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

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MODIFIED MACE FILTERS FOR DISTORTION-INVARIANT RECOGNITION OF RELOCATABLE TARGETS

MODIFIED MACE FILTERS FOR DISTORTION-INVARIANT RECOGNITION O...

引用

13TH AIRBORNE RECONNAISSANCE CONF

作者： CASASENT, D RAVICHANDRAN, G Carnegie Mellon University (United States)

ISBN: (纸本)0819401927

The original MACE (Minimum Average Correlation Energy ) filters are addressed with attention to the effect of iterative refinements, new database tests (on strategic relocatable objects, missile launch-ers), depression angle and resolution effects on the number of training set imagery required and noise performance. Major attention is given to our new MACE filter algorithms for distortion-invariant pattern recognition: iterative shift filter synthesis, MV-MACE (Minimum Variance-MACE) filters (for improved noise performance), multiple symbolic encoded filters and Gaussian Minimum Mean Square Error(MMSE) filters.

关键词： Image filtering Gaussian filters Electronic filtering detection and tracking algorithms Interference (communication) Airborne reconnaissance Optical filters Databases Target recognition Image resolution

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DIRECT SCATTER DISTRIBUTION MEASUREMENTS - COMPARISON TO MONTE-CARLO SIMULATIONS 4

DIRECT SCATTER DISTRIBUTION MEASUREMENTS - COMPARISON TO MON...

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CONF ON MEDICAL IMAGING 4 : IMAGE INFORMATION

作者： SEIBERT, JA BOONE, JM Univ. of California Medical Ctr./Davis (United States) Thomas Jefferson Univ. (United States)

ISBN: (纸本)0819402753

"Direct" measurement of the scatter point spread function (PSF) was obtained with a digital imaging system for the purpose of comparison of a Monte Carlo (MC) scatter distribution algorithm that takes into account polychromatic spectra and detector absorption characteristics. An image intensifier (II) TV system was used to experimentally acquire digital x-ray scatter images in a geometry designed to eliminate detection of the primary beam and to optimize the dynamic range for scattered radiation as well as correct for image variations caused by veiling glare and shading. Both computer generated and experimentally acquired scatter data were measured in concentric annular bins and individually integrated to provide a direct PSF profile. Results indicate a good match between the MC and experimental PSFs for homogeneous scatter distributions at short range airgaps and radial distances. Discrepancies at larger radial distances are likely due to the spherical II input phosphor geometry. For an ll/1'V system detector, therefore, geometric image warping correction for pincushion distortion is indicated, as well as modifications in the MC algorithm for geometry of the detector. This will help to minimize differences between simulated and measured system characteristics.

关键词： Sensors Monte Carlo methods Point spread functions Medical imaging Scatter measurement X-rays Digital imaging Image acquisition detection and tracking algorithms Photons

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NEURAL NETWORK TECHNOLOGY FOR AUTOMATIC TARGET RECOGNITION

NEURAL NETWORK TECHNOLOGY FOR AUTOMATIC TARGET RECOGNITION

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1ST CONF ON APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS

作者： ROTH, MW Johns Hopkins Univ. (United States)

ISBN: (纸本)0819403458

A brief review is presented of neural network tools for Automatic Target Recognition (ATR) . These tools include collective computation for implementing a variety of computational-vision techniques learning and adaptation for pattern recognition knowledge integration for expert-system capabilities and beyondsupercomputer- level hardware. As a specific example neural networks for stereo vision are introduced as a potentially fruitful approach to ATR. Preliminary results are presented which show substantial performance improvements over previous stereo algorithms for producing accurate dense displacement maps. These maps can be used in turn to derive accurate geometrical shape information that can result in improved recognition performance. 1.

关键词： Neural networks Automatic target recognition Evolutionary algorithms detection and tracking algorithms Image processing Analog electronics Algorithm development Very large scale integration Artificial neural networks Environmental sensing

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COMPARISON OF THE ALGEBRAIC RECONSTRUCTION TECHNIQUE WITH THE MAXIMUM-ENTROPY RECONSTRUCTION TECHNIQUE FOR A VARIETY OF detection TASKS 4

COMPARISON OF THE ALGEBRAIC RECONSTRUCTION TECHNIQUE WITH TH...

引用

CONF ON MEDICAL IMAGING 4 : IMAGE INFORMATION

作者： MYERS, KJ HANSON, KM Ctr. for Devices and Radiological Health/FDA (United States) Los Alamos National Lab. (United States)

ISBN: (纸本)0819402753

A method for comparing reconstruction algorithms is presented based on the ability to perform certain detection tasks on the resulting images. The reconstruction algorithms compared are the algebraic reconstruction technique (ART) and the maximum entropy reconstruction method (MaxEnt). Task performance is assessed through a Monte Carlo simulation of the complete imaging process, including the generation of a set of object scenes, followed by data-taking, reconstruction, and performance of the specified task by a machine observer. For these detection tasks the figure of merit used for comparison is the detectability index, d'. When each algorithm is run with approximately optimized parameters, these studies find comparable values for d'.

关键词： Reconstruction algorithms Signal detection Monte Carlo methods Image processing Medical imaging Image acquisition Imaging systems Optimization (mathematics) Computer simulations detection and tracking algorithms

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STANDARD TEST TARGETS FOR AUTOMATIC TARGET RECOGNIZERS

STANDARD TEST TARGETS FOR AUTOMATIC TARGET RECOGNIZERS

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CONF ON ELECTRO-OPTICAL MATERIALS FOR SWITCHES, COATINGS, SENSOR OPTICS, AND DETECTORS

作者： CURRIE, GD U.S. Army Electronic Proving G (United States)

ISBN: (纸本)081940358X

This paper briefly reviews current methods intended to test automatic target recognition systems (ATRS) and the databases needed to support these methods. A new approach to field testing ofATRS is described.1 This approach can also provide means ofgenerating needed realistic, closely documented imagery for ATRS development and testing.

关键词： Automatic target recognition Target recognition Sensors Computer simulations detection and tracking algorithms Electro optical modeling Electro optical sensors Navigation systems Projection systems Scene simulation

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IMAGE RECOGNITION AND LEARNING IN PARALLEL NETWORKS

IMAGE RECOGNITION AND LEARNING IN PARALLEL NETWORKS

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CONF ON NONLINEAR IMAGE PROCESSING

作者： RAGHAVAN, R ADAMS, FW NGUYEN, HT SLAWNY, J Lockheed Palo Alto Research Lab. (United States) Virginia Polytechnic Institute and State Univ. (United States)

ISBN: (纸本)081940294X

We describe the design of an image-recognition system and its performance on multi-sensor imagery. The system satisfies a list of natural requirements, which includes locality of inferences (for efficient VLSI implementation), incorporation of prior knowledge, multi-level hierarchies, and iterative improvement. Two of the most important new features are: a uniform parallel architecture for low-, mid- and high- level vision; and achievement of recognition through short-, as opposed to its long-time behavior, of a dynamical system. Robustness depends on collective effects rather than high precision of the processing elements. The resulting network displays a balance of high speed and small size. We also indicate how this architecture is related to the Dempster-Shafer calculus for combining evidence from multiple sources, and present novel methods of learning in such networks, including one that addresses the integration of model-based and data-driven approaches.

关键词： Sensors Nonlinear image processing Dynamical systems Information operations Data modeling Model-based design Calculus detection and tracking algorithms Image processing Infrared imaging

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FAST PARALLEL algorithms - FROM IMAGES TO LEVEL SETS AND LABELS

FAST PARALLEL ALGORITHMS - FROM IMAGES TO LEVEL SETS AND LAB...

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CONF ON PARALLEL ARCHITECTURES FOR IMAGE PROCESSING

作者： NGUYEN, HT JUNG, KK RAGHAVAN, R Lockheed Palo Alto Research Lab. (United States)

ISBN: (纸本)0819402931

Decomposition into level sets refers to assigning a code with respect to intensity or elevation while labeling refers to assigning a code with respect to disconnected regions. We present a sequence of parallel algorithms for these two processes. The process of labeling includes re-assign labels into a natural sequence and compare different labeling algorithm. We discuss the difference between edge-based and region-based labeling. The speed improvements in this labeling scheme come from the collective efficiency of different techniques. We have implemented these algorithms on an in-house built Geometric Single Instruction Multiple Data (GSIMD) parallel machine with global buses and a Multiple Instruction Multiple Data (MIMD) controller. This allows real time image interpretation on live data at a rate that is much higher than video rate. The performance figures will be shown.

关键词： Image processing Binary data Image segmentation detection and tracking algorithms Image processing algorithms and systems Parallel computing Parallel processing Array processing Information operations Video

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tracking CELLULAR-FEATURES USING MOTION CONSTRAINTS AND GLOBAL INFORMATION

TRACKING CELLULAR-FEATURES USING MOTION CONSTRAINTS AND GLOB...

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CONF ON BIOIMAGING AND TWO-DIMENSIONAL SPECTROSCOPY

作者： LIFSHITZ, L FAY, F GILBERT, S FOGARTY, K CARRINGTON, W Univ. of Massachusetts Medical School (United States)

ISBN: (纸本)081940246X

This paper discusses research directions and results from a multidisciplinary effort to develop feature extraction tools for analysis of the changes in molecular distribution during cell movement. This work is part of a broader effort directed at developing hardware for a new digital imaging microscope, as well as image restoration algorithms which precede the extraction steps, making them simpler. New voxel based display techniques are also being developed for improved visualization of the two and three dimensional data sets. The most complete feature extraction algorithm developed so far analyzes a time sequence of two-dimensional phase contrast images of newt eosinophilic granulocytes (white blood cells). It tracks a moving cell and also identifies the lamellipods of the cell. This allows the extraction of quantitative information relating cell motility to lamellipod formation. The algorithm finds the cell by finding those pixels in the image which belong to the boundary of the cell . Potential boundary pixels are identified by locating intensity changes due to the phase contrast halo surrounding the cell. While most boundary based image segmentation algorthms form a closed boundary by moving from a starting boundary pixel along a path which locally or globally optimizes a cost function our algorithm does not trace a path from a starting point and does not minimize a cost function. Instead, we close the boundary by examining the geometrical and topological relationships among potential boundary pixels. Gaps in the boundary are closed by connecting gap points to the "closest" boundary point. "Close" is determined by a distance metric which combines Euclidean and other types of geometric information about the boundary pixels already found The position of the cell in the previous image is used both to constrain the location of the cell in the image being examined and to insure that the boundary eventually found is indeed closed.

关键词： Algorithm development detection and tracking algorithms Phase contrast Spectroscopy Blood Image analysis Analytical research Image processing algorithms and systems Image segmentation Feature extraction

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ADAPTIVE CLASSIFICATION OF TEXTURED IMAGES USING MOMENTS AND AUTOREGRESSIVE MODELS

ADAPTIVE CLASSIFICATION OF TEXTURED IMAGES USING MOMENTS AND...

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CONF ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING 90

作者： SUKISSIAN, L TIRAKIS, A KOLLIAS, S National Technical Univ. of Athens (Greece)

ISBN: (纸本)0819404217

An adaptive approach to the classification of textured images is presented, based on the extraction of appropriate features from images. Autoregressive linear prediction models, as well as moments of images, are features which are examined and compared in the paper. Classification is achieved in an adaptive way, using an artificial feedforward neural network, which is trained by examples, using an efficient variant of the backpropagation learning algorithm. It is also shown that an adaptive least squares estimation algorithm can be appropriately interweaved with the network, resulting in an on-line adaptive classification scheme. Simulation results are given, which illustrate the performance of the presented method.

关键词： Autoregressive models Image classification Image processing Neural networks Visual communications Curium Image segmentation detection and tracking algorithms Feature extraction Multilayers

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GEOMETRIC TRANSFORMATION ALGORITHM FOR CHARACTER-RECOGNITION USING A GRADIENT-METHOD

GEOMETRIC TRANSFORMATION ALGORITHM FOR CHARACTER-RECOGNITION...

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CONF ON IMAGE COMMUNICATIONS AND WORKSTATIONS

作者： KAMIMURA, T MIZOGUCHI, M NEC Corp. (Japan)

ISBN: (纸本)0819403059

This paper proposes a feedback process approach to shape transformation in OCR character recognition for achieving higher recognition rates. An input image is deformed by warping function so that the stroke in the input image and the corresponding stroke in the reference image will overlap each other as much as possible. Pattern matching between both images is accomplished at several blurring levels, and a gradient method is applied to obtain the optimal warping parameters for minimizing the distance between the images in each blurring level. Third order polynomials by expanding Affine transformations are used as warping functions. Two kinds of pattern matching experiments were carried out. First, the image generated from an original image by warping function with certain parameters was matched with the original image by the proposed method. Second, machine-printed character images of different fonts were used for pattern matching. Both experimental results show that the optimal warping parameters for global minimization of the distances were successfully determined by the combination of a coarse-to-fine pattern matching and a gradient method. The proposed method is applicable to a variety of shape compensations, based on other matching criteria.

关键词： Optical character recognition Image processing Electroluminescence detection and tracking algorithms Lead Image classification Iterative methods Bismuth Image analysis Optimization (mathematics)

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