1087results about How to "Real-time processing" patented technology

The present invention provides a video encoding device in which a capacity of a binary data storing unit is small, a size of the video encoding device is small, a video signal can be processed in real time, and reduction in quality of images generated from the eventually obtained data can be prevented. The video encoding device according to the present invention includes: a video encoding unit which encodes a video signal; a binarization unit which binarizes an encoded value obtained from the video encoding unit; and an entropy encoding unit which subjects entropy encoding to binary data obtained from the binarization unit. Here, the video encoding unit encodes the video signal based on a characteristic of the binarization performed by the binarization unit, so that an amount of binary data obtained from the binarization unit by binarizing the encoded value that is encoded based on the characteristic is less than an amount of binary data obtained by binarizing an encoded value that is encoded without being based on the characteristic.

The invention discloses a data processing and transmitting system of high-speed multichannel CCD (charge-coupled device), which comprises a CCD analog front end, a data processing unit, a high-speed serial transmission unit and a high-speed image data collection system which are sequentially connected. The CCD analog front end is used for converting an analog signal output by a CCD detector and subjected to sampling and pulse control into n channels of digital image data via n A / D (analog / digital) converters, transmitting the digital image data to the data processing unit, and acquiring data of each channel at the same time. The data processing unit is used for transmitting single-channel high-speed data streams, a data transmitter clock and a horizontal synchronizing signal acquired from integration of the digital image data to the high-speed serial transmission unit. The high-speed serial transmission unit is used for converting single-channel high-speed data streams via LVDS (low-voltage differential signaling) serial chips into high-speed LVDS data streams for transmitting. The high-speed image data collection system is used for collecting the high-speed serial LVDS data streams and realizing real-time storing and displaying of the image data.

The invention provides a measuring device and method for the target line-of-sight angel offset and distance. The device is composed of a four-quadrant avalanche photodetector, a receiving and sending optical unit, a noise compensation circuit, a four-circuit front amplification circuit, a video amplification circuit, an automatic gain amplification circuit, a peak keeping circuit, an AD conversion circuit, a laser, a dominant wave sampling circuit, a summing circuit, a time identifying circuit, a time test circuit and a digital processing circuit, wherein the receiving and sending optical unit enables narrow pulse laser rays emitted by the laser to be converged on the photoelectric detector to form echo light spots after target reflection, photovoltaic conversion of the four-quadrant avalanche photodetector, front amplification, video amplification and automatic gain amplification are conducted, narrow-pulse peak keeping is conducted, transmission of the AD conversion circuit is conducted, and the digital processing circuit extracts the digital line-of-sight angel offset; summing is conducted on the four-circuit front amplification circuit, the dominant wave sampling circuit is combined, the time identifying circuit determines laser emitting and echo coming and returning time, the time is transmitted to the time identifying circuit to be measured, and the digital processing circuit decodes the corresponding distance.

The invention discloses a target tracking method and a related device. The target tracking method and the related device are used for achieving real-time tracking and processing of a target. The target tracking method comprises the steps of according to a position of the target in a video monitoring image of a previous frame, using a motion predicting model built for the target for predicting positions of the target in a video monitoring image of a current frame, obtaining predicted positions of the target, conducting target detecting in an image area where the predicted positions are distributed according to a detecting model built for the target, obtaining detected positions of the target, conducting target tracking in the image area where the predicted positions are distributed according to a tracking model built for the target, obtaining tracked positions of the target, conducting weight fusion on the detected positions and the tracked positions according to an image position overlapping ratio, obtaining the tracked positions of the target in the video monitoring image of the current frame, adjusting an intelligent video monitoring device according to the tracked positions of the target in the video monitoring image of the current frame, and achieving tracking of the target.

The present invention discloses a data protection transmission method for peer-to-peer network. The method has an encryption server arranged in a peer-to-peer network, and comprises following the steps that: A. a data publication party sends data needing to be published to the encryption server; B. the encryption server encrypts the data needing to be published, saves a corresponding key and returns the encrypted data to the data publication party; C. the data publication party publishes the encrypted data in different pieces; D. a data request client collects the published encrypted data pieces through the peer-to-peer network; the data request client acquires the corresponding key from the encryption server and decrypts the collected encrypted data pieces according to the key. The present invention can be applicable to the characteristics of the peer-to-peer network, improve the data transmission security of the peer-to-peer network, prevent hackers from attacking the peer-to-peer network data and guarantee the rights and benefits of data owners and users.

An adaptive capacitive touch sense control circuit includes a voltage buffer, a current setting resistor, a current mirror, a capacitor, a start comparator, an end comparator and a time-to-digital converter. The capacitor is connected with the current setting resistor. The circuit further includes a latch with a first control switch and a second control switch. The current setting resistor is switched between the ground and a voltage source through a switching element, so that when the current setting resistor is grounded, the first control switch is closed and the second control switch is opened, and when the current setting resistor is connected with the voltage source, the second control switch is closed and the first control switch is opened. An adaptive charging mode is adopted to sense a capacitance variation with a great ability of interference recognition, a simple structure, low power consumption and real time processing.

The invention relates to a road network grid matching method, which comprises: obtaining GPS original point data and de-noising the GPS original point data to gain GPS point data; partitioning the road network into grids according to the GIS road network structure information to get road network grid units; and matching the GPS point data to the corresponding road network grid units to obtain grid matching data. The invention also relates to an information acquisition method for real-time road conditions, which comprises: matching road network grids to get grid matching data; integrating the grid matching data with GPS traffic flow data; and filtering the integrated data according to types of driving routes to obtain the information of real-time road conditions. The invention provides theroad network grid matching method based on the GPS road network grid partitioning technique aiming at large concurrent GPS data for achieving real-time treatment of the large concurrent GPS data; andacquires information of real-time road conditions and real-time guiding routes by using the road network grid matching method.

The invention discloses an infrared image-based weak and small moving target detecting method. The method disclosed by the invention comprises the steps of median background difference image generation, accumulated difference image generation, difference image segmentation, periodical motion area elimination and false target elimination. Concretely, the method comprises: establishing a grayscale histogram for each pixel to count the frequency of the appearance of the pixel on each grayscale in the latest time period, calculating a median to obtain median background, and calculating the absolute frame difference between the median background and a detected frame to obtain a median background difference image; calculating the frame difference between each two adjacent frames continuously, and accumulatively adding difference images to obtain an accumulated difference image; eliminating interference from periodical motion areas, and highlighting a real moving target; and finding a reasonable target track by using motion and grayscale consistency of the target. The method disclosed by the invention can accurately and continuously detect the weak and small moving target day and night at a remote distance, has high real-time performance and high robustness, and is easy to promote in application field of military robot battle reconnaissance, video monitoring and the like.

The invention relates to a system for realizing image high dynamic range compression. The system comprises a primary image input unit, an exposure area calculation unit, a comparison unit, a correction unit, and a compressed image output unit. The invention also relates to a method for realizing the image high dynamic range compression. By adopting the system and the method for realizing the image high dynamic range compression, the problems of damage to a normal exposure area, Halo existing at the edge and over loss of image contrast in the method are effectively solved; the contrast of the normal exposure area is reserved, at the same time, the visibility of the under exposure area and the exposure area is improved; the system and method not only are directly applied in an overall high dynamic compression method, but also can be applied in the brightness (lighting layer) compression in a partial high dynamic compression manner; and besides, the complexity of the operation in the invention is extremely low, so that real time process is facilitated, the process is quick and efficient, the working performance is stable and reliable, and the scope of the application is broad.

The invention discloses a constructing method of an airborne radar space-time two-dimensional filter based on clutter covariance matrix reconstruction, which belongs to the technical field of radar signal processing and mainly solves the problems that the existing filtering technique has high requirement on data training samples, large operand for filtering clutter and poor real-time application performance. The constructing method comprises the following implementation steps of: firstly, constructing clutter covariance matrix according to the movement velocity and working parameters of the radar; next, realizing random clutter covariance matrix reconstruction by changing space-time relevant functions and adjusting clutter bandwidth; then, designing a group of filters with different notch widths based on a Wiener filtering principle; and finally, conducting nonlinear selection to filter coefficients according to a minimum residual energy criterion so as to obtain the optimal airborne radar space-time two-dimensional filter. Simulation analysis and measured data indicate that the constructing method has better clutter inhibition performance and moving-target detection performance when processing heterogeneous clutter environmental data compared with the small degree of freedom dimension-reducing self-adaptive method.

The invention provides a pipeline FFT processor variable in the number of points, which comprises a first 1024-point variable FFT processing module, a twiddle-factor processing module, a second 1024-point variable FFT processing module and a selection-control module, wherein the four modules and an intermediate data storage module outside the processor jointly complete FFT two-dimensional processing large in the number of points; each 1024-point variable FFT processing module comprises a first 32-point variable FFT processing sub-module, a second 32-point variable FFT processing sub-module, a twiddle-factor processing sub-module, an intermediate data storage sub-module and a selection-control sub-module; variable-point FFT operation is implemented through the 32-point variable FFT processing sub-modules; the twiddle-factor processing module generates and multiplies intermediate twiddle factors by the result of FFT operation; and the selection-control module realizes control over a whole chip. The processor is suitable to be realized in single-chip FPGA or ASIC, and can simultaneously obtain high speed, low power consumption, high precision and other characteristics.

The invention presents a new quick searching method for mass images, which comprises the following steps: 1, transforming images of red, green and blue (RGB) colored spaces to a hue, saturation and value (HSV) colored space; 2, extracting HSV color histogram information of every small block respectively by blocking the image spaces; 3, obtaining the index characteristics of the images by using a hashing algorithm; and 4, searching the returned similar image sets by using the hashing index characteristics; blocking the color histogram characteristics by using an original HSV colored space; rearranging the similar image sets returned by the index characteristics generated on the basis of hashing by adopting a street distance as the function of a similarity measurement between the images. The test shows that the algorithm provided in the invention can exactly process millions of image data in real time in comparison to the algorithm in the past; the method can be used in the search of the content-based images on internet, on-line electronic shopping website, and other scenes.

The invention discloses a human body pose estimation method. The human body pose estimation method is suitable for marking human body key points in the video to be processed so as to extract the humanbody pose information, and is suitable for application in a mobile terminal. The human body pose estimation method includes the steps: acquiring the video to be processed, and determining whether thekey point position of the previous image frame of the current image frame exists; if the key point position of the previous image frame does not exist, detecting the human body position in the current image frame, and generating a target frame containing the human body position; if the key point position of the previous image frame exists, according to the human body key point position marked inthe previous image frame, generating a target frame corresponding to the current image frame; performing scale transformation on the generated target frame to generate a human body image with the preset size; inputting the human body image with the preset size into a preset pose estimation model so as to output the image on which the human body key point position is marked; and according to the marked key point position, estimating the human body pose. The invention also discloses a corresponding mobile terminal.

The invention discloses a method for electrically forecasting a danger in underground tunneling engineering, which comprises: building an approximately even current field in the direction of a tunnel or a laneway by burying long-distance fixed-source first and second power supply electrodes underground in the direction of the tunnel and the laneway; measuring and recording current field change under the background of the approximately even current field by using a measuring electrode buried in tunnel heading face of the laneway and a measuring electrode arranged in or outside the tunnel; and predicating and forecasting a danger around the tunnel heading face according to a law for the change of the electric field. The method has the advantages that: an electrical instrument can be placed in ground station for observation; intra-laneway power supply is avoided; the arrangement of the electrodes is convenient; and the early warning and forecasting cost is low. The method can be widely used in the field of projections involving laneway or tunnel construction, such as coal mine, mine production, communication, water conservancy and hydropower and subway projections.

The invention discloses a high precision direction measurement method for linear arrays, comprising: forming frequency domain traditional wave beam for the two-dimensional space-time signals received by a linear array; scanning in the wave beam domain to obtain a target angle measured roughly; dividing the linear array into a plurality of sub arrays; in the target angle range measured roughly, processing frequency domain traditional wave beam formation and focusing on the space-time two dimension signals received by each sub array to form frequency domain-wave number data; in the target angle range measured roughly, processing the frequency domain-wave number data according to a wideband focusing minimum variance distortion-less method, to obtain the direction of target signal. The invention has high calculation speed, can realize real-time processing, has high algorithm robustness, and has high target detection precision.

The invention discloses a stream preprocessing system and method based on mass information of a mobile internet, and belongs to the field of big data. The system comprises the mobile internet (000), an interface machine (100), a Kafka cluster (200), a Spark cluster (300) and a Hadoop cluster (400) which are communicated in sequence. The method mainly comprises the steps that a control module is connected with the Kafka cluster through a Zookeeper and reads data cached in the Kafka cluster; and a preprocessing module processes the data according to a specified processing process and finally writes the data into an HBase. According to the preprocessing system and method, the deficiency that MapReduce does not support stream data processing is made up for; the processing speed is high and the fault tolerance is achieved; by integrating three technologies of a distributed message system, a distributed stream processing framework and a hadoop distributed file system in the field of big data, a reference is provided for modular integration of other big data technologies; and all the mass information of the mobile internet can be processed in real time and technical support can be provided for real-time services of operators.

The invention is a fire monitoring method and device based on all- direction computer vision, mainly making field monitoring by all-direction computer vision sensor, inputting the taken continuous all-direction image into the computer for continuous image processing and analysis, and obtaining a synthetic result by simple fire mode classification, flame area change characteristic judgment, flame shape change characteristic judgment, flame color characteristic judgment, flame flickering rule characteristic judgment, whole flame motion characteristic judgment and fire intensity characteristic judgment, making different processings according to the calculation and synthetic judgment quantized values to reduce false alarm rate of fire. And the invention provides a truly original, quicker, accurater, more reliable multiparameter intelligent fire monitoring method and device.

The invention discloses a microwave photon MIMO radar detection method comprising modulating M intermediate-frequency linear frequency-modulated signals with the same bandwidth and chirp rate and non-overlapped frequency on M optical carriers with different wavelengths to generate M optical signals where only the positive and negative second-order sidebands are retained; merging the M optical signals by an optical wavelength division multiplexer and then dividing a combined optical signal into two channels; dividing the optical signal in one channel into N reference light beams; subjecting theoptical signal in the other channel to photoelectric conversion and separating and transmitting M orthogonal linear frequency-modulated signals therein; receiving, by N receiving antennas, the targetreflected signals, performing de-chirp processing and wavelength demultiplexing, and subjecting the obtained M optical signals to photoelectric conversion, low-pass filtering and analog-to-digital conversion to obtain M*N digital signals, processing the digital signals to obtain a target detection result. The invention also discloses a microwave photon MIMO radar system. The method can greatly improve the range resolution and azimuth resolution of the radar system.

The present invention discloses a hierarchical monitoring video clearness system and method of image quality evaluation and weather status guidance, and belongs to the video processing and analysis technology field. The system of the present invention comprises a video acquisition module, a video conversion module, a video image processing module and a display module. The video acquisition module and the video conversion module acquire the images and convert the images into the digital image frames, and the video image processing module synthesizes the weather condition and the image quality evaluation to determine the image defogging grades, and adopts the corresponding algorithms to defog aiming at the images of different grades. The system of the present invention is simple and intelligent in structure, is easy to realize, and has wide application value in the fields, such as the outdoor video monitoring, etc., and the method of the present invention enables the monitoring video online clearness processing efficiency and quality to be improved greatly, at the same time, can effectively avoid the limit that one defogging algorithm can not satisfy the degradation of the videos of different types.

The present invention relates to a computer-aided geological survey system based on portable machine. It adopts the multiple S integration technique including GIS, GPS, DBS, RS, CADS, ES and ANNS systems and method oriented towards object to make design and development. The data collected by said system are fed into unified space data base and attribute data base, and the data base technique can be used to make effective connection and information extraction. The system includes front-stage material collecting and reduction, wild data acquisition and indoor data comprehensive reduction three subsystem platforms.

The invention belongs to the technical field of target track generation, particularly relates to an outer transmitter-based radar target track processing method based on clustering. The outer transmitter-based radar target track processing method based on clustering includes the steps of firstly, receiving the signal of each transmitter through a receiving antenna, and conducting channel balancing and down-conversion on the signal of each transmitter to obtain original data; secondly, sequentially conducting clutter cancellation, distance-Doppler operation, constant false alarm rate detection and amplitude comparison angle measurement on the original data so as to obtain front end processed data; thirdly, generating the tracks of all targets through a clustering method according to the front end processed data.

The invention provides a signal processing method and device for frequency-agile radar based on a variable repetition frequency technology. The method includes the following steps: designing a frequency point sequence of random hopping according to a random number and the carrier frequency related parameters of radar, and designing a pulse time interval sequence according to the frequency point sequence and the distance range of a target to be detected; emitting a radar pulse signal according to the designed frequency point sequence and the designed pulse time interval sequence, receiving an echo signal of the radar pulse signal, and sampling and preprocessing the echo signal to obtain a baseband echo sampling signal; processing the baseband echo sampling signal by a single pulse to obtaina time-domain echo signal after pulse compression; and coherently accumulating the time-domain echo signal after pulse compression in the two dimensions of frequency point and pulse number, and obtaining the fine resolution distance and Doppler velocity values of the target to be detected through threshold decision. Accurate detection of the distance and velocity of a moving target by coherent frequency-agile radar is realized, and the amount of computation for the processing of coherent frequency-agile signals can be reduced.

The invention provides an intelligent field unmanned plane search and rescue method and system based on double source video analysis. The intelligent field unmanned plane search and rescue method based on double source video analysis includes the steps: utilizing an infrared image to extract the candidate target and the region-of-interest ROI; using an improved deep convolutional neural network target detection framework Single-shot Multi-box Detector to perform optical target detection on the target region so as to locate the personnel to be searched and rescued; after locating the personnelto be searched and rescued, accurately delivering first aid materials; during the flying process, using LiDAR to perform autonomous obstacle avoidance; and based on detection of AprilTag, performing accurate autonomous landing. Mutual assistance between infrared and optical video analysis can effectively overcome the illumination factor, the shielding factor and other factors, so that the intelligent field unmanned plane search and rescue method and system based on double source video analysis can work all time so as to guarantee the search and rescue efficiency.

The invention relates to a method for detecting and positioning a text area in a video. The method is characterized by comprising the following steps of: inputting the video, and sampling the input video at equal time intervals; carrying out edge detection on an image obtained by sampling; generating a text confidence map by utilizing the image obtained by detection; extracting a text candidate area according to the generated text confidence map; fusing the text candidate areas of approximately same multiple frames of images in the text candidate area; and analyzing the images of in the text area after fusing. With the adoption of the method, multi-language texts appearing in the video can be accurately positioned in real time. The method is applicable to various functions such as video content editing, indexing and retriving and the like.

The invention discloses a real-time binary image connected domain mark realizing method based on FPGA, which belongs to the large scale integrated circuit design, object identification and visual measurement technical field. The invention aims to achieve real-time connected domain marking of large scale moving objects on the basis of field programmable gate array devices in a hardware way. Four symmetrical processing nodes are used. A newest serial exchange architecture (VPX architecture) is adopted. Each processing node comprises XC5VX95TI-2FPGA of the XILINX corporation and a DDR memory cell of a 16G-bit storage capacity. The nodes are interconnected through 16 pairs of 2.5GHz RocketIO. Each processing node is composed of a first-time scanning unit, a main controller module, a correlation memory group, a common scanning unit, a DDR access arbitration module, a DDR controller, and a framing and data output module. Real-time marking of large scale moving objects is achieved through superscalar streamline and dynamic delay streamline technologies. Adaption to various resolutions is further realized. The performance is not affected when the moving object shape and number are changed. Strong robustness is achieved. The calculation result is completely consistent with the MATLAB bwlabel function.

The invention is applicable to storage systems like supercomputing centers or cloud computing centers which need to meet the requirements of applying variety, elastic distribution, horizontal expansion and so on under the environment of cloud storage, and provides a distributed file system supporting mixed cloud storage application and a realization method. The system comprises a plurality of cloud storage systems of various types, standard access interfaces for providing various cloud storage systems, a client module for forwarding requests from application programming interfaces and realizing establishment and maintenance of rear-end cloud storage systems, a distributed uniformity cache module for caching cloud storage system information of various types, and a cloud storage system agent module for establishing and managing the cloud storage systems of various types through commands of packaging the cloud storage systems or tools. The client module and the cloud storage systems of various types are respectively connected with the cloud storage system agent module.

The invention discloses a local path planning algorithm for an unmanned vehicle. The algorithm comprises the following steps: inputting parameters required by local path planning; selecting a previewpoint; performing trajectory planning based on the road coordinate system to generate a basic trajectory; matching the basic track with a road shape to generate an alternative track; calculating a speed limit value based on the alternative track and a corresponding speed limit position; optimizing the alternative trajectories to obtain trajectories executed by the unmanned vehicle, called optimaltrajectories; and planning the speed of the unmanned vehicle based on the optimal trajectory. According to the local path planning algorithm, the planning failure in a complex road is avoided, the local path planning in the complex environment is simplified, and the driving behavior is close to the driving behavior of people. The algorithm can effectively process the influence of static obstacles,dynamic objects, traffic signal lamps, various traffic facilities of a speed limit belt and the like on the unmanned vehicle in real time in a complex urban road environment.

An illuminating apparatus is provided with an image sensor (11), a calculating section (12), a control section (13) and a light source section (14). The light source section (14) can output at least red, green and blue lights. The image sensor (11) photographs an object illuminated by the light source section. The calculating section (12) calculates color components distributed over the object, based on the photographed image. The control section (13) controls the color light of the light source section in accordance with the color components which are distributed over the object and are obtained by the calculating section.

The present invention discloses a real-time star point centroid location method based on FPGA. The method comprises the following steps: calculating threshold of the current scanned and input star image pixels; performing threshold segmentation of M channel data formed by the pixels; outputting the M-channel results through threshold segmentation to an M*M template; performing the determination of the star point centroid of the pixels through adoption the template; determining whether the sum of the pixel gray level of the row where the centre pixel in the template is located is the maximum of the sum of each row of gray level pixels or not, determining whether the sum of the pixel gray level of the column where the centre pixel in the template is located is the maximum of the sum of each column of gray level pixels or not, and determining whether the position where the star point centroid is roughly located is the coordinate position where the centre pixel is located or not; performing centroid calculation of the pixels in the template of the star point; finely locating the coordinate position of the star point centroid; and finally, outputting the centroid features and the coordinate buffer memory. The real-time star point centroid location method based on FPGA fully employs the characteristic of hardware running parallelism to realize direct determination and extraction of star points, and the hardware design adopts pipeline architecture to realize pixel processing in real time, therefore the consumption of storage resources is small, and the centroid location is rapid and accurate.

The invention belongs to the technical field of image enhancement and in particular relates to a method, a device and a system for image enhancement based on a YCbCr color space. The method comprises the steps of extracting the luminance component Y in an original image according to the input original image, performing median filtering on the obtained luminance component Y and then performing normalization processing to obtain a normalized image Ym, calculating the average value avgYm of the normalized image according to Ym and judging the measure of the fog concentration of the original image according to the range of avgYm, performing MSR processing and DCP processing on the original image to obtain corresponding processed images Y1 and Y2, putting Y1 and Y2 into a formula X=aY1+bY2 to calculate an image X after fusion processing, and performing automatic contrast control optimization on the image X after the fusion processing to obtain an optimized image, wherein a and b in the formula are fusion coefficients. The method for the image enhancement based on the YCbCr color space is capable of effectively eliminating the halo and over-enhancement phenomena, and therefore, the stability and quality of the output image can be improved.