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Automatic organs' detection in WCE

Automatic organs' detection in WCE

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International Symposium on Artificial Intelligence and Signal processing (AISP)

作者： Omid Haji-Maghsoudi Alireza Talebpour Hamid Soltanian-Zadeh Navid Haji-maghsoodi Department of Radiation Medicine Shahid Beheshti University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Hospital Detroit MI USA Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Mechatronics Sharif University of Tehran Tehran Iran

Wireless capsule endoscopy (WCE) views the entire gastrointestinal (GI) tract. A main problem associated with this novel device is that too many frames must be reviewed by physicians. Thus it is essential to find an automatic and intelligent method to help physicians. One of the problems in WCE is its difficulty to distinguish among different organ's tissues. So, we introduce two novel algorithms which are able to classify main organs (among esophagus, stomach, small bowel and colon) in WCE's frames. In order to obtain our aim, we use statistic features (Haralick features) and non-statistic features (different diagrams and Gabor filter banks), colored features and non-colored features. Our experimental studies indicate good results that are shown in conclusion.

关键词： Level set Medical services Gabor filters Active contours Wireless communication Optical wavelength conversion Esophagus

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Elastic shape registration using an incremental free form deformation approach with the ICP algorithm

Elastic shape registration using an incremental free form de...

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Canadian Conference on computer and Robot vision

作者： Abdelmunim, Hossam Farag, Aly A. Computer and Systems Engineering Department Faculty of Engineering Ain Shams University Cairo 11517 Egypt Computer Vision and Image Processing Laboratory Electrical and Computer Engineering Department University of Louisville KY 40292 United States

ISBN: (纸本)9780769543628

Shape registration is one of the most challenging problems in computer vision and medical imaging. The process is affected by the way the shape is represented and the form of transformation used to move the source shape. Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point-based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as a criteria to establish point correspondences in each level of the IFFD framework. The free form deformation (FFD) is well known in the literature and works by forming a lattice of control points that can move and hence deform the domain grid points smoothly and uniformly under some shape constrains. The control lattice resolution is increased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems. © 2011 IEEE.

关键词： Medical imaging

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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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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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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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Secret Sharing in the Encrypted Domain with Secure Comparison

Secret Sharing in the Encrypted Domain with Secure Compariso...

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2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

作者： Bin Zhao Edward J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

Secret sharing refers to the sharing and reconstruction of a secret among a group of participants. In light of a few disadvantages of the traditional secret sharing, it is desirable to reconstruct the secret directly from the encrypted shares to protect the secret and shares during secret reconstruction. This paper develops several useful techniques for processing encrypted data. A new secure comparison protocol based on the additive homomorphic property and a new scheme of secret sharing in the encrypted domain with secure comparison are proposed. In this scenario, secret reconstruction could be done on an untrusted device while comparison is performed in a trusted environment. Experimental results confirm the effectiveness of the proposed scheme and protocol.

关键词： Protocols Additives Encryption Polynomials computer science

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Frequency domain feature-based face recognition technique for different poses and low-resolution conditions

Frequency domain feature-based face recognition technique fo...

引用

IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Seyed Omid Shahdi S.A.R. Abu-Bakar Computer Vision Video and Image Processing (CvviP) Research Laboratory Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

Pose variations are known to give real challenges in face recognition system. In this paper we proposed a method to recognize non-frontal faces with high performance by relying only on single full frontal gallery faces. By utilizing only small regions of the face or patches, we compute the Fourier coefficients of these patches for each image and transform them into a single vector. Hence, instead of comparing and matching pixels values we use these vectors to form a linear relationship which is then used to estimate the frontal face vector and then compare it with the actual frontal feature vector. The results show an average performance accuracy of 90% across all pose.

关键词： Face Face recognition Databases Feature extraction Training Vectors

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Co-ordinate mapping and analysis of vehicle trajectory for anomaly detection

Co-ordinate mapping and analysis of vehicle trajectory for a...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Satyam Srivastava Ka Ki Ng Edward J. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

Behavioral information can be inferred from the trajectory of a rigid object. We propose a method to detect anomalies in the approach of a vehicle by observing the patterns in its velocity and describe methods for more effective analysis of the velocity trajectory. First we define a hypothetical co-ordinate system in which the axes are specified with respect to the road and distances are true ground measurements. In this co-ordinate system the (axial) velocity is a one dimensional quantity. We estimate the “normal” trends in the velocities by activity path modeling after scaling the velocities by the vehicle's average speed. We detect an anomaly if a vehicle's velocity does not fall in the available path models. Finally, we use the shape of the trajectory to determine turns and other significant maneuvers. We also detect an anomaly if a vehicle's velocity falls in a path model which is inconsistent with the shape of its trajectory. We observe that our proposed co-ordinate system also improves trajectory shape analysis by suppressing false turns.

关键词： Trajectory Vehicles Shape Roads Table lookup Real time systems Object detection

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Foreground segmentation with sudden illumination changes using a shading model and a Gaussianity test

Foreground segmentation with sudden illumination changes usi...

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International Symposium on image and Signal processing and Analysis

作者： Ka Ki Ng Satyam Srivastava Edward J. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

In this paper, we propose a simple method for foreground segmentation based on a “Gaussianity test” and a shading model. The proposed method works under a hierarchical framework that combines a block based and a pixel based processing. The first step is a block-level classification based on the intensity differences and intensity ratios of a background model and the current frame. We then use pixel-wise adaptive background subtraction on the foreground classified blocks to obtain the foreground mask. We test our proposed method on several sequences with indoor scenes with extreme sudden illumination changes, and outdoor scenes under strong sunlight, waving tree leaves, and walking pedestrians. The method is shown to be robust to extreme sudden illumination changes and the presence of relatively small scene clutter motion (e.g. waving tree branches and leaves).

关键词： image segmentation Robustness Educational institutions

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