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Proceedings: 2005 International Conference on Parallel processing Workshops

Proceedings: 2005 International Conference on Parallel Proce...

引用

International Conference on Parallel processing Workshops 2005, ICPP 2005

The proceedings contain 74 papers. The topics discussed include: web services composition for distributed data mining;how to run scientific applications over web services;resource management services for a grid analysis environment;a comparison of two methods for building astronomical image mosaics on a grid;gene sequence alignment on a public computing platform;parallel module network learning on distributed memory multiprocessors;a scalable parallel poisson solver in three dimensions with infinite-domain boundary conditions;factoring solution sets of polynomial systems in parallel;a programmable array processor architecture for flexible approximate string matching algorithms;and speculative parallel threading architecture and compilation.

关键词： World Wide Web

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Computational Imaging systems for iris recognition

Computational Imaging systems for iris recognition

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Conference on Advanced Signal processing algorithms, Architectures, and Implementations xiv

作者： Plemmons, R Horvath, M Leonhardt, E Pauca, P Prasad, S Robinson, S Setty, H Torgersen, T van der Gracht, J Dowski, E Narayanswamy, R Silveira, PEX Wake Forest Univ Winston Salem NC 27109 USA Univ New Mexico Albuquerque NM 87131 USA

ISBN: (纸本)0819454974

Computational imaging systems are modem systems that consist of generalized aspheric optics and image processing capability. These systems can be optimized to greatly increase the performance above systems consisting solely of traditional optics. Computational imaging technology can be used to advantage in iris recognition applications. A major difficulty in current iris recognition systems is a very shallow depth-of-field that limits system usability and increases system complexity. We first review some current iris recognition algorithms, and then describe computational imaging approaches to iris recognition using cubic phase wavefront encoding. These new approaches can greatly increase the depth-of-field over that possible with traditional optics, while keeping sufficient recognition accuracy. In these approaches the combination of optics, detectors, and image processing all contribute to the iris recognition accuracy and efficiency. We describe different optimization methods for designing the optics and the image processing algorithms, and provide laboratory and simulation results from applying these systems and results on restoring the intermediate phase encoded images using both direct Wiener filter and iterative conjugate gradient methods.

关键词： biometrics iris recognition high performance imaging extended depth-of-field pattern recognition feature extraction image restoration

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Missile signal processing common computer architecture for rapid technology upgrade

Missile signal processing common computer architecture for r...

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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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Design of a color image processing algorithm using on-line arithmetic modules

Design of a color image processing algorithm using on-line a...

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Conference on Advanced Signal processing algorithms, Architectures, and Implementations xiv

作者： Sinky, MH Tenca, AF Shantilal, AC Lucchese, L Oregon State Univ Corvallis OR 97331 USA

ISBN: (纸本)0819454974

A new class of nonlinear filters for color image processing was proposed by Lucchese and Mitra. This type of color filter processes the chromatic component of images encoded in the International Commission. on Illumination (CIE) u'v' color space. images processed by this filter do not show color shifts near edges between regions with different intensities. The filter uses linear convolution operations internally and is effective and efficient for denoising and regularizing color images. image processing systems are computationally intensive and usually require a large amount of area in order to reach desirable levels of performance. The use off on-line arithmetic can decrease the area of the hardware implementation and still maintain a reasonable throughput. This work presents the design of the color filter as a network of on-line arithmetic modules. The network topology and some detail of each arithmetic module are provided. The final implementation targets FPGAs and it is compared in terms of area against an estimate of a conventional design. The throughput of this solution is capable of supporting real-time processing of common image formats.

关键词： achromatic chromatic convolution DSP DIP FPGA on-line arithmetic RGB SRT division

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Pupil-phase optimization for extended-focus, aberration-corrected imaging systems

Pupil-phase optimization for extended-focus, aberration-corr...

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Conference on Advanced Signal processing algorithms, Architectures, and Implementations xiv

作者： Prasad, S Pauca, VP Plemmons, RJ Torgersen, TC van der Gracht, J Univ New Mexico Ctr Adv Studies Albuquerque NM 87131 USA Wake Forest Univ Dept Comp Sci Winston Salem NC 27109 USA Wake Forest Univ Dept Comp Sci Winston Salem NC 27109 USA Wake Forest Univ Dept Comp Sci & Math Winston Salem NC 27109 USA Holospex Inc Columbia MD 21044 USA

ISBN: (纸本)0819454974

The insertion of a suitably designed phase plate in the pupil of an imaging system makes it possible to encode the depth dimension of an extended three-dimensional scene by means of an approximately shift-invariant PSF. The so-encoded image can then be deblurred digitally by standard image recovery algorithms to recoup the depth dependent detail of the original scene. A similar strategy can be adopted to compensate for certain monochromatic aberrations of the system. Here we consider two approaches to optimizing the design of the phase plate that are somewhat complementary-one based on Fisher information that. attempts to reduce the sensitivity of the phase encoded image to misfocus and the other based on a minimax formulation of the sum of singular values of the system blurring matrix that attempts to maximize the resolution in the final image. Comparisons of these two optimization approaches are discussed. Our preliminary demonstration of the use of such pupil-phase engineering to successfully control system aberrations particularly spherical aberration, is also presented.

关键词： pupil-phase mask wavefront coding integrated imaging aberration control Fisher information minimax focus extension image quality nonlinear optimization

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Adaptive infrared target detection

Adaptive infrared target detection

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14th Conference on Automatic Target Recognition

作者： McBride, JC Stevens, MR Eaton, RS Snorrason, M Charles River Analyt Cambridge MA USA

ISBN: (纸本)0819453498

Automatic Target Recognition (ATR) algorithms are extremely sensitive to differences between the operating conditions under which they are trained and the extended operating conditions (EOCs) in which the fielded algorithms are tested. These extended operating conditions can cause a target's signature to be drastically different from training exemplars/models. For example, a target's signature can be influenced by: the time of day, the time of year, the weather, atmospheric conditions.. position of the Sun or other illumination sources, the target surface and material properties, the target composition, the target geometry, sensor characteristics, sensor viewing angle and range, the target surroundings and environment, and the target and scene temperature. Recognition rates degrade if an ATR is not trained for a particular EOC. Most infrared target detection techniques are based on a very simple probabilistic theory. This theory states that a pixel should be assigned the label of "target" if a set of measurements (features) is more likely to have come from an assumed (or learned) distribution of target features than from the distribution of background features. However, most detection systems treat these learned distributions as static and they are not adapted to changing EOCs. In this paper, we present an algorithm for assigning a pixel the label of target or background based on a statistical comparison of the distributions of measurements surrounding that pixel in the image. This method provides a feature-level adaptation to changing EOCs. Results are demonstrated on infrared imagery containing several military vehicles.

关键词： automatic target recognition image processing infrared target detection

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Proceedings of the International Conference on Parallel processing Workshops

Proceedings of the International Conference on Parallel Proc...

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International Conference on Parallel processing Workshops, ICPPW 2001

ISBN: (纸本)0769512607

The proceedings contain 67 papers. The topics discussed include: designing parallel sparse matrix algorithms beyond data dependence analysis;run-time characterization of irregular accesses applied to parallelization of irregular reductions;solution of computational fluid dynamics problems on parallel computers with distributed memory;a data and task parallel image processing' environment for distributed memory systems;parallel implementation of wavelet transforms on distributed-memory multicomputers;performance comparison of parallel finite element and Monte Carlo methods in optical tomography;parallel ray tracing using processor farming model;parallel domain decomposition methods for dam problem;an efficient parallel algorithm for solving unsteady nonlinear equations;partial stabilization of large-scale discrete-time linear control systems;and modular construction of model partitioning processes for parallel logic simulation.

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Software systems testing of a closed loop tracking system using a SIMULINK based simulation

Software systems testing of a closed loop tracking system us...

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Conference on Acquisition, Tracking, and Pointing xiv

作者： Robinson, B Sasaki, D Raytheon Co El Segundo CA 90245 USA

ISBN: (纸本)0819436518

Problems associated with integrating, debugging and validating real time software systems are well known. Closed loop tracking systems contain functional elements that illustrate the most difficult aspects of integrating, debugging, and ultimately validating the performance of real time software. Among these are severe real time constraints for line of sight control processing, image processing, inter-processor and peripheral communication. In addition, these highly complex algorithms are running on the target processors that are seldom tested end-to-end prior to system integration. The problem is exacerbated by unavailable or intermittently available hardware during the development and the integration phase of a typical program. Even with fully integrated hardware and software, performance validation is difficult because operational conditions of the platform and targets cannot be adequately represented in a laboratory setting without costly equipment to support hardware-in-the-loop simulation. The pressure to reduce cost and algorithm development to real-time software cycle time further aggravates the problem by limiting the time available for gaining confidence in the algorithms and software before they are committed to integration. This paper discusses a simulation approach that has streamlined the real-time software development process for a closed loop image-based tracking system. The MATLAB/SIMULINK simulation consists of elements constructed from common source modules shared with the deliverable system. The simulation has provided a tool to support algorithm development for the fundamental system components, including a system controller, a servo controller, and an image processor. In addition, the simulation has provided a testbed for verification of system performance. The context for this application is the low rate initial production phase of a tactical airborne avionics system that includes an image-based tracking system.

关键词： closed loop tracking pointing and stabilization image based tracking

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Experiments with driving modes for urban robots

Experiments with driving modes for urban robots

引用

Conference on Mobile Robots xiv

作者： Hebert, M MacLachlan, R Chang, P Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)0819434310

In this paper, we describe experiments on semi-autonomous control of a small urban robot. Three driving modes allow semiautonomous control of the robot through video imagery, or by using partial maps of the environment. Performance is analyzed in terms of maximum speed, terrain roughness, environmental conditions, and ease of control. We concentrate the discussion on a driving mode based on visual servoing. In this mode, a template designated in an image is tracked as the robot moves toward the destination designated by the operator. Particular attention is given to the robustness of the tracking with respect to template selection, computational resources, occlusions, and rough motion. The discussion of algorithm performance is based on experiments conducted at Ft. Sam Houston, TX, on Jul. 5-9 1999. In addition to the driving modes themselves, the performance and practicality of an omnidirectional imaging sensor is discussed. In particular, we discuss the typical imaging artifacts due to ambient lighting.

关键词： Robots Cameras Detection and tracking algorithms Algorithm development image processing Visualization Light sources and illumination Robotics Control systems Fourier transforms

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image segmentation using Gaussian curvature

Image segmentation using Gaussian curvature

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Conference on Intelligent Robots and Computer Vision xiv - algorithms, Techniques, Active Vision, and Materials Handling

作者： Shrikhande, N Ramaswamy, S CENT MICHIGAN UNIV DEPT COMP SCIMT PLEASANTMI 48859

ISBN: (纸本)0819419524

One of the central problems of computer vision is segmentation of images into salient features such as edges and surfaces. Different kinds of similarity criteria can be used to group related pixels together. One such criterion is the curvature of surfaces in an image of a multiobject scene that contains several objects with different shapes. In practice, however, curvature is difficult to calculate because small amount of noise can cause large amounts of errors in calculations of first and second derivatives. In this paper, we use a discrete approximation of Gaussian curvature that is efficient to compute. The approximation is used to segment the image into individual surfaces. Both synthetic and real images have been tested. Results appear quite encouraging.

关键词： image segmentation Visual process modeling Data modeling Software development Computer vision technology image processing algorithms and systems Machine vision Object recognition Reliability Visualization

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