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Fusion of visible and synthesised near infrared information for face authentication

Fusion of visible and synthesised near infrared information ...

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IEEE International Conference on Image processing

作者： Seyed Mohammad Mavadati Mohammad Taghi Sadeghi Josef Kittler Signal Processing Research Laboratory Department of Electrical & Computer Engineering Yazd University Iran CVSSP University of Surrey Guildford Surrey UK

Changes in illumination conditions can cause drastic variations in face appearance and affect the performance of a face authentication system. Near infrared (NIR) face imaging systems have been proposed as a promising way towards illumination invariant face verification. We show that when NIR face images cannot be observed, learning the relationship between NIR information and the corresponding visible images can provide useful complementary information about visible light image data. In particular, we use Canonical Correlation Analysis (CCA) to synthesise the NIR eigenfaces from their corresponding visible ones. In this paper, the verification performance of a CCA-based synthesising algorithm is developed first. Although, synthesised NIR images do not perform as well as the real NIR, it is shown that by fusing the visible and synthesised near infrared information at the score level, the performance of the authentication system considerably improves.

关键词： Face Lighting Correlation Support vector machines Authentication Databases Linear regression

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Volume-based magnetic resonance brain image classification

Volume-based magnetic resonance brain image classification

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International Conference on Genetic and Evolutionary Computing

作者： Chiou, Yaw-Jiunn Chai, Jyh-Wen Chen, Clayton Chi-Chang Chen, Shih-Yu Chen, Hsian-Min Ouyang, Yen-Chieh Su, Wu-Chung Tsai, Ching Tsorng Yang, Ching-Wen Lee, San-Kan Chang, Chein-I Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Section of Radiology College of Medicine China Medical University Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung Taiwan Department of Biomedical Engineering Hungkuang University Taichung Taiwan Computer Science Department Tunghai University Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780769542812

This paper develops a volume-based technique, called Volume Sphering Analysis (VSA) which can process all acquired Magnetic Resonance (MR) image slices-formed image cube using only one set of training samples obtained from an image slice. So, several significant advantages and benefits can be gained from our proposed VSA. In the past, when MR image classification is performed, each image slice requires its own specific training samples and training samples obtained from one slice are not applied to another slice. The VSA allows users to reduce computational time. In addition, it saves significant effort in selecting training samples for each of image slices. Thirdly, it is robust to all image slices compared to the traditional one-slice MR image classification which is sensitive to each image slice. Experimental results demonstrate that the VSA performs as well as does that using specifically selected training samples for individual image slices. © 2010 IEEE.

关键词： Support vector machines

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A LOW COMPLEXITY METHOD FOR DETECTION OF TEXT AREA IN NATURAL IMAGES

A LOW COMPLEXITY METHOD FOR DETECTION OF TEXT AREA IN NATURA...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Katherine L. Bouman Golnaz Abdollahian Mireille Boutin Edward J. Delp Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109 USA Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette Indiana USA

ISBN: (纸本)9781424442959

We propose a low complexity method for segmentation of text regions in natural images. This algorithm is designed for mobile applications (e.g. unmanned or hand-held devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, character set or the camera angle. However, the text is assumed to be located on a piecewise homogeneous background with a contrasting color. We have deployed our method on a Nokia N800 Internet tablet as part of a system for automatic detection and translation of outdoor signs. Our experiments show that the 0.3 megapixel images taken by the phone camera can be accurately segmented within the device in a fraction of a second.

关键词： Text Detection Text Segmentation Sign Detection Mobile Devices Mobile devices text segmentation images lens angle hand-held equipment Mobile Applications UNMANNED automatic detection Energy sources

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Wireless tomography, part I: A novel approach to remote sensing

Wireless tomography, part I: A novel approach to remote sens...

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International Waveform Diversity and Design Conference

作者： Qiu, R.C. Wicks, M.C. Li, L. Hu, Z. Hou, S.J. Chen, P. Browning, J.P. Cognitive Radio Insitute Department of Electrical and Computer Engineering Tennessee Technological University Cookeville TN United States Air Force Research Laboratory Sensors Directorate Rome NY United States Department of Mathematics Syracuse University Syracuse NY United States Air Force Research Laboratory Sensors Directorate Radar Signal Processing Branch Dayton OH United States

ISBN: (纸本)9781424482009

Wireless tomography, a novel approach to remote sensing, is proposed in Part I of this series. The methodology, literature review, related work, and system engineering are presented. Concrete algorithms and hardware platforms are implemented to demonstrate this concept. Self-cohering tomography is studied in depth. More research will be reported, following this initiative.

关键词： Tomography

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A NEW APPROACH FOR ROBUST REALTIME VOICE ACTIVITY DETECTION USING SPECTRAL PATTERN

A NEW APPROACH FOR ROBUST REALTIME VOICE ACTIVITY DETECTION ...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： M. H. Moattar M. M. Homayounpour Nima Khademi Kalantari Laboratory for Intelligent Signal and speech Processing Computer Engineering and Information Technology Department Amirkabir University of Technology Tehran Iran Electrical Engineering Department Amirkabir University of Technology Tehran Iran

ISBN: (纸本)9781424442959

In this paper a Voice Activity Detection approach is proposed which applies a voting algorithm to decide on the existence of speech in audio signal. For this purpose, the proposed approach uses three different short time features along with the pattern of spectral peaks of every frame. Spectral peaks pattern is appropriate for determining vowel sounds in speech signal even in the presence of noise. Therefore this measure can be applicable in voice activity detection in which the vowels characterize the speech signal. Experiments show that incorporating this measure along with our recently proposed approach for VAD, will improve the results of the algorithm considerably while imposing little computational overhead. The proposed approach is evaluated on different datasets with various noises and SNR levels and satisfying results are achieved.

关键词： Voice Activity Detection Spectral Peaks Pattern Spectral Flatness Activity Detection Voice Signal Voice Noise audio signals voice activity

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Bacterial Foraging Algorithm for neutron radiography image quality improvement

Bacterial Foraging Algorithm for neutron radiography image q...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： S. Saadi A. Kouzou A. Guessoum M. Bettayeb University Ziane Achour of Djelfa Algeria Department of Electronics Signal and image Processing Laboratory USDB Burgas Algeria Department of Electrical and Computer Engineering University of Sharjah UAE

We want to implement a new optimal approach for image restoration problem, which is useful for neutron radiography images enhancement to assist the physician interpreter on his evaluation. Our approach is based on using swarm intelligence optimization algorithms to solve a least squares minimization ill-posed problem, using Bacterial Foraging Optimization (BFO) Algorithm. To get smoothed images in presence of noise, a Laplacian constraint is introduced for regularization purpose.

关键词： Wiener filter Image restoration Radiography Strontium

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ADVANCED SIGNALING STRATEGIES FOR THE HYBRID MIMO PHASED-ARRAY RADAR

ADVANCED SIGNALING STRATEGIES FOR THE HYBRID MIMO PHASED-ARR...

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IEEE Radar Conference

作者： Daniel R. Fuhrmann J. Paul Browning Muralidhar Rangaswamy Department of Electrical and Computer Engineering Michigan Technological University U.S. Air Force Research Laboratory Sensors Directorate Radar Signal Processing Branch

ISBN: (纸本)9781424458110

The Hybrid MIMO Phased Array Radar, or HMPAR, is a notional concept for a multisensor radar architecture that combines elements of traditional phased-array radar with the emerging technology of Multiple-Input Multiple Output (MIMO) radar. A HMPAR comprises a large number, MP, of T/R elements, organized into M subarrays of P elements each. Within each subarray, passive element-level phase shifting is used to steer transmit and receive beams in some desired fashion. Each of the M subarrays are in turn driven by independently amplified phase-coded signals. This paper proposes new transmit signal selection strategies based on the observation that some MIMO signal sets, such as those proposed by us previously, cause a very rapid sequential or raster scan across some field of view. Exploiting this property allows one to create and process multiple beams simultaneously. Furthermore, there exists a range-angle coupling in the transmit and receive signals that may lead to high-resolution target localization.

关键词： Transposons multiple input multiple output systems radar Phase shift phased array HYBRID TRANSMITTING raster scanning Beams and girders phased array radar field of view

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A comparative study to select an image deconvolution method

A comparative study to select an image deconvolution method

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： S. Saadi A. Kouzou A. Guessoum M. Bettayeb Department of Electronics University Ziane Achour of Djelfa Algeria Department of Electronics Signal and Image Processing Laboratory USDB Burgas Algeria Department of Electrical and Computer Engineering University of Sharjah UAE

Image deconvolution is an important subject in image processing. It is an ill-posed inverse problem, so regularization techniques are used to solve this problem by adding constraints to the objective function. Various popular algorithms have been developed to solve such problem. This paper studies various approaches to the nonlinear degraded images restoration problem which are useful in many images enhancement applications. Swarm intelligence is applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method which is often used. In this work, we attempt to reconstruct or recover corrupted images that have been degraded during acquisition; using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition (TSVD) method is also considered for image deconvolution in this paper. A comparison between these methods made on examples is included.

关键词： Noise measurement

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Image encryption using the reciprocal-orthogonal parametric transform

Image encryption using the reciprocal-orthogonal parametric ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Saad Bouguezel M. Omair Ahmad M. N. S. Swamy Scientific Instrumentation Laboratory Department of Electronics Faculty of Engineering University Farhat Abbas of Setif Setif Algeria Center of Signal processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal Canada

Discrete transforms have been widely used in various signal processing applications. Specifically, transform-based data encryption techniques have become attractive for many recent communication systems. In this paper, we propose a fast and efficient image encryption method based on the reciprocal-orthogonal parametric (ROP) transform. By exploiting the properties of the ROP transform, we show that its independent parameters can successfully be used as an additional secret key for encryption. Experiments results carried clearly show the efficiency of the proposed encryption method.

关键词： Cryptography Discrete transforms Signal processing Watermarking Instruments Laboratories Image coding Application software Matrix decomposition Software algorithms

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A vector SIFT operator for interest point detection in hyperspectral imagery

A vector SIFT operator for interest point detection in hyper...

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Workshop on Hyperspectral Image and Signal processing: Evolution in Remote Sensing, WHISPERS

作者： Leidy P. Dorado-Muñoz Miguel Velez-Reyes Amit Mukherjee Badrinath Roysam Laboratory of Applied Remote Sensing and Image Processing University of Puerto Rico Puerto Rico Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute NY USA

An algorithm for automated extraction of interest points (IP) in hyperspectral images is presented. IP are features of the image that capture information from its neighbors and are distinctive and stable under translation and rotation. IP operators for gray level images were proposed more than a decade ago and have since been studied extensively. IP are helpful in data reduction to reduce the computational burden of various algorithms by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. The vector SIFT approach extends Lowe's IP operator that uses local extrema of Difference of Gaussian at multiple scales to detect interest point in gray level images by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Vector anisotropic diffusion is used for scale-space generation which enhances edges and improves IP detection. Experiments with hyperspectral images of different spatial resolutions and evaluation of IP found based on image registration is presented.

关键词： Hyperspectral imaging Pixel Detectors Feature extraction Image edge detection IP networks

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