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3rd International Symposium on Communications, Control, and Signal processing (ISCCSP 2008), vol.1

作者： Mohammad Hosain Kayvanrad Shabnam Sodagari Alireza Nasiri Avanaki Hossein Ahmadi-Noubari Embedded Video (EV) Laboratory Department of ECE National University of Singapore Singapore Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Iran Department of ECE University of British Columbia University of Tehran Iran

A novel reduced reference (RR) method of channel estimation for image transmission through lossy channels is presented. Estimation is based on the amount of distortion the low frequency content of the image or its histogram suffers during transmission. This distortion is computed by sending the low frequency content of the original image or the corresponding histogram to the receiver by means of a robust watermark. Simulations for different types of images and different channel losses yield large amounts of correlation between the estimated Mean Square Error (MSE) and the structural similarity (SSIM) index.

关键词： Image transmission Reduced reference quality assessment Watermarking Two dimensional wavelet transform Histogram

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A Comparative Study of Classification Techniques for Knowledge-Assisted Image Analysis

A Comparative Study of Classification Techniques for Knowled...

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International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS

作者： G. T. Papadopoulos K. Chandramouli V. Mezaris I. Kompatsiaris E. Izquierdo M. G. Strintzis Informatics and Telematics Institute Centre for Research and Technology Hellas Thessaloniki Greece Information Processing Laboratory Electrical & Computer Engineering Department Aristotle University of Thessaloniki Thessaloniki Greece Multimedia and Vision Research Group Queen Mary University of London London UK

In this paper, four individual approaches to region classification for knowledge-assisted semantic image analysis are presented and comparatively evaluated. All of the examined approaches realize knowledge-assisted analysis via implicit knowledge acquisition, i.e. are based on machine learning techniques such as support vector machines (SVMs), self organizing maps (SOMs), genetic algorithm (GA)and particle swarm optimization (PSO). Under all examined approaches, each image is initially segmented and suitable low-level descriptors are extracted for every resulting segment. Then, each of the aforementioned classifiers is applied to associate every region with a predefined high-level semantic concept. An appropriate evaluation framework has been employed for the comparative evaluation of the above algorithms under varying experimental conditions.

关键词： Image analysis Image segmentation Algorithm design and analysis Knowledge acquisition Machine learning Support vector machines Support vector machine classification Self organizing feature maps Genetic algorithms Particle swarm optimization

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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system computer vision Motion detection

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

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International Conference on Information Fusion

作者： Nima Tajbakhsh Babak N. Araabi Hamid Soltanianzadeh Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Iris Feature extraction Discrete cosine transforms Image recognition Databases Training Humans

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Constrained optimization of nonparametric entropy-based segmentation of brain structures

Constrained optimization of nonparametric entropy-based segm...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi Asl Hamid Soltanian-Zadeh School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

We propose a constrained, three-dimensional, nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capture structural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function, which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, constraints are used to improve segmentation quality. These constraints are extracted from training data. Sample results are given for the segmentation of caudate, hippocampus, and putamen, illustrating highly superior performance of the proposed method compared to the most similar methods in the literature.

关键词： Constraint optimization Brain Iterative algorithms Image segmentation Shape Couplings Magnetic resonance Magnetic resonance imaging Principal component analysis Buildings

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Digitally Enhanced Analog Circuits: System Aspects

Digitally Enhanced Analog Circuits: System Aspects

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2008 IEEE International Symposium on Circuits and Systems (ISCAS 2008), vol.2

作者： Boris Murmann Christian Vogel Heinz Koeppl Department of Electrical Engineering University of Stanford Stanford CA USA Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria School of Communication and Computer Sciences EPF Lausanne Lausanne Switzerland

An overview of digital enhancement techniques for analog circuits is presented. Recent research suggests that the high density and low energy of digital circuits can be leveraged to enable a new generation of interface electronics that is based on minimal precision, low complexity analog blocks. Today, examples of enhancement schemes can be found in diverse applications and include nonlinearity compensation of ADCs, predistortion of power amplifiers and mismatch calibration in radio receivers. Since it is often difficult to identify commonalities among these different, but conceptually related schemes, this tutorial paper aims to provide a unified and system-oriented perspective of the field.

关键词： Analog circuits Calibration Signal processing Microprocessors Circuit noise Digital circuits Linearity Power dissipation Signal resolution Digital signal processing

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Updated radiometric calibration for the Landsat-5 thematic mapper reflective bands

Updated radiometric calibration for the Landsat-5 thematic m...

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作者： Helder, Dennis L. Markham, Brian L. Thome, Kurtis J. Barsi, Julia A. Chander, Gyanesh Malla, Rimy Department of Electrical Engineering and Computer Science South Dakota State University Brookings SD 57007 United States Landsat Project Science Office NASA Goddard Space Flight Center Greenbelt MD 20771 United States Remote Sensing Group Optical Sciences Center University of Arizona Tucson AZ 85721 United States Science Systems and Applications Inc. NASA Goddard Space Flight Center Greenbelt MD 20771 United States Science Applications International Corporation U.S. Geological Survey Center for Earth Resources Observation and Science Sioux Falls SD 57198 United States Image Processing Laboratory South Dakota State University Brookings SD 57007 United States

The Landsat-5 Thematic Mapper (TM) has been the workhorse of the Landsat system. Launched in 1984, it continues collecting data through the time frame of this paper. Thus, it provides an invaluable link to the past history of the land features of the Earth's surface, and it becomes imperative to provide an accurate radiometric calibration of the reflective bands to the user community. Previous calibration has been based on information obtained from prelaunch, the onboard calibrator, vicarious calibration attempts, and cross-calibration with Landsat-7. Currently, additional data sources are available to improve this calibration. Specifically, improvements in vicarious calibration methods and development of the use of pseudoinvariant sites for trending provide two additional independent calibration sources. The use of these additional estimates has resulted in a consistent calibration approach that ties together all of the available calibration data sources. Results from this analysis indicate a simple exponential, or a constant model may be used for all bands throughout the lifetime of Landsat-5 TM. Where previously time constants for the exponential models were approximately one year, the updated model has significantly longer time constants in bands 1-3. In contrast, bands 4, 5, and 7 are shown to be best modeled by a constant. The models proposed in this paper indicate calibration knowledge of 5% or better early in life, decreasing to nearly 2% later in life. These models have been implemented at the U.S. Geological Survey Earth Resources Observation and Science (EROS) and are the default calibration used for all Landsat TM data now distributed through EROS. © 2008 IEEE.

关键词： Landsat

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A Journey from signal processing to surveillance

A Journey from signal processing to surveillance

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2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007

作者： Chen, Tsuhan Advanced Multimedia Processing Laboratory Dept. of Electrical Computer Engineering Carnegie Mellon University Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States IEEE Signal Processing Society

ISBN: (纸本)9781424416967

Traditionally, signal processing is considered simply lowlevel 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. © 2007 IEEE.

关键词： Hidden Markov models

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Performance of a self-paced brain computer interface on data contaminated with eye-movement artifacts and on data recorded in a subsequent session

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Computational Intelligence and Neuroscience 2008年第1期2008卷 749204页

作者： Fatourechi, Mehrdad Ward, Rabab K. Birch, Gary E. Image and Signal Processing Laboratory Department of Electrical and Computer Engineering University of British Columbia Vancouver BC V6T 1Z4 Canada Institute for Computing Information and Cognitive Systems University of British Columbia Vancouver BC V6T 1Z4 Canada Neil Squire Society Burnaby BC V5M 3Z3 Canada

The performance of a specific self-paced BCI (SBCI) is investigated using two different datasets to determine its suitability for using online: (1) data contaminated with large-amplitude eye movements, and (2) data recorded in a session subsequent to the original sessions used to design the system. No part of the data was rejected in the subsequent session. Therefore, this dataset can be regarded as a pseudo-online test set. The SBCI under investigation uses features extracted from three specific neurological phenomena. Each of these neurological phenomena belongs to a different frequency band. Since many prominent artifacts are either of mostly low-frequency (e.g., eye movements) or mostly high-frequency nature (e.g., muscle movements), it is expected that the system shows a fairly robust performance over artifact-contaminated data. Analysis of the data of four participants using epochs contaminated with large-amplitude eye-movement artifacts shows that the system's performance deteriorates only slightly. Furthermore, the system's performance during the session subsequent to the original sessions remained largely the same as in the original sessions for three out of the four participants. This moderate drop in performance can be considered tolerable, since allowing artifact-contaminated data to be used as inputs makes the system available for users at ALL times.

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A first-order mechanical device to model traumatized craniovascular biodynamics

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Journal of Medical Devices, Transactions of the ASME 2007年第1期1卷 89-95页

作者： Kohles, Sean S. Mangan, Ryan W. Stan, Edward McNames, James Kohles Bioengineering Portland OR 97214-5135 United States Department of Mechanical and Materials Engineering Portland State University Portland OR 97207-0751 United States Department of Electrical and Computer Engineering Portland State University Portland OR 97207-0751 United States Biomedical Signal Processing Laboratory Department of Electrical and Computer Engineering Portland State University Portland OR 97207-0751 United States Department of Surgery Oregon Health and Science University Portland OR 97239-3098 United States

Mathematical models currently exist that explore the physiology of normal and traumatized intracranial function. Mechanical models are used to assess harsh environments that may potentially cause head injuries. However, few mechanical models are designed to study the adaptive physiologic response to traumatic brain injury. We describe a first-order physical model designed and fabricated to elucidate the complex biomechanical factors associated with dynamic intracranial physiology. The uni-directional flow device can be used to study interactions between the cranium, brain tissue, cerebrospinal fluid, vasculature, blood, and the heart. Solid and fluid materials were selected to simulate key properties of the cranial system. Total constituent volumes (solid and fluid) and volumetric flow (650 ml/min) represent adult human physiology, and the lengths of the individual segments along the flow-path are in accord with Poiseuille's equation. The physical model includes a mechanism to simulate autoregulatory vessel dynamics. Intracranial pressures were measured at multiple locations throughout the model during simulations with and without post-injury brain tissue swelling. Two scenarios were modeled for both cases: Applications of vasodilation/constriction and changes in the head of bed position. Statistical results indicate that all independent variables had significant influence over fluid pressures measured throughout the model (p < 0.0001) including the vasoconstriction mechanism (p=0.0255). The physical model represents a first-order design realization that helps to establish a link between mathematical and mechanical models. Future designs will provide further insight into traumatic head injury and provide a framework for unifying the knowledge gained from mathematical models, injury mechanics, clinical observations, and the response to therapies. Copyright © 2007 by ASME.

关键词： Biomechanics

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