20 results about "3D lookup table" patented technology

The invention relates to the technical field of vertical shaft guide detection, in particular to an industrial intelligent visual detection and diagnosis system for a vertical shaft guide. The coal dust shadow quantization unit extracts a coal dust region by adopting a double-peak self-adaptive threshold segmentation combined region growing algorithm, and introduces a space weight factor to calculate an average gray value and a coverage area proportion, and the dynamic coupling calibration unit depends on a three-dimensional lookup table calibrated by multiple working conditions and nonlinear interpolation; the optimal deviation compensation coefficient of the jitter and coal dust combination is matched, a dynamic gray segmentation threshold value is generated, and a defect diagnosis decision unit accurately calculates the abrasion depth through partition self-adaptive segmentation, multi-scale morphological filtering and denoising and gradient amplitude and curvature double-constrained sub-pixel edge detection. A hierarchical control instruction is output according to the real-time depth and the historical trend, coupling interference is eliminated, the cage guide abrasion detection accuracy is improved, and a reliable basis is provided for safe operation and maintenance.

This invention provides a method for extracting three-dimensional features of steel stamps on water transfer printing paper based on multispectral fusion, relating to the fields of optical inspection, machine vision, and automated quality control. This method utilizes adaptive illumination and image acquisition, employing optimal band optimization, polarization decoupling, and dynamic structured light projection to obtain a series of images separating geometric deformation and pattern interference. Three-dimensional reconstruction is performed using a physically constrained neural network, embedding a double-layer reflection optical model into the network to decouple and predict the paper substrate normal map and integrate to generate a high-precision three-dimensional point cloud. Multi-dimensional geometric features such as height, curvature, and shape are then extracted from the point cloud. Finally, based on a three-dimensional lookup table, the features are mapped to a comprehensive defect level, and automated, differentiated graded processing is performed. This invention achieves non-contact, micron-level high-precision inspection and intelligent quality control of steel stamps on complex surfaces.

The application discloses a three-dimensional look-up table (3D-LUT) construction method and a color correction method based on FPGA, wherein the construction method comprises: interval sampling a 3D-LUT from three dimensions to form a three-dimensional look-up table, and the three-dimensional look-up table comprises: eight Sub-LUTs for storing split 3D-LUT data; wherein N is the sampling point number of three RGB channels in the 3D-LUT; the 3D-LUT contains (N-1) 3 cubic units; the Sub-LUT contains (M-1) 3 cubic units; and M is the sampling point number of three RGB channels in the Sub-LUT. The method can reduce BRAM resource occupation and is suitable for the technical field of image and video processing.

The present application relates to the vertical shaft cage detection technical field, specifically, it relates to a kind of industrial intelligent vision detection and diagnosis system for vertical shaft cage, acquisition unit synchronously obtains cage flange surface image and cage car pitch angle, coal dust shadow quantization unit uses bimodal adaptive threshold segmentation combined with region growing algorithm to extract coal dust area, introduce space weight factor to calculate average gray value and coverage area proportion, dynamic coupling calibration unit relies on three-dimensional look-up table and nonlinear interpolation of multi-working condition calibration, match the optimal deviation compensation coefficient of the combination of jitter and coal dust, generate dynamic gray scale segmentation threshold, defect diagnosis decision unit is through zoned adaptive segmentation, multiscale morphological filtering denoising, combined with gradient amplitude and curvature double-constraint subpixel edge detection accurately calculate wear depth, according to real-time depth and historical trend output grading control instruction, eliminate coupling interference, improve cage wear detection accuracy, provide reliable basis for safe operation.

The application discloses an image processing method and device and a training method, relates to the field of image processing, and particularly relates to the fields of computer vision, deep learning and artificial intelligence. The specific implementation scheme is as follows: for each pixel point in a to-be-processed image, according to a first color value of the pixel point, a voxel index of the pixel point in a three-dimensional lookup table and a relative coordinate of the pixel point in a target voxel corresponding to the voxel index are determined; according to the voxel index, first color information of each vertex of the target voxel is acquired; a weight generation model obtained by joint training of the three-dimensional lookup table is used to determine a first weight of the vertex according to the relative coordinate; according to the first color information and the first weight, second color information of the pixel point after color mapping is determined; and a target image is generated according to the second color information of each pixel point.

The application discloses a land use type prediction method and system based on multi-source data fusion, and the method comprises the following steps: acquiring historical land use and multi-source driving factor grid data of a target region; generating a shape self-adaptive conversion probability through a neural network coupled with deformable convolution; determining future land demand based on scenario and policy coupling; iteratively simulating by using a dynamic double feedback cellular automaton model, the model synchronously adjusts the competition inertia coefficient and the spatial neighborhood weight, and dynamically integrates spatial constraints such as ecological protection red lines in a three-dimensional lookup table; finally, the prediction result is converted into standardized land cover data through a probabilistic multi-level classification mapping engine, and a spatial uncertainty distribution map and an area confidence interval are synchronously generated. The method realizes the deep internalization of regulatory rules, provides complete decision support information containing uncertainty quantification, and provides a scientific and reliable technical tool for land space planning and management.

The present disclosure provides a method for generating a screen color calibration file and a screen color calibration method, and relates to the field of screen color calibration under multiple luminances. The method comprises the following steps: determining a color coordinate matrix of three primary colors corresponding to the screen under N luminances, wherein N is a positive integer greater than 2; determining a conversion function matrix corresponding to the screen according to the N color coordinate matrices, wherein the conversion function matrix is used to map the color gamut of the screen under each luminance to the color gamut under a reference luminance; performing color calibration on the screen under the reference luminance to obtain a three-dimensional lookup table under the reference luminance; and determining the conversion function matrix and the three-dimensional lookup table as the color calibration file of the screen. Thus, the color gamut under different luminances can be kept consistent, and color calibration under the maximum luminance can ensure the color accuracy under all luminances, thereby ensuring the reliability of screen color calibration and improving the calibration efficiency.

The invention relates to a display device and an image bright color enhancement method. A display device includes a display and a controller. Wherein the display is configured to display a user interface; the controller is configured to: a display configured to display an image and / or a user interface; the controller is configured to convert the down-sampling RGB image to obtain an ICtCp image; inputting the ICtCp image into a first convolutional neural network, and outputting a one-dimensional lookup table of a brightness component I and a two-dimensional lookup table of a chrominance component CtCp; performing ICtCp color space inverse conversion to generate a first RGB three-dimensional lookup table; fixing network parameters of the first convolutional neural network, and inputting the downsampling RGB image into a second convolutional neural network to generate a residual RGB three-dimensional lookup table; and according to the first RGB three-dimensional lookup table and the residual RGB three-dimensional lookup table, performing lookup mapping operation on the original RGB image to generate a target RGB image. By adopting the method, the accuracy and computing power requirements are considered, so that the computing power of the television end can be better adapted.

In an example method, for a plurality of octants, residual information is obtained for one or more vertices of the respective octant, where the vertices correspond to respective points in a three-dimensional lookup table. The lookup table is decoded recursively as follows: at least a first one of the plurality of octants is decoded by reconstructing at least a first color sample value from the residual information for at least a first vertex of the first octant; and a plurality of second octants in the plurality of octants are decoded, where the second octants are obtained by splitting the first octant. A color transform is then applied based on the decoded lookup table.

This application discloses a method, apparatus, and electronic device for reconstructing a three-dimensional lookup table, belonging to the field of image processing technology. The method includes: acquiring a base image dataset and a target image dataset; wherein the matching degree of image content between any base image in the base image dataset and the corresponding target image in the target image dataset is greater than a preset threshold; performing three-dimensional point cloud registration on the base image dataset and the target image dataset to obtain a mapping relationship between the pixels of the base images in the base image dataset and the pixels of the target images in the target image dataset; and reconstructing an initial three-dimensional lookup table based on the mapping relationship to obtain a target three-dimensional lookup table.

According to the drawing assisting system and method based on intelligent composition, personalized and dynamic drawing assisting is achieved through cooperation of multiple modules, the stroke position, pressure and speed are monitored in real time, composition complexity and a pressure thermodynamic diagram are calculated, a user concerned area is marked, the user stroke is compared with an art rule base, a three-dimensional lookup table is established, and the drawing assisting effect is achieved. The method comprises the following steps: storing user preferences, historical analysis and general rule coefficients, dynamically switching a local lightweight AI and a cloud deep optimization model, identifying a creation environment through multi-sensor fusion, calculating a fatigue index in combination with stroke pressure, speed and path curvature, providing strength adjustment suggestions, and storing user data by adopting a time sequence database. Through K-means clustering and LSTM behavior prediction, a model is updated in a weekly incremental manner, preference changes are captured, suggestions are optimized through testing, and through multi-dimensional data fusion, dynamic model adaptation and user behavior learning, creation efficiency and an artistic effect are remarkably improved.

The invention relates to the technical field of pipeline measurement, and discloses a three-dimensional prior pipe diameter extraction method and electronic equipment, and the method comprises the steps: obtaining multi-physics field coupling data; constructing a three-dimensional lookup table based on materials, dielectric constants and conductivity; inquiring the velocity initial value of the electromagnetic wave and the pipeline estimated depth value from the three-dimensional lookup table, adopting adaptive edge detection and picking up the vertex and edge feature points of the hyperbolic curve of the pipeline at a sub-pixel level, and outputting a confidence label; taking the vertex, the edge feature point and the confidence label as input, and calculating an initial circle center and a radius of the pipeline by utilizing sub-pixel-level scattering point inversion; and performing triple weighted voting and sub-pixel peak value optimization on the initial circle center and radius by utilizing triple weighted Hough circle detection to obtain the circle center and coordinates of the pipeline, and controlling the pipe diameter identification error and improving the pipe diameter precision by depending on the three-dimensional lookup table based on the material, the dielectric constant and the conductivity and combining the sub-pixel-level scattering point inversion and the triple weighted Hough circle detection.

This invention discloses a real-time downconversion method for high dynamic range to standard dynamic range, comprising the following steps: S10, inputting an HDR video image into a static 3D lookup table (3DLUT) downconversion algorithm template, and outputting a first standard dynamic range (SDR) signal; S20, inputting the first SDR signal into an SDR image detection module to determine whether there is overexposure abnormality in the image after 3DLUT downconversion: if there is no overexposure abnormality, directly outputting the first SDR signal; if there is overexposure abnormality, correcting the 3DLUT mapping curve through a 3DLUT mapping curve adjustment module to complete the static 3DLUT parameter update; then, based on the updated static 3DLUT, regenerating the SDR signal through the static 3DLUT downconversion algorithm template, repeating the above detection and static 3DLUT parameter update process until the output SDR signal image has no overexposure abnormality.

The invention discloses a land utilization type prediction method and system based on multi-source data fusion. The method comprises the steps of obtaining historical land utilization and multi-source driving factor raster data of a target area; a morphological adaptive transition probability is generated by coupling a deformable convolutional neural network; future land requirements are determined based on scene and policy coupling; a dynamic double-feedback cellular automaton model is adopted for iterative simulation, the model synchronously adjusts a competitive inertia coefficient and a spatial neighborhood weight, and spatial constraints such as an ecological protection red line are dynamically integrated through a three-dimensional lookup table; and finally, the prediction result is converted into standardized land coverage data through a probabilistic multilevel classification mapping engine, and a spatial uncertainty distribution diagram and an area confidence interval are synchronously generated. The deep internalization of the control rule is realized, complete decision support information containing uncertainty quantification is provided, and a scientific and reliable technical tool is provided for land space planning and management.

The embodiment of the invention discloses a color adjustment method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of display. The method comprises the following steps: acquiring an environment color temperature and a user color temperature; obtaining a plurality of three-dimensional lookup tables, wherein the plurality of three-dimensional lookup tables respectively correspond to different color temperatures; determining a first three-dimensional lookup table according to the similarity between the environment color temperature and the color temperature corresponding to each of the plurality of three-dimensional lookup tables; determining a second three-dimensional lookup table according to the similarity between the color temperature of the user and the color temperature corresponding to each of the plurality of three-dimensional lookup tables; and fusing the first three-dimensional lookup table and the second three-dimensional lookup table to obtain a target three-dimensional lookup table, and performing color adjustment based on the target three-dimensional lookup table. Therefore, the scheme can realize color temperature adjustment in combination with environment and user preference.

The application relates to a backlight white balance control method and device, electronic equipment and a storage medium. The method comprises the following steps: constructing a multi-temperature three-dimensional lookup table set; detecting the current working temperature of a backlight module when an image is displayed on a backlight display device, and determining the target light output characteristics of the current display picture; selecting a target three-dimensional lookup table from the multi-temperature three-dimensional lookup table set according to the current working temperature; inputting the target luminance value and the target chroma coordinate into the target three-dimensional lookup table to obtain a target three-color driving current value and generate a driving signal, and driving the backlight module to output mixed light matched with the target light output characteristics, so as to realize backlight white balance control. Based on the luminance, chroma and three-color driving current mapping relationship of the backlight, the mixed light meeting the target white balance requirement can be quickly and accurately output, the chroma coupling error caused by the traditional independent correction of the sub-channel is avoided, and the control precision and response speed of the backlight white balance are improved.

A device includes a memory circuit capable of storing a non-uniform 3-dimensional lookup table (3D LUT) specifying color correction data. For one or more of a red dimension, a green dimension, and a blue dimension, the non-uniform 3D LUT includes a number of color correction values within one or more first light ranges of the non-uniform 3D LUT that exceeds a number of color correction values included within one or more second light ranges of the non-uniform 3D LUT. The device includes a color correcting circuit capable of transforming a source frame into a color corrected frame using the non-uniform 3D LUT.

This invention discloses a multi-layer cloud detection method based on a 3D lookup table. The method constructs and trains a 3D lookup table in the model training phase, and constructs a confidence score based on the confidence parameters retrieved from the trained 3D lookup table in the model invocation phase. The final confidence score determines the probability of a multi-layer cloud. The model training phase includes a data feature creation stage, a feature combination stage, a 3D lookup table creation stage, and an optimal segmentation threshold determination stage. The model invocation phase includes a 3D lookup table reading stage, a threshold segmentation stage, and a weight combination stage. This invention solves the problems of low accuracy and poor linearity between the final confidence score and detection accuracy in existing technologies. The method of this invention can be used 24 / 7, both day and night. Detection results show good linearity between the final confidence score and detection accuracy, with high accuracy at a final confidence score of 1, and a maximum detection accuracy of approximately 90%.

The invention provides an image color migration method and device, electronic equipment and a readable storage medium, and relates to the technical field of artificial intelligence such as computer vision, deep learning and image processing. The image color migration method comprises the following steps: acquiring a source image and a reference image, and obtaining source feature vectors corresponding to different semantic regions in the source image and reference feature vectors corresponding to different semantic regions in the reference image; for each semantic region, obtaining a color transformation parameter set corresponding to the semantic region according to the source feature vector and the reference feature vector corresponding to the semantic region; according to the initial three-dimensional lookup table and the color transformation parameter sets corresponding to the different semantic areas, respectively obtaining area three-dimensional lookup tables corresponding to the different semantic areas; and obtaining a target image according to the regional three-dimensional lookup table corresponding to the target semantic region, the regional source mask image and the source image. The color migration accuracy of the target image obtained according to the regional three-dimensional lookup table corresponding to the target semantic region can be improved.

The invention provides a three-dimensional lookup table updating method and device, computer equipment and a storage medium. The method comprises the following steps: performing up-sampling processing on an original three-dimensional lookup table to generate a first three-dimensional lookup table; the first three-dimensional lookup table is input into a table updating model to obtain a reference three-dimensional lookup table, the table updating model is obtained by training according to first color difference data of each color point in a display picture, and the reference three-dimensional lookup table is obtained according to the first color difference data of each color point in the display picture; the table updating model is used for converting the first three-dimensional lookup table based on a color standard to generate a second three-dimensional lookup table so as to reduce first color difference data between color information of each color point and the color standard; and performing down-sampling processing on the reference three-dimensional lookup table to obtain a target three-dimensional lookup table. Through the method, the color accuracy of the picture displayed by the screen based on the target three-dimensional lookup table is improved, and the problem of uneven color transition caused by blowing is avoided.