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作者： Mohammadzadeh, M. Shahabadi, M. Soltanian-Zadeh, H. Tavakoli, A. Rafiei, B. Javidnia, D. Oghabian, M.A. Department of Physics Amir-Kabir University of Technology Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Electrical Engineering Amir-Kabir University of Technology Tehran Iran Medical Imaging Center Imam Khomeyni Hospital Tehran Iran Research Center for Science and Technology in Medicine Tehran University of Medical Sciences Tehran Iran

In this paper, design principles and application of a thin and flexible intravascular top hat monopole probe with increased signal-to-noise ratio (SNR) and improved longitudinal and radial coverage are described and compared with the conventional monopole probe. The top hat probe is constructed by removing a segment of the shield of a coaxial cable. A flexible thin copper foil in contact with the inner conductor of the cable is added to the end section of the cable. The copper foil acts as an antenna top hat load increasing the uniformity of the current distribution on the probe and establishes a uniform region of SNR distribution around the probe. Improvement of the SNR distribution of the top hat probe relative to the conventional monopole probe is evaluated using quantitative indices. Experimental results show that for the top hat probe, the ratio of the maximum image SNR to its relative standard deviation (SR) is 2.73 times higher than that of a conventional probe. © 2006 IOP Publishing Ltd.

关键词： Medical imaging

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Multi-Modal Human Verification Using Face and Speech

Multi-Modal Human Verification Using Face and Speech

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IEEE International Conference on computer Vision Systems (ICVS)

作者： Changhan Park Joonki Paik Taewoong Choi Soonhyob Kim Youngouk Kim J. Namkung Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Multimedia Signal Processing Laboratory Kwangwoon University Seoul South Korea Precision Machinery Center Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University Seoul South Korea

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time.

关键词： Humans Speech Face detection Face recognition Biometrics Principal component analysis Feature extraction Hidden Markov models image edge detection Laboratories

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Multi-modal human verification using face and speech

Multi-modal human verification using face and speech

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Fourth IEEE International Conference on computer Vision Systems, ICVS'06

作者： Park, Changhan Choi, Taewoong Kim, Youngouk Kim, Soonhyob Namkung, Jaechan Paik, Joonki Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-dong Tongjak-Ku Seoul 156-756 Korea Republic of Multimedia Signal Processing Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Precision Machinery Center Korea Electronics Technology Institute 401-402 B/D 193 Yakdae-dong Wonmi-Gu Puchon Kyunggido 420-140 Korea Republic of

ISBN: (纸本)0769525067

关键词： Face recognition

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CNNUM-Based Methods Using Deformable Contours on Smooth Boundaries

CNNUM-Based Methods Using Deformable Contours on Smooth Boun...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Tamas Szabo Peter Szolgay Department of Image Processing and Neurocomputing Faculty of Information Technology University of Pannonia Veszprem Hungary Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper two methods are presented. A CNNUM-based method is shown to quantify the displacement of the normal interhemisperic bilateral symmetry line. The method uses a deformable open contouring technique. Anothe... 详细信息

关键词： Active contours Computed tomography Magnetic resonance Anatomical structure image segmentation Biomedical imaging Electronic mail computer networks Pixel image resolution

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Determination of the Grey Level Ranks for the Segmentation of Textured images

Determination of the Grey Level Ranks for the Segmentation o...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Z. Ameur A. Adane S. Ameur Faculty of Electrical Engineering and Computer Science Department of Electronics Laboratory of Random Phenomena Analysis and Modeling LAMPA Mouloud Mammeri University Tizi Ouzou Algeria Faculty of Electronics and Computer Science Department of Telecommunications Laboratory of Image Processing and Radiation University of Sciences and Technology of Algiers U. S. T. H. B. Bab-Ezzouar Algeria

In many cases, an image is made of various types of texture. Such diversity can be usefully exploited to get a suitable decomposition of the image into typical classes and then, identify its constitutive elements. Among the approaches used to segment textured images, those based on the statistical analysis of the neighborhood of each pixel seem to be most efficient. In this paper, this kind of method is implemented, which consists in coding the pixels surrounding each point of the image by taking into account the path traveling through them and their grey levels. The rank vectors namely the codes obtained for all the possible paths, are then classified using the K-means algorithm. Considering the 24- rank vectors, this method is tested on different images of the Brodatz album and compared with Laws filters and GLCM. It yields a satisfactory reproduction of the image contours and a classification ratio exceeding 98 %. The 24 rank based-method is also applied to meteorological images collected by Meteosat over Europe and North Africa during December 1994. It is found that these images can be segmented into eight typical classes assignable to the soils, the seas and the clouds observed in the regions under study.

关键词： image segmentation Pixel Statistical analysis image coding Testing Filters Meteorology Europe Africa Soil

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Brain MR image segmentation using tabu search and hidden markov random field model

Brain MR image segmentation using tabu search and hidden mar...

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2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Nanda, P.K. Patra, D. Pradhan, A. Department of Electrical Engineering Image Processing and Computer Vision Laboratory National Institute of Technology Rourkela Orissa 769008 India

ISBN: (纸本)0972741216

In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Field (GHMRF) is used to model the available degraded image. In supervised framework, the apriori image MRF model parameters as well as the GHMRF model parameters are assumed to be known. The class labels are estimated using the Maximum a Posteriori (MAP) estimation criterion. In unsupervised framework, the problem of model parameter estimation and label estimation is formulated in Expectation Maximization (EM) framework. The labels are estimated using the proposed Tabu Search algorithm while the model parameters are the maximum likelihood estimates. Our proposed algorithm yields results with arbitrary initial paramater set and thus overcomes the problem of proper choice of initial parameters. The results obtained are comparable with the results obtained by using the algorithm proposed by Zhang ***. [15] , where the Iterated Conditional Mode (ICJM) algorithm is used for computing the MAP estimates. Copyright © IICAI 2005.

关键词： Tabu search

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Fast DCT-I, DCT-III, and DCT-IV via Moments

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Eurasip Journal on Applied Signal processing 2005年第12期2005卷 1902-1909页

作者： Liu, J.G. Liu, Y.Z. Wang, G.Y. Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China Department of Computer Science and Engineering China University of Geosciences Wuhan 430074 China Key Laboratory of State Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. This enables us to use computational techniques developed for computing moments to compute DCTs efficiently. We demonstrate this by applying our earlier systolic solution to this problem. The method can also be applied to multidimensional DCTs as well as their inverses. © 2005 Hindawi Publishing Corporation.

关键词： Method of moments

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Support vector machines for face recognition

Support vector machines for face recognition

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2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Hareesha, K.S. Gangashetty, Suryakanth V. Ramaswamy, V. Department of Computer Science and Engineering Image Processing Laboratory Bapuji Institute of Engineering and Technology Davangere - 577 004 Karnataka India

ISBN: (纸本)0972741216

Face recognition is one of the challenging problems in human-computer interaction. An automated face recognition system requires an efficient method for detection of face region in the image sequence, extraction of facial features, and construction of a recognition model. In recent years, support vector machines (SVMs) have demonstrated excellent performance in a variety of pattern recognition problems. In this paper, we apply SVMs for face recognition (recognition model). Multi-class recognition system using SVMs are built using onc-against-the-rest approach. In this approach, one SVM model is built for each persons face (class). For each SVM model an optimal hyperplane is constructed in the kernel feature space to separate the examples of a class from the examples of all the other classes. SVMs learn the boundary regions between patterns of two classes by mapping the patterns into a higher dimensional space, and seeking a separating hyperplane, so as to maximize its distance from the closest training examples. SVM based approach for face recognition has been demonstrated for partial CMU face data base. The face recognition system is evaluated on faces of 10 different persons. For each person there arc 75 faces. The results of our studies show that, the system gives about 100% detection rate. Copyright © IICAI 2005.

关键词： Support vector machines

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A Local image Interpolation Method Based On Gradient Analysis

A Local Image Interpolation Method Based On Gradient Analysi...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Tian Yan Liu Bin Li Tao Department of electronic and information engineering Huazhong University of Science & Technology School of computer science and technology Huazhong University of Science & Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology

ISBN: (纸本)0780394224

image interpolation has been widely used and studied in the fields of image *** the different complexities along the different directions,a novel image interpolation method based on gradient analysis is presented in this ***,for each point that need to be interpolated,it's the gradient values along the horizontal and vertical directions are estimated ***,different interpolation methods are carried out along these two directions according to the gradient values,that is a higher order interpolation method is applied if the gradient value is greater than certain threshold;otherwise,a lower order interpolation method is *** method gives an attention to the precision and complexity of interpolation procedure. Experimental results show that the proposed method is feasible and promising.

关键词： Gradient image interpolation root mean square error

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Using a free-parts representation for visual speech recognition

Using a free-parts representation for visual speech recognit...

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Digital Imaging Computing: Techniques and Applications, DICTA 2005

作者： Lucey, Patrick Lucey, Simon Sridharan, Sridha Speech Audio Image and Video Research Laboratory Queensland University of Technology GPO Box 2424 Brisbane 4001 Australia Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 United States

ISBN: (纸本)0769524672

Motivated by the success of free-parts based representations in face recognition, we have attempted to address some of the problems associated with applying such a philosophy to the task of speaker-independent visual speech recognition. A major problem with canonical area-based approaches in automatic visual speech recognition is the dependence these approaches have on locating and tracking the speaker's region of interest (ROI) correctly. By employing a free-parts representation, we assume that the position/structure of patches within the mouth image can be relaxed so they can "freely" move to varying extents, hence reducing the influence of the front-end effect. In this paper, we show that by using a free-parts representation we gain some robustness against the problem of ROI localisation and tracking compared to current area-based feature extraction techniques such as the discrete cosine transform (DCT). Also in this paper, we expose the importance of representation for the task of visual speech recognition highlighted by the poor results current representations yield. © 2005 IEEE.

关键词： Speech recognition

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