801 results about "Color transformation" patented technology

The invention discloses a pavement crack detection method based on a Yolov8 model, and belongs to the technical field of crack detection. Comprising the following steps: constructing a pavement crack segmentation data set: acquiring a road crack image through an unmanned aerial vehicle, performing data enhancement processing of geometric transformation and color transformation on the image in combination with a public data set, performing Gaussian filtering denoising on a noise image, and performing crack labeling by using Label; based on a YOLOv8-Seg model, improvement is carried out by introducing a PKIblock multi-scale convolution kernel, generalizing an efficient layer aggregation network GELAN module, an EMA attention mechanism and replacing a spatial pyramid pooling layer SPPF into a SimSPPF, and a road crack recognition model YOLOv8-RCI is constructed; and performing crack detection and instance segmentation on the unmanned aerial vehicle image by using the trained YOLOv8-RCI model, and outputting a crack position and mask information. Through the improvement in the four aspects, the detection segmentation performance of the model is improved, and the model meets the requirement of real-time detection.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that recolors a digital design according to colors of a digital image and further generates an enhanced recolored digital design. In particular, in some embodiments, the disclosed systems identify a digital image for recoloring a digital design and recolors the digital design utilizing a color affine transformation algorithm to generate a recolored digital design. Further, in some embodiments, the disclosed systems generate the enhanced recolored digital design by transforming one or more colors of the recolored digital design to be within a range of the colors of the digital image utilizing a convex hull projection method. Moreover, in some embodiments, the disclosed systems further enhance the recolored digital design utilizing a contrast enhancement algorithm to modify luminescence values.

The invention provides an image color correction method and device, a color correction robot and a storage medium, and the method comprises the steps: obtaining a to-be-processed image, extracting the color value of each pixel point in a plurality of color blocks in the to-be-processed image, and obtaining a color value list; setting a weight coefficient for each color value in the color value list; fitting a polynomial regression model by using the color value list with the weight coefficient to obtain a fitted polynomial regression model; generating a color conversion matrix by using the fitted polynomial regression model, wherein the color conversion matrix is used for representing a mapping relation between a color value in the to-be-processed image and a standard color value in the colorimetric card; and correcting the color values of the pixel points in the to-be-processed image by using the color conversion matrix to obtain a corrected image. According to the embodiment, the color accuracy of the image is improved, the reliability and authenticity of image information are ensured, and therefore reliable data support is provided for subsequent intelligent analysis and auxiliary diagnosis.

An information processing apparatus includes an obtaining unit which obtains first color information from an image that includes a pixel representing color information of a first color and a pixel representing color information of a second color. A determination unit determines whether the obtained first color information includes second color information. A conversion unit executes first color conversion processing on the image. A correction unit, in a case where a color difference between the third color and the fourth color is less than a predetermined threshold, corrects a conversion parameter in the first color conversion processing such that a color obtained by converting the first color is a seventh color which is different from the third color and whose color difference from the fourth color is greater than the color difference between the third color and the fourth color.

The invention provides a flow velocity identification method and device based on an improved U-Net network model, and belongs to the technical field of flow velocity measurement, and the method comprises the steps: carrying out the sampling of collected river image data, and obtaining the sampling image data; randomly cutting the sampling image data according to a preset size to obtain a cut image; performing color transformation on the cut image according to a preset random probability to obtain an image sequence, the color transformation including at least one of luminosity transformation, contrast transformation, saturation transformation and tone transformation; and inputting the image sequence into an improved U-Net network model to carry out flow velocity identification so as to obtain a flow velocity prediction result of the river channel. According to the flow velocity identification method based on the improved U-Net network model, the time sequence information and the texture information of the river channel video frame are extracted through the improved U-Net network model, and then the corresponding flow velocity value is output, so that the identification precision and the identification efficiency of the flow velocity can be improved.

The invention provides an image defogging enhancement and intelligent perception collaborative optimization method based on stream matching, and the method comprises the steps: obtaining a foggy input image, and constructing an ordinary differential equation for defining image transformation; the input image is input into a fog perception vector field, the fog perception vector field comprises an atmospheric scattering purifier and a defogging perception color lookup table, and the atmospheric scattering purifier is used for extracting multi-scale features from the foggy input image to generate clearer output; the defogging perception color lookup table adaptively adjusts the image color through a nonlinear color transformation mechanism; and solving the ordinary differential equation through an RK4 solver, iteratively updating the foggy input image at each time step, and ensuring that the input image can be stably converted into a clear image from an initial foggy state. The technical problems that in the prior art, the existing method is forced to reduce the model capacity due to the calculation efficiency constraint in the ultra-high-definition image defogging, so that the fog concentration estimation is incomplete, and the perception quality and the calculation efficiency cannot be considered at the same time are solved.

The invention discloses a figure scene generation system based on AI interaction. The figure scene generation system comprises a user interaction design module, a figure image shooting module, a figure image analysis and processing module, a figure image processing module, an image integration and correction module, an image generation module and a management database. The figure image shooting module is used for acquiring a user image and a microstructure of a skin surface by using a high-definition camera, the microstructure comprises a skin glossiness reference value, a wrinkle level reference value, pore characteristics and pigmentation, and the user image contains a hair coverage rate; according to the method, an algorithm is used for calculating pore features, color conversion is carried out on a microstructure to obtain pigmentation, a user age evaluation correlation coefficient is obtained through calculation of skin glossiness, a wrinkle level, the pore features, the pigmentation and a hair coverage rate, and a more accurate age evaluation result is provided by improving an age prediction method. The features of skin texture, pigmentation and the like can be quantified more accurately, so that the accuracy of age assessment is improved.

An image processor for a medical observation device includes a color conversion function, The image processor is configured to retrieve an input pixel of a digital input color image and a location of the input pixel in the input color image, and apply the color conversion function to the input pixel to generate an output pixel in a digital output color image. The color conversion function depends on the location of the input pixel.

A light source of a photographing environment in which the electronic device is located is a flicker light source. The method includes: running a camera application in the electronic device; displaying a first image, where first exposure time is less than first duration, and the first image includes banding and / or a color cast image area; detecting a first operation; obtaining a second image in response to the first operation, where second exposure time is an integer multiple of the first duration; obtaining a color transformation matrix and / or a brightness parameter based on the first image and the second image; performing first image processing on the first image based on the color transformation matrix and / or the brightness parameter, to obtain a third image, where the third image is an image obtained by removing the banding and / or the color cast image area; and displaying or saving the third image.

An imaging device includes: an imaging sensor configured to capture a subject image to generate image data; a storage configured to store a plurality of color conversion data each defining a corresponding relationship between color information of an image before and after color conversion; an output unit configured to output a live view screen based on the image data; an operation unit configured to receive a user operation; and a controller configured to designate first color conversion data and second color conversion data from the plurality of color conversion data, in accordance with the user operation. The live view screen presents a live view image resultant of image processing of applying the first color conversion data and the second color conversion data to the image data.

Provided are a color converting substrate and a display device including same. The color converting substrate includes: a base portion in which a first light transmission area, a first light blocking area, and a second light transmission area, which are sequentially and closely arranged in a first direction, are defined; a first wavelength converting pattern located on the base portion and configured to wavelength-covert a first color light into a second color light; a second wavelength converting pattern located on the base portion and configured to wavelength-convert the first color light into a third color light; and a light transmission pattern located on the base portion and configured to transmit the first color light.

There is provided with an information processing apparatus. A first obtaining unit obtains first color information from a first image, which includes a pixel representing color information of a first color defined in a first color gamut and a pixel representing color information of a second color defined in the first color gamut. A first correction unit, in a case where a color difference between a third color defined in a second color gamut and a fourth color defined in the second color gamut is less than a predetermined threshold, corrects a first conversion parameter for the color conversion processing such that a color obtained by converting the first color is a fifth color. A conversion unit performs color conversion processing in which the corrected first conversion parameter is used on a second image different from the first image.

The invention discloses a pathological image self-supervised dyeing normalization method and device, and belongs to the technical field of combination of digital pathology and image processing, and the method comprises the steps: constructing a pathological image database; a dyeing normalization model is designed, the dyeing normalization model comprises a public feature domain extraction module, a content perceptron, a scene perceptron and a fusion module, and the dyeing normalization model can perform color conversion on the pathological image to obtain a dyed normalized image; a self-supervised loss function is constructed based on the pixel level difference of the input original pathological image and the dyed and normalized image, and a dyeing and normalization model is trained. The model can perform adaptive dyeing style normalization on any image of an unknown pathological data center towards a selected pathological data center image.

Aspects of hair simulation, hair classification, and networks therefor including aspects to train such networks are provided. A classifier model alleviate the impact of human bias where the modeling of the real label distribution and annotators' biases are separated by incorporating annotator confusion matrices into a baseline model. The model was trained using a consistency-based semi-supervised learning framework. With the use of only 1000 labeled data, the final classifier model achieved a classification accuracy that was 20% higher than a human professional annotator. The model is useful as a color classifier to train generative models for hair color translation. There is provided a generative model for hair simulation (e.g. via VTO) that is guided during training by a hair classifier model. Further provided is a color mapping network to process an input image and target hair color for the generative model to define the hair simulation.

A color conversion substrate includes: a base part in which a first light-transmitting area and a second light-transmitting area are defined; a first stack disposed on the base part and a second stack disposed on the first stack; a first wavelength conversion pattern overlapping the second light-transmitting area, and disposed on the second stack, where the first wavelength conversion pattern converts light of a first color into light of a second color; and a light-transmitting pattern overlapping the first light-transmitting area and disposed between the first stack and the second stack, where portions of the first stack and the second stack in the second light-transmitting area are in direct contact with each other to constitute a blue light reflective layer.

Devices having a reflective geometry are provided. The device includes a color conversion layer including luminescent material. The color conversion layer having a first side and a second side and a substrate having a first side and a second side. The second side of the color conversion layer located on the first side of the substrate. The device including an LED light source located remotely from the color conversion layer where the LED light source is optically coupled and / or radiationally connected to the first side of the color conversion layer. The device includes at least one of: (a) the substrate has a reflectivity of at least 20%, (b) a reflective layer located between the substrate and the color conversion layer, or (c) a back reflective layer located on the second side of the substrate. The devices are especially useful for lighting and display applications. Articles including the device are also provided.

Methods for actively managing remnant voltage on backplane electrodes when driving an electrophoretic display, especially with short waveforms, such as used for scrolling, pinch-zoom, pulldown menus, and even video. The methods track the remnant voltage changes for each backplane electrode during a series of image updates and use same color transitions to either improve the optical quality state of the display pixel or to decrease the remnant voltage at the display pixel. Thus, it is not necessary to employ full reset pulses, which typically drive a backplane electrode to both extreme voltage states and appear very “flashy” to a user.

A novel functional panel that is highly convenient or highly reliable is provided. The functional panel includes a first pixel. The first pixel includes a first element, a color conversion layer, and a first functional layer. The first functional layer is positioned between the first element and the color conversion layer. The first element has a function of emitting light and contains gallium nitride. The color conversion layer has a function of converting the color of light emitted from the first element into a different color. The first functional layer includes a first insulating film and a pixel circuit. The first insulating film includes a region positioned between the pixel circuit and the first element, and has an opening. The pixel circuit includes a first transistor. The first transistor includes a first oxide semiconductor film and is electrically connected to the first element through the opening.

A display device includes: a substrate that includes first to third light emitting areas and a light blocking area that surrounds the first to third light emitting areas; a light emitting layer that includes first to third light emitting layers disposed in the first to third light emitting areas, respectively; and a color conversion layer that includes a first bank disposed in the first light emitting area on the light emitting layer, overlaps an edge of the first light emitting layer, and includes a first opening that exposes a central portion of the first light emitting layer, a second bank disposed in the light blocking area on the light emitting layer, contacts a side surface of the first bank, and includes a material different from the first bank, and a first color conversion pattern disposed inside the first opening.

A display device according to an embodiment includes a display panel, and a color conversion layer disposed on the display panel, wherein the color conversion layer includes a quantum dot and a scatterer, the scatterer includes a first particle having a first diameter, and the first diameter is from about 100 nm to about 180 nm.

A printing apparatus includes: a display device; a controller; and a memory configured to store computer-readable instructions, including: a first acquisition operation of acquiring first image data for printing a first image on a printing medium using an ink ejected from a nozzle; a first color conversion operation of performing color conversion on the first image data to generate second image data; a second color conversion operation of performing, according to a display condition when displaying the first image on the display device, color conversion on the second image data to generate third image data; and a display operation of displaying a second image on the display device based on the third image data. In the first color conversion operation, the color conversion is performed according to any one of a printing medium, a printing condition, and a combination of the printing medium and the printing condition.

The invention discloses a non-contact heart rate estimation method and system based on multi-modal signal fusion, and relates to the technical field of image processing, and the method comprises the steps: positioning a region of interest in a face video, extracting HSV and Lab color space signals, and fusing the HSV and Lab color space signals; suppressing ambient light interference through background brightness compensation to obtain a color conversion signal and normalizing the color conversion signal; adjusting the bandwidth filtering signal of a band-pass filter by using the historical heart rate to generate an rPPG signal; performing time domain and frequency domain analysis on the rPPG signal, and performing weighted averaging by combining two results to obtain a heart rate estimation value; a historical data smoothing strategy is adopted to correct a heart rate estimation result to ensure accuracy. According to the method, high-precision non-contact heart rate estimation is realized through extraction and fusion of HSV and Lab color space signals, background brightness compensation, signal normalization and processing of human face video signals based on a historical heart rate adjustment band-pass filter.

A display device includes a substrate; a light-emitting device disposed on the substrate; a color conversion layer disposed on the light-emitting device; a color filter layer disposed on the color conversion layer; a first coating layer disposed on the color filter layer and including a scattering particle and a dispersion layer in which the scattering particle is dispersed; and a second coating layer disposed on the first coating layer and having a smaller refractive index than a refractive index of the first coating layer.

A display device includes a light-emitting element layer including light-emitting elements, a first insulating layer including an inorganic layer above the light-emitting element layer, a color conversion layer including a bank and a quantum dot above the first insulating layer, a low refractive layer above the color conversion layer, and a second insulating layer including an inorganic material above the low refractive layer.

The present invention discloses a method and device for self-supervised color normalization of pathological images, which belongs to the technical field of combining digital pathology and image processing, and includes: constructing a pathological image database; designing a color normalization model, which includes a common feature domain extraction module, a content sensor, a scene sensor, and a fusion module, and the color normalization model can perform color conversion on the pathological image to obtain a color normalized image; based on the pixel-level difference between the input original pathological image and the color normalized image, a self-supervised loss function is constructed and the color normalization model is trained, and the model can realize adaptive color style normalization of an image of any unknown pathological data center toward an image of a selected pathological data center.

The invention relates to the field of image processing, and provides an image processing method and electronic equipment, the method is applied to the electronic equipment, a light source of a shooting environment where the electronic equipment is located is a stroboscopic light source, and the method comprises the following steps: running a camera application program of the electronic equipment; a first image is displayed, the first exposure time is shorter than the first duration, and the first image comprises stripes and / or color cast image areas; detecting a first operation; in response to the first operation, obtaining a second image, the second exposure time being an integral multiple of the first duration; obtaining a color conversion matrix and / or a brightness parameter based on the first image and the second image; performing first image processing on the first image based on the color conversion matrix and / or the brightness parameter to obtain a third image, the third image being an image in which stripes and / or color cast image areas are removed; and displaying or storing the third image. Based on the scheme of the invention, stripes and / or local color cast in the image can be removed when the moving object is shot, and the image quality is improved.

To provide an image processing apparatus that appropriately executes settings of a color conversion method and application of the set color conversion method to image data.SOLUTION: An image processing apparatus comprises: area setting means that sets, on an image represented by input image data, a first area used for settings of a color conversion method for image data, and a second area not used for the settings of the color conversion method; color conversion method setting means that, when the first area and the second area are included on the image as a result of the settings performed by the area setting means, sets the color conversion method on the basis of the image data of the first area set by the area setting means; and generation means that determines the color conversion method set by the color conversion setting means, as a color conversion method to be applied to an area including the first area and at least part of the second area on the image, and generates image data after the color conversion by using the determined color conversion method.SELECTED DRAWING: Figure 3

The invention provides a laser color converter preparation method and a laser color converter structure. The laser color converter structure comprises a heat dissipation substrate, a fluorescent glass layer, a bonding layer and a heat dissipation cover plate. Wherein a groove is formed in the heat dissipation substrate; the fluorescent glass layer is filled in the groove, the heat dissipation cover plate is located above the heat dissipation substrate, and the heat dissipation cover plate and the heat dissipation substrate are fixed through the bonding layer. The heat dissipation performance of the laser color converter is improved by utilizing the heat-conducting groove structure, the light-emitting saturation problem is avoided, and the light-emitting brightness and the heat stability of the white laser light source are effectively improved; no organic bonding material is used in the laser color converter, so that the organic bonding material is prevented from losing efficacy and even being carbonized at high temperature, and the long-term reliability of the white laser light source is improved.

The invention discloses an optimization method of a furrow recognition algorithm, and the method comprises the steps: S1, obtaining an image or point cloud data of a furrow region, S2, carrying out the preprocessing of the image or point cloud data, and carrying out the denoising, filtering, color conversion and morphological operation, the method comprises the following steps: S1, preprocessing data, S3, carrying out preliminary segmentation of furrow areas on the preprocessed data by using an improved random sampling consistency algorithm and a clustering algorithm, S4, identifying and optimizing furrow boundaries in the segmented areas through a machine learning model, and carrying out repeated iterative training on the model, and S5, carrying out conditional filtering on the furrow boundaries to remove interference information; according to the optimization method of the furrow recognition algorithm, the complexity of manual setting and possible errors are reduced, the optimized furrow recognition algorithm can be dynamically adjusted, the efficient management requirement of large-scale agricultural production is met, the automation degree and management efficiency of agricultural production are greatly improved, and the development of precision agriculture is promoted.