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Chemical and Biological Standoff Detection III

作者： Wu, Lin Wang, Jianwei Ramakrishna, Bharath Hsueh, Mingkai Liu, Jonathan Wu, Qufei Wu, Chao-Cheng Cao, Mang Chang, Chein-I. Jensen, Janet L. Jensen, James O. Knapp, Harlan Daniel, Robert Yin, Ray Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 US Army Edgewood Chemical and Biological Center Aberdeen Proving Ground MD 21010 ANP Technologies Inc. 824 Interchange Boulevard Newark DE 19711

The US Army Joint Service Agent Water Monitor (JSAWM) program is currently interested in an approach that can implement a hardware-designed device in ticket-based hand-held assay (currently being developed) used for chemical/biological agent detection. This paper presents a preliminary investigation of the proof of concept. Three components are envisioned to accomplish the task. One is the ticket development which has been undertaken by the ANP, Inc. Another component is the software development which has been carried out by the Remote Sensing Signal and image processing laboratory (RSSIPL) at the University of Maryland, Baltimore County (UMBC). A third component is an embedded system development which can be used to drive the UMBC-developed software to analyze the ANP-developed HHA tickets on a small pocket-size device like a PDA. The main focus of this paper is to investigate the third component that is viable and is yet to be explored. In order to facilitate to prove the concept, a flatbed scanner is used to replace a ticket reader to serve as an input device. The Stargate processor board is used as the embedded System with Embedded Linux installed. It is connected to an input device such as scanner as well as output devices such as LCD display or laptop etc. It executes the C-Coded processing program developed for this embedded system and outputs its findings on a display device. The embedded system to be developed and investigated in this paper is the core of a future hardware device. Several issues arising in such an embedded system will be addressed. Finally, the proof-of-concept pilot embedded system will be demonstrated.

关键词： Embedded systems

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A robust multi-view freehand three-dimensional ultrasound imaging system using volumetric registration

A robust multi-view freehand three-dimensional ultrasound im...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Honggang Yu M.S. Pattichis M.B. Goens Department of Electrical and Computer Engineering Image and Video Processing and Communications Laboratory USA Childrens Hospital Heart Center University of New Mexico Albuquerque NM USA

In this paper, we describe a freehand, three-dimensional ultrasound imaging system. The system uses an electromagnetic position and orientation measurement device to capture two-dimensional ultrasound images at arbitrary planar orientations in space. For robust performance, we use a novel electromagnetic interference detection algorithm that can be used to estimate the probability density function of position and orientation measurement errors. Another important contribution of the proposed system is its ability to reconstruct from multiple standard views. The multi-view reconstruction procedure results in significant reduction in reconstruction error. The system uses object-based 3D volume registration, allowing for arbitrary rigid object movements in inter-view acquisition. The proposed system has been validated on simulated data and a physical, 3D ultrasound calibration phantom. Quantitative experimental results demonstrate the effectiveness of the 3D registration system, and a significant reduction in the mean-squared error via the use of the proposed multi-view reconstruction method.

关键词： Ultrasonic imaging Robustness image reconstruction Position measurement Electromagnetic devices Extraterrestrial measurements Electromagnetic interference Detection algorithms Probability density function Calibration

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Approximation of a linear shift-variant system by a set of linear shift-invariant systems

Approximation of a linear shift-variant system by a set of l...

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International Symposium on Signals, Circuits and Systems (ISSCS)

作者： V. Buzuloiu M. Malciu S.K. Mitra Image Processing and Analysis Laboratory University “Politehnica” of Bucharest Bucharest Romania CERN Geneva Department of Electrical and Computer Engineering University of California at Santa Barbara USA

This paper describes a method to approximate the impulse response of a linear shift-variant system by the impulse responses of a set of linear shift-invariant systems which process in parallel on various windowed versions of the input signal. The method is outlined for one-dimensional systems but the extension to multidimensional case is straightforward.

关键词： Linear approximation Large scale integration image processing image analysis Laboratories Multidimensional systems Linearity image restoration Signal restoration Transfer functions

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Radar backscattering model for multilayer mixed-species forests

Radar backscattering model for multilayer mixed-species fore...

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作者： Liang, Pan Moghaddam, Mahta Pierce, Leland E. Lucas, Richard M. IEEE Atmospheric and Environmental Research Inc. Lexington MA Department of Electrical Engineering and Computer Science Radiation Laboratpry University of Michigan Ann Arbor URSI Commission B Electromagnetics Academy Phi Kappa Phi Tau Beta Pi Eta Kappa Nu Microwave Image Processing Facility Within the Radiation Laboratory Electrical Engineering and Computer Science Department University of Michigan University of Wales Aberystwyth Aberystwyth United Kingdom Radiation Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2122 United States Institute of Geography and Earth Sciences University of Wales Aberystwyth SY23 3DB United Kingdom

A multilayer canopy scattering model is developed for mixed-species forests. The multilayer model provides a significantly enhanced representation of actual complex forest structures compared to the conventional canopy-trunk layer models. Multilayer Michigan Microwave Canopy Scattering model (Multi-MIMICS) allows overlapping layer configuration and a tapered trunk model applicable to forests of mixed species and/or mixed growth stages. The model is the first-order solution to a set of radiative transfer equations and includes layer interactions between overlapping layers. It simulates SAR backscattering coefficients based on input dimensional, geometrical, and dielectric variables of forest canopies. The Multi-MIMICS is an efficient realization of actual forest structures and can be shaped for specific interest of forest parameters. We present the model's application and validation in the paper. The model is parameterized using data collected from a 220 000-ha area of forests in central Queensland, Australia. Fifteen 50 × 50 m test sites representing the general forest diversity and growth stages are chosen as ground truth. Polarimetric backscattering Airborne SAR (AIRSAR) data of the same area are acquired to validate the model simulations. The model predicts SAR backscattering coefficients of the test areas. Simulation results show a good agreement with AIRSAR data at most frequencies and polarizations. The simulated backscattering coefficient from the multilayer model and the standard MIMICS are also compared and significant improvements are observed. © 2005 IEEE.

关键词： Mathematical models

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Online modeling and tracking of pose-varying faces in video

Online modeling and tracking of pose-varying faces in video

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： X. Liu T. Chen General Electric Global Research Center Visualization and Computer Vision Laboratory Schenectady NY USA Advanced Multimedia Processing Lab Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)0769523722

We propose a face mosaicing approach to model both the facial appearance and geometry from pose-varying videos, and apply it in face tracking and recognition. The basic idea is that by approximating the human head as a 3D ellipsoid, multi-view face images can be back projected onto the surface of the ellipsoid, and the surface texture map is decomposed into an array of local patches. During the online modeling process, the position and pose of the first frame is assumed to be known for a given video sequence. For each frame in the sequence, the algorithm estimates the face-position and pose, and generates a texture map, which is further utilized in updating the mosaic model.

关键词： Face recognition Solid modeling Geometry Ellipsoids Face detection Video sequences computer vision Humans Lighting Head

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Pose-robust face recognition using geometry assisted probabilistic modeling

Pose-robust face recognition using geometry assisted probabi...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Xiaoming Liu Tsuhan Chen General Electric Global Research Center Visualization and Computer Vision Laboratory Schenectady NY USA Advanced Multimedia Processing Lab Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)0769523722

Researchers have been working on human face recognition for decades. Face recognition is hard due to different types of variations in face images, such as pose, illumination and expression, among which pose variation is the hardest one to deal with. To improve face recognition under pose variation, this paper presents a geometry assisted probabilistic approach. We approximate a human head with a 3D ellipsoid model, so that any face image is a 2D projection of such a 3D ellipsoid at a certain pose. In this approach, both training and test images are back projected to the surface of the 3D ellipsoid, according to their estimated poses, to form the texture maps. Thus the recognition can be conducted by comparing the texture maps instead of the original images, as done in traditional face recognition. In addition, we represent the texture map as an array of local patches, which enables us to train a probabilistic model for comparing corresponding patches. By conducting experiments on the CMU PIE database, we show that the proposed algorithm provides better performance than the existing algorithms.

关键词： Face recognition Geometry Solid modeling Ellipsoids Humans Lighting Head Testing Surface texture image recognition

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Cost-effective video filtering solution for real-time vision systems

Cost-effective video filtering solution for real-time vision...

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作者： Fischer, Viktor Lukac, Rastislav Martin, Karl Laboratoire Traitement du Signal et Instrumentation Unité Mixte de Recherche CNRS 5516 Université Jean Monnet 10 rue Barrouin 42000 Saint-Etienne France Multimedia Laboratory Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 10 King's College Road Toronto Ont. M5S 3G4 Canada Jean Monnet University of Saint-Etienne France Department of Electronics and Computer Science Micronic Košice Slovakia Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto Canada IEEE Circuits and Systems IEEE Consumer Electronics IEEE Signal Processing Societies IEEE Signal Processing Society Communications Society

This paper presents an efficient video filtering scheme and its implementation in a field-programmable logic device (FPLD). Since the proposed nonlinear, spatiotemporal filtering scheme is based on order statistics, its efficient implementation benefits from a bit-serial realization. The utilization of both the spatial and temporal correlation characteristics of the processed video significantly increases the computational demands on this solution, and thus, implementation becomes a significant challenge. Simulation studies reported in this paper indicate that the proposed pipelined bit-serial FPLD filtering solution can achieve speeds of up to 97.6 Mpixels/s and consumes 1700 to 2700 logic cells for the speed-optimized and area-optimized versions, respectively. Thus, the filter area represents only 6.6 to 10.5% of the Altera STRATIX EP1S25 device available on the Altera Stratix DSP evaluation board, which has been used to implement a prototype of the entire real-time vision system. As such, the proposed adaptive video filtering scheme is both practical and attractive for real-time machine vision and surveillance systems as well as conventional video and multimedia applications.

关键词： computer vision

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A computer-aided system for mass detection and classification in digitized mammograms

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Biomedical engineering - Applications, Basis and Communications 2005年第5期17卷 215-228页

作者： Yang, Sheng-Chih Wang, Chuin-Mu Chung, Yi-Nung Hsu, Giu-Cheng Lee, San-Kan Chung, Pau-Choo Chang, Chein-I. Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Department of Computer Science and Information Engineering National Chin Yi Institute of Technology Taichung Taiwan Department of Electrical Engineering Da-Yeh University Chunghua Taiwan Department of Radiology Tri-Service General Hospital National Defense Medical Center Taipei Taiwan Administrative Office Suao Veterans Hospital Yilan Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD United States

This paper presents a computer-assisted diagnostic system for mass detection and classification, which performs mass detection on regions of interest followed by the benign-malignant classification on detected masses. In order for mass detection to be effective, a sequence of preprocessing steps are designed to enhance the intensity of a region of interest, remove the noise effects and locate suspicious masses using five texture features generated from the spatial gray level difference matrix (SGLDM) and fractal dimension. Finally, a probabilistic neural network (PNN) coupled with entropic thresholding techniques is developed for mass extraction. Since the shapes of masses are crucial in classification between benignancy and malignancy, four shape features are further generated and joined with the five features previously used in mass detection to be implemented in another PNN for mass classification. To evaluate our designed system a data set collected in the Taichung Veteran General Hospital, Taiwan, R.O.C. was used for performance evaluation. The results are encouraging and have shown promise of our system.

关键词： computer aided analysis

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Journal of Information Science and engineering: Editorial notice

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Journal of Information Science and engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

No abstract available

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The symbiotic relationship of parts and monolithic face representations in verification

The symbiotic relationship of parts and monolithic face repr...

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2004 IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2004

作者： Lucey, Simon Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States

Techniques that treat the face holistically as a vector of pixel values, which we refer to as a monolithic representation, are still widely considered state of the art for the task of face verification in literature. Recently good performance has be attained in the task of face verification, using Gaussian mixture models (GMMs), via estimating a parts (i.e. image patch) face model;where the shape (i.e. spatial) information is largely ignored. In this paper we postulate that the characteristics current algorithms employ for verifying a face using monolithic and parts representations differ and are in many ways symbiotic;lending themselves to synergetic combination and improved verification performance. Results are presented on the BANCA database that demonstrate excellent verification performance in the presence of many common real world variabilities (e.g. camera degradation, minor pose variabilities, some changes in background and lighting). © 2004 IEEE.

关键词： Face recognition

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