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Motion Compensated Frame Interpolation Using Adaptive Adjacency Pixel Information

Motion Compensated Frame Interpolation Using Adaptive Adjace...

引用

International Conference on computer Graphics, Imaging and Visualization, CGIV

作者： Hyeongchul Oh Joohyun Lee Changki Min Jechang Jeong Image Communication and Signal Processing Laboratory Department of Electrical and Computer Engineering Hanyang University Seoul South Korea

We propose an adaptive motion compensated frame interpolation scheme which is capable of developing a frame rate from a lower number into a higher number and a decoded video quality at the decoder. The proposed algorithm utilizes the preliminary frames of the forward and backward directions using bilateral prediction. In the processing of the preliminary frames, an additional interpolation is performed to fill the occlusion areas. If the calculated values between the reference and current frames are larger than the predetermined threshold, the block is chosen as the occlusion area. In addition, we performed a re-search in order to acquire the best blocks, taking into account the number of available adjacent blocks for the occlusion areas. The experimental results show that the performance of the proposed algorithm has better PSNR and visual quality than those of the conventional methods.

关键词： Interpolation Pixel Robustness PSNR Motion estimation Algorithm design and analysis Motion compensation

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Online signature verification using combination of two classifiers

Online signature verification using combination of two class...

引用

Iranian Machine Vision and Image processing (MVIP)

作者： M. Saeidi R. Amirfattahi A. Amini M. Sajadi Digital Signal processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

The objective of signature verification is to distinguish forgery signature from genuine one. Online signature is the one which is registered through electronic devices such as digitizers and stored on computers in time sequence form. In this kind of signatures in addition to location information, time information such as speed and acceleration is stored. In this paper after accomplishment of some pre-processing procedures like normalization of signature size, smoothing and elimination of rotation on signatures using algorithms based on extremum matching of signals and ant colony, their time duration will be equalized. Afterwards, similarities between signatures will be determined using extended regression and finally will try to distinguish between forgery signatures from genuine one using support vector machine (SVM). The suggested online verification system is tested on SVC2004 signature set which is related to the first international signature verification competition and results are compared to respective results of participants. The results state that suggested method exhibits equal error rate (EER) of %4.3 in skilled forger group.

关键词： Forgery Mathematical model Equations Support vector machines Training Error analysis

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Adapting a MIMO/phased-array radar transmit beampattern to target location

Adapting a MIMO/phased-array radar transmit beampattern to t...

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International Workshop on Cognitive Information processing

作者： Fuhrmann, Daniel R. Browning, J. Paul Rangaswamy, Muralidhar Department of Electrical and Computer Engineering Michigan Technological University Houghton MI 49931 United States U.S. Air Force Research Laboratory Sensors Directorate Radar Signal Processing Branch Wright-Patterson AFB OH United States

ISBN: (纸本)9781424464593

Proposed MIMO and hybrid MIMO/phased array (HMPAR) radar systems have the potential for tremendous flexibility in the choice of the transmit beampattern, through the selection of multiple transmitted signals. This paper considers how one might exploit that flexibility in light of prior information or uncertainty in target spatial location, for parameter estimation or tracking applications. We first consider an idealized problem of distributing energy across multiple target sites given a prior probability distribution on those sites. It shown that the optimal allocation of energy would be proportional to the square root of the prior probability. Second, we propose a method to approximate this optimal distribution of energy using a MIMO radar or HMPAR radar system. The method chooses signals that realize an intrapulse beamscan over the region of interest, with a nonuniform distribution of scan points matched to the desired distribution of energy. © 2010 IEEE.

关键词： MIMO radar

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Improved learning in grid-to-grid neural network via clustering

Improved learning in grid-to-grid neural network via cluster...

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International Joint Conference on Neural Networks (IJCNN)

作者： W. White K. Iftekharuddin A. Bouzerdoum Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis TN USA Department of Electrical and Computer Engineering University of Memphis TN USA School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong NSW Australia

The maze traversal problem involves finding the shortest distance to the goal from any position in a maze. Such maze solving problems have been an interesting challenge in computational intelligence. Previous work has shown that grid-to-grid neural networks such as the cellular simultaneous recurrent neural network (CSRN) can effectively solve simple maze traversing problems better than other iterative algorithms such as the feedforward multi layer perceptron (MLP). In this work, we investigate improved learning for the CSRN maze solving problem by exploiting relevant information about the maze. We cluster parts of the maze using relevant state information and show an improvement in learning performance. We also study the effect of the number of clusters on the learning rate for the maze solving problem. Furthermore, we investigate a few code optimization techniques to improve the run time efficiency. The outcome of this research may have direct implication in rapid search and recovery, disaster planning and autonomous navigation among others.

关键词： Euclidean distance Kalman filters Training Navigation Artificial neural networks Testing

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Techniques for automatic magnetic resonance image classification

Techniques for automatic magnetic resonance image classifica...

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International Conference on Genetic and Evolutionary Computing

作者： Chen, Hsian-Min Chen, Shih-Yu Chai, Jyh Wen Chen, Clayton Chi-Chang Wu, Chao-Cheng Ouyang, Yen-Chieh Tsai, Ching Tsorng Yang, Ching-Wen Lee, San-Kan Chang, Chein-I Department of Biomedical Engineering Hungkuang University Taichung Taiwan 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 Electrical Engineering National Taipei University of Technology Taipei 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

Designing and developing automatic techniques for magnetic resonance images (MR) for data analysis is very challenging. One popular and public available method, FAST (FMRIB Automatic Segmentation Tool) has been widely used for automatic brain tissue segmentation for this purpose. This paper investigates limitations of this software algorithm on implementation and further develops a new approach to automatic MR brain tissue classification. The proposed new technique first implements an unsupervised training sample generation process (UTSGP) which includes a Pixel Purity Index (PPI) to generate an initial set of training samples that are further refined by a Support Vector Machine. The resulting training samples are then as a set of training samples for an Iterative Fisher's Linear Discriminant Analysis (IFLDA) which implements FLDA iteratively to improve classification. In order to conduct a fair comparison synthetic images are used for performance evaluation. Experimental results show that our proposed technique is superior in practical implementation to this software algorithm in several aspects of generalization ability, flexibility of choosing number of classes to be classified, avoidance of inconsistent results caused by different initial conditions. © 2010 IEEE.

关键词： Support vector machines

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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...

引用

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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