92 results about "Histogram method" patented technology

The invention provides an improved VFH algorithm-based positioning and obstacle avoidance method and robot. According to the improved VFH algorithm-based positioning and obstacle avoidance method and robot, on the basis of an improved vector field histogram method and a scan matching algorithm, environmental information is acquired by the adoption of a laser range-finder sensor, and the pose error brought by speedometer is amended by the adoption of the polar coordinate scan matching algorithm. After robot positioning is finished, environmental information is rasterized, an obstacle is expanded according to the relationship between the robot and the obstacle and considering the sensing uncertainty of a movable robot and the real size of the robot, an original polar coordinate histogram is built, the free walking area and the obstacle avoidance area are acquired, a binary polar coordinate histogram is acquired through the definition of two threshold values, a shielding polar coordinate histogram is built through estimating the movement trail of the movable robot, and finally, the cost function is introduced to determine the best movement direction of the robot so as to solve the problem of shielding route planning of the movable robot in a home environment.

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.

The invention discloses an expression identification method fusing a depth image and multi-channel features. The method comprises the steps of performing human face region identification on an input human face expression image and performing preprocessing operation; selecting the multi-channel features of the image, extracting a depth image entropy, a grayscale image entropy and a color image salient feature as human face expression texture information in the texture feature aspect, extracting texture features of the texture information by adopting a grayscale histogram method, and extracting facial expression feature points as geometric features from a color information image by utilizing an active appearance model in the geometric feature aspect; and fusing the texture features and the geometric features, selecting different kernel functions for different features to perform kernel function fusion, and transmitting a fusion result to a multi-class support vector machine classifier for performing expression classification. Compared with the prior art, the method has the advantages that the influence of factors such as different illumination, different head poses, complex backgrounds and the like in expression identification can be effectively overcome, the expression identification rate is increased, and the method has good real-time property and robustness.

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.

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.

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.

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 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.

The invention discloses a distributed event detection method based on a correlation. The temporal correlation of data is analyzed in nodes through a clustering structure based on the locality of a wireless sensor network event area, the spatial correlation of the data is analyzed between adjacent nodes, and the node where an event happens is recognized. The abnormal correlation of the nodes is analyzed through the histogram method, and the detecting accuracy is improved. Due to the fact that the summary information of a histogram is transmitted among the nodes, the communication energy consumption among the nodes is reduced. The occurrence of new events can be effectively detected, the method has a low false alarm rate and low energy consumption, and compared with a centralized abnormality detection method, the distributed event detection method based on the correlation has the advantages of being high in detection performance and obviously reducing communication cost.

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 segmentation-based airborne LiDAR point cloud building extraction method. The method comprises the steps of: (1) loading airborne laser LiDAR point cloud data; (2) identifying noise points in the airborne laser LiDAR point cloud, and removing the noise points; (3) carrying out material distribution simulation filtering to separate ground points from non-ground points; (4)carrying out region growth segmentation on filtered non-ground point cloud; and (5) calculating the direction cosine of the local normal vector and normal vector of each cluster which is obtained after the segmentation, generating a histogram, separating building point cloud from non-building point cloud through the generated histogram, thereby realizing the accurate extraction of the building point cloud. The invention provides the simple and efficient histogram method for distinguishing buildings from non-buildings. According to the difference of the normal vector characteristics of a building roof and a vegetation surface, a PCL-based region growing algorithm is utilized to perform three-dimensional point cloud segmentation on the non-ground points; and the histogram method is used incombination to distinguish the buildings from the non-buildings, so that the building point cloud data are accurately extracted.

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 present invention discloses a pavement damage type identification method based on a classifier ensemble. The method comprises the following steps of: 1) performing homomorphic filter preprocessing on detected damaged pavement images; 2) establishing a pavement damage image database by using the preprocessed pavement images, and guaranteeing the balance of image samples in the database, namely, guaranteeing the images to be same in size and number, wherein the database comprises horizontal crack, longitudinal crack, net crack and precipitation damage types; 3) extracting eigenvectors of the pavement damage images by respectively using Contourlet conversion and edge direction histogram methods, and establishing union eigenvectors of the pavement damage images by using a serial combined policy; and 4) based on a cross kernel support vector machine, establishing a random subspace ensemble classifier to identify the pavement damage images. The pavement damage type identification method based on the classifier ensemble, provided by the present invention, effectively improves the efficiency of pavement damage image type identification,and provides an efficient and intelligent management basis for road management work, particularly pavement maintenance.

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.

Systems and methods 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 systems and methods apply image processing operators to find prominent features in the vertical and horizontal direction of the DNA spectrograms. The systems and methods for detecting and / or classifying repetitive DNA patterns include: (a) a comparative histogram method, (b) feature selection and classification using support vector machines and genetic algorithms, and (c) generation of a spectrovideo from a plurality of spectral images.

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 discloses a method restraining image impulse noise based on an iteration non-local mean value. The method is mainly used for solving the problems that an existing method can not retain image detail information in the denoising process, and a sharp image can not be restored under high noise density. The method comprises the following realizing steps that (1) for a noise image, a histogram method is used for detecting the noise position; (2) an option switch median filter is used for carrying out pre-filtering on the noise image; (3) the iteration non-local mean value method is used for the image processed in a pre-filtering mode is carried out so that the sharp image with the impulse noise effectively restrained can be obtained. A simulation experiment shows that under the circumstance of the impulse noise of different degrees, the method is better in subjective visual effect and objective evaluation result compared with an existing algorithm, and the method can be used for restraining the high-density impulse noise and restoring the sharp image.

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.

The invention discloses a coalfield well logging curve standardization method, comprising a step of performing standardization on a coalfield well logging curve by a frequency histogram method, wherein the well logging curve of a coalfield work area is analyzed firstly, and a standard well is selected from wells subjected to logging in the coalfield work area; then, a standard stratum is selected from strata subjected to logging research in the coalfield work area; then, well logging data are respectively analyzed through the frequency histogram method; finally, coalfield well logging curve standardization is performed by using a standardization formula. After the step, a standardized well logging curve is obtained, thus providing high-quality well logging data for follow-up work such as inverting.