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7th Conference on Mathematics of Data/Image Coding, Compression, and Encryption

作者： Stiller, PF Texas A&M Univ College Stn TX 77843 USA

ISBN: (纸本)0819454990

Recent progress in shape theory, including the development of object/image equations for shape matching and shape space metrics (especially object/image metrics), is now being exploited to develop new algorithms for target recognition. This theory makes use of advanced mathematical techniques from algebraic and differential geometry to construct generalized shape spaces for various projection and sensor models, and then uses that construction to find natural metrics that express the distance (difference) between two configurations of object features, two configurations of image features, or an object and an image pair. Such metrics produce the most robust tests for target identification;at least as far as target geometry is concerned. Moreover, they also provide the basis for efficient hashing schemes to do target identification quickly and provide a rigorous foundation for error analysis in ATR.

关键词： Target recognition Algorithm development Image sensors algorithms detection and tracking algorithms Matrices Sensors Error analysis Mathematical modeling Mathematics

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Performance evaluation of road detection and following systems

Performance evaluation of road detection and following syste...

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Conference on Mobile Robots XVII

作者： Hong, T Takeuchi, A Foedisch, M Shneier, M Natl Inst Stand & Technol Gaithersburg MD 20899 USA

ISBN: (纸本)0819455628

We describe a methodology for evaluating algorithms to provide quantitative information about how well road detection and road following algorithms perform. The approach relies on generating a set of standard data sets annotated with ground truth. We evaluate the algorithms used to detect roads by comparing the output of the algorithms with ground truth, which we obtain by having humans annotate the data sets used to test the algorithms. Ground truth annotations are acquired from more than one person to reduce systematic errors. Results are quantified by looking at false positive and false negative regions of the image sequences when compared with the ground truth. We describe the evaluation of a number of variants of a road detection system based on neural networks.

关键词： Roads detection and tracking algorithms Algorithm development Image segmentation Video Neural networks Visualization Databases Evolutionary algorithms Pattern recognition

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Distorted IR target detection and tracking using composite filters

Distorted IR target detection and tracking using composite f...

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Conference on Photonic Devices and algorithms for Computing V

作者： Iftekharuddin, KM Shaik, JS Univ Memphis Intelligent Syst & Image Proc ISIP Lab Dept Elect & Comp Engn Memphis TN 38152 USA

ISBN: (纸本)081945074X

The automatic target recognition (ATR), often time, is limited by the presence of background clutter and distortions such as scale, translation and rotation (both in-plane and out-of-plane) in both single and multi object cases. Such distortion invariant ATR and image understanding have been the subject of intense research in machine vision. In a previous work, we have demonstrated the usefulness of an amplitude-coupled minimum-average correlation energy (AC-MACE) filter in in-plane rotated SAR image ATR. The AC-MACE filter outperforms the regular MACE filter in rotation-related cases. Motion tracking is also an important task in computer vision, especially, when objects are subjected to certain viewing transformation. There are many problems in which very small objects undergoing motion must be detected and then tracked. For example, one of the most difficult goals of ATR is to spot incoming objects at long range, wherein the motion appears small and the signal to noise ratio (SNR) is poor. The system must be able to track such targets long enough to identify whether the object is a friend or foe. In this work, we are interested in locating both long-range and short-range moving objects in IR images wherein the object may vary from a few pixels in size to a large number of pixels in a sequence of IR images. The targets are submerged in background noise and clutter. Additionally, the tracking problem also involves out-of-plane rotation of the target. Thus, we investigate both MACE and AC-MACE filter for rotation and size invariant target detection and tracking using realistic IR images.

关键词： detection and tracking algorithms Image filtering Optical filters Automatic target recognition Electronic filtering Infrared imaging Nonlinear filtering Phase only filters Composites Target detection

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Bayesian cluster detection and tracking using a generalized Cheeseman approach

Bayesian cluster detection and tracking using a generalized ...

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Conference on Signal Processing, Sensor Fusion, and Target Recognition XII

作者： Mahler, R Lockheed Martin Tactical Syst Eagan MN USA

ISBN: (纸本)0819449563

Cluster tracking is the problem of detecting and tracking clustered formations of large numbers of targets, without necessarily being obligated to track each and every individual target. We address this problem by generalizing to the dynamic case a static Bayesian finite-mixture data-clustering approach due to P. Cheeseman. After summarizing Cheeseman's approach, we show that it implicitly draws on random set theory. Making this connection explicit allows us to incorporate it into a multitarget recursive Bayes filter, thereby leading to a rigorous Bayesian foundation for finite-mixture cluster tracking. A computational approach is proposed, based on an approximate, multitarget first-order moment filter ("cluster PHD" filter).

关键词： Digital filtering Target detection Electronic filtering Filtering (signal processing) Data modeling Statistical modeling detection and tracking algorithms Sensor fusion Signal processing Target recognition

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Multiresolution, dynamic, and adaptive image quantization methodology: automation and analysis

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JOURNAL OF ELECTRONIC IMAGING 2003年第2期12卷 229-243页

作者： Soh, LK Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68588 USA

We describe a multiresolution, dynamic, and adaptive image quantization methodology with automation being the goal of our research. To improve the robustness of the approach, we incorporate dynamic local thresholding and multiresolution peak detection. The first strategy extracts bisector values from local regions of the image and builds a histogram based on those values. The second strategy maps, the derived histogram into multiple levels of resolution, allowing peaks be scored for their significance and localized. We conduct several. experiments to analyze different versions of our quantization methodology and to compare it with the equal probability quantization. We also investigated the relationships between image attributes and the key parameters in our quantizers: Based on the findings, we developed a fully automated quantizer called QTR0.5. We have applied QTR0.5 to a variety of images-aerial, photographic, and satellite images-and have also used it as a preprocessor in an image segmentation software tool. (C) 2003 SPIE and IST.

关键词： Quantization Signal detection Tolerancing Image segmentation detection and tracking algorithms Image quality Buildings Calibration Satellite imaging Satellites

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Image segmentation in compressed domain

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JOURNAL OF ELECTRONIC IMAGING 2003年第3期12卷 390-397页

作者： Feng, GC Jiang, JM Univ Bradford Sch Informat Bradford BD7 1DP W Yorkshire England Zhongshan Univ Fac Math & Comp Sci Guangzhou Peoples R China

We propose a direct image segmentation algorithm in the JPEG compressed domain. The algorithm features extracting statistical parameters from direct cosine transform (DCT) coefficients without its inverse transform, and growing regions in line with JPEG compression seamlessly in blocks of 8 x 8 pixels. In comparison with the latest research efforts in region-based image segmentation, our proposed algorithm achieves significant advantages, including (1) no iteration is involved, (2) no full decompression is required, and (3) segmentation performance is competitive. (C) 2003 SPIE and IST.

关键词： Image segmentation Image compression Image processing algorithms and systems Algorithm development Image processing Image retrieval Sensors detection and tracking algorithms Edge detection Feature extraction

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Morphological characterization of dithering masks

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JOURNAL OF ELECTRONIC IMAGING 2003年第2期12卷 278-283页

作者： Misic, V Parker, KJ Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA

We present some novel tools for the analysis of blue-noise binary patterns. Unlike most of the existing methods that evaluate the frequency content of a given mask or its lower order statistics, our new metrics characterize the morphological content of a mask that is quantified using simple one-pass filtering. An analytical filter expression is given. As a result, one can balance the structural content of the mask-diagonal, vertical, and horizontal interconnections of the majority (or minority) pixels-at the same level. In addition, it is possible to improve the overall mask quality by prescribing the occurrence of morphological shapes of connected pixels. Examples of morphological analysis are given to demonstrate the different qualities of blue-noise and white-noise patterns. (C) 2003 SPIE and IST.

关键词： Binary data Halftones Image filtering Visualization Convolution detection and tracking algorithms Digital filtering Morphological analysis Statistical analysis Visual system

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Invertibility and transitivity analysis for nonrigid image registration

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JOURNAL OF ELECTRONIC IMAGING 2003年第1期12卷 106-117页

作者： Christensen, GE Johnson, HJ Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA

We present a new method for evaluating the performance of nonrigid image registration algorithms by analyzing the invertibility and transitivity properties of the transformations that they produce. The invertibility and transitivity of transformations computed using a unidirectional and a consistent linear-elastic registration algorithm are evaluated. The invertibility of the transformations is evaluated by comparing the composition of transformations from images A to B and B to A to the identity mapping. The transitivity of the transformations is evaluated by measuring the difference between the identity mapping and the composition of the transformations from images A to B, B to C, and C to A. Transformations are generated by matching three computer-generated phantoms, three computed tomography (CT) data of infant heads, and 23 magnetic resonance imaging (MRI) data of adult brains. In all cases, the inverse consistency constraint (ICC) algorithm out-performs the unidirectional algorithm by producing transformations that have less inverse consistency error and less transitivity error. For the MRI brain data, the ICC algorithm reduced the maximum inverse consistency error by 205 times, the average transitivity error by 50%, and the maximum transitivity error by 37% on average compared to the unidirectional algorithm. (C) 2003 SPIE and IST.

关键词： Image registration Magnetic resonance imaging Computed tomography detection and tracking algorithms 3D image processing Error analysis Brain Head Image analysis Neuroimaging

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Retinex preprocessing of uncalibrated images for color-based image retrieval

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JOURNAL OF ELECTRONIC IMAGING 2003年第1期12卷 161-172页

作者： Ciocca, G Marini, D Rizzi, A Schettini, R Zuffi, S CNR Tecnol Informat Multimediali ITC Milan Italy Univ Milan Dipartimento Sci Informaz I-20122 Milan Italy Univ Milan Dip Tecnol Informaz I-20122 Milan Italy Univ Milan DISCO I-20122 Milan Italy CNR Ist Biostrutture & Bioimmagini Naples Italy

In image databases, variations in imaging conditions and preprocessing may result in similar originals that exhibit a low measure of similarity when color information is used in standard image retrieval methods. We examine the performance of various color-based retrieval strategies to see whether, and to what degree, the effectiveness of retrieval improves with Retinex-based preprocessing, regardless of the strategy adopted. The results of experiments performed on four different databases are reported and discussed. (C) 2003 SPIE and IST.

关键词： Databases Image retrieval Ceramics RGB color model Colorimetry Image processing Feature extraction detection and tracking algorithms Image filtering Visualization

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Quantum oracles and the optical Bernstein-Vazirani algorithm

Quantum oracles and the optical Bernstein-Vazirani algorithm

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19th Congress of the International-Commission-for-Optics

作者： Walmsley, I Londero, P Dorrer, C Anderson, M Wallentowitz, S Banaszek, K Univ Oxford Clarendon Lab Oxford OX1 3PU England

ISBN: (纸本)0819445967

We implement the Bernstein-Vazirani algorithm on a 15-bit register encoding 2(15)-1 elements using optics. The apparatus is efficient in that the physical size of the apparatus scales linearly with the size (i.e. number of digits) of the register. We demonstrate also that the algorithm may be performed not only without entanglement, as Meyer has indicated, but also with a computational basis that does not consist of orthogonal states, and that this coding is the source of the efficiency of the algorithm. This raises several questions: is this the only algorithm that makes use of these simplifying features, or do all quantum Oracles in fact require exponential resources for their construction?

关键词： Particles Databases Computing systems detection and tracking algorithms Quantum computing Computer programming Optical components Classical physics Data compression Data processing

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