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2006 IEEE 10th International Symposium on Consumer Electronics, ISCE 2006

作者： Malik, Aamir Saeed Nisar, Humaira Choi, Tae-Sun Signal and Image Processing Laboratory Gwangju Institute of Science and Technology 1 Oryong-Dong Buk-Gu Gwangju 500-712 Korea Republic of

ISBN: (纸本)1424402166

The currently available 3-Dimensional (3D) cameras are quite expensive because they employ technologies like using three separate lasers to capture XYZ and RGB values, the triangulation method using laser scanner etc. We propose passive methods as a solution to decrease the high cost involved in 3D cameras. For this purpose, we have developed a focus measure and an approximation technique. The focus measure is based on an optical transfer junction and it has shown robustness in the presence of noise. For the approximation technique, our algorithm is based on Fuzzy-Neuro approach. A Fuzzy Inference System (FIS) is designed and trained using the neural network for the calculation of the depth map. The proposed focus measure and approximation technique can further be employed in any of the passive methods to acquire depth map for a 3D camera.1. © 2006 IEEE.

关键词： Cameras

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Design of a High Performance Monolithic Current-Mode Boost DC-DC Converter

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电子学报(英文版) 2006年第4期15卷 599-603页

作者： YU Hua ZOU Xuecheng CHEN Chaoyang ZHANG Jing Department of Electronic Science and Technology Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

The work presented in this paper mainly focuses on designing a monolithic current-mode boost DC-DC converter with integrated 22V DMOS FET power switch and control circuits. The boost converter operating at fixed frequency of 1.6MHz has been fabricated with a 1.5μm Bipolar-CMOS-DMOS (BCD) process. The chip with features of wide input voltage range (2.7V to 14V), high efficiency over large load range (1mA to 500mA), low shutdown current, fast transient response and low power, was designed for mobile power management applications. Besides issues such as technology choice, power switch optimization and ramp compensation, the paper also copes with the monolithic switching noise in switching power IC circuits.

关键词： DC-DC转换器变速补偿电流控制脉冲调制

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Statistical modeling and analysis of laser-evoked potentials of electrocorticogram recordings from awake humans

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Computational Intelligence and Neuroscience 2007年第unknown期2007卷 1-25页

作者： Chen, Zhe Ohara, Shinji Cao, Jianting Vialatte, François Lenz, Fred A. Cichocki, Andrzej Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Wako-shi 351-0198 Saitama Japan Neuroscience Statistics Research Lab Massachusetts General Hospital Harvard Medical School Boston MA 02114 United States Department of Neurosurgery Johns Hopkins Hospital Baltimore MD 21287-7274 United States Department of Neurosurgery Kyoto Kizugawa Hospital Hirakawa Joyo 610-0101 Kyoto 26-1 Nishi-Rokutan Japan Department of Electronics and Information Engineering Saitama Institute of Technology Fukaya-shi 369-0293 Saitama Japan

This article is devoted to statistical modeling and analysis of electrocorticogram (ECoG) signals induced by painful cutaneous laser stimuli, which were recorded from implanted electrodes in awake humans. Specifically, with statistical tools of factor analysis and independent component analysis, the pain-induced laser-evoked potentials (LEPs) were extracted and investigated under different controlled conditions. With the help of wavelet analysis, quantitative and qualitative analyses were conducted regarding the LEPs' attributes of power, amplitude, and latency, in both averaging and single-trial experiments. Statistical hypothesis tests were also applied in various experimental setups. Experimental results reported herein also confirm previous findings in the neurophysiology literature. In addition, single-trial analysis has also revealed many new observations that might be interesting to the neuroscientists or clinical neurophysiologists. These promising results show convincing validation that advanced signal processing and statistical analysis may open new avenues for future studies of such ECoG or other relevant biomedical recordings.

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Using Optical Transfer Function and Fuzzy-Neuro Logic for a 3-Dimensional (3D) Camera

Using Optical Transfer Function and Fuzzy-Neuro Logic for a ...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： A.S. Malik H. Nisar Tae-Sun Choi Signal and Image Processing Laboratory Gwangju Institute of Science and Technology Gwangju South Korea

The currently available 3-dimensional (3D) cameras are quite expensive because they employ technologies like using three separate lasers to capture XYZ and RGB values, the triangulation method using laser scanner etc. We propose passive methods as a solution to decrease the high cost involved in 3D cameras. For this purpose, we have developed a focus measure and an approximation technique. The focus measure is based on an optical transfer function and it has shown robustness in the presence of noise. For the approximation technique, our algorithm is based on fuzzy-neuro approach. A fuzzy inference system (FIS) is designed and trained using the neural network for the calculation of the depth map. The proposed focus measure and approximation technique can further be employed in any of the passive methods to acquire depth map for a 3D camera

关键词： Transfer functions Fuzzy logic Cameras Optical noise Costs Noise measurement Optical computing Noise robustness Approximation algorithms Inference algorithms

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A DSP/FPGA -based parallel architecture for real-time image processing

A DSP/FPGA -based parallel architecture for real-time image ...

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6th World Congress on Intelligent Control and Automation, WCICA 2006

作者： Luxin, Yan Tianxu, Zhang Sheng, Zhong Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)1424403324

DSP/FPGA-based parallel architecture oriented to real-time image processing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high image processing performance, which achieve a good balance for parallel image processing. © 2006 IEEE.

关键词： Digital signal processing

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Research on management and scheduling of event in the HLA-based training system for crisis management

Research on management and scheduling of event in the HLA-ba...

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Spring Simulation Interoperability Workshop 2007, 07 Spring SIW

作者： Yang, Qing Wang, Hong-Wei Hongliu Wan, Hu Key Laboratory for Image Processing and Intellectual Control Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 China Tongji Medicine Collage Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781604239232

A new method of management and scheduling is pointed out to solve a key problem what is management and scheduling of event in general training systems. Firstly, every event is classified depended on the kinds of federates and indicated the trigger-relation. Secondly, a XML-based training scenario through the combination of the workflow and conceptions in HLA is compiled. an event engine is designed on the basis of the training scenario, being responsible for the scheduling of events which are in and between federates. A practical example of a training system for crisis management was presented to introduce the particular process of the design and implement.

关键词： Scheduling

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Quantization-based probabilistic feature modeling for kernel design in content-based image retrieval

Quantization-based probabilistic feature modeling for kernel...

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8th ACM Multimedia International Workshop on Multimedia Information Retrieval, MIR 2006, co-located with the 2006 ACM International Multimedia Conferenc

作者： Xie, Hua Andreu, Victor Ortega, Antonio Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena CA 91109 Signal and Image Processing Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA 90089

ISBN: (纸本)1595934952

In this paper, a quantization-based probabilistic feature modeling approach is proposed for relevance feedback in content-based image retrieval. We demonstrate its performance by using the resulting models within a support vector machine (SVM) based technique. Each feature component is quantized and mapped to probabilistic quantities representing the likelihood of the image being relevant (and irrelevant). These probabilistic quantities are then used to derive an information divergence-based kernel function for SVM classification which we introduced in earlier work. We show that the proposed method leads to the optimal maximum likelihood solution as the knowledge of the actual underlying probability model improves (i.e.,as the feature space is partitioned into arbitrarily small "regions "and accurate models are known for all regions). vWe investigate several practical quantization designs for feature modeling specifically in relevance feedback applications,where the scarcity of the data and high dimensionality prevent usage of vector quantization and parametric modeling *** proposed framework naturally takes into account the statistics of the data that is available during relevance feedback for the purpose of discriminating between relevant and irrelevant *** with the Corel dataset show that quantizers specifically designed for this application achieve gains over simple uniform quantizers (e.g.,5% to 10% in retrieval accuracy) when combined with our information divergence kernel. This kernel achieves gains (e.g.,17% in retrieval accuracy after first relevance feedback)as compared to the standard radial basis function (RBF) kernel used for SVM-based relevance feedback. Copyright 2006 ACM.

关键词： Content based retrieval

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Feature Selection Based on Adaptive Fuzzy Membership Functions

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自动化学报 2006年第4期32卷 496-503页

作者： XIE Yan-Tao SANG Nong ZHANG Tian-Xu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.

关键词： Membership function feature selection architecture pruning artificial neural networks

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3D reconstruction of the coronary tree from two X-ray angiographic views

3D reconstruction of the coronary tree from two X-ray angiog...

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Medical Imaging 2006: image processing

作者： Sang, Nong Peng, Weixue Li, Heng Zhang, Zhen Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)0819464236

In this paper, we develop a method for the reconstruction of 3D coronary artery based on two perspective projections acquired on a standard single plane angiographic system in the same systole. Our reconstruction is based on the model of generalized cylinders, which are generated by sweeping a two-dimensional cross section along an axis in three-dimensional space. We restrict the cross section to be circular and always perpendicular to the tangent of the axis. Firstly, the vascular centerlines of the X-ray angiography images on both projections are semiautomatically extracted by multiscale vessel tracking using Gabor filters, and the radius of the coronary are also acquired simultaneously. Secondly, the relative geometry of the two projections is determined by the gantry information and 2D matching is realized through the epipolar geometry and the consistency of the vessels. Thirdly, we determine the three-dimensional (3D) coordinates of the identified object points from the image coordinates of the matched points and the calculated imaging system geometry. Finally, we link the consequent cross sections which are processed according to the radius and the direction information to obtain the 3D structure of the artery. The proposed 3D reconstruction method is validated on real data and is shown to perform robustly and accurately in the presence of noise.

关键词： image reconstruction

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LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

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Asian Journal of Control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

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