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1547 results about "Random noise" patented technology

System and method for 3D imaging using structured light illumination

InactiveUS8224064B1Acquisition speed is fastMore robust to extremely worn ridges of the fingersImage enhancementImage analysisRandom noiseComputer science
A biometrics system captures and processes a handprint image using a structured light illumination to create a 2D representation equivalent of a rolled inked handprint. The biometrics system includes an enclosure with a scan volume for placement of the hand. A reference plane with a backdrop pattern forms one side of the scan volume. The backdrop pattern is preferably a random noise pattern and the coordinates of the backdrop pattern are predetermined at system provisioning. The biometrics system further includes at least one projection unit for projecting a structured light pattern onto a hand positioned in the scan volume on or in front of the backdrop pattern and at least two cameras for capturing a plurality of images of the hand, wherein each of the plurality of images includes at least a portion of the hand and the backdrop pattern. A processing unit calculates 3D coordinates of the hand from the plurality of images using the predetermined coordinates of the backdrop pattern to align the plurality of images and mapping the 3D coordinates to a 2D flat surface to create a 2D representation equivalent of a rolled inked handprint. The processing unit can also adjust calibration parameters for each hand scan from calculating coordinates of the portion of backdrop pattern in the at least one image and comparing with the predetermined coordinates of the backdrop pattern.
Owner:UNIV OF KENTUCKY RES FOUND

Novel Karaoke and Multi-Channel Data Recording / Transmission Techniques via Wavefront Multiplexing and Demultiplexing

An advanced channel storage and retrieving system is achieved that is capable of simultaneously transporting multiple-stream data concurrently, with encryptions and error detection and limited correction capability using wavefront (WF) multiplexing (muxing) at the pre-processing and WF demultiplexing (de-muxing) in the post-processing. The WF muxing and demuxing processing can be applied for multiple signal streams with similar contents and format such as cable TV delivery systems or multiple signal streams with very distinct contents and format such as Karaoke multimedia systems. The stored or transported data are preprocessed by a WF muxing processor and are in the formats of multiple sub-channels. Signals in each sub-channel are results of unique linear combination of all the input signals streams. Conversely, an input signal stream is replicated and appears on all the sub-channels. Furthermore the replicated streams in various sub-channels are “linked” together by a unique phase weighting vector, which is called “wavefront” or WF. Various input signal streams will feature different WFs among their replicated signal streams in the sub-channels. The WF muxing processing is capable to generating a set of orthogonal WFs, and the WF demuxing processing is capable of reconstituting the input signal streams based on the retrieved sub-channel data only if the orthogonal characteristics of a set of WFs are preserved. Without the orthogonality among the WF, the signals in sub-channels are mixed and become effectively pseudo random noise. Therefore, an electronic locking mechanism in the preprocessing is implemented to make the WFs un-orthogonal among one another. Similarly, an electronic un-locking mechanism in the post-processing is implemented to restore the orthogonal characteristics among various WFs embedded in the sub-channel signals. Some of the phenomena due to the selected locking mechanisms are reproducible in nature, such as wave propagating effects, and other are distinctively man-made; such as switching sub-channel sequences. There are other conventional encryption techniques using public and private keys which can be applied in conjunction with the WF muxing and de-muxing processor, converting plain data streams into ciphered data streams which can be decoded back into the original plain data streams. An encryption algorithm along with a key is used in the encryption and decryption of data. As to the optional parallel to serial and serial to parallel conversions in the pre and post processing, respectively, we assume that transmissions with single carrier are more efficient than those with multiple carriers. We also assume single channel recording is more cost effective than multiple channel recording. However, there are occasions that continuous spectrum is hard to come-by. We may use fragmented spectrum for transmissions. There are techniques to convert wideband waveforms using continuous spectra into multiple fragmented sub-channels distributed on non-continuous frequency slots. Under these conditions we may replace the parallel to serial conversion processing by a frequency mapping processor.
Owner:SPATIAL DIGITAL SYST

Image classification method based on confrontation network generated through feature recalibration

The invention discloses an image classification method based on a confrontation network generated through feature recalibration. The image classification method based on the confrontation network generated through feature recalibration is suitable for the field of machine learning and comprises the steps that to-be-classified image data are input into a confrontation network model for network training; a generator and a discriminator which are constituted by a convolutional network are constructed; random noise is initialized and input into the generator; the random noise is subjected to multilevel deconvolution operation in the generator through the convolutional network, and finally, generated samples are obtained; the generated samples and authentic samples are input into the discriminator; and the input samples are subjected to convolution and pooling operation in the discriminator through the convolutional network, thus a feature graph is obtained, a compressed and activated SENetmodule is imported into an intermediate layer of the convolutional network to calibrate the feature graph, thus the calibrated feature graph is obtained, global average pooling is used, and finally,image data classification is output. The SENet module is imported into the intermediate layer of the discriminator, the importance degree of each feature channel is automatically learned, useful features relevant to a task are extracted, features irrelevant to the task are restrained, and thus semi-supervised learning performance is improved.
Owner:JIANGSU YUNYI ELECTRIC

Temperature compensation method for denoising fiber-optic gyroscope on basis of time series analysis

A temperature compensation method for denoising a fiber-optic gyroscope on the basis of time series analysis comprises four steps of: step 1, designing an experimental scheme, performing fixed point low and high temperature testing experiment on the fiber-optic gyroscope, and utilizing acquisition software for data acquisition; step 2, performing time series analysis on the zero offset data of the gyroscope, and establishing the mathematical model of the random error of the fiber-optic gyroscope; step 3, adopting a kalman filtering algorithm to filter random noise in the zero offset data of the fiber-optic gyroscope; and step 4, utilizing the data which is de-noised by the kalman filtering to identify the model structure of the temperature shift error of the fiber-optic gyroscope, and calculating the parameters of the identified model. The method establishes the multinomial model of the static temperature shift error of the fiber-optic gyroscope through time series analysis, kalman filtering denoising treatment and identification of the temperature shift error model structure and parameters. The method completely meets the real-time compensation requirement on the project, and has a better practicable value and a wide application prospect in the technical field of aerospace navigation.
Owner:BEIHANG UNIV

High-sensitivity satellite navigation signal capturing method and system

The invention discloses a high-sensitivity satellite navigation signal capturing method and a system. The system comprises a digital down-conversion module, an average sampling and block accumulation module, an FFT (fast Fourier transform) module, a circumference shifting module, a local PRN (pseudo random noise) code FFT conjugate memory, a complex multiplier module, an IFFT (inverse fast Fourier transform) module, a differential coherence integration module, a peak detection module and a sequential control module. The digital down-conversion module realizes digital down-conversion operation for satellite digital intermediate frequency signals; the average sampling and block accumulation module averagely samples satellite data and completes a block accumulation function; the FFT module searches code phase frequency domains; the circumference shifting module utilizes Doppler circumference shifting search to replace frequency compensation; the local PRN code FFT conjugate memory stores a local PRN code FFT conjugate result; the complex multiplier module realizes signal de-spreading; the IFFT module calculates different code phase coherence results; the differential coherence integration module accumulates differential coherence energy of de-spread satellite signals; the peak detection module realizes signal capturing output; and the sequential control module controls timing sequence of the various modules of the system. Weak signal capturing speed and sensitivity of a satellite navigation receiver are improved, and parameters can be configured flexibly.
Owner:JINAN UNIVERSITY
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