2661results about How to "Quick extraction" patented technology

Disclosed is an apparatus for autonomously compressing, phase-compensating and waveform-shaping an ultrashort light pulse that is fast and high in sensitivity in compensating for phase fluctuations and allows the use of a usual laser light source that is low in light intensity and has large temporal fluctuations in phase. The apparatus comprises: a pulsed light source (2); a spectroscopic spatial dispersing device (4) for spatially dispersing a light pulse (3) emitted from the pulsed light source (2) into spectral components thereof; a spatial light modulator (5) for adding a phase to each of the spectral components of the spatially dispersed light pulse (3); a multiplexer (6) for combining the phase added spectral components of the light pulse (3) together to form a composite output light pulse (7); a modified SPIDER device (8) for forming a spectral interference figure from a portion of the composite output light pulse (7); and a feedback device (9) for detecting a spectral phase from the spectral interference figure and feeding a signal representing a difference between the detected spectral phase and a pre-established phase back to the spatial light modulator (5). The modified SPIDER device (8) comprises: a pulsed light source for a chirped light pulse (8a); a delay unit (8c) for delaying a light pulse (8b) from the pulsed light source (8a) with an adjustable delay time; a dispersive medium (28) for forming a chirped light pulse (29) from the light pulse whose delay time is adjusted by the delay unit (8c); a replica pulse former (24) for forming from a portion of the output light pulse (7) a pair of replica light pulses (24a, 24b) one delayed after the other; a nonlinear optical crystal (31) for frequency-mixing the two replica pulses (24a, 24b) with the chirped light pulse (29); a spectrometer (8e) for forming an interference figure of the resultant two frequency-mixed replica light pulses; and an image reader (8f) for reading the interference figure of the two frequency-mixed replica light pulses.

Methods and apparatus are provided for processing an information signal containing content presented in accordance with at least one modality. In one aspect of the present invention, a method of processing an information signal containing content presented in accordance with at least one modality, comprises the steps of: (i) obtaining the information signal; (ii) performing content detection on the information signal to detect whether the information signal includes particular content presented in accordance with the at least one modality; and (iii) generating a control signal, when the particular content is detected, for use in controlling a rendering property of the particular content and/or implementation of a specific action relating to the particular content. Various illustrative embodiments in the context of speech signal processing for use in voicemail and/or cellular phone applications are provided, as well as illustrative embodiments associated with the processing of multi-modal or multimedia information signals. Also, the present invention provides for storing selectively marked information, even in the absence of content detection, such that the information may be rendered and/or used at a later time. The invention also extends to processing of text-based and markup language-based signals, e.g., XML documents.

A method for identifying data is provided that includes receiving a data stream and performing a hashing operation on a portion of the data stream in order to identify a key that reflects an identity associated with the data stream. The method further includes storing a plurality of first and second hash table entries and comparing the key to the first and second hash table entries in order to evaluate if there is a match between the key and the first and second hash table entries.

A method and apparatus for clustering data, particularly regarding an image, that constructs a graph in which each node of the graph represents a pixel of the image, and every two nodes represent neighboring pixels associated by a coupling factor. Block pixels are selected with unselected neighboring pixels coupled with a selected block to form aggregates. The graph is coarsened recursively by performing iterated weighted aggregation to form larger blocks (aggregates) and obtain hierarchical decomposition of the image while forming a pyramid structure over the image. Saliency of segments is detected in the pyramid, and by computing recursively, a degree of attachment of every pixel to each of the blocks in the pyramid. The pyramid is scanned from coarse to fine starting at the level a segment is detected, to lower levels and rebuilding the pyramid before continuing to the next higher level. Relaxation sweeps sharpen the boundaries of a segment.

The invention discloses a track obstacle detection system based on machine vision, and belongs to the field of railway safety. Black and white video images are obtained by an on-board camera installed at the head of a train, and the track is similarly linear or bent is judged according to that whether the camera is over travel. Manual detection of bend states is achieved by fixing a high definition camera and a wireless transmitting device at a bend for receiving wireless images. A similar straightway analyzes the obtained real-time image sequence, and divides forward obstacles into a non-dangerous class (including static small obstacles, moving objects quickly crossing the track) and a dangerous class (static large obstacles, moving obstacles influencing pass of the train) by adopting a track edge extraction algorithm based on hood conversion and Otsu threshold value, combining an inter-frame difference method based on mathematical morphology improvement with a background difference method and adopting an angular point feature matching tracking algorithm. The track obstacle detection system based on machine vision can quickly process track images, more effectively and accurately extract track edges, and is high in detection precision of track obstacles.

The invention discloses a video flame-detecting method based on multi-features fusion, which is characterized in that: a fast Gaussian hybrid model is established and a pixel counter is arranged when a computer reads a first frame image a monitoring site captured by a colored camera; when the computer reads new images of a second frame and the following frames, a fast Gaussian hybrid method is firstly used for carrying out motion detection so as to extract a moving object and then a flame color decision is carried out to the moving object to obtain an alternative flame area; and finally, flicker analysis is carried out on the alternative flame area so as to identify a real flame object. The video flame-detecting method carries out modeling to flame color characteristics, motion characteristics and flickering characteristics in flame areas; various flame detection interfering resources are gradually and rapidly eliminated in accordance with the recognition sequence of motion, color and flickering. The test results show that the method has relatively strong robustness; in addition, based on an AMD 2.04GHz processor, the processing speed can reach 22 frames per second for video images with pixels of 320 multiplied by 240.

The invention provides a joint measurement method based on a laser radar and a binocular visible light camera to obtain accurate and dense three-dimensional information simply and efficiently. The joint measurement method comprises assuming that the laser radar is a camera device with a fixed internal reference; directly projecting three-dimensional point cloud data into a two-dimensional image, calculating rotation and translation relationships between the laser radar device and the binocular camera by using an image processing method and the matching between the two-dimensional images; creatively introducing an idea for obtaining a matrix norm and a matrix trace to solve a rotation matrix; finally fusing laser radar and binocular stereo vision point cloud data. The method not only can obtain an accurate position and attitude information, but also can reconstruct the special texture and feature information of a target surface, which has a high application value for spacecraft dockingand hostile satellite capture in the military field and workpiece measurement and unmanned driving in the civilian field.

A beverage preparation material (1) comprising a substantially insoluble and water-permeable tiller matrix (3) having a beverage ingredient (2) dispersed therein, wherein a plurality of layers, cells, or individual particles (2) of said beverage ingredient are held in a spaced-apart relationship within said material by regions of said tiller matrix (3). Also provided are beverage preparation pods and capsules (5) containing a beverage preparation material according to the invention.

The invention aims to provide a micro-fluidic serum extracting chip. The chip is formed by a blood sample introduction pool, a micro channel, a serum separation chamber and a sample collecting pool, wherein the interior of the serum separation chamber is filled with two kinds of micro balls with different hole diameters. The operating principle of the chip is as follows: the whole blood is added from a sample introduction port, the blood sample flows through the serum separation chamber along the micro channel under the action of surface tension or certain negative pressure, hemocytes are intercepted by a micro ball structure, and the serum flows out from ventages among the micro balls, and finally enters the sample collecting pool. The chip provided by the invention can be used for rapidly extracting the serum on line, the operation is simple and convenient, the separation efficiency is high, and the further integration with other operation units is easy to realize.

A method for fast locating a decipherable pattern in an input image, which is characterized in utilizing an overly downscaled binary image to not only reduce computation time but also facilitate extraction of skeletons for fast and accurately locating pattern, is disclosed. First, a pre-process is applied to an input image to acquire a binary image downscaled n times, from which at least one skeleton corresponding to a decipherable pattern is extracted. Coordinate values of at least one pixel of each skeleton are respectively enlarged n^1/2 times and used as the central points on the original image plane for establishing a plurality of detecting blocks with the identical size. Subsequently, a grading mechanism is employed to determine the corresponding detecting blocks of the decipherable pattern.

The invention discloses a building roof reconstruction method based on airborne LiDAR data. The method comprises the steps of 1, obtaining LiDAR point cloud data, and 2, processing the LiDAR point cloud data; the step 2 comprises the processes of 201, dividing building roof patches to obtain a plurality of roof patches from the building roof, 202, obtaining building roof point cloud data, 203, extracting outer contour points of the building roof and the roof patches, and meanwhile, extracting the outer boundary line of the building roof, 204, obtaining the vector boundaries of the roof patches, including establishing a search information set, carrying out neighborhood search, determining the types of the outer contour points and determining the vector boundaries, and 205, obtaining a vector model of the building roof, namely obtaining the vector model of the building roof after determining the vector boundaries of the plurality of roof patches. The method is simple in steps, reasonable in design and convenient to realize, good in using effect, and capable of completing the reconstruction processes of the building roof simply, conveniently and quickly with high quality.

The invention brings forward a traffic label identification method of vehicle-mounted laser scanning point cloud data. The method comprises the following steps: 1, point cloud real-time preprocessing; 2, point cloud structure feature obtaining; 3, multi-scale Markov random field point cloud clustering; and 4, traffic label identification. The method has the following advantages: "surface-shaped", "linear-shaped" and "scattered" features of point clouds are reinforced, differences between points are enhanced, and while under-segmentation is avoided, reasonable segmentation of the scale of a traffic label component can be rapidly realized; classification and identification of a traffic label can be conveniently realized from point cloud data of deficiency of a part of the traffic label, caused by ground object shielding or ground object self-occlusion; the method can effectively satisfy the requirements for rapid extracting, monitoring and identifying city components at present, can be conveniently promoted to the industry of manned or unmanned navigation and barrier avoiding based on computer vision, helps a driver to perform navigation and decision-making under complex road conditions, and effectively reduces the traffic accident probability.

The invention relates to the field of point cloud processing, and specifically discloses a three-dimensional point cloud road boundary automatic extraction method. The method comprises the steps of S1, screening seed points for the whole acquired three-dimensional point cloud data set P so as to perform super voxel classification; S2, extracting boundary points between adjacent non-coplanar super voxels by using an alpha-shape algorithm; S3, extracting road boundary points by using a graph cut based energy minimization algorithm; S4, removing outliers based on an Euclidean distance clustering algorithm; and S5, fitting the extracted road boundary points into a smooth curve. The method can directly operate on the large-scale three-dimensional point cloud, can be applied to different scenes, is high in calculation speed and good in algorithm robustness, and can extract road boundaries quickly.

The invention discloses a steel rail surface defect image adaptive segmentation method. The method comprises the following steps of S1, extracting a steel rail region by adopting a row grayscale mean successive summation method; S2, preprocessing a steel rail region image; S3, performing structure region and non-structure region division on the steel rail region image; S4, further distinguishing a defective region and a shadow region by utilizing a non-local feature of the image in the structure region; S5, adaptively building a background image model according to different features in the image; S6, performing image difference; and S7, performing dynamic threshold segmentation. The image is divided into the structure region and the non-structure region by utilizing image local information, the size of a pixel neighborhood window is adaptively adjusted by utilizing non-local information to calculate a mean, the accurate background image model is built, and the image difference and the dynamic threshold setting are performed, so that while a defective part of the image is highlighted, the influence of uneven illumination and steel rail surface reflection property on steel rail surface defect detection is effectively reduced, an ideal image segmentation effect is achieved, and the rail surface detection precision is ensured.

A computer system that provides stereoscopic images is described. During operation, the computer system generates the stereoscopic images at a location corresponding to a viewing plane based on data having a discrete spatial resolution, where the stereoscopic images include image parallax. Then, the computer system scales objects depicted in the stereoscopic images so that depth acuity associated with the image parallax is increased, where the scaling is based on the spatial resolution and a viewing geometry associated with a display. For example, the viewing geometry may include a distance from an individual that views the stereoscopic images on the display and the display. Alternatively, the viewing geometry may include a focal point of the individual. Next, the computer system provides the resulting stereoscopic images to the display. In this way, the computer system may optimize the depth acuity for data having discrete sampling.

The present invention relates to a satellite image based coastline automatic extraction and classification method. The method is characterized technically by comprising the following steps: step 1, using a multi-spectral image of a coastal zone after precise registration, and by combining a normalized difference water index (NDWI) and a level set model, obtaining a precise contour of a water boundary line; step 2, performing object-oriented segmentation on a land portion region, and extracting coastline coastal feature basic units by means of a spatial position topological relationship between the basic units; step 3, based on a decision tree, performing determination and classification on each coastline coastal feature basic unit; step 4, determining a coastline position according to a coastline interpretation rule; and step 5, on the basis of a result of the coastline position based on the multi-spectral image in the step 4 and property information, outputting a coastline vector based on a high-resolution panchromatic image. According to the method provided by the present invention, the coastline position can be rapidly, accurately and comprehensively surveyed and the change of the coastline position can be dynamically monitored.

The invention discloses a magnetic tile surface defect detection method based on an improved machine vision attention mechanism. The magnetic tile surface defect detection method comprises the following steps: I, inputting a magnetic tile image, and enhancing the overall gray contrast ratio of the image by using a method of combination of morphological top cap and bottom cap conversion; II, uniformly dividing the obtained image into a*b image blocks, and distinguishing defect image blocks and non-defect image blocks according to gray characteristic quantities of the divided image blocks; III, calculating the conspicuousness of an obtained image block by using an improved Itti vision attention mechanism model, and selecting a primary characteristic so as to form a comprehensive saliency map; and IV, thresholding the comprehensive saliency map by using an Ostu threshold method, and extracting a defect area. By virtue of morphological processing, image blocking and vision attention mechanism ideas, problems that the brightness is not uniform, the magnetic tile defect area is relatively small, a magnetic tile has texture interference and the like can be effectively overcome, various magnetic tile defects can be rapidly and effectively extracted, and thus the magnetic tile surface defect detection method is very good in adaptability.

An information processing device and method enable swift extraction of a user's preference. The relevant item evaluation value of the preference is increased based on characteristic information about a moving image content whose replay has been directed, based on characteristic information about a still image content whose replay has been directed, based on characteristic information about a sound content whose replay has been directed, based on information about an executed game content, and based on information about a used network content. The relevant item evaluation value of the preference is decreased based on characteristic information about a deleted content. The invention is applicable to video recorders.