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Effective supervised classification of fMRI activation maps between populations by spatial descriptors

Effective supervised classification of fMRI activation maps ...

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2011 7th Iranian Conference on Machine vision and image processing, MVIP 2011

作者： Eshaghian, Shaghayegh Hossein-Zadeh, Gholam-Ali Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI 48202 United States

ISBN: (纸本)9781457715358

The major obstacle in discrimination between different groups of subjects in a common cognitive state, by functional Magnetic Resonance Imaging (fMRI), has been the high intersubject functional and anatomical variability in the spatial patterns of brain activity. To overcome this, we have used two types of spatial descriptors that characterize the brain regions of interest (ROIs) involved in the cognitive tasks. They include, firstly three-dimensional invariant moment descriptors (3-DMIs), and secondly k-dimensional feature vectors based on concentric spheres. Both types of descriptors are applied to analyze the spatial patterns of cognitive activity of a challenging task and then to classify them across two different subject groups. SVM classifiers along with sequential floating forward feature selection technique are applied to the extracted descriptors of each ROI across the subjects. Our method is applied to experimental fMRI data with the aim of discriminating mental status of heroin IV (Intravenous) abusers and from of those in control subjects in a visual cue task which can induce drug craving. Our results demonstrate that 3-D texture of activation maps provide a good discrimination (with high accuracy) between healthy and addict group. © 2011 IEEE.

关键词： Brain

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Minutiae Triangle Graphs: A New Fingerprint Representation with Invariance Properties

Minutiae Triangle Graphs: A New Fingerprint Representation w...

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International Conference on image and vision Computing New Zealand, IVCNZ

作者： Akmal-Jahan Mohamed-Abdul-Cader Watcharapong Chaidee Jasmine Banks Vinod Chandran Vision and Signal Processing Lab School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Australia Signal and Image Processing Laboratory Kasetsart University Bangkok Thailand

A new algorithm for matching finger or palm prints is presented for use where the full hand is considered as a biometric and only parts may be available in images for comparison. The algorithm uses an extended version of the minutiae-based approach treating the pattern as a graph of minutiae-like points. The procedure to identify minutiae-like points uses Gabor filtering, edge detection and thinning and following line patterns. A set of such points is subjected to Delaunay triangulation yielding a starting set of base-triangles for matching. There can be multiple matches of such triangles between the template and test - as similar triangles with a tolerance in the angles. Graphs are then grown to 5 and more nodes as long as a match can be found, until the maximum size matching graph is obtained. If the test matches a significant part of the template, the maximum order of graph matched will be high. The matching process is robust to transformations such as rotation, translation and scale changes. It can be applied to any part of the hand provided minutiae-like points are identifiable prior to the matching steps. The algorithm is tested using 158 fingerprint images from FVC 2002 DB1. 100 genuine and 5048 impostor scores are generated from 46 templates and 112 testing images. It had an EER of about 6%. It proves the principle behind the methodology and demonstrates that the method can be effective with degraded fingerprint images and is robust to similarity transformations present in the data. It can be applied for forensic fingerprint matching from the palm or parts other than the fingertips. By using multiple parts and multiple templates, the accuracy of the method will be improved with fusion in future versions of the algorithm.

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Model-based multiview stereo via level sets with statistical shape prior

Model-based multiview stereo via level sets with statistical...

引用

IEEE International Conference on image processing

作者： Moumen El-Melegy Nagi Al-Ashwal Aly A. Farag Electrical Engineering Department Assiut University Asyut Egypt Computer Vision and Image Processing Laboratory University of Louisville KY USA

In this paper, we propose a methodology to incorporate 3D shape prior information in multi-view stereo. This is important for applications that deal with specific category of objects. The methodology is based on a new formulation of a level-set based energy functional. Shape prior model is then embedded in the energy functional to allow the reconstruction of an object with shape variations consistent with the training model examples. Several experiments to evaluate the proposed methodology are presented.

关键词： Shape image reconstruction Level set Stereo vision Solid modeling Training Ellipsoids

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Variational-based method to extract parametric shapes from images

Variational-based method to extract parametric shapes from i...

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International Conference on computer vision (ICCV)

作者： M.T. El-Melegy N.H. Al-Ashwal A.A. Farag Electrical Engineering Department Assiut University Asyut Egypt Computer Vision and Image Processing Laboratory University of Louisville KY USA

In this paper, we propose a variational method to segment image objects, which have a given parametric shape based on a level-set formulation of the Mumford-Shah functional, and the shape parameters. We define an energy functional composed by two complementary terms. The first one detects object boundaries using a Chan-Vese-like method. The second term constrains the contour to find a shape compatible with the parametric shape. The segmentation of the object of interest is given by the minimum of our energy functional. This minimum is computed with the calculus of variation and the gradient descent method that provide a system of evolution equations solved with the well-known level set method. We focus in this paper on the parametric category of image linear objects. Applications of the proposed model are presented on synthetic and real images

关键词： Shape image segmentation Level set computer vision Focusing image processing Object detection Calculus Application software Equations

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Universal image steganalysis against spatial-domain steganography based on energy distribution of singular values

Universal image steganalysis against spatial-domain steganog...

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7th International Conference on Information Technology and Application, ICITA 2011

作者： Shojaei-Hashemi, Anahita Soltanian-Zadeh, Hamid Ghaemmagham, Shahrokh Kamarei, Mahmoud School of Electrical and Computer Engineering College of 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 Electronics Research Institute Sharif University of Technology Tehran Iran

ISBN: (纸本)9780980326741

A passive image steganalysis method is proposed to universally detect spatial-domain steganography schemes. It is shown to have better performance than universal steganalyzers known to be powerful in spatial domain, including the WFLogSv and the WAM methods. This level of accuracy is the result of improving the WFLogSv steganalyzer by considering a more comprehensive relationship between the singular values of each image block and the linear correlation of the rows and the columns. That is, instead of the closeness of the lower singular values to zero, the energy distribution of the singular values is investigated. An innovative measure is proposed for this investigation, which is inspired from arithmetic mean-geometric mean inequality. Experimental results confirm the supremacy of the proposed steganalysis scheme over its counterparts.

关键词： Singular value decomposition

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Universal steganalysis based on local prediction error in wavelet domain

Universal steganalysis based on local prediction error in wa...

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7th International Conference on Intelligent Information Hiding and Multimedia Signal processing, IIHMSP 2011

作者： Shojaei-Hashemi, Anahita Mehdipour-Ghazi, Mostafa Ghaemmaghami, Shahrokh Soltanian-Zadeh, Hamid School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electronics Research Institute Sharif University of Technology 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

ISBN: (纸本)9780769545172

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes. © 2011 IEEE.

关键词： Wavelet decomposition

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An improved low-complexity multiple description coding for peer-to-peer video streaming

An improved low-complexity multiple description coding for p...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Majid R. Ardestani Ali Asghar Beheshti Shirazi Mahmoud Reza Hashemi Image Processing Laboratory School of Electrical Engineering Iran University of Science and Technology Tehran Iran Multimedia Processing Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

Multiple description scalable coding based on T+2D wavelet decomposition structure is highly flexible for peer-to-peer (P2P) video streaming. Finding the optimal truncation point of each code block (CB) within each description is an NP-hard problem. To implement an efficient low-complexity solution, we propose a simple clustering algorithm for partitioning the CBs into a limited number of clusters, such that one can find the optimal cluster-level redundancy-rate assignment matrix using a low-complexity full search. This approach improves the decoding quality compared to the co-echelon frameworks in which a non-optimal rate assignment matrix is used. In addition, the proposed clustering approach may be analytically represented by closed-form relations for low-complexity computation of optimal encoding parameters. The simulation results demonstrate that the adaptive proposed framework outperforms the approaches in by (0.25~1 dB), the scheme of by (1.3~1.6 dB), and the non-adaptive multiple description coding by (2.3~4.3 dB). Furthermore, the proposed clustering approach requires %52-%88 less computations compared to the framework in.

关键词： Encoding Clustering algorithms Streaming media Resource management Peer to peer computing Video coding Algorithm design and analysis

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Rate-distortion modeling for scalable video coding

Rate-distortion modeling for scalable video coding

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International Conference on Telecommunications (ICT)

Scalable video coding allows for post-encoding adaptation of the coded bit stream. An appropriate rate-distortion model of the embedded bit stream can be useful for deriving closed-form relations between the parameters of the scalable encoder and the time-varying channel condition values. With a well-defined model, an adaptation mechanism can quickly update the optimal values of the encoder parameters within each transmission period, and hence, a real-time implementation may be realized. In this paper, two simple and accurate empirical (hyperbolic and exponential) models are developed for modeling the rate-distortion characteristics of a scalable video encoder based on motion-compensated temporal filtering (MCTF) and two-dimensional (spatial) discrete wavelet transform (2D-DWT). The experimental results demonstrate that the hyperbolic model has an acceptable approximation error (0.2~0.85dB) relative to the actual measurements, however, the exponential model demonstrates more error (0.75~3dB) relative to the actual measurements.

关键词： Rate-distortion Video coding Streaming media Filtering Approximation error Discrete wavelet transforms Peer to peer computing Bandwidth Static VAr compensators image processing

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A new video watermarking protocol

A new video watermarking protocol

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： E. Delp E. Lin Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

This paper overviews the problems with temporal synchronization in video watermarking and describes a new approach for efficient synchronization and resynchronization. A complete version of the new method has been pre... 详细信息

关键词： Watermarking Protocols Detectors Signal processing Robustness Streaming media image processing Laboratories Digital TV Digital video broadcasting

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Backward Channel Aware Wyner-Ziv Video Coding

Backward Channel Aware Wyner-Ziv Video Coding

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IEEE International Conference on image processing

作者： Limin Liu Zhen Li Edward J. Delp School of Electrical and Computer Engineering Purdue University Video and Image Processing Laboratory West Lafayette IN USA

Wyner-Ziv video coding is a low complexity video encoding method that exploits source statistics at the decoder and shifts much of the computational complexity from the encoder to the decoder. Many Wyner-Ziv video coding schemes rely on the use of INTRA frames so that the decoder can derive sufficiently accurate side information. In this paper we extend our previous work on Wyner-Ziv coding that uses backward channel aware motion estimation. The basic idea is to perform motion estimation at the decoder and send the motion information back to the encoder through a backward channel. Experimental results show that this method can significantly improve the coding efficiency with a minimal use of the backward channel bandwidth. We also propose an error resilient technique by using error detection and adaptive coding to handle the situation when the backward channel is subject to erasure errors or delays.

关键词： Video coding Decoding Motion estimation image coding Extrapolation Noise reduction Interpolation image processing Statistics Computational complexity

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