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15th European Signal processing Conference, EUSIPCO 2007

作者： Papadopoulos, G.Th. Mezaris, V. Kompatsiaris, I. Strintzis, M.G. Informatics and Telematics Institute Thermi-Panorama Road Thessaloniki GR-57001 Greece Information Processing Laboratory Electrical and Computer Engineering Department Aristotle University of Thessaloniki Thessaloniki GR-54124 Greece

ISBN: (纸本)9788392134022

In this paper, a learning approach to semantic image analysis and classification is proposed that combines global and local information, with explicitly defined knowledge in the form of an ontology. The ontology specifies the selected domain, its sub-domains, the concepts related to each sub-domain as well as contextual information. Support Vector Machines (SVMs) are employed in order to provide image classification to one of the defined sub-domains based on global image descriptions and, after a segmentation algorithm is applied, to perform an initial mapping between region low-level visual features and the concepts in the ontology. Then, a decision function, that receives as input the region to concepts associations together with contextual information, realizes image classification based on local-level information. The contextual information used is in the form of frequency of appearance of each concept in every particular sub-domain. A fusion mechanism combines the intermediate classification results, provided by the local-and global-level information processing, and decides on the final classification. A Genetic Algorithm (GA) is employed for optimizing the fusion process. Experiments with images from the personal collection domain demonstrate the performance of the proposed approach. © 2007 EURASIP.

关键词： Ontology

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Erratum: “Decoupling of silicon carbide optical sensor response for temperature and pressure measurements” [J. Appl. Phys. 102, 073111 (2007)]

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Journal of Applied Physics 2008年第11期104卷

作者： A. Chakravarty N. R. Quick A. Kar 1Laser-Aided Manufacturing Materials and Micro-Processing Laboratory (LAMMMP) College of Optics and Photonics/CREOL Department of Electrical Engineering and Computer Science University of Central Florida Orlando Florida 32816-2700 USA 2AppliCote Associates LLC 1445 Dolgner Drive Suite 23 Sanford Florida 32771 USA 3Laser-Aided Manufacturing Materials and Micro-Processing Laboratory (LAMMMP) College of Optics and Photonics/CREOL Department of Mechanical Materials and Aerospace Engineering University of Central Florida Orlando Florida 32816-2700 USA

The unit of temperature in Eq. (1) and the correct form of Eq. (5) are:

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Chesapeake bay water quality monitoring using satellite imagery

Chesapeake bay water quality monitoring using satellite imag...

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作者： Ramakrishna, Bharath Chang, Chein-I. Trou, Bruce Henqemihle, Jerry Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 Microtel LLC 111 Centerway Greenbelt MD 20770

The Chesapeake Bay is a valued ecological, economic, recreational, cultural and scenic resource. The Bay watershed States and the District of Columbia, in conjunction with the EPA Chesapeake Bay Program, have worked and teamed together over the past 20 years to protect and restore the Bay ecosystem. A key component of this effort is water quality and habitat monitoring to assess the impact of management actions and natural, processes, and evaluate habitat parameters on living resources such as submerged aquatic vegetation (SAV), oysters, and fisheries. Using aerial and satellite remote sensing imagery has become a practical and effective means of monitoring water quality in a timely manner. Of particular interest in evaluation of water clarity are several initiative measures. Specifically, Secchi-Disk Transparency (SDT) and Chlorophyll α (Chl-α) have been widely accepted as critical indicators of water quality and their reliable estimation using satellite imagery provides a cost effective and speedy means for water quality monitoring. Work done at Water Resources Center, University of Minnesota has demonstrated the feasibility of performing regional assessment of lake water quality using LANDSAT image data. This paper investigates an approach similar to their work but uses a different type of satellite imagery, EO-1 ALI imagery where the SDT and Chl-a are also used as indicators to estimate water quality for the Chesapeake Bay and DC area (Potomac River). In doing so, three major issues are investigated, which are (1) the study site that is an open Bay area, not a self-contained lake;(2) investigation of applicability of equations that are used to specify the SDT and Chl-α to our Bay area study;(3) the use of a different type of satellite imagery for water quality monitoring. This paper develops techniques to address these three issues and presents preliminary experiments which show encouraging results. © World Scientific Publishing Company.

关键词： Water quality

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Ontology-driven semantic video analysis using visual information objects

Ontology-driven semantic video analysis using visual informa...

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2nd International Conference on Semantics and Digital Media Technologies, SAMT 2007

作者： Papadopoulos, Georgios Th. Mezaris, Vasileios Kompatsiaris, Ioannis Strintzis, Michael G. Information Processing Laboratory Electrical and Computer Engineering Department Aristotle University of Thessaloniki Greece Informatics and Telematics Institute/CERTH 1st Km Thermi-Panorama Road Thessaloniki GR-57001 Greece

ISBN: (纸本)9783540770336

In this paper, an ontology-driven approach for the semantic analysis of video is proposed. This approach builds on an ontology infrastructure and in particular a multimedia ontology that is based on the notions of Visual Information Object (VIO) and Multimedia Information Object (MMIO). The latter constitute extensions of the Information Object (IO) design pattern, previously proposed for refining and extending the DOLCE core ontology. This multimedia ontology, along with the more domain-specific parts of the developed knowledge infrastructure, supports the analysis of video material, models the content layer of video, and defines generic as well as domain-specific concepts whose detection is important for the analysis and description of video of the specified domain. The signal-level video processing that is necessary for linking the developed ontology infrastructure with the signal domain includes the combined use of a temporal and a spatial segmentation algorithm, a layered structure of Support Vector Machines (SVMs)-based classifiers and a classifier fusion mechanism. A Genetic Algorithm (GA) is introduced for optimizing the performed information fusion step. These processing methods support the decomposition of visual information, as specified by the multimedia ontology, and the detection of the defined domain-specific concepts that each piece of video signal, treated as a VIO, is related to. Experimental results in the domain of disaster news video demonstrate the efficiency of the proposed approach. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Object recognition

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Analysis and Modeling of Crosstalk Noise in Domino CMOS Circuits

Analysis and Modeling of Crosstalk Noise in Domino CMOS Circ...

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IEEE Region 5 Annual Technical Conference

作者： Vipin Sharma Waleed K. Al-Assadi Department of Electrical & Computer Engineering Information Processing Laboratory University of Missouri Rolla USA Department of Electrical & Computer Engineering University of Missouri Rolla USA

Domino CMOS logics offer designers with the advantage of most influential circuit design parameters viz., speed, higher integration density and lower power dissipation. This has made a common practice to use the domino CMOS in high performance integrated circuits. However, along with these positives comes inherently low crosstalk noise immunity. This reduced noise immunity of domino CMOS logics is continuously aggravating as recent trends in integrated circuit technology are constantly followed. Although several works investigate the problem of crosstalk noise at the inputs of domino circuits, crosstalk at the dynamic node of the domino circuits has been ignored. In this paper, we propose a model for crosstalk noise at the dynamic node of domino CMOS logic circuits. The model developed incorporates a newly derived switching threshold for the output static inverter in domino CMOS logics to more accurately predict the crosstalk noise immunity of the design. Application of this model can ensure immunity of domino circuits from crosstalk failures.

关键词： Semiconductor device modeling Crosstalk CMOS logic circuits Logic design Circuit synthesis Power dissipation CMOS integrated circuits Noise reduction Integrated circuit noise Integrated circuit technology

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A journey from signal processing to surveillance

A journey from signal processing to surveillance

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Tsuhan Chen Advanced Multimedia Processing Laboratory Department of Electrical Computer Engineering Carnegie Mellon University USA

Traditionally, signal processing is considered simply low-level processing. In the past decade, however, signal processing has grown to become the area where a variety of tools are created to solve high-level problems that conventionally would be studied by computer vision or machine learning researchers exclusively. For example, multiresolution analysis created popular image features like SIFT (scale-invariant feature transform), and statistical analysis gave birth to graphical models such as HMM (hidden Markov models) and topic models. In this talk, we will use one application to illustrate this growth of signal processing: object discovery, i.e., extracting the "object of interest" from a set of images in a completely unsupervised manner. Often based on image features like SIFT, and the topic models, object discovery has recently attracted a lot of attention in video content extraction. In this talk, we will outline this approach and extend it from still images to motion videos. We will propose a novel spatial-temporal framework that applies statistical models to both appearance modeling and motion modeling. The spatial and temporal models are integrated so that motion ambiguities can be resolved by appearance, and appearance ambiguities can be resolved by motion. In addition, we can extract hierarchical relationships among objects, completely driven by data without any manual labeling. This framework finds application in video retrieval (e.g., for YouTube or Google Video) and video surveillance.

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A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING VECTOR MAPS

A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING ...

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IEEE International Symposium on Biomedical Imaging

作者： Hossam E. Abd El Munim Aly A. Farag Computer Vision and Image Processing (CVIP) Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA

ISBN: (纸本)1424406714

In this paper, we introduce a novel global image registration approach using vector distance functions (VDF's). Edges of the source and target objects are used to represent their images. The VDF's of these edges are calculated as an implicit representation of these boundaries. An energy is formulated to measure the differences of these vectors. A variational formulation is considered to estimate the transformation parameters. Promising results in 2D and 3D are demonstrated to show the efficiency of the proposed algorithm.

关键词： Biomedical imaging Image edge detection Image registration Parameter estimation computer vision Mutual information Data mining Shape Image processing Energy measurement

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Editorial: Knowledge engineering, semantics, and signal processing in audio - visual information retrieval

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IEEE Transactions on Circuits and Systems for Video Technology 2007年第3期17卷 257-258页

作者： Izquierdo, Ebroul Zhang, Jian Sikora, Thomas Huang, Thomas S. Department of Electrical Engineering Queen Mary University of London London El 4NS United Kingdom Sydney Australia School of Computer Science and Engineering University of New South Wales Australia Communication Systems Group Technical University Berlin Berlin Germany ITG University of Illinois at Urbana-Champaign United States Department of Electrical and Computer Engineering Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Institute for Advanced Science and Technology United States Institute's Major Research Theme Human Computer Intelligent Interaction National Academy of Engineering Chinese Academies of Engineering and Sciences China International Association of Pattern Recognition Optical Society of American United States

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关键词： Special issues and sections Knowledge engineering Information retrieval Audio-visual systems

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Does an endmember set really yield maximum simplex volume?

Does an endmember set really yield maximum simplex volume?

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chao-Cheng Wu Chein-I Chang Remote Sensing Signal and Image Processing Laboratory the Department of Computer Science and Electrical Engineering Department University of Maryland Baltimore MD USA

One of commonly used criteria for finding an endmember set is to assume that for a given number of endmembers, p, a p-vertex simplex with its vertices specified by p endmembers always yields the maximum volume. Since there are also other criteria which have been widely used for endmember extraction, the issue of interest is "does an endmember set really produce a simplex with maximum volume?" In other words, using the criterion of a simplex with maximum volume is a better and more effective measure than other criteria currently being used by endmember extraction such as orthogonal projection-based pixel purity index (PPI), fully constrained least squares-based spectral unmixing, etc. This paper explores this issue by investigating a number of popular endmember extraction algorithms which are designed by different criteria. An extensive experiment-based study is also conducted for comparative analysis.

关键词： Algorithm design and analysis Least squares methods Hyperspectral imaging Indexes Volume measurement Chaos Data mining Subspace constraints Computational efficiency Current measurement

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3D Protein Classification using Topological, Geometrical and Biological Information

3D Protein Classification using Topological, Geometrical and...

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IEEE International Conference on Image processing

作者： V. Tsatsaias P. Daras M.G. Strintzis Department of Electrical & Computer Engineering Information Processing Laboratory Aristotle University of Thessaloniki Thessaloniki Greece Informatics and Telematics Institute Thessaloniki Greece

Computational approaches for protein classification have been proposed over the last years in order to speed up the analysis of the biological mechanics in living organisms. Most of the approaches tend to focus in geometrical comparison of the 3D molecules to reach their goals. In this paper a method suitable for partial (sub)graph matching of 3D proteinic models, in order to achieve fast and accurate classification, is proposed. The 3D objects are firstly segmented to their molecular structure. Then, descriptors are extracted for each segment using spherical harmonics algorithms, and graphs are constructed for the molecules. Next, a sub-graph matching procedure is utilized and the results are refined using biochemical properties to get biological meaningful classification. The experimental results proved that the proposed method achieves accurate classification of the proteinic data.

关键词： Protein engineering Biology computing Organisms Biological system modeling Spine Information processing Informatics Telematics Electronic mail Data mining

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