332 results about "YCbCr" patented technology

The invention discloses a color digital image enhancing and denoising method under random illumination. The method is characterized by comprising the following steps of: 1, image denoising processing, namely converting an original image from an RGB space to a YCbCr space, removing a Gaussian noise by using a Gaussian filter and removing a salt and pepper noise by performing median filter; 2, image brightness/contract stretch processing, converting the image from the RGB space to an HSI space, decomposing the image by using a two-sided filter, processing by an improved Retinex model algorithm, and obtaining a new image saturation by performing saturation compensation; and 3, performing fusion display on the image acquired after denoising the YCbCr space and the image acquired by HSI space processing. By the method, the color constancy of the image can be kept, the dynamic range of the image can be improved well, and simultaneously noises of the image can be inhibited and removed with less texture and detail information loss.

The invention relates to a dexterous hand teleoperation control method based on Kinect human hand motion capturing. The hardware for realizing the method comprises a Kinect sensor, a computer and a remote robot dexterous hand system. A mixing movement outline model is used for tracking the outline of the hand, hand posture tracking is realized through a particle filter algorithm, the far-end situation is observed through feedback image information transmitted by a robot in real time, and therefore a specific operation task is implemented. Through the movement outline model combining depth information and YCbCr skin color detection space technology, the problem that a real solution can not be obtained easily when an image contains high noise or a target is provided with a weak boundary is solved. A particle filter posture detection method based on template matching is adopted, and the human hand three-dimensional posture with high-dimensional characteristics can be detected and estimated. Through a master-slave operation combining a manual control mode and a program mode, convenience and rapidness are realized, and the guiding performance and usability of human-machine interaction are represented.

Under the premise of no extraneous high-resolution image library, a super-resolution sparse representation method for acquiring a high-resolution image is provided. The method comprises the steps of: (1) carrying out space conversion on a given low-resolution color image to obtain the YCbCr space image of the color image, and reconstructing the constituents of Cb and Cr by using an interpolation method; (2) constructing a database used for training, namely, a high-resolution image block Xh and a low-resolution image block Xl, and combining the two image blocks into a database X; (3) generating a dictionary D from the database X by using a sparse coding method, decomposing the dictionary D into a high-resolution image dictionary Dh and a low-resolution image dictionary Dl; (4) solving a sparse coefficient by using the Dl and characteristic images corresponding to an image of upsampling the low-resolution image by 2 times; (5) solving an image of upsampling the original low-resolution image by 3 times through the sparse coefficient and the Dh; and (6) combining Y, Cb, and Cr to obtain a YCbCr image, and converting the YCbCr image into an RGB image and storing the RGB image to obtain the final super-resolution representation image.

Disclosed is an apparatus for processing a digital signal in an image sensor. The apparatus includes: a line memory unit for storing an inputted digital signal of red (R), green (G) and blue (B); a kernel generation unit for generating a plurality of kernels after receiving the RGB digital signal from the line memory unit; a false color detection unit for detecting false colors by using the plurality of kernels; an edge detection unit for detecting edges by using the plurality of kernels; an interpolation unit for interpolating the RGB digital signal from the line memory unit; a color space conversion unit for converting the interpolated RGB digital signal into a YCbCr signal; and an image enhancement unit for suppressing the false colors and enhancing the edges in the YCbCr signal in response to outputs of the false color detection unit and the edge detection unit.

Various techniques are provided herein for processing raw image data in front-end processing logic of an image signal processing system. In one embodiment, the front-end processing logic includes a statistics processing unit configured to process raw image data acquired by an image sensor to obtain one or more sets of statistics. The statistics processing unit may first correct defective pixels in the raw image data and then correct lens shading errors in the raw image data prior to extracting the statistics information. In certain embodiments, black level compensation may be applied between the defective pixel correction and lens shading correction steps, and inverse black level compensation may be applied between the lens shading correction step and the extraction of the statistics information. The acquired statistics information may be utilized by an image signal processing pipeline for converting the raw image data into a color (e.g., RGB) and/or luma (e.g., YCbCr) image.

A digital white balance device is simply implemented in a digital processing scheme by employing a grey world algorithm. In the device, a timing controller receives vertical and horizontal synchronization signals of an input image and produces a timing control signal. An RGB multiplier multiplies input RGB image data by RGB gains received from an RGB gain controller. A first YCbCr averaging unit converts input RGB image data to YCbCr image data, and obtains first YCbCr averages of this YCbCr image data. A second YCbCr averaging unit converts output RGB image data to YCbCr image data, and obtains second YCbCr averages of this YCbCr image data. According to the timing control signal, the RGB gain controller compares the second YCbCr averages with predetermined target YCbCr averages, respectively, and obtains RGB gains based on the first YCbCr averages, according to the compared result, and provides them to the RGB multiplier.

A video signal receiving apparatus comprises a HDMI receiver, signal processing section and control section. The HDMI receiver separates a digital signal conformable to HDMI standards into video component and audio component, determining whether a received digital video signal is a RGB or YCbCr signal, and changing its setting in accordance with the determination result. The signal processing section decodes video signal and audio signal separated by the HDMI receiver to restore analog video signal and audio signal. The control section changes the setting of the HDMI receiver by an operation.

The processing of RGB image data can be optimized by performing optimization operations on the image data when it is converted into the YCbCr color space. First, a raw RGB color space is converted into a YCbCr color space, and raw RGB image data is converted into YCbCr image data using the YCbCr color space. For each Y-layer of the YCbCr image data, a 2D LUT is generated. The YCbCr image data is converted into optimized CbCr image data using the 2D LUTs, and optimized YCbCr image data is generated by blending CbCr image data corresponding to multiple Y-layers. The optimized YCbCr image data is converted into sRGB image data, and a tone curve is applied to the sRGB image data to produce optimized sRGB image data.

A multiple pornographic image classification method based on an image segmentation algorithm and deep learning relates to the technical field of information, especially to the technical field of image identification. The method is characterized by comprising the following four major steps: skin color identification, principal component analysis of the skin color region, deep learning, and pornographic image identification based on a convolutional neural network. First, non-pornographic images are screened out through a skin color pixel detection and skin region partitioning algorithm based on the YCbCr theory. Undetermined images are input to a LeNet5-based convolutional neural network model for identification after feature extraction. Compared with the traditional identification based on skin color and features, the method can eliminate the noise influence of non-body-part images, is not constrained by light and human postures, and can greatly improve the accuracy of traditional pornographic image classification. Compared with general deep learning based on a convolutional neural network, the method does not need massive labeled images, and the characteristics of a deep residual network determine that the model can better analyze the characteristics of pornographic images. Only through about ten hours of training, an identification effect above 90% can be achieved.

A method for detecting human skin tone in a video signal by comparing image data from the video signal to a color profile table obtained from a plurality of training sequences. The image data comprising a plurality of pixels each having a plurality of color components, the components preferably being in the YCbCr color space. The method includes separating image data for each frame in the video signal into sets of data, averaging the image data in each data set to generate mean values for each color component in the data set, comparing the mean values to a stored color profile correlating to human skin tone, and identifying data sets falling within the stored color profile.

The invention mainly relates to a method for automatically detecting acupuncture points on the back of a human body by an image processing technology mainly, so that the current situation that doctors artificially and subjectively determine acupuncture points is improved, the efficiency of detecting the acupuncture points is improved, unnecessary manpower is reduced, the foundation for automatic diagnosis and classification systems of diseases and human health automatic analysis systems are laid, and necessary technical support is provided. The method comprises the following steps of calculating YCbCr value of an input image; performing skin color segmentation by an elliptical model to acquire a human body back figure; acquiring the upper edge curve and the lower edge curve of the human body back by using a Canny edge detection algorithm and seeking white points from inside to outside; calculating a midpoint to fit a straight line so as to acquire a human body spine line; rotating the image to acquire a target image; performing grayscale standardization on a sample image; summating and averaging to acquire a template image; matching the target image with the template image; and determining the positions of the acupuncture points of the target image through the positions of the acupuncture points in the template image.

The invention is applicable on the image treatment field, which provides a method, a system and a picture pick-up device for adjusting white balance, wherein the method comprises the following steps switching a image data of a RGB format into a image data of a YCbCr format, estimating the color temperature information of reference white points in images, calculating the gain of channels of R, G and B according to the effective color temperature information, and using the gain of channels of R, G and B to adjust the pixel values of R, G and B in the images. The invention estimates the availability of the color temperature of the reference white point during the white balance adjustment and adjusts the white balance according to the effective color temperature information, which can improve the efficiency and accuracy of the white balance adjustment.

The algorithm is used in the image compression field. It integrates the color space transition, quantification and DCT three steps in order to reduce the operand; while reducing the operand of color transition, except the little adjustment of quantification step length, the structure and operand in both DCT and quantification process steps are not influenced. In case the image sub-sampling is 4:4:4, the new algorithm realizes the 40% and 42% reduction on the multiplication and additive operation in process of transition from RGB to YCbCr in compression process; in the de-compression process, the 60% and 42% reduction on the multiplication and additive operation is realized in the process of transition from YCbCr to RGB.

It is possible to realize a novel video processing device that can utilize the compatibility between the spaces of an encoded image in an xvYCC system with a wide color gamut and an encoded image in the conventional YCbCr system. The video signal processing device (100) detects the type of the recording medium with a video medium type detection portion (104), obtains the color gamut of the video signal with a video color gamut obtaining portion (103), determines a color adjustment parameter with a color adjustment parameter determining portion (106), performs color adjustment on the video signal with a video color adjustment portion (102) based on that parameter, records the color-adjusted video signal to the recording medium.

The invention provides a fatigue driving monitoring device and a fatigue driving monitoring method. The fatigue driving monitoring method comprises the steps of: 1) acquiring an acquired image; 2) converting the acquired image into a YCbCr space, extracting a skin color region and carrying out binarization to obtain a face rectangular frame; 3) scanning pixel points in the face rectangular frame, increasing radius by taking each pixel point as a circle center, finishing the scanning until the pixel points exceeding a preset proportion in the scanning regions are white points or the scanning regions reach the boundary of the face rectangular frame, and regarding the diameter of a maximum scanning regions as pupil diameter; 4) and judging whether a driver is fatigued through monitoring the pupil size in real time according to a PERCLOS algorithm. The fatigue driving monitoring device and the fatigue driving monitoring method can form the face rectangular frame in the YCbCr space quickly, simply and accurately, and detects the fatigue state of the driver through combining the real-time pupil size monitoring with the PERCLOS fatigue detection method. The fatigue driving monitoring device and the fatigue driving monitoring method are simple and efficient, fast in operation speed and high in accuracy, and the monitoring process and result are not affected by the inclination angle of face.

The invention discloses a video-based flame detection method, and solves the technical problem in improving the flame detection accuracy. The video-based flame detection method comprises the followingsteps of obtaining a video image sequence; performing image preprocessing; performing color detection; performing flame feature extraction; and performing AdaBoost prediction. Compared with the priorart, the method has the advantages that all candidate flame points meeting a condition in a video image are found out according to characteristics of flame pixels in RGB and YCbCr color spaces; then,the video image is subjected to block segmentation; covariance matrixes corresponding to color and brightness attributes of flame pixel sets in video blocks are calculated; upper or lower triangularparts in the color and brightness covariance matrixes are extracted as eigenvectors; an obtained eigenvector set serves as an input of an AdaBoost classifier; the eigenvectors are input to an AdaBoostclassification model; an output is a judgment whether a fire happens or not; the fire happening situation can be detected out in real time; the false alarm rate can be reduced; and relatively high accuracy and strong robustness are achieved.

A signal conversion apparatus, connected to one or more electronic apparatuses and a display device, mainly includes one or more input interfaces, a signal conversion unit, and an output interface. Each input interface is for connecting to an electronic apparatus and receiving signals therefrom. The input interfaces include analog interfaces and digital interfaces. The signal conversion unit is for receiving the signals in multiple formats from the input interfaces, and converting the signals, when necessary, into a predetermined format, which is supported by the display device. The predetermined format includes RF format, RCA format, S-Video format, YPbPr/YCbCr format, VGA format, MPEG format, DVI format, HDMI format, and so on. The output interface is for transmitting the signals from the signal conversion unit to the display device through a cable. The display device receives the signals from the output interface and displays corresponding information thereof.

An image processing method is provided and includes the following steps. A source image arranged in a Bayer pattern is captured. A first-order image process is performed on the source image to produce a first image in YCbCr format. A second-order image process is performed on the source image to produce a second image in YCbCr format. Then, a noise-reducing process is performed on the first image in YCbCr format to produce a noise-reduced image. A blending operation is performed on luminance image of the noise-reduced image and luminance image of the second image in YCbCr format, and thereafter a chrominance image is combined with the blended image to produce a processed image. A noise reducing degree of the noise-reduced image is higher than that of the second image in YCbCr format.