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International Conference on Security and Cryptography (SECRYPT)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Fac. des nouvelles technologies de l'information et de la communication Lab. de Génie Electrique Ouargla Algeria Electronics and Computer Science Faculty Signal and Image Processing Laboratory Algiers Algeria Department of Computer Science and Digital Technologies Northumbria University Newcastle Newcastle upon Tyne U.K

In current society, reliable identification and verification of individuals are becoming more and more necessary tasks for many fields, not only in police environment, but also in civilian applications, such as access control or financial transactions. Biometric systems are used nowadays in these fields, offering greater convenience and several advantages over traditional security methods based on something that you know (password) or something that you have (keys). In this paper, we propose an efficient online personal identification system based on Multi-Spectral Palmprint (MSP) images using Contourlet Transform (CT) and Gabor Filter (GF) response. In this study, the spectrum image is characterized by the contourlet coefficients sub-bands. Then, we use the Hidden Markov Model (HMM) for modeling the observation vector. In addition, the same spectrum is filtered by the Gabor filter. The real and imaginary responses of the filtering image are used to create another observation vector. Subsequently, the two sub-systems are integrated in order to construct an efficient multi-modal identification system based on matching score level fusion. Our experimental results show the effectiveness and reliability of the proposed method, which brings both high identification and accuracy rate.

关键词： Biometrics (access control) Feature extraction Hidden Markov models Databases Computational modeling Computed tomography Hamming distance

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SAR image multiclass segmentation using a multiscale and multidirection triplet Markov fields model in nonsubsampled contourlet transform domain

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Information Fusion 2013年第4期14卷 441-449页

作者： Yan Wu Peng Zhang Ming Li Qiang Zhang Fan Wang Lu Jia Remote Sensing Image Processing and Fusion Group School of Electronic Engineering Xidian University P.O. Box 140 Xi’an Shaanxi 710071 China National Key Lab. of Radar Signal Processing Xidian University Xi’an 710071 China

Triplet Markov fields (TMFs) model recently proposed is to deal with nonstationary image segmentation and has achieved promising results. In this paper, we propose a multiscale and multidirection TMF model for nonstationary synthetic aperture radar (SAR) image multiclass segmentation in nonsubsampled contourlet transform (NSCT) domain, named as NSCT-TMF model. NSCT-TMF model is capable of capturing the contextual information of image content in the spatial and scale spaces effectively by the construction of multiscale energy functions. And the derived multiscale and multidirection likelihoods of NSCT-TMF model can capture the dependencies of NSCT coefficients across scale and directions. In this way, the proposed model is able to achieve multiscale information fusion in terms of image configuration and features in underlying lab.ling process. Experimental results demonstrate that due to the effective propagation of the contextual information, NSCT-TMF model turns out to be more robust against speckle noise and improves the performance of nonstationary SAR image segmentation.

关键词： SAR image multiclass segmentation NSCT-TMF model NSCT-HMT NSCT-TMF energy function Multiscale information fusion

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Adaptive image compression using sparse dictionaries

Adaptive image compression using sparse dictionaries

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2012 19th International Conference on Systems, signals and image processing, IWSSIP 2012

作者： Horev, Inbal Bryt, Ori Rubinstein, Ron Signal and Image Processing Lab. Department of Electrical Engineering Technion Haifa Israel Geometric Image Processing Lab. Department of Computer Science Technion Haifa Israel

ISBN: (纸本)9783200023284

Transform coding is a widely used image compression technique, where entropy reduction can be achieved by decomposing the image over a dictionary which provides compaction. Existing algorithms, such as JPEG and JPEG2000, utilize fixed dictionaries which are shared by the encoder and decoder. Recently, works utilizing content-specific dictionaries show promising results by focusing on specific classes of images and using highly specialized dictionaries. However, such approaches lose the ability to compress arbitrary images. In this paper we propose an input-adaptive compression approach, which encodes each input image over a dictionary specifically trained for it. The scheme is based on the sparse dictionary structure, whose compact representation allows relatively low-cost transmission of the dictionary along with the compressed data. In this way, the process achieves both adaptivity and generality. Our results show that although this method involves transmitting the dictionary, it remains competitive with the JPEG and JPEG2000 algorithms. © 2012 Institute of Telecommunica.

关键词： image compression

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Robust and efficient change detection algorithm based on 3D line segments

Robust and efficient change detection algorithm based on 3D ...

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2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

作者： Zohar, Tom Ariav, Ido Bar-Zohar, Meir Signal and Image Processing Lab. Department. of Electrical Engineering Technion Israel Institute of Technology Haifa 32000 Israel

ISBN: (纸本)9781467346801

In this paper we examine and improve a new approach for change detection (introduced in [1]) which is based on the appearance and disappearance of 3D line segments as seen in a new image. These 3D line segments are estimated from a set of learning images taken from arbitrary viewpoints and under arbitrary light conditions in an unsupervised manner. The main advantage of the proposed method lies in the fact that the change detection is performed by comparing line segments, and not surfaces or gray levels. Computing 3D surfaces in an image can be computationally intensive, and other methods such as image subtraction or cross-correlation are sensitive to lighting conditions and changes in viewpoints. Moreover, most man-made objects such as buildings, cars, and even cities viewed from above consist mainly of straight lines, and therefore this method is highly applicable for such structures. The proposed algorithm first focuses on the reconstruction of a set of 3D line segments forming a certain 3D scene using a set of 2D line segments obtained from the learning images in an unsupervised manner, without any prior knowledge on the cameras' positions or relative distance. In the change detection stage, we use the reconstructed 3D scene of line segments to check if changes, such as appearance or disappearance of objects, have occurred in a given test image. This test image can be taken from arbitrary viewpoint and under arbitrary lighting conditions. Our change detection algorithm not only distinguishes between the states of 'changed' and 'not-changed' line segments, it also classifies the 'changed' line segments as appeared - objects that entered the scene in the test image, and disappeared - objects that left the 3D scene reconstructed from the lines of the learning images. © 2012 IEEE.

关键词： Three dimensional computer graphics

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Remote nautical bottom estimation for the safety of navigation offshore Amazon River mouth

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The Journal of the Acoustical Society of America 2014年第4_SUPPLEMENT期135卷 2168-2168页

作者： Qunyan Ren Jean-Pierre Hermand Acoust. & Environ. HydroAcoust. Lab. Labs. of Image Signal Processing and Acoust.-Ecole polytechnique de Bruxelles / Faculté des Sci. U.L.B. ave. F.-D. Roosevelt 50 CP 165/57 Brussels 1050 Belgium qunyren@ulb.ac.be

In muddy areas, the fluid sediment layer can reach a level of “nautical bottom” that can contact with a ships keel causing either damage or unacceptable effects on controllab.lity and maneuverability. Consequently, the minimum depth and allowed draught need to be determined for the safety of navigation. An acoustic remote sensing technique is proposed to facilitate navigation safety applications through the determination of sediment layer properties. It uses range and frequency-dependent features of the vertical waveguide characteristic impedance, as defined by the ratio of pressure and vertical particle velocity (or pressure gradient) at a given frequency. Such ratio can circumvent inversion uncertainty due to insufficient knowledge of complex time-varying ship noise spectrum because of its source spectral level independent. Real ship noise data recorded on a compact array offshore at the mouth of the Amazon River in Brazil, 2012, are processed by a global optimization based inversion scheme. The inverted results demonstrate that technique can estimate the effective water depth through resolving sediment layers properties, especially the density. The promising results demonstrate the feasibility of this technique to facilitate safety navigation applications at port areas.

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DYNAMIC 3D PET RECONSTRUCTION FOR KINETIC ANALYSIS USING PATCH-BASED LOW-RANK PENALTY

DYNAMIC 3D PET RECONSTRUCTION FOR KINETIC ANALYSIS USING PAT...

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IEEE Nuclear Science Symposium and Medical Imaging Conference

作者： K. S. Kim Y. D. Son Z. H. Cho J. B. Ra J. C. Ye Bio Imaging & Signal Processing Lab. Dept. of Bio& Brain Engineering KAIST Neuroscience Research Institute Gachon University of Medicine and Science Image Systems Lab. Electrical Engineering KAIST

ISBN: (纸本)9781467320283

Dynamic positron emission tomography (PET) is widely used to identify metabolism over time. However, conventional reconstruction algorithm provides a noisy reconstruction due to the lack of photon counts in each frame. Therefore, the main goal of this paper is to develop a novel spatio-temporal regularization approach that exploits inherent similarities within intra- and inter- frames. One of the main contributions of this paper is to demonstrate that such correlations can be exploited using a low rank constraint of overlapping similarity blocks. The resulting optimization framework is, however, non-smooth and non Lipschitz due to the low-rank penalty terms and Poisson log-likelihood. Therefore, we propose a novel globally convergent optimization method using the concave-convex procedure (CCCP) by exploiting Legendre-Fenchel *** confirm that the proposed algorithm can provide significantly improved image quality.

关键词： CCCP PET LOW-RANK PENALTY

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Performances in multitarget tracking for convoy detection over real GMTI data

Performances in multitarget tracking for convoy detection ov...

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作者： Pollard, Evangeline Pannetier, Benjamin Rombaut, Michèle Information Processing and Modeling Department ONERA Chatillon France Image and Signal Department GIPSA-lab. Grenoble France

ISBN: (纸本)9780982443811

A convoy is defined as a group of vehicles traveling together for mutual support and protection. It constitutes an object of high military interest in the context of the situation assessment. However, it is a challenging task to track and evaluate because convoy targets are very close of each other. In this view, the Onera recently developed a new two step convoy detection process. The first is an original tracking algorithm appropriate for Ground Moving Target Indicator (GMTI) data based on the hybridization of two classical multitarget tracking algorithms, and adapted to closely spaced target tracking. Then, by using algorithm outputs and other data, vehicle aggregates are detected and their characteristics are introduced into a Dynamic Bayesian Network (DBN) which processes the probability for an aggregate to be a convoy. This process gives encourageous results with simulated data. In this paper, we validate this process by showing real data results.

关键词： Aggregates

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A Bayesian hierarchical mixture of experts approach to estimate speech quality

A Bayesian hierarchical mixture of experts approach to estim...

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2010 2nd International Workshop on Quality of Multimedia Experience, QoMEX 2010

作者： Mossavat, S. Iman Amft, Oliver De Vries, Bert Petkov, Petko N. Kleijn, W. Bastiaan Signal Processing Systems Department of Electrical Engineering Eindhoven University of Technology Netherlands Sound and Image Processing Lab. Department of Electrical Engineering KTH-Royal Institute of Technology Sweden

ISBN: (纸本)9781424469604

This paper demonstrates the potential of theoretically motivated learning methods in solving the problem of non-intrusive quality estimation for which the state-of-the-art is represented by ITU-T P.563 standard. To construct our estimator, we adopt the speech features from P.563, while we use a different mapping of features to form quality estimates. In contrast to P.563 which assumes distortion-classes to divide the feature space, our approach divides the feature space based on a clustering which is learned from the data using Bayesian inference. Despite using weaker modeling assumptions, we are still able to achieve comparable accuracy on predicting mean-opinion-scores with P.563. Our work suggests Bayesian model-evidence as an alternative metric to correlation-coefficient for determining the necessary number of experts for modeling the data. ©2010 IEEE.

关键词： Bayesian networks

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Edge-adaptive transforms for efficient depth map coding

Edge-adaptive transforms for efficient depth map coding

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28th Picture Coding Symposium, PCS 2010

作者： Shen, G. Kim, W.-S. Narang, S.K. Ortega, A. Lee, Jaejoon Wey, HoCheon Signal and Image Processing Institute University of Southern California United States Multimedia Lab. Samsung Advanced Institute of Technology Samsung Electronics Co. Ltd. Korea Republic of

ISBN: (纸本)9781424471348

In this work a new set of edge-adaptive transforms (EATs) is presented as an alternative to the standard DCTs used in image and video coding applications. These transforms avoid filtering across edges in each image block, thus, they avoid creating large high frequency coefficients. These transforms are then combined with the DCT in H.264/AVC and a transform mode selection algorithm is used to choose between DCT and EAT in an RD-optimized manner. These transforms are applied to coding depth maps used for view synthesis in a multi-view video coding system, and provides up to 29% bit rate reduction for a fixed quality in the synthesized views. © 2010 IEEE.

关键词： image coding

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3-D video coding using depth transition data

3-D video coding using depth transition data

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28th Picture Coding Symposium, PCS 2010

作者： Kim, Woo-Shik Ortega, Antonio Lee, Jaejoon Wey, Ho Cheon Signal and Image Processing Institute Ming Hsieh Dept. of Electrical Engineering University of Southern California Los Angeles CA 90089 United States Multimedia Lab. Samsung Advanced Institute of Technology Samsung Electronics Co. Ltd. Korea Republic of

ISBN: (纸本)9781424471348

The objective of this work is to develop a new 3-D video coding system which can provide better coding efficiency with improved subjective quality as compared to existing 3-D video systems. We have analyzed the distortions that occur in rendered views generated using depth image based rendering (DIBR) and classified them in order to evaluate their impact on subjective quality. As a result, we found that depth map coding distortion leads to "erosion artifacts" at object boundaries, which lead to significant degradation in perceptual quality. To solve this problem, we propose a solution in which depth transition data is encoded and transmitted to the decoder. Depth transition data for a given pixel indicates the camera position for which this pixel's depth will change. A main reason to consider transmitting explicitly this information is that it can be used to improve view interpolation at many different intermediate camera positions. Simulation results show that the subjective quality can be significantly improved by reducing the effect of erosion artifacts, using our proposed depth transition data. Maximum PSNR gains of about 0.5 dB can also be observed. © 2010 IEEE.

关键词： image coding

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