The infrared thermal sensor is configured to generate an original sensing data. The processor is configured to process the original sensing data and generate an invisible light image whose pixel data size is one byte and multiple temperature data whose unit data size is two bytes. The interface module includes multiple transmission interfaces and is configured to transmit a heterogeneous image whose pixel data size is three bytes through one of the multiple transmission interfaces, where a bit-value of the three bytes is a linear combination of a bit-value of the one byte and a bit-value of the two bytes. The processor is configured to merge the invisible light image and the multiple temperature data according to an RGB color model channel to obtain the heterogeneous image of a visible light image format.

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.

A camera includes an infrared thermal sensor, a processor, and an interface module is disclosed. The infrared thermal sensor is configured to generate an original sensing data. The processor is configured to process the original sensing data and generate an invisible light image whose pixel data size is one byte and multiple temperature data whose unit data size is two bytes. The interface module includes multiple transmission interfaces and is configured to transmit a heterogeneous image whose pixel data size is three bytes through one of the multiple transmission interfaces, where a bit-value of the three bytes is a linear combination of a bit-value of the one byte and a bit-value of the two bytes. The processor is configured to merge the invisible light image and the multiple temperature data according to an RGB color model channel to obtain the heterogeneous image of a visible light image format.

An embodiment of the present invention provides a method for coloring comic images based on a conditional generative adversarial network. It is applied to the field of image processing technology and includes: obtaining a pair of comic line drawings and color manuscript data, as well as high-dynamic-range imaging image data, and constructing a training set and a test set; constructing a coloring model and a shadow addition model, training the coloring model and the shadow addition model with the training set, and evaluating the coloring model and the shadow addition model with the test set; re-obtaining a line drawing image, inputting it into the trained coloring model and shadow addition model for processing to obtain a final image. In this way, the present invention can automatically color the input hand-drawn image using the learned model, not only without manual intervention but also maintaining a good visual effect.

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 present invention relates to a three-dimensional point cloud preprocessing method for assembled pavements based on a depth camera, including: collecting three-dimensional information of the assembled pavement based on the depth camera; optimizing the camera pose, determining the transformation relationship between the camera coordinate system and the world coordinate system based on the camera pose, and screening key frames of the point cloud image; point cloud denoising: removing abnormal points and outliers at the boundary of the key frame point cloud image; point cloud background point removal: converting the RBG color model of the key frame point cloud image to the HSV color model, and removing background points based on the color distance; point cloud reduction: extracting the plate boundary of the key frame point cloud image, and performing point cloud reduction based on the plate boundary and the point cloud features inside the plate respectively; point cloud stitching and registration: converting the point cloud coordinates of the key frame to the world coordinate system, and performing precise registration of the point cloud based on the ICP algorithm to complete point cloud stitching. Compared with the prior art, the present invention has the advantages of complete retention of point cloud features and facilitation of subsequent point cloud processing, etc.

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.