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International Conference on Pattern Recognition

作者： Osman G. Sezer Joseph L. Mundy Yucel Altunbasak David B. Cooper Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA Laboratory for Engineering Man/Machine Systems Brown University Providence RI USA

ISBN: (纸本)9781424421749

This paper presents a new normalcy model of a scene for change detection using images taken from multiple views and varying illumination conditions. Each coregistered pixel site is statistically modeled by a probability distribution conditioned on a set of pixels in a non-local neighborhood that are less likely to be affected by a change that happens at the pixel of interest. These ldquonon-compact neighborsrdquo are located using information theoretic approaches. The associated change detection algorithm is called non-compact Markovian Likelihood (NorMaL), which predicts normalcy of a scene based on non-compact neighborhoods using non-parametric conditional density estimation.

关键词： Layout Lighting Detection algorithms Probability distribution Satellites Markov random fields Pixel signal processing image processing Laboratories

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Ant Colony Optimization Algorithm for Feature Selection and Classification of Multispectral Remote Sensing image

Ant Colony Optimization Algorithm for Feature Selection and ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Lintao Wen Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

In classification of a multispectral remote sensing image, it is usually difficult to obtain higher classification accuracy if we only consider the image's spectral feature or texture feature alone. In this paper, we present a new approach by applying the Ant Colony Optimization (ACO) algorithm to find a multi-feature vector composed of spectral and texture features in order to get a better result in the classification. The experimental results show that ACO algorithm is helpful in subset searching of the features used to classify the multispectral remote sense image. Using the combination of the spectral and texture features obtained by ACO in classification always produces a better accuracy.

关键词： Ant colony optimization Remote sensing Remote monitoring Multispectral imaging image analysis Data mining Feature extraction Entropy image processing Pattern recognition

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Comparison of discriminant analysis methods applied to diffractive optically variable image

Comparison of discriminant analysis methods applied to diffr...

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IEEE International Workshop on Anti-counterfeiting, Security, Identification, ASID

作者： Rukun Hu Youji Feng Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

As a kind of powerful anti-counterfeiting device, diffractive optically variable image (DOVI) has been developed and widely used in information security field. However, the identification of DOVI today by bare eyes is not reliable. In this paper we investigate the recognition of DOVI with machine learning method, and five kinds of algorithms, namely quadratic discriminate analysis (QDA), linear discriminate analysis (LDA), regularized discriminate analysis (RDA), leave-one-out covariance matrix estimate (LOOC), and Kullback-Leibler information measure based method (KLIM) are applied to the recognition of DOVI. Considering both time cost and correct classification rate, KLIM classifier exceeds others.

关键词： image analysis Optical diffraction Information analysis Algorithm design and analysis Optical devices Information security Eyes Learning systems Machine learning algorithms Linear discriminant analysis

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Experimental Study of Discriminant Method with Application to Fault-Prone Module Detection

Experimental Study of Discriminant Method with Application t...

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International Conference on Computational Intelligence and Security

作者： Gege Guo Ping Guo School of Computer Science and Technology Beijing Institute of Technology Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781424441969

Some techniques have been applied to improving software quality by classifying the software modules into fault-prone or non fault-prone categories. This can help developers focus on some high risk fault-prone modules. In this paper, a distribution-based Bayesian quadratic discriminant analysis (D-BQDA) technique is experimental investigated to identify software fault-prone modules. Experiments with software metrics data from two real projects indicate that this technique can classify software modules into a proper class with a lower misclassification rate and a higher efficiency.

关键词： Fault detection Software quality Support vector machines Support vector machine classification Pattern recognition Software metrics Bayesian methods Fault diagnosis Software performance Computational intelligence

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General linear model and inference for near infrared spectroscopy using global confidence region analysis

General linear model and inference for near infrared spectro...

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IEEE International Symposium on Biomedical Imaging

作者： Sungho Tak Kwang-Eun Jang Jinwook Jung Jaeduck Jang Jong Chul Ye Bio-Imaging & Signal Processing Laboratory Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology Daejeon South Korea

ISBN: (纸本)9781424420025

Near infared spectroscopy (NIRS) is a non-invasive method to measure the brain activity as the changes of hemoglobin oxygenation through the intact skull. In this paper, we statistically analyze the NIRS data based on general linear model (GLM) and propose a new theory for making inference using Sun's tube formula. More specifically, we calculate the p-values as the excursion probability of an inhomogeneous Gaussian random field on a two dimensional representation manifold that are dependent on the structure of error co variance matrix and the interpolating kernels. These powerful tools for excursion probability allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis.

关键词： Infrared spectra Probability Optical scattering Optical attenuators Brain Kernel signal resolution Skull Sun Covariance matrix

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An SMR based advance resource reservation scheme for combined mobility and QoS Provisioning

An SMR based advance resource reservation scheme for combine...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Hao Wang David I. Laurenson Jane Hillston Institute for Digital Communications Joint Research Institute for Signal & Image Processing School of Engineering & Electronics University of Edinburgh UK Laboratory for Foundations of Computer Science School of Informatics University of Edinburgh UK

One of the major problems of deploying RSVP in the mobile environment is called the advance resource reservation problem. If an RSVP reservation path is reserved in advance in the subnet that a mobile node will visit, the mobile node can continue its QoS session smoothly when it hands over to that subnet. However, if too many network resources are used for advance reservation, new QoS sessions originating from that subnet will experience a higher probability of being blocked needlessly. In this paper, we propose a new advance resource reservation scheme that properly constrains the amount of advance reservations in a subnet and only allows the mobile nodes with large value of session-to-mobility ratio (SMR) to make advance reservation. We evaluate the proposed scheme and the results show that our scheme can effectively reduce both active and passive reservation blocking probabilities and achieves a better utilisation of the network resources, especially when the traffic intensity is high.

关键词： Quality of service Protocols Communication system traffic control Digital communication signal processing image processing Computer science Informatics Mobile computing Telecommunication traffic

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Evaluation of RSVP and Mobility-Aware RSVP Using Performance Evaluation Process Algebra

Evaluation of RSVP and Mobility-Aware RSVP Using Performance...

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IEEE International Conference on Communications (ICC)

作者： H. Wang D. I. Laurenson J. Hillston Institute for Digital Communications Joint Research Institute for Signal & Image Processing School of Engineering & Electronics University of Edinburgh UK Laboratory for Foundations of Computer Science School of Informatics University of Edinburgh UK

As a resource reservation mechanism, the Resource ReSerVation Protocol (RSVP) faces a lot of challenges when applying it to the wireless and mobile networks. The interworking problems of RSVP and mobility management protocols have been extensively discussed over the last decade. As the solutions of this problem, mobility-aware RSVP schemes that integrate RSVP and micro-mobility management are becoming more and more popular. Therefore, the investigation on how much they improve the performance of the basic RSVP is necessary and useful. Instead of the traditional simulation based approaches, in this paper we introduce a formal performance evaluation formalism, named Performance Evaluation Process Algebra (PEPA), and employ it to investigate the performance of the basic RSVP and mobility-aware RSVP. Important performance metrics such as handover blocking probability and signalling cost are presented.

关键词： Algebra Protocols Quality of service Measurement Mobile radio mobility management Costs Communications Society Digital communication signal processing image processing

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Novel way achieving 3D reconstruction of actual human face using multi images

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2008年第4期36卷 661-666页

作者： Hou, Wen-Guang Chan, Tai-Wai Ding, Ming-Yue Image Processing and Intelligent Control Key Laboratory Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Industrial Centre Hong Kong Polytechnic University Hong Kong Hong Kong

A novel way achieving geometrical reconstruction of actual human face through projecting two types of texture on face in short time is advanced. The first type texture is stripe which is used to establish parallax grid between images. Taking into account of its results, the second type projecting texture is used to match by virtue of its abundant traits. After realizing geometrical reconstruction, the paper provides a general way about achieving actual texture reconstruction by the outer spherical surface surrounding object. In order to uniform color, it deals with parts of images in conjunct region and makes the color change meeting a certain function on condition of keeping their original information mostly. Results show this way can improve reconstruction quality and decrease complicacy of algorithm.

关键词： image reconstruction

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High resolution dynamic MRI using motion estimated and compensated compressed sensing

High resolution dynamic MRI using motion estimated and compe...

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IEEE International Symposium on Biomedical Imaging

作者： Hong Jung Jong Chul Ye Department of Bio and Brain engineering Korea Adv. Institute of Science & Technology Bio-Imaging and Signal Processing Laboratory Daejeon South Korea

ISBN: (纸本)9781424420025

A model based approach called k-t BLAST/SENSE, has drawn significant attentions from MR imaging community due to its improved spatio-temporal resolution. Recently, we showed that k-t BLAST/SENSE corresponds to the special case of a new dynamic MRI algorithm called k-t FOCUSS that is asymptotically optimal from compressed sensing perspective. The k-t FOCUSS exploits the sparsity of x-f support of dynamic scene and converts imaging problem into an L 1 minimization problem that can be solved using FOCal Underdetermined System Solver (FOCUSS). In this paper, we extend the idea of k-t FOCUSS and introduce motion estimation and compensation (ME/MC) based prediction step and residual encoding step. The ME/MC based prediction step exploits the temporal redundancies using the motion field estimation and provides much sparser residual signals. The sparse residual signal can then be effectively encoded using much smaller number of k-t samples. Simulation results demonstrate that high resolution dynamic MR images can be accurately obtained even from very limited data samples.

关键词： Magnetic resonance imaging Motion estimation Compressed sensing Focusing image resolution High-resolution imaging Heuristic algorithms Layout Encoding signal resolution

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Tomographic image reconstruction from limited-view projections with Wiener filtered focuss algorithm

Tomographic image reconstruction from limited-view projectio...

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IEEE International Symposium on Biomedical Imaging

作者： Rafal Zdunek Zhaoshui He Andrzej Cichocki Institute of Telecommunications Teleinformatics and Acoustics Wroclaw University of Technology Wroclaw Poland Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Saitama Japan

In tomographic image reconstruction from limited-view projections the underlying inverse problem is ill-posed with the rank-deficient system matrix. The minimal-norm least squares solution may considerably differs from the true solution, and hence a priori knowledge is needed to improve the reconstruction. In our approach, we assume that the true image presents sparse features with uniform spacial smoothness. The sparsity constraints are imposed with the lscr p diversity measure that is minimized with the FOCUSS algorithm. The spacial smoothness is enforced with the adaptive Wiener noise removing implemented in each FOCUSS iterations. The simulation results demonstrate the benefits of the proposed approach.

关键词： Tomography image reconstruction Wiener filter Focusing Iterative algorithms Inverse problems Least squares methods signal processing algorithms Acoustics Electronic mail

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