1124 results about "Chromaticity" patented technology

The invention provides a self-adaptive underwater image enhancement method and system based on a Retinex theory and Mama, and relates to the technical field of underwater image enhancement, and the method comprises the steps: taking an original underwater image and a corresponding illumination priori image as input, obtaining illumination factor mapping through feature splicing, a first convolution layer, a multi-scale channel aggregation module layer and a second convolution layer, and obtaining an illumination priori image; performing Hadamard product operation on the illumination factor mapping and an original image to obtain a basic enhanced image; the multi-scale degradation features of the basic enhanced image are extracted step by step through an encoder, the spatial resolution is recovered through jump connection of a decoder, the illumination-texture relevance is enhanced through selective state space modeling of a WLMama bottleneck module, and finally a high-quality underwater image enhancement result is generated. According to the method, the mathematical representation system of the optical characteristics of the water body is established, the model can adaptively adjust the chromaticity compensation intensity, and image restoration under the constraint of the physical characteristics of the underwater scene is realized.

The invention relates to the technical field of display screen color adjustment, and discloses a display screen color adjustment method and system based on environment information, and the method comprises the steps: obtaining display content data, environment color data, environment light data and a display screen type of a display screen; calculating color perception data according to the environment color data and the display screen type, and performing data processing on the color perception data to obtain chromaticity feedback data; establishing a relationship between the ambient light data and user preferences through a support vector machine method to obtain user evaluation data; inputting the chromaticity feedback data and the user evaluation data into a color correction model to obtain color adjustment data; classifying the display content data and calculating a type weight index through a squirrel optimization algorithm to obtain a weight index; and generating a color adjustment instruction according to the color adjustment data and the weight index, and performing adaptive adjustment on the display content. The method solves the problems that the color adjustment of the display screen has high requirements on a light source environment and is strong in subjectivity.

A display device whose change in chromaticity is small and grayscale controllability is high is provided. The display device can turn on and turn off a light-emitting device by PAM and PWM control (a pulse width control involving changes in amplitude). The display device writes the same input signal (data potential) to a first node and a second node to turn on the light-emitting device in accordance with a potential of the first node and generate a pulse signal in accordance with a potential of the second node. The potential of the first node can be reset in accordance with the generated pulse signal. Therefore, the light-emitting device can emit light for a desired period with a desired emission intensity.

The invention discloses an atmosphere lamp user color calibration matching method. The method comprises the steps that K PCBA boards are installed on a lamp shell; measuring a color coordinate value and a luminous flux value of the atmosphere lamp; the color coordinate value and the luminous flux value of any atmosphere lamp serve as color correction data, and the pwm duty ratio is calculated; the controller controls the LED driver to drive the K atmosphere lamps to complete primary color correction; the PCBA board in any atmosphere lamp is taken out, and the actually measured luminous flux value of the PCBA board is measured; comparing the actually measured luminous flux value with a target luminous flux value to obtain a ratio r; increasing the target luminous flux value Yt by r times, and calculating a pwm target duty ratio in combination with color correction data; the controller controls the LED driver to drive the K atmosphere lamps to complete secondary color correction; and the color coordinate value and the luminous flux value of the atmosphere lamp after color correction are measured and compared with customer standards. The method has the advantages that assembly user color adjustment of multiple styles of atmosphere lamps is achieved, the matching degree of chromatic value control of the atmosphere lamps and real environment requirements is met, the production time cost is greatly saved, and the production efficiency is improved.

The invention relates to a color calibration method and system based on a display driving chip, and the method comprises the following steps: carrying out the sub-pixel spectrum reconstruction of an original spectrum data stream based on a color gamut boundary vector group, and obtaining a sub-pixel spectrum matrix; performing white point chromaticity estimation on the sub-pixel spectrum matrix to obtain white point chromaticity coordinates; performing gamma curve correction on the sub-pixel spectrum matrix based on the white point chromaticity coordinates to obtain a gamma correction coefficient matrix; performing color space conversion on the gamma correction coefficient matrix through a preset three-dimensional lookup table to obtain color control parameters, and inputting the color control parameters into a preset display driving chip to drive sub-pixels of each pixel unit in the display panel to emit light to obtain color calibration display output, the defects of a traditional display driving chip in the aspect of color calibration are overcome, and the defects are mainly embodied in the technical problems that color differences between different display panels cannot be effectively processed and the color drift phenomenon occurs along with time lapse.

The invention relates to the technical field of biomedical engineering and digital image processing, in particular to a digital image enhancement method based on cytopathology. The method comprises the following steps: eliminating noise and artifacts caused by non-uniform dyeing, section folding and dust factors; the problem of dyeing difference caused by different scanning devices is solved; key areas including cell nucleuses and cell membranes are highlighted, so that the visual effect of a low-contrast image is improved; segmenting an area, including cell nucleuses and cytoplasm, of the cells, and extracting morphological characteristics; the detail resolution of a low-resolution image, especially the definition of a small cell structure, is improved; the brightness component Y is corrected to compensate for the difference of different dyeing methods and dyeing qualities in brightness response, then the chromatic value is adjusted according to the color correction factor to make the colors of the images more consistent, and finally, the images which are acquired by different dyeing methods and dyeing qualities and subjected to brightness and chroma correction are fused to make the color of the images more consistent. And a final corrected image is obtained.

The invention relates to the technical field of machine vision and optical detection, in particular to a tea color automatic evaluation method and system based on machine vision. The method comprises the following steps: constructing a stable and repeatable optical measurement environment and calculating radiation baseline parameters; performing multi-band polarization sequence imaging on the tea sample to obtain original data with spectrum and structural characteristics; separating mirror surface and diffuse reflection components on the surfaces of the tea leaves, and performing spectrum consistency correction by combining a radiation baseline; performing multiband spectrum reconstruction and normalization processing on the basis of the corrected diffuse reflection image, mapping to a CIE Lab color space, extracting pixel-level brightness, chromaticity and color distribution statistical indexes, and generating a color feature vector in combination with spatial weighting matrix optimization; a final score is calculated by constructing a quantitative evaluation and grade judgment model and integrating perception color separation, drying calibration color separation and a penalty term, and a grade result is output. According to the method, objective, accurate and automatic evaluation of the color of the tea leaves is realized.

The invention discloses a color constancy method based on physical imaging characteristics and light source spectral power embedding. According to the method, the consistency of image colors under different illumination conditions is ensured through a series of fine steps. The method comprises the following steps of: firstly, rendering spectral data by adopting a sunlight and ambient light dual-light-source model, converting the spectral data into an RGB space through a CIE standard observer function, and generating spectrums under different color temperatures and corresponding RGB data of the spectrums; then, a characteristic spectrum of a non-shadow area in the scene is extracted to serve as input of a variational auto-encoder, and hidden layer distribution of the auto-encoder guides a light source decoder to output light source spectrum power distribution matched with the label. In addition, spectral features and color and texture features of an RGB image are extracted through a convolutional neural network, and the features are fused to estimate the chromaticity of an image light source. And finally, according to the estimated chromaticity of the light source, performing color correction on the original RGB image by using a colorimetric principle, so that the image color adapts to a standard light source.

The invention provides a new energy battery coating thickness control method, which comprises the following steps: presetting a chromatic value range of a coating color, segmenting a stable image into a coating area and a non-coating area, carrying out binarization processing on the segmented coating area to obtain a coating binarization image, according to the segmented coating binarization image, carrying out closed operation on a coating area, filling small holes in the coating area, and removing noisy points outside the coating area through open operation to obtain a coating area image after morphological processing; a motion model of color change is established according to historical focusing data, the color change trend of a next frame of image is predicted, a predicted value is used as a feedforward control signal of a focusing system, and oscillation of the focusing system is suppressed.

The invention belongs to the technical field of display screens, and mainly provides a model construction method, a display screen uniformity correction method, a display screen uniformity correction device and display screen uniformity correction equipment. Inputting the brightness information and the chromaticity information of the display area to be corrected into a pre-established display screen RGB gain prediction model to obtain an estimated RGB gain output by the display screen RGB gain prediction model, and performing brightness and chromaticity uniformity correction on the display area to be corrected based on the estimated RGB gain. The brightness and chromaticity uniformity correction of the to-be-corrected display area is realized by one key based on the brightness information and chromaticity information of the to-be-corrected display area and the pre-established display screen RGB gain prediction model, and the problems that a traditional display screen brightness and chromaticity uniformity correction method is low in correction efficiency and needs to consume relatively high manpower and time are solved; and frequent implementation is difficult.

The invention relates to the technical field of image detection, in particular to a boiler scale detection method and device based on a multi-modal image, and the method comprises the steps: carrying out the panoramic scanning of the inner wall of a boiler through a dual-spectrum imaging system at a detection temperature, and synchronously collecting a visible light image and an infrared thermal imaging image; based on the scale chromaticity difference value in the visible light image, scale types are judged, and a scale classification graph is generated; based on a standard infrared thermal imaging image, obtained at the detection temperature, of the scale-free boiler, the infrared thermal imaging image is converted into a temperature anomaly distribution diagram with temperature anomaly blocks; inputting the temperature anomaly distribution diagram into a deep neural network to output a scale thickness distribution diagram, and aligning the scale classification diagram with the scale thickness distribution diagram through a spatial registration technology to ensure that pixels at the same spatial position contain scale types and thickness values at the same time; and generating a scale feature fusion graph of scale types presenting different color areas and corresponding thicknesses, thereby realizing accurate detection and quantification of the boiler scale.

The invention discloses a compensation method and device of a display panel and a computer readable storage medium. The compensation method of the display panel comprises the following steps: acquiring brightness data and chromaticity data of the display panel; determining a brightness compensation coefficient of each sub-pixel color in the to-be-compensated area according to the brightness data of each sub-pixel color in the to-be-compensated area and the brightness data of each sub-pixel color in a brightness reference area; determining a chromaticity compensation coefficient of each sub-pixel color of the to-be-compensated area according to the chromaticity data of the to-be-compensated area and chromaticity data of a chromaticity reference area; determining a total compensation coefficient of each sub-pixel color in the to-be-compensated area according to the brightness compensation coefficient and the chromaticity compensation coefficient; and compensating the to-be-compensated area by using the total compensation coefficient. The display uniformity of the display panel can be improved.

The invention provides a consistency correction method and device based on a multi-source satellite inversion water color index, and the method comprises the steps: converting the surface reflectance of a multi-source satellite sensor of a target water area into remote sensing reflectance, and carrying out the water body range extraction of the multi-source satellite sensor, so as to determine the water body range, carrying out multi-class interference pixel removal on the image of the surface reflectance in the water body range to obtain effective remote sensing reflectance; calculating a chromaticity angle inverted by the multi-source satellite sensor based on the effective remote sensing reflectivity and a CIE chromaticity system; performing spectral response correction on the chromaticity angle inverted by the multi-source satellite sensor based on a polynomial spectral correction model constructed by the water optical simulation data set; performing system deviation correction on the chromaticity angle of the multi-source satellite sensor after spectral response correction by a cross calibration correction model established based on the synchronous observation data of the multi-source satellite sensor; and determining the water color index of the target water area based on the chromaticity angle after system deviation correction.

The invention discloses a vehicle-mounted HUD optical performance comprehensive detection method, and aims to solve the problems that a traditional detection method depends on manual operation and is low in detection efficiency and large in error. Project loading and test starting, picture height position calibration, multi-parameter test, brightness and chromaticity test, ghosting test, static distortion test and binocular parallax test items are automatically implemented through detection equipment, and accurate control (such as application of camera pixel-millimeter ratio) of advanced image recognition algorithm and equipment in the test process is carried out. The vehicle machine controls the step number of the curved mirror motor, and the industrial personal computer controls the motion module, so that high-precision measurement of optical parameters is realized, and the test efficiency and the test accuracy are improved.

The invention provides a machine learning-based OLED display screen image defect detection method, which comprises the following steps of: acquiring brightness distribution data and chromaticity distribution data of an OLED display screen through an image acquisition device, calculating a spatial difference between the brightness data and a standard template to obtain an abnormal degree index, determining a geometric center coordinate of a defect area, and calculating the abnormal degree index according to the abnormal degree index. Judging whether the neighborhood contains normal pixels or not; if not, a defect feature texture map in the brightness data is extracted through the convolutional neural network, and after the defect feature texture map is matched with a preset defect type, defect positioning information and a quality early warning instruction are generated and sent to the detection terminal. According to the invention, high-precision automatic detection and classification of image defects of the OLED display screen can be realized, and the accuracy and detection efficiency of defect identification are effectively improved.

The present invention discloses a jaundice detection method and system based on visual recognition, and the detection method comprises: obtaining first image data of a person to be detected under white light shooting illumination, and obtaining second image data of the person to be detected under blue light shooting illumination; performing image color extraction on the first image data based on HSV color space to obtain color data of the first image data; performing comparison on the color data of the first image data with the image chromaticity data of a standard image to obtain first comparison data; extracting the proportion of green component and yellow component from the second image data based on Lab color space recognition, and obtaining second comparison data based on shooting parameter settings; obtaining an image yellow chromaticity change evaluation value of the person to be detected based on the first comparison data and the second comparison data, and outputting a detection result based on the evaluation value. By performing image analysis on the yellow component change value, the image detection accuracy is improved, thereby improving the evaluation reliability of the occurrence of jaundice symptoms.

The invention relates to the technical field of soil image processing, in particular to a vegetation detection method and system for soil environment restoration. According to the method, color features and position distribution features of pixel points are analyzed, a vegetation coverage factor of each superpixel block is obtained, and vegetation coverage blocks are screened out; according to the position distribution of the pixel points in each vegetation coverage block and the chromaticity fluctuation characteristics, the artificial cultivation characteristic degree of each vegetation coverage block is obtained; according to the centroid position and the vegetation coverage factor of each superpixel block, obtaining a vegetation coverage class cluster and a non-vegetation coverage class cluster; and in combination with the relative position between each vegetation coverage block in each non-vegetation coverage class cluster and each vegetation coverage block in the adjacent vegetation coverage class cluster, obtaining the soil remediation vegetation significance of each super-pixel block, and further obtaining the soil remediation weighted significance of each super-pixel block. According to the method, the vegetation characteristics in the soil environment restoration process are accurately analyzed, so that the accuracy of soil environment restoration assessment is improved.

The invention discloses a method for dynamically monitoring the drying quality of fruits and vegetables by fusing chromatic aberration-shrinkage rate analysis. The method comprises the following steps: placing a fruit and vegetable sample on a rotatable objective table, drying according to a preset program, and carrying out multi-angle shooting by using a digital camera according to a timestamp to obtain an RGB color image; the method comprises the following steps: preprocessing by an image analysis system, converting an image into a Lab chromaticity space, calculating a chromatic aberration value delta E and a comprehensive shrinkage rate S, integrating data to generate a change curve, and constructing an appearance form model. In actual drying, real-time data and the model are compared, and early warning is carried out when the color difference value exceeds 3.5 or the shrinkage rate deviation exceeds 15% and image acquisition is abnormal. The drying equipment is provided with a high-precision electric rotary objective table, a specific annular light source array, a high-resolution camera and a standard calibration color card, and illumination and color measurement accuracy is ensured through calibration. Through multi-step operation, accurate and dynamic monitoring of fruit and vegetable drying quality is achieved, and drying process optimization is assisted.

An article including at least one first metallic layer, at least one dielectric layer; and at least one second metallic layer is disclosed. The at least one dielectric layer can include at least one of (i) a photo-initiator, (ii) an oxygen inhibition mitigation composition, (iii) a leveling agent, and (iv) a defoamer.

The invention discloses a spectrum correction type imaging colorimeter and a chromaticity coordinate measuring method. The spectrum correction type imaging colorimeter is used for reducing the rotating angle of a wheel rotating disc when chromaticity coordinates are measured. The colorimeter comprises a colorimeter main body, a wheel rotating disc and a conduction assembly, the wheel rotating disc and the conduction assembly are respectively arranged on the colorimeter main body; a shooting lens and a measuring plate which are adjacent to each other are arranged on the wheel rotating disc, the measuring plate is divided into a first part and a second part, the measuring plate is circular, the circle center of the measuring plate is located in the second part, a reflecting prism is arranged in the first part, and the distance from the geometric center to the rotating center of the reflecting prism is equal to that of the reflecting prism; the distance from the circle center of the shooting lens to the rotation center is equal; the wheel turntable has a shooting position and a measuring position, and at the shooting position, the shooting lens and the incident light path are coaxial; at the measuring position, the wheel rotating disc is controlled to rotate, so that the reflecting prism is coaxial with the incident light path, the reflecting direction of the reflecting prism is coaxial with the arrangement direction of the conduction assembly, and the conduction assembly is used for being connected with a spectrograph.

The invention discloses a high-quality multispectral demosaicing method based on residual error guidance, belongs to the technical field of image restoration, and aims to solve the problems that a large amount of high-frequency information is not effectively processed and RGB image chromaticity channel restoration is insufficient. The method comprises the following steps: step 1, designing nine-channel multispectral optical filter array arrangement; step 2, interpolating a dense sampling channel image; 3, preliminarily reconstructing a sparse sampling channel image; and 4, further restoring the sparse sampling channel image by using a residual interpolation method. According to the demosaicing method based on residual guidance, when pixels of other channels are reconstructed, interpolation is carried out on residual values, and the problems of key detail reservation, fuzziness and detail loss are emphasized. And the mutual influence between different spectrum channels is considered, so that more accurate color restoration is realized, and the visual perception and the practical application value of the image are improved. The reconstructed image is excellent in the aspect of recovering the chromaticity channel of the RGB image, and the real effect of the reconstructed image is closer to that of the original image.

An article including a thin film interference pigment; and a coating including a selectively absorbing nanoparticle is disclosed. The article can exhibit increased chromaticity as compared to the thin film interference pigment alone. A method of making the article is also disclosed. The method comprises providing a thin film interference pigment and coating the thin film interference pigment with a selectively absorbing nanoparticle.

The present invention relates to a Micro-LED micro-display device driving control method and device, comprising the following steps: dividing a target pixel area by a preset display image to obtain sub-pixel blocks; performing electroluminescence spectrum analysis on a target micro-display device based on the sub-pixel blocks to obtain a spectral radiation power distribution; performing chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; performing pulse width modulation on the target micro-display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; using a distributed control architecture to transmit the multi-level grayscale driving waveform to a corresponding target micro-display device to obtain a Micro-LED display image, thereby solving the technical problem of how to efficiently perform electroluminescence spectrum analysis since each pixel point in a Micro-LED array is an independent light source, and adjusting the luminous characteristics of each pixel point accordingly to ensure consistency of image quality.

The invention provides an exhaled gas alcohol content intelligent verification system based on image recognition, relates to the technical field of intelligent detection, and aims to solve the problems that a traditional sensor is prone to environmental interference, needs frequent calibration and is insufficient in dynamic response. Comprising a gas-sensitive developing unit, a multispectral dynamic imaging unit, a data processing unit and a closed-loop control unit, the gas-sensitive color development unit adopts a reversible gas-sensitive film and generates a color change signal through an alcohol specific color development reaction; the multispectral dynamic imaging unit is combined with an ambient light suppression and dynamic region positioning technology to capture spectral reflectivity time sequence data in a color development process; the data processing unit maps the chromaticity characteristic into an alcohol concentration value based on a Gaussian process regression model, and triggers near-infrared auxiliary verification through confidence evaluation; and the closed-loop control unit maintains a constant detection environment through the temperature control and airflow stabilization module. According to the scheme, non-intrusive high-precision detection of the alcohol concentration in a complex environment can be realized.

The invention discloses a fire-fighting equipment control system and method based on the Internet of Things, and relates to the technical field of the Internet of Things. An indoor scene environment monitoring network is constructed to collect real-time environment data and scene image data of a monitored scene; indoor scene image data is called to construct a pixel point decomposition model, comprehensive evaluation is performed on chromaticity information of each pixel point in the image data based on the decomposition model, and abnormal point location analysis is performed on each pixel point based on pixel point chromaticity evaluation data; based on the scene image data pixel abnormal point analysis data, constructing a spatial model to determine a scene abnormal area; performing steady-state fire abnormality index analysis on the indoor scene abnormal area according to the space abnormal area, and performing abnormality judgment on the scene fire based on analysis data; outputting the indoor scene monitoring data through an Internet of Things monitoring port, and labeling a scene abnormal area and feeding back fire data; according to the invention, the conditions of low precision and high false alarm rate of the traditional fire extinguishing system are improved.

An end-to-end color imaging system chromaticity characterization method based on hyperspectral calibration belongs to the field of color imaging, color display and imaging chromaticity measurement, and comprises the following steps: firstly, acquiring or calling hyperspectral cube data, and measuring red, green and blue three-channel spectral sensitivity curves and calibration coefficients of imaging equipment; fixed weight linear mapping is adopted, a pixel-level RGB image and a corresponding XYZ tristimulus value image are generated, and paired calibration samples are formed. And an end-to-end deep network is constructed to map any RGB image into an XYZ image. The method has good prediction precision and robustness, and can be widely applied to scene chromaticity measurement, color imaging color management, display calibration, camera color recovery and other chromaticity consistency demand scenes.

The invention relates to the field of image processing, and discloses a figure image optimization method based on green screen image matting, which is used for carrying out optimization processing on a figure image. The figure image optimization method based on green screen image matting comprises the steps of performing fractional order differential transformation and other processing on an input green screen figure image, constructing a continuous chromaticity representation space, generating a chromaticity gradient field and multi-resolution chromaticity representation, establishing a geometric topology constraint model according to chromaticity information, generating an initial transparency field, and performing collaborative optimization. Optimizing a boundary curve, generating an accurate boundary contour, establishing a color mixing model, realizing natural transition between a foreground and a background, generating an optimized image, performing subsequent processing such as material optical attribute analysis and the like, and finally outputting an image completely fused with a background environment. According to the method, the foreground can be accurately separated, the edge can be optimized, natural transition and material simulation can be realized, and finally a high-quality figure image which is seamlessly fused with the background and has a physical reality sense is generated.

The present invention relates to an AR diffractive optical waveguide rainbow pattern testing device, which includes a Z-axis hollow rotary table, an A-axis rotary displacement table, a hollow waveguide carrier stage, an imaging brightness and chromaticity meter, and an optical generation module. By simulating the usage scenario of the diffractive optical waveguide in a hemispherical space, the present invention acquires and analyzes multi-dimensional information such as the brightness and chromaticity, azimuth angle, solid angle, and position of the rainbow pattern, and has the ability of calibration, achieving the effects of multi-dimensional and high-precision detection and analysis of the rainbow pattern and improving the repeated measurement accuracy.

The invention discloses a brightness and chrominance consistency correction method and system for an LED spliced screen, and the method comprises the steps: firstly recognizing the batch features of a module, dividing the batch features into correction partitions, and respectively collecting the original brightness and chrominance data of a high-gray linear region and a low-gray nonlinear region; and then, calculating the geometric intersection of the original color gamuts of all the partitions to determine the maximum common target color gamut, and eliminating the metamerism phenomenon caused by multi-batch mixed use from the physical level. Then, constructing a non-linear dual-order correction model, and generating a correction coefficient set containing a main linear conversion matrix and a low-gray-scale non-linear offset item; when the control system runs, the linear matrix is dynamically called according to the input gray level, and bias compensation is superposed. According to the invention, the problems of cross-batch visual angle chromatic aberration and color temperature drift and pocking marks under low gray level of the spliced screen are effectively solved, and the high-fidelity display consistency of the full gray level is realized.

The present invention relates to the technical field of accounting information processing, and in particular to an intelligent accounting information processing system based on cloud computing. The present invention obtains seals in account information to be identified through a cloud information acquisition module, and an information classification module determines a seal confidence representation value according to a chromaticity deviation value combined with the completeness of the seal contour in the account information to be identified, divides the category of the image to be identified, selects a verification unit to verify the seal in the image to be identified according to the category of the image to be identified, and adaptively adopts different methods to verify whether the seal in the image to be identified of the account information to be identified meets the verification standard. The present invention can classify the seals in the image to be identified, and can determine whether different categories of images to be identified meet the verification standard, thereby improving the verification capability of the intelligent accounting information processing system for the account information to be identified and ensuring the reliability of the intelligent accounting information processing system.