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检索条件"主题词=Detection and tracking algorithms"

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Missile signal processing common computer architecture for rapid technology upgrade

Missile signal processing common computer architecture for r...

引用

Conference on Advanced Signal Processing algorithms, Architectures, and Implementations XIV

作者： Rabinkin, D Rutledge, E Monticciolo, P MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819454974

Interceptor missiles process IR images captured by a focal plane array for locating and guiding the interceptor toward an intended target. A typical interceptor signal processing chain comprises two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. Signal processing requirements increased as sensor bandwidth increases and interceptors operate against more sophisticated targets. In the past, video processing was implemented using ASICs or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs. DSPs and general-purpose processors. The resulting systems tended to be very function-specific, and required custom software development. These systems were developed using non-integrated toolsets, and test equipment had to be developed along with the processor platform. The lifespan of the interceptor platform on which the signal processors operate often spans decades, while the specialized nature of processsor hardware and software makes it difficult and costly to upgrade. As a result., the signal processing systems often run on outdated components, signal processing algorithms are difficult to update. and system effectiveness is impaired by the inability to rapidly, respond to new threats. A new design approach to interceptor signal processing is made possible by three developments: Moore's Law - driven improvement in computational throughput;a newly introduced vector computing capability in general-purpose processors and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms hav

关键词： Signal processing Digital signal processing Target detection detection and tracking algorithms Image processing Standards development MATLAB Commercial off the shelf technology Signal to noise ratio Software development

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Moving Target detection for a Multi-Band Pushbroom Sensor

Moving Target Detection for a Multi-Band Pushbroom Sensor

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Conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII

作者： Cheng, Beato T. Goodrich ISR Syst Chelmsford MA 01824 USA

ISBN: (纸本)9780819481320

A pushbroom MSI sensor collects image data from the ground, parallel to the flight path, at a specific point angle. Images taken at two instances of time while the scanner moves with the platform usually have a spatial offset, and need to be registered before they can be compared for any changes between the two images. Moving target detection is a special case of change detection that requires the time between frames be small enough that a moving vehicle remains in close proximity on the two frames. We propose an algorithm for the detection of moving targets in a multi-band line scanning pushbroom sensor. Ideally, change detection works best when images have the same spectral bandwidth and are perfectly registered to one another, since differencing the two images automatically removes most of the common background signal. However, this is not always the case. For example, the sensor considered here has different bandwidths for its component bands, and since it is a line-scanner it is much more challenging regarding image registration than a framed-based scanner. In this study, we will use simulated data of the same bandwidth to demonstrate the fundamental algorithm of detection and velocity calculation. The velocity calculation is that of distance divided by time;but, depending on the focal plane layout and other operating considerations and conversion between image space to physical units, this calculation is not as simple as it seems. We will also discuss our effort in applying our algorithm to real line-scan imagery, of different bandwidths in the two channels. We will show the extra image processing efforts needed to make it work, and show some of the test results.

关键词： Image segmentation Sensors detection and tracking algorithms Target detection Image processing Image quality Raster graphics Image registration Image processing algorithms and systems Image sensors

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Consistent estimation of shape parameters in statistical shape model by symmetric EM algorithm

Consistent estimation of shape parameters in statistical sha...

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Conference on Medical Imaging - Image Processing

作者： Shen, Kaikai Bourgeat, Pierrick Fripp, Jurgen Meriaudeau, Fabrice Salvado, Olivier CSIRO ICT Ctr Australian E Hlth Res Ctr Herston Qld Australia Univ Bourgogne CNRS LE2I UMR 5158 F-21004 Dijon France

ISBN: (纸本)9780819489630

In order to fit an unseen surface using statistical shape model (SSM), a correspondence between the unseen surface and the model needs to be established, before the shape parameters can be estimated based on this correspondence. The correspondence and parameter estimation problem can be modeled probabilistically by a Gaussian mixture model (GMM), and solved by expectation-maximization iterative closest points (EM-ICP) algorithm. In this paper, we propose to exploit the linearity of the principal component analysis (PCA) based SSM, and estimate the parameters for the unseen shape surface under the EM-ICP framework. The symmetric data terms are devised to enforce the mutual consistency between the model reconstruction and the shape surface. The a priori shape information encoded in the SSM is also included as regularization. The estimation method is applied to the shape modeling of the hippocampus using a hippocampal SSM.

关键词： Expectation maximization algorithms Statistical modeling Data modeling Principal component analysis Error analysis Statistical analysis detection and tracking algorithms Reconstruction algorithms Algorithm development Shape analysis

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Fast dual graph based hotspot detection

Fast dual graph based hotspot detection

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26th Annual BACUS Symposium on Photomask Technology

作者： Kahng, Andrew B. Park, Chul-Hong Xu, Xu Univ Calif San Diego ECE Dept La Jolla CA 92093 USA

ISBN: (纸本)9780819464446

As advanced technologies in wafer manufacturing push patterning processes toward lower-k(1) subwavelength printing, lithography for mass production potentially suffers from decreased patterning fidelity. This results in generation of many hotspots, which are actual device patterns with relatively large CD and image errors with respect to on-wafer targets. Hotspots can be formed under a variety of conditions such as the original design being unfriendly to the RET that is applied, unanticipated pattern combinations in rule-based OPC, or inaccuracies in model-based OPC. When these hotspots fall on locations that are critical to the electrical performance of a device, device performance and parametric yield can be significantly degraded. Previous rule-based hotspot detection methods suffer from long runtimes for complicated patterns. Also, the model generation process that captures process variation within simulation-based approaches brings significant overheads in terms of validation, measurement and parameter calibration.

关键词： Critical dimension metrology Lithography Edge detection Optical proximity correction detection and tracking algorithms Optical lithography Metals Process modeling Model-based design Resolution enhancement technologies

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AUTOMATIC tracking OF SPAMM GRID AND THE ESTIMATION OF DEFORMATION PARAMETERS FROM CARDIAC MR-IMAGES

AUTOMATIC TRACKING OF SPAMM GRID AND THE ESTIMATION OF DEFOR...

引用

CONF ON BIOMEDICAL IMAGE PROCESSING AND BIOMEDICAL VISUALIZATION

作者： KUMAR, S GOLDGOF, D Univ. of South Florida (United States)

ISBN: (纸本)0819411388

In this paper, we present a new approach for the automatic tracking of SPAMM (Spatial Modulation of Magnetization) grid in Cardiac MR images and consequent estimation of deformation parameters. The tracking is utilized to extract grid points from MR images and to establish correspondence between grid points in images taken at consecutive frames. These correspondences are used with a thin plate spline model to establish a mapping from one image to the next. This mapping is then used for motion and deformation estimation. Spatio- temporal tracking of SPAMM grid is achieved by using snakes--active contour models with an associated energy functional. We present a minimization strategy which is suitable for tracking the SPAMM grid. By continuously minimizing their energy functionals, the snakes lock on to and follow the in-slice motion and deformation of the SPAMM grid.

关键词： Magnetic resonance imaging detection and tracking algorithms Automatic tracking Motion estimation Motion models Heart Image processing Modulation Optical flow Image analysis

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DISCRIMINATION OF HANDWRITTEN FROM MACHINE-PRINTED TEXT 4

DISCRIMINATION OF HANDWRITTEN FROM MACHINE-PRINTED TEXT

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4th Conference on Hybrid Image and Signal Processing

作者： CHAHAL, S GRUMMAN DATA SYST CORP CHANTILLYVA 22021

ISBN: (纸本)0819415421

The problem of discriminating handwritten from machine-printed text is important for character recognition applications because most recognition algorithms for handwritten text differ considerably from those for machine-printed text. Therefore, an efficient segregation of the two streams is necessary prior to recognition in order to minimize systems cost and complexity. Several techniques have been proposed based on character connectivity and heuristics; but very few achieve results at the 99% level. The technique described in this paper has been proven to yield performance figures in the high 99% on tens of thousands of IRS tax forms and postal envelopes. The technique proposed is based on the use of density of black to white for a given binary field and the overall density of pixels for a gray-scale field as a main discrimination feature. First, the given field is boxed very closely and its boundaries are isolated in space. A horizontal histogram is extracted for this field, and the total number of black pixels is computed. The amount of black pixels per unit area is generated for binary text, and the sum of all pixels is generated for gray-level text. When tested on a large number of samples, these densities cluster following distinct normal distributions for handwritten and machine-printed text respectively. Fuzzy thresholds are set where the two normal curves cross with a confidence interval of 99%. The samples whose densities fall below the threshold are considered handwritten and the samples whose densities fall above the threshold are considered machine-printed.

关键词： Binary data Image processing Statistical analysis Image analysis Fuzzy logic Image segmentation Infrared imaging detection and tracking algorithms Image resolution Optical character recognition

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NEURAL NETWORKS FOR EDDY detection IN SATELLITE IMAGERY 4

NEURAL NETWORKS FOR EDDY DETECTION IN SATELLITE IMAGERY

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4th International Conference on Applications of Artificial Neural Networks

作者： PECKINPAUGH, SH CHASE, JR HOLYER, RJ NAVAL RES LAB BAY ST LOUISMS 39529

ISBN: (纸本)0819412015

For several years the Naval Research Laboratory has worked toward the development of automated techniques for the analysis and interpretation of satellite oceanographic imagery. These techniques are combined to form the Semi-Automated Mesoscale Analysis System (SAMAS), which produces mesoscale charts of the Gulf Stream region. A key requirement of SAMAS is the ability to define location and size of mesoscale features known as eddies. A new method consists of a data reduction step using the Fourier power spectrum and a classification step using a neural network to define the presence or absence of eddies in satellite imagery. The original imagery is divided into chips, each of which overlaps the next by half the chip size. For each chip, a magnitude and direction of the maximum image 'energy' are computed from the local power spectrum. These magnitudes and directions are then used as the inputs into the neural network. The neural network has been successfully trained to distinguish 'warm eddy' and 'no-warm eddy' areas in the imagery. Accuracy of the method is shown to be high enough to produce useful results.

关键词： Neural networks Clouds Satellite imaging Satellites Earth observing sensors Analytical research Climatology detection and tracking algorithms Evolutionary algorithms Infrared imaging

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IMAGE ALGEBRA NETWORKS FOR PATTERN-CLASSIFICATION 5

IMAGE ALGEBRA NETWORKS FOR PATTERN-CLASSIFICATION

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Conference on Image Algebra and Morphological Image Processing V

作者： GADER, PD WON, YW KHABOU, MA UNIV MISSOURI DEPT ELECT & COMP ENGNCOLUMBIAMO 65211

ISBN: (纸本)081941624X

A neural network structure that learns feature extraction and classification operations simultaneously is described. The feature extraction operations are represented using generalized image algebra operations. Learning rules are described. Linear operations and nonlinear, hit-or-miss operations are used to perform handwritten digit recognition.

关键词： Feature extraction Neural networks Image classification Binary data Algorithm development detection and tracking algorithms Electroluminescence Evolutionary algorithms Pattern recognition Structural design

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Time-frequency based ISAR image formation technique

Time-frequency based ISAR image formation technique

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Conference on algorithms for Synthetic Aperture Radar Imagery IV

作者： Chen, VC Naval Research Lab. (United States)

ISBN: (纸本)0819424854

Conventional radar range-Doppler imaging uses the Fourier transform to retrieve Doppler information. Due to a target`s complex motion. the Doppler frequency shifts are actually time-varying. By using the Fourier transform. the Doppler spectrum becomes smeared and the image becomes bluured. In this paper, we propose a time-frequency based ISAR image formation technique to replace the Fourier based ISAR image formation for resolving image blurring problem without resorting to sophisticated motion compensation algorithms. Some high resolution time-frequency transforms are discussed and examples of applying the time-frequency based image formation to simulated ISAR data are given.

关键词： Time-frequency analysis Doppler effect Fourier transforms Transform theory Radar Image acquisition Image processing detection and tracking algorithms Image resolution Image restoration

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Multichannel image processing system for thermal supervision systems

Multichannel image processing system for thermal supervision...

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18th International Conference on Photoelectronics and Night Vision Devices

作者： Zorin, AA Razumova, II Tarkov, VA Siberian Res Inst Opt Syst Novosibirsk 630049 Russia

ISBN: (纸本)0819458287

Foundation principles of multichannel real-time information processing system, which is solving a problem of automatic object tracking, are considered in this work. Image processing algorithms, which are used for three-channel system foundation and optimally approaching for system core - Microprocessor Neuro Matrix NM6403 are realized. Information processing is accomplished with using of Hopfield neural network, one 384x288 frame processing time is about 100... 140 ms.

关键词： Data processing Neural networks Image processing Automatic tracking detection and tracking algorithms Evolutionary algorithms Convolution Data analysis Image quality Visualization

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