66 results about "Color depth" patented technology

An image fusion device and an image fusion parallel optimization method are provided. After a plurality of images are aligned to each other to form a superimposed image, the image fusion device filters the superimposed image to obtain a feature image. The image fusion device compares color depths of pixel points in each of a plurality of pixel regions of the feature image with each other to determine a maximum color depth of each of the plurality of pixel regions. When a relationship between the color depth of any one of the pixel points and the maximum color depth in each of the plurality of pixel regions does not meet a preset relationship, the image fusion device adjusts the color depth of the one of the pixel points according to the maximum color depth. The image fusion device generates a fused image according to the adjusted feature image.

The invention provides a display device and a driving method thereof, and the display device comprises a display module which comprises a time schedule controller and a display panel which are electrically connected; the backlight module comprises a backlight driving circuit and a light-emitting unit which are electrically connected, and the backlight driving circuit is used for driving the light-emitting unit to emit light; the control module is electrically connected with the backlight module and the display panel; the control module is configured to analyze a frame image in a received video signal to obtain sub-field pixel data and sub-field backlight data; and generating the liquid crystal driving signal and the backlight driving signal according to the sub-pixel data and the sub-field backlight data, and sending the liquid crystal driving signal and the backlight driving signal to the time schedule controller and the backlight driving circuit. According to the method, the gray-scale value of the input data is mapped, the color depth of field order display is improved, and the time crosstalk problem is optimized.

The invention belongs to the field of supply and demand platforms, and particularly relates to a carbon neutralization field-oriented supply and demand intelligent docking platform, and the platform comprises an upper chain registration module which constructs a user registration auditing chain through a block chain, and dynamically maps the user level authority based on a registration channel, a historical reputation score and release limit limitation; the auditing module is used for classifying auditing rules into a first auditing rule and a second auditing rule, and mapping the first auditing rule and the second auditing rule to a basic information auditing sub-node and an application publishing sub-node of the user node by using an intelligent contract to realize automatic grading auditing; the matching engine module is used for analyzing the release template corresponding to the user identity, outputting a candidate list and matching accuracy in combination with an authority level, a supply and demand double-layer node network and a historical rapid index, and dynamically optimizing a matching result based on a score fed back by the user; the visual module is used for regulating and controlling the length and color depth of a connection relation between supply and demand nodes in real time; according to the application, the auditing efficiency, matching precision and interaction experience of carbon neutralization resource docking are remarkably improved.

The present application relates to a kind of road crack detection method, device and medium based on cross-modal feature fusion, method includes the following steps: obtaining the color feature and depth feature of road crack data, color depth feature is obtained by fusing color feature and depth feature, color feature, depth feature and color depth feature are input into the detection network based on cross-modal three-flow feature fusion network for detection;Wherein, cross-modal three-flow feature fusion network includes cross-modal interactive fusion module and global interactive module, color feature extraction module and depth feature extraction module extract the color feature and depth feature of road crack data respectively, color feature, depth feature and color depth feature are fused by improved cross-modal interactive fusion module, form comprehensive feature, again by global interactive module for splicing, obtain splicing result, and detection network obtains detection result based on splicing result.Compared with prior art, the present application has the advantages of high precision, high definition and the like.

The invention relates to the technical field of image processing, and discloses an image color adjustment method and device, electronic equipment and a computer storage medium, and the method comprises the steps: obtaining color channel parameters of pixel points in a to-be-debugged image, the color channel parameters comprising the current color gradation of a plurality of color components of the pixel points in the to-be-debugged image in the current color space; determining a coordinate range of each color component in a preset coordinate system according to the target color depth; based on a mapping relationship between the coordinate range and a total color gradation corresponding to the color component, determining a position coordinate corresponding to a current color gradation of a color channel parameter of the to-be-debugged image in the coordinate range; and adjusting the color channel parameters on the position coordinates to obtain a target debugging image. According to the method and the device, accurate control and free debugging of the image color are realized, and the color debugging precision can be concrete, so that when the image color is debugged, the high-precision color gradation can be adjusted through the coordinates, and the fineness of image color debugging is improved.

The invention belongs to the technical field of image processing and privacy protection, and particularly relates to a deep face anonymization standardization processing and evaluation system. The system comprises a data preprocessing module, a multi-technology integration anonymization module, a cross-scene test set module, a multi-dimensional evaluation module and a visual interaction module. The data preprocessing module realizes face data standardization processing by unifying image size, resolution and color depth standards and combining Dlib face detection and feature point positioning; the multi-technology integration anonymization module packages mainstream anonymization technologies such as FIT, G2Face, DeepPrivacy and the like, and provides an extensible interface; the cross-scene test set module covers face samples of different illumination, postures and ages; the multi-dimensional evaluation module constructs an evaluation system from privacy protection intensity (re-recognition rate, cosine similarity and the like), image quality (FID, SSIM and the like), attribute maintenance (difference measurement of expressions, hairstyles and the like) and processing efficiency (time / memory consumption); and the visual interaction module supports data uploading, technology selection, result viewing and automatic report generation. According to the method, the problems of no unified architecture and evaluation fragmentation in the prior art are solved, standardized processing and fair evaluation of a face anonymization technology are realized, and a privacy protection technology is promoted to be applied to the ground.

The invention discloses a color image and depth image fusion processing method and computer equipment, and the method comprises the steps: obtaining a first two-dimensional color image and a first two-dimensional grayscale image of a current field of view from an image sensor, and obtaining a second two-dimensional grayscale image of the current field of view according to the output of a laser radar sensor; acquiring a depth image and a second two-dimensional grayscale image of the current view field; carrying out registration on the first two-dimensional gray scale image and the second two-dimensional gray scale image so as to obtain registration information; according to the registration information, converting the first two-dimensional color image to obtain a second two-dimensional color image; and according to the second two-dimensional color image, endowing color information to corresponding pixels on the depth image so as to generate a color depth image. By implementing the technical scheme of the invention, more accurate registration information can be obtained, and color dislocation of the generated color depth image is greatly reduced.

The application provides an image processing method and device, a computer readable storage medium and an electronic device, relates to the technical field of image processing, and can cut a first image corresponding to a first color depth into a second image corresponding to a second color depth, and normalize the second image into a sample image of the first color depth to simulate a low dynamic range image. Application of such a sample image in model training can facilitate the model to learn the problem of the low dynamic range image, thereby avoiding the model from generating an image with a highlight edge smear problem.

The present disclosure discloses a display method and device in a game, electronic equipment and readable storage medium, which relates to the technical field of computer. The method comprises the following steps: rendering a model in response to a rendering instruction to obtain color data of the model; performing first vertex expansion on the model to obtain a first model; generating color data of a first hollow part based on the first model; performing second vertex expansion on the model to obtain a second model; generating color data of a second hollow part based on the second model; performing third vertex expansion on the model to obtain a third model; generating color data of a first stroke part based on the third model; performing fourth vertex expansion on the model to obtain a fourth model; generating color data of a second stroke part based on the fourth model; and displaying the model with a hollow ink stroke effect according to the color depth data of the model, the color depth data of the first hollow part, the color depth data of the second hollow part, the color data of the first stroke part and the color data of the second stroke part.

The invention discloses a display terminal color depth testing method and related equipment, and relates to the technical field of display terminal testing, and the method comprises the steps: obtaining a plurality of candidate color depth levels supported by a to-be-tested display terminal; respectively converting the plurality of candidate color depth levels into respective corresponding gray scale ranges; generating a color depth test picture based on all the gray scale ranges obtained through conversion; a test signal containing the color depth test picture is sent to the display terminal to be tested for display; and determining the highest color depth level actually supported by the to-be-tested display terminal according to the visual distinguishable condition between the display areas in the picture obtained after the to-be-tested display terminal displays the received test signal. According to the method, the color depth levels of the candidate colors supported by the display terminal to be tested are obtained at a time, and the color depth test picture containing the multiple corresponding display areas is generated, so that the problem of low efficiency caused by the fact that signals must be generated, switched and displayed step by step in an existing serialization test method is directly solved.

The invention provides an abnormal lamp point detection method, device and equipment, a medium, a product and a system, relates to the technical field of display, and can accurately detect the color mixing defect when an LED display screen is normally turned on. The abnormal lamp point detection method comprises the following steps: acquiring a target image obtained by shooting display content of a lightened to-be-detected display module; acquiring a brightness feature and a chrominance feature of the target image; the brightness feature is used for representing the brightness of each lamp point in the display module to be detected; the chromaticity feature is used for representing the color depth of each lamp point in the display module to be detected; and according to the brightness characteristics and the chroma characteristics, detecting abnormal lamp points with color mixing defects in the display module to be detected.

An image display method includes: obtaining both an original image and a color rendering parameter corresponding to an image to be displayed, a bit number of color depth of the original image being smaller than a bit number of color depth of the image to be displayed; generating the image to be displayed according to the original image and the color rendering parameter; and displaying the image to be displayed.

This specification discloses a method, apparatus, storage medium, and electronic device for generating report charts. The method includes: acquiring chart data input by a user; identifying the chart data to determine whether it contains a theme marker; if so, determining the primary color of the report chart based on the hue corresponding to the theme marker; otherwise, inputting the chart data into a pre-trained classification model to determine the industry sector to which the chart data belongs, and determining the primary color based on the industry sector; if a call instruction corresponding to a geographic information component is received, determining a first background color based on the hue corresponding to the primary color, and setting the background color of the report chart to the first background color; otherwise, setting the background color of the report chart to a second background color, wherein the color depth of the first background color is greater than the color depth of the second background color; and rendering each element contained in the chart data according to the background color and primary color of the report chart to generate a report chart.

The utility model discloses a lining paper production color matching system which comprises a machine frame, a mixer arranged in the machine frame, a material matching control tank arranged at the top of the machine frame and a color matching system, the color matching system comprises a processor, the input end of the processor is electrically connected with a color input device, and the output end of the processor is electrically connected with a controller. The output end of the processor is electrically connected with a color ingredient data storage module in a bidirectional mode, the output end of the processor is electrically connected with a proportion displayer, the output end of the proportion displayer is electrically connected with a controller, the output end of the controller is electrically connected with a motor, and the output end of the controller is electrically connected with an air cylinder. According to the utility model, the color mixing system is arranged, so that the proportion of pigments can be accurately adjusted, the colors are uniform, the uniform proportion is ensured when a user uses the color mixing device, the same color is uniformly mixed, and the same color can be uniformly mixed, so that the normal use of the user is ensured.

The embodiment of the invention discloses a hyperspectral image processing method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining crop images of a target crop, wherein the crop images comprise a first color image and a first depth image collected by a color depth camera and a first hyperspectral image collected by a hyperspectral camera; obtaining target joint calibration parameters of the color depth camera and the hyperspectral camera; and performing three-dimensional point cloud reconstruction on the first color image and the first depth image by using the target joint calibration parameter, and determining depth information corresponding to the first hyperspectral image based on first point cloud data obtained by reconstruction, the depth information being used for representing a first distance between the hyperspectral camera and the target crop when the hyperspectral camera collects the first hyperspectral image. According to the scheme, information of the color depth camera and information of the hyperspectral camera can be fused, and the first distance between the hyperspectral camera and the target crop is accurately determined when the hyperspectral camera collects the first hyperspectral image.

The present disclosure relates to the field of artificial intelligence, in particular to an online point cloud semantic segmentation method, an online point cloud semantic segmentation device, a storage medium and an electronic device. The online point cloud semantic segmentation method comprises: collecting a color depth image in real time, and converting pixel points in the color depth image into a current point cloud set based on depth data of the pixel points; performing vertex fusion on the current point cloud set and a historical point cloud set through point cloud registration to obtain geometric features and time sequence semantic states corresponding to the pixel points; performing feature fusion on the geometric features and color data of the pixel points in the color depth image to obtain semantic features of the color depth image; and performing semantic segmentation according to the semantic features and the time sequence semantic states to obtain a semantic segmentation result of the pixel points. The online point cloud semantic segmentation method aims to output accurate and stable point cloud semantic segmentation results online.

The present application relates to a method for enhancing display effects by dynamically regulating voltage differences, comprising: constructing a mathematical model of biological morphology changing over time, wherein the mathematical model introduces random variables to characterize individual differences in biological organisms; obtaining pixel data of a display sequence based on the resolution, color depth, and refresh rate parameters of a display device, and dynamically adjusting the accuracy of the mathematical model and the parameters of the encoding strategy; processing the received display sequence through a visual characteristic model, and decoding and recovering hidden information in the display sequence based on a pixel brightness change sequence and a predefined nonlinear mapping relationship; employing a filtering algorithm to process different interference factors; and employing an integrity verification algorithm for the extracted hidden information. If information is found to be missing or erroneous, the information is recovered and reconstructed based on redundant information and error correction coding.

The invention relates to the field of LED display, and discloses a color depth extension method and device of an LED display screen, electronic equipment and a storage medium. The method comprises: acquiring an image; performing frequency multiplication on the image to obtain an image after frequency multiplication; processing the image after frequency multiplication, and determining an integer part and a decimal part; determining an offset according to the integer part and the decimal part; and determining the displayed image data based on the offset, thereby increasing the image color depth and ensuring that the image color is lossless.

A video generation method is provided. After a source image is acquired by an electronic device, sketch images of different stages in a process of simulating a painter to draw a target sketch are generated based on the source image in an order of color from light to dark, and a plurality of subgraphs in the process of simulating the painter to draw the sketch image are generated in an order of drawing completion degrees from low to high. Then, respective subgraphs of respective sketch images in the plurality of sketch images are taken as video frames of a sketch drawing video, an order of the video frames is set according to the order of color depth from light to dark and the order of drawing completion degrees from low to high.

Electronic display devices include digital and analog control of pixel intensity. A digital pixel control circuit and an analog pixel control circuit are provided within each pixel. The digital pixel control circuit employs digital PWM techniques to control a number of subframes within each frame during which a driving current is supplied to a light emitting element within the pixel. The analog pixel control circuit controls the level of the driving current supplied to the light emitting element within the pixel during the frame. In one example, the digital pixel control circuit and the analog pixel control circuit may together control pixel intensity with the analog pixel control circuit providing additional in-pixel bits for increased color depth. Alternatively, the digital pixel control circuit may control pixel intensity and the analog pixel control circuit may control non-uniformity compensation.

The application belongs to the technical field of signal generation and edge intelligence processing, and particularly relates to a simulation verification test system for edge intelligent information generation. The system comprises: a signal generation module, which is used for generating a CameraLink format video signal as edge intelligent information according to a preset image resolution, color depth and signal modulation function, and outputting the video signal to an edge intelligent platform to be tested; a signal conversion module, which is used for collecting and converting the format of the CameraLink format video signal; a signal analysis module, which is used for analyzing and calculating key evaluation indexes of the collected video signal, generating a test report, and performing alarm processing when an abnormal signal occurs; and a control and configuration module, which is used for providing an interface, receiving configuration parameters input by a user, and monitoring a test process.

1. The name of the design product: water quality colorimetric detector. 2. The use of the design product: a detection device for comparing the color depth of water samples to determine the degree of water pollution. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention relates to the technical field of medical artificial intelligence and machine vision, and discloses a pathological section cell intelligent identification system based on robot vision, and the system comprises an image collection module which is used for obtaining a digital image of a pathological section, segmenting the digital image into a plurality of local regions, and calculating the gray level distribution characteristics of each local region; the feature extraction module is used for performing color correction and texture enhancement on the local area to generate a standardized feature map; and the dynamic adaptation module is used for calculating the color depth distribution entropy and the texture complexity index of the local area and generating adaptation parameters. According to the invention, image heterogeneity is analyzed and model parameters are adjusted through the dynamic adaptation module, image colors and textures are unified in combination with the feature extraction module, section preparation, dyeing and scanning differences of different mechanisms can be adapted, the situation that the recognition accuracy of an existing system is reduced due to image heterogeneity is avoided, and stable recognition under multiple scenes is ensured.

This application relates to an image detection method, apparatus, system, and electronic device. The image detection method includes: acquiring a white light image and a NBI image of an image to be detected; performing feature extraction processing on the white light image and the NBI image respectively to obtain color depth features of the white light image and texture depth features of the NBI image; performing depth feature fusion processing based on the color depth features and the texture depth features to obtain fused depth features; performing image quality detection processing based on the fused depth features; and generating a target image detection result for the image to be detected. This application solves the problem of low accuracy in image detection and achieves an accurate and efficient image detection method.

The embodiment of the invention provides a three-dimensional imaging method, device and system and a storage medium, and relates to the technical field of three-dimensional imaging. According to the method, the matching accuracy and the depth calculation stability of complex surfaces such as weak texture or repeated texture areas are improved by projecting a mixed coding pattern containing random texture and stripe structures and combining the high precision of structured light coding and the robust matching advantage of the random texture; through two-time disparity map acquisition, the resolution and the detail reduction capability of the disparity map are improved; by fusing the high-precision disparity map, the system geometric calibration parameters and the color image, the reconstruction of the high-quality color depth image is realized, and the method has both accurate three-dimensional geometric information and real surface color rendition, and is suitable for three-dimensional perception application scenes with high requirements on precision and visualization effect.

The invention belongs to the technical field of computer vision and three-dimensional perception, and particularly relates to a variable-focus binocular ranging method and system fusing instance segmentation and self-calibration, and the method comprises the specific steps: carrying out the self-calibration through employing an image collected by a binocular camera through a self-calibration method based on deep learning, and obtaining the internal and external parameters of the camera; acquiring a mask area, a category label and confidence of each detection instance in the image; the method comprises the following steps: preprocessing left and right images collected by a binocular camera, inputting the preprocessed left and right images into a stereo matching network to obtain a dense disparity map, and adjusting the dense disparity map to the size of an original image; calculating a dense depth map by using the focal length obtained by self-calibration, and converting the dense depth map into a pseudo-color depth map; extracting a depth value corresponding to a mask area pixel from the dense depth map, taking a depth median of the area as a distance estimation value of the instance, and superposing the distance estimation value in an original image collected by a camera to obtain an instance depth superposition map; and respectively converting the pseudo-color depth map and the instance depth overlay map into image messages and publishing the image messages.

An endoscope device, an endoscopic medical assistance system and an endoscopic image processing method are provided. An endoscope in the endoscope device and the endoscopic medical assistance system senses light beams reflected by an object to generate initial images. After the initial images are aligned with each other to form a superimposed image, an image fusion device of the endoscopic medical assistance system analyzes features of the superimposed image to convert the superimposed image into a feature image. The image fusion device adjusts a color depth of each of a plurality of pixel points of the feature image according to a relationship between the color depth of each of the pixel points and a maximum color depth that are classified in the same color tone in each of pixel regions of the feature image. The image fusion device generates a fusion image according to the adjusted feature image.

The present invention discloses a meta-toluidine compound, a preparation method thereof, and an application in a thermal color developer, and relates to the technical field of color developers. A meta-toluidine compound is. Compared with comparative products, the thermal color developer prepared by the present invention has a decreasing trend in overall activation temperature, is easier to trigger a color development reaction, broadens the color development temperature range, and can meet the differentiated temperature requirements of more different application scenarios. The thermal color developer prepared using the meta-toluidine compound of the present invention has a higher color contrast and a more significant color depth in color development effect, and can present a clearer and more vivid color development result, which helps to improve the visualization effect of thermal color development technology in scenarios such as thermal printing.

The present application provides a face anti-misbrushing method, device and equipment and storage medium, relating to the technical field of computer. The method comprises: collecting color two-dimensional images of multiple faces and depth images of the multiple faces; mapping the depth images to the color two-dimensional images to obtain color depth images; determining the spatial relationship between a first face and a second face in the multiple faces based on the position information of the first face and the second face in the color depth images; and outputting prompt information based on the spatial relationship between the first face and the second face, the prompt information being used to prompt user operation behavior for the first face or the second face. The method can prevent unintentional face brushing users from misbrushing, not only improving the face brushing experience of users, but also avoiding causing property loss of unintentional face brushing users.

The invention discloses an interface identification method and system based on a minimum dynamic mean error, and belongs to the technical field of image processing and geophysical exploration. The method comprises the following steps of: dividing a geophysical prospecting image into vertical strips with single-pixel width, and sequentially identifying candidate interface points of which the color depths meet requirements in each strip; starting from the leftmost strip, taking a vertical coordinate minimum point as an initial target point; for a subsequent strip, dynamically calculating a vertical coordinate average value of the identified target point, comparing the candidate point with the average value, and selecting a point with a difference value within a tolerance threshold value or with a minimum difference value as a current target point; and finally, all target points are connected to form a continuous and smooth target interface. The method can automatically and accurately recognize the underlying interface in the geophysical prospecting image, is high in anti-interference capability, and is suitable for batch processing of data such as geological radars and seismic sections.