91 results about "Histogram method" patented technology

Spectrogram extraction from DNA sequence has been known since 2001. A DNA spectrogram is generated by applying Fourier transform to convert a symbolic DNA sequence consisting of letters A, T, C, G into a visual representation that highlights periodicities of co-occurrence of DNA patterns. Given a DNA sequence or whole genomes, with this method it is easy to generate a large number of spectrogram images. However, the difficult part is to elucidate where are the repetitive patterns and to associate a biological and clinical meaning to them. The present disclosure provides systems and methods that facilitate the location and/or identification of repetitive DNA patterns, such as CpG islands, Alu repeats, tandem repeats and various types of satellite repeats. These repetitive elements can be found within a chromosome, within a genome or across genomes of various species. The disclosed systems and methods apply image processing operators to find prominent features in the vertical and horizontal direction of the DNA spectrograms. Systems and methods for fast, full scale analysis of the derived images using supervised machine learning methods are also disclosed. The disclosed systems and methods for detecting and/or classifying repetitive DNA patterns include: (a) comparative histogram method, (b) feature selection and classification using support vector machines and genetic algorithms, and (c) generation of spectrovideo from a plurality of spectral images.

The present invention provides a method of detecting segment boundaries for a series of successive frames in a video sequence. The method includes the steps of acquiring color information from each frame, determining a color histogram for each frame, and applying a boundary detection technique utilizing the color histograms. Finally, the method includes segmenting the frames of the video sequence into uniform color segments. In addition, a system is provided for detecting segment boundaries for a series of successive frames in a video sequence. The system includes means for acquiring color information from each frame, means for determining a color histogram for each frame, and means for applying a boundary detection technique utilizing the color histograms. Finally, the system includes means for segmenting the frames of the video sequence into uniform color segments. The boundary detection techniques include a family color histogram method, a weighted average color histogram method, a successive color histogram method, a stochastic method, a shot-based color histogram method, a mosaic color histogram method, and a computable macro-segment boundary method.

Methods and apparatus are configured to provide data to generate and/or render (medical) images using medical volumetric data sets by electronically analyzing a medical volume data set associated with a patient that is automatically electronically divided into a plurality of local histograms having intensity value ranges associated therewith and programmatically generating at least one α-histogram of data from the local histograms used for at least one of peak detection, transfer function design or adaptation, tissue detection or tissue classification.

A method of and apparatus for determining and controlling the inertial attitude of a spinning artificial satellite without using a suite of inertial gyroscopes. The method and apparatus operate by tracking three astronomical objects near the Earth's ecliptic pole and the satellite's and/or star tracker's spin axis and processing the track information. The method and apparatus include steps and means for selecting preferably three astronomical objects using a histogram method and determining a square of a first radius (R₁²) of a track of a first astronomical object; determining a square of a second radius (R₂²) of a track of a second astronomical object; determining a square of a third radius (R₃²) of a track of a third astronomical object; determining the inertial attitude of the spin axis using the squares of the first, second, and third radii (R₁², R₂², and R₃²) to calculate pitch, yaw, and roll rate; determining a change in the pitch and yaw of the artificial satellite; and controlling on-board generated current flow to various orthogonally-disposed current-carrying loops to act against the Earth's magnetic field and to apply gyroscopic precession to the spinning satellite to correct and maintain its optimum inertial attitude.

The invention presents a scalable solution to encode the whole 12-bit raw video once to generate one bitstream that contains an H.264/AVC compatible base layer and a scalable enhancement layer. If a color bit depth scalable decoder is available at the client end, both the base layer and the enhancement layer sub-bitstreams will be decoded to obtain the 12-bit video and it can be viewed on a high quality display that supports more than eight bit; otherwise only the base layer sub-bitstream is decoded using an H.264/AVC decoder and the decoded 8-bit video can be viewed on a conventional 8-bit display. The enhancement layer contains a residual based on a prediction from the base layer, which is either based on bit-shift or based on an advanced bit depth prediction is utilized, wherein the advanced bit depth prediction method is a Smoothed Histogram method or a Localized Polynomial Approximation method.

Methods, systems and circuits predict cardiotoxicity induced cardiac injury prior to an irreversible state by electronically generating at least one histogram of mean intensities of voxels/pixels in an MRI image of a left ventricle myocardium and electronically determining a likelihood of cardiac injury due to cardiotoxicity based on data from the at least one histogram.

A method of and apparatus for determining and controlling the inertial attitude of a spinning artificial satellite without using a suite of inertial gyroscopes. The method and apparatus operate by tracking three astronomical objects near the Earth's ecliptic pole and the satellite's and/or star tracker's spin axis and processing the track information. The method and apparatus include steps and means for selecting preferably three astronomical objects using a histogram method and determining a square of a first radius (R₁²) of a track of a first astronomical object; determining a square of a second radius (R₂²) of a track of a second astronomical object; determining a square of a third radius (R₃²) of a track of a third astronomical object; determining the inertial attitude of the spin axis using the squares of the first, second, and third radii (R₁², R₂², and R₃²) to calculate pitch, yaw, and roll rate; determining a change in the pitch and yaw of the artificial satellite; and controlling on-board generated current flow to various orthogonally-disposed current-carrying loops to act against the Earth's magnetic field and to apply gyroscopic precession to the spinning satellite to correct and maintain its optimum inertial attitude.

A computer-based method for processing data is described. The method includes receiving, at a processing device, data to be processed, processing the data to assign spatial information to the data, the spatial information defining an element on a grid, determining, with the processing device, a sparseness of the processed data through application of the processed data to a multiple resolution level sparse tree filter, placing the processed data within a histogram based on the determined sparseness, and filtering the data based on spatial statistics using a sparse histogram method.

A form line extraction method integrating global information and local information combines local information and global information in an image. Firstly, smooth denoising is carried out on a grayscale image, and secondly image binaryzation based on an overlapping window is carried out; then a local contour in a foreground area is extracted, and straight line sections in the image are detected through local contour information; grids are set up by using of a projection histogram method, global distributed information of a form on the image is obtained, and the general location of the form is determined; at last, the straight line sections are connected in the range of the grids, so the whole form line is extracted. According to experimental result statistics, the false detection rate is less than 5% and the omission ratio is less than 3% according to the form line extraction method for exacting the form line in the image.

A method for acquisition of a weak signal from a satellite in the presence of a strong interfering signal from another satellite is disclosed. The method encompasses identifying the auto-correlation peak due to the weak satellite signal from the cross correlation peaks due to the strong satellite signal. This invention presents a method and apparatus of acquiring a weak satellite signal in the presence of a strong interfering satellite signal in a receiver by two techniques, namely, the millisecond boundary correlation histogram method, and the frequency response correlation histogram method. Both the techniques distinguish between the correlation characteristics for auto-correlation and cross-correlation. The apparatus presented in the invention implements the methods of weak satellite signal acquisition in presence of a strong interfering satellite signal in a pseudorandom noise (PRN) receiver.

The invention discloses a greenhouse vegetable disease surveillance video key frame extracting method and extracting system. According to the extracting method and the extracting system, the visual significance is combined with an online clustering algorithm. Firstly, an X2 histogram method is utilized to measure interframe difference and remove the effects of video frame images with the similar characteristics on the algorithm calculation amount; then the video frame images are transferred to an HSV color space, a visual significance diagram is calculated through characteristics of greenhouse vegetable surveillance video, an H channel and an S channel to extract the significance areas in the video frame images, and scab information, possible to be lost, in the significance areas is repaired through a morphological method; finally, key frames can be extracted through the online clustering algorithm and a pixel frame average algorithm. The extracting method can effectively obtain disease information in greenhouse vegetable surveillance video to establish solid foundation for accurate identification on greenhouse vegetable diseases. If combined with image processing techniques and mode identifying techniques, the extracting method and the extracting system can make great contributions to greenhouse vegetable disease identification.

The invention provides a two-valued method for license plate based on compensation principle and center region scanning. Firstly, the license plate region is converted through grey level stretching to realize reinforcement of the character region on the license plate; second the grey levels of the character pixel element and the background pixel element g1 and g2 of the reinforced license plate are figured out through a histogram method; thirdly the mean and the standard deviation of the reinforced license plate image is calculated and an illumination compensation factor is also obtained according to the mean and the standard deviation; fourthly an illumination penalty function is accordingly calculated based on the illumination compensation factor; fifthly a two-valued threshold value is consequently obtained according to the illumination penalty function, the standard deviation and the mean; and finally the type of the license plate can be judged through a center region scanning method with normalization treatment. Compared with the prior global dynamic thresholding method, the method of the invention has the advantages of not only quick two-valued process, but also high robustness and realization of complete separate between background and characters.

The invention discloses a method for modeling a background based on a camera response function in an automatic gain scene, which comprises the following steps of: performing automatic gain progressiveness-based analysis to obtain a roughly divided background area, obtaining low-noise training data by using a joint histogram method, and performing recovery once to obtain a globally optimal camera response function by the method based on maximum likelihood estimation and parameter constraints; online calculating a gain ratio frame by frame by utilizing correlation between a foreground and background difference and the gain ratio and the homography of a grayscale difference function relative to the gain ratio; and if the gain ratio is not 1, performing updating to obtain a background reference frame the same as a current reference frame by using the camera response function and the gain ratio, otherwise determining the background reference frame is unchanged, and obtaining the background reference frame with a gain coefficient the same as that of the current frame along with the change of the gain coefficient of a camera. By the method, the shortcomings of high background change speed, caused by difficulties in realizing automatic gain along with the camera, of the conventional methods are overcome, thereby ensuring high-efficiency motion detection.

The invention discloses a particle swarm optimization method based on a mutual information similarity strategy. The particle swarm optimization method based on the mutual information similarity strategy is characterized by using a combined histogram method of mutual information solving to redefine a speed updating formula of h (e, g) and a particle in a combined histogram, wherein the e and the g are a path to be matched and a template path respectively; and the h (e, g) expresses generation times of a position g corresponding to a historical path at a position where an optimal path e is generated. Compared to an existing basic PSO algorithm, by using the method of the invention, iteration times are reduced, a convergence speed is increased and an average result of searching is increased too.

The embodiment of the invention discloses an image data processing method, an image data processing device, image data processing equipment and a computer-readable storage medium, wherein the method comprises the steps of: obtaining original image data to be processed, and obtaining the pixel value and the pixel distribution information of the original image data; generating a grey-level histogramaccording to the pixel value and the pixel distribution information; according to pre-set inhibition parameters, calculating piecewise linearly changed piecewise threshold values based on the grey-level histogram; and performing piecewise linear grey-level transformation on the grey-level histogram according to various piecewise threshold values, so that processed image data is obtained. According to the image data processing method, the image data processing device, the image data processing equipment and the computer-readable storage medium disclosed by the invention, in combination with the ideas of histogram equalization and piecewise linear transformation, the piecewise threshold values of a piecewise linear transformation function are determined by adoption of the histogram method;because piecewise linear grey-level transformation based on the histogram is a pixel point processing method, the image contrast can be stretched; images are clear; characteristics are obvious; therefore, the visual effect of the processed image data is improved; the image data display effect is improved; and the image data quality is improved.

The invention relates to a background clutter measurement method based on edge structures, comprising the following steps: segmenting a background image into cells of the same size as a target image; establishing a similarity measure between the target image and cell background clutter images in an image structure feature space; establishing edge structure feature descriptions of the target image and the cell background clutter images through a gradient histogram method, and selecting a Bhattacharyya coefficient to calculate the similarity measure between the image edge structures; and weighting the structure similarity measure between the target image and each cell background clutter image as the clutter measure of the cell background image based on the edge structure similarity measure between the target image and the cell background clutter image, and taking the average clutter measure of all the cell background images as the clutter measure of the whole background image. The method fully embodies the fact that human eye vision mainly focuses on the object structure in target identification, and improves the accuracy of imaging system field performance prediction and evaluation.

The invention discloses a video shot detection method. The detection method comprises the following steps: histogram method processing procedure which comprises the following steps: extracting two adjacent frames from the video, computing histogram intersection according to weighting proportion of three color components in a HSV space; and judging whether the shot change occurs; frame difference method processing procedure, if judging that the shot change occurs, entering the frame difference method processing procedure, wherein the frame difference method processing procedure further comprises the following steps: extracting two adjacent frames from the shot and performing non-uniform blocking; computing pixel difference value of each of the blocks; comparing the pixel difference value with a predetermined block frame difference threshold value so as to perform sign; performing weighting summation on the sign variables in the blocks; comparing the summation with a set block weighting threshold value, if the summation is greater than the block weighting threshold value, regarding that the shot change occurs.

The invention provides a remote sensing image change detection method based on a texton. The method includes the following steps of selecting images, which are well registered in the same area, of two time phases, and carrying out segmentation on the images of the previous time phase to obtain a segmentation result; counting texture features of segmented image blocks in a first image, wherein a texton histogram method is used as a computing method of the texture features; counting texture features of all segmented image blocks in the images of the latter time phase with the segmentation result of the images of the previous time phase as a restriction boundary, wherein a computing method of the texture features is also applied to the texton histogram method; carrying out similarity comparison on the texture features of corresponding image blocks in the two time phases, wherein changes occur if the distance is larger than a certain threshold value, and otherwise no change occurs; marking changed areas on original segmentation results to obtain change detection images based on texture feature extraction.

Embodiments of the present invention provide a character identification method and apparatus. The method comprises: generating a to-be-identified high-pixel image by performing enlargement processing on a to-be-identified image; performing binarization processing on the to-be-identified high-pixel image, and filtering out a disturbing factor in the to-be-identified high-pixel image; acquiring a picture containing a to-be-identified character from a binarized image by adopting a projection histogram method; and inputting the acquired picture containing the to-be-identified character into a multi-layer artificial neural network model, and acquiring the to-be-identified character output by the multi-layer artificial neural network model. By adopting the technical scheme of the present invention, binarization processing is performed on the to-be-identified image, so that disturbing factors such as a background image can be effectively filtered out, thereby ensuring accuracy of a final recognition result. The Binarized image is segmented by adopting the projection histogram method, so that it is ensured that each picture containing the to-be-identified character that is obtained through segmentation contains a complete character, and accuracy of the recognition result is higher.