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Optimum parameter estimation for non-local means image de-noising using corner information

Optimum parameter estimation for non-local means image de-no...

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2008 9th International Conference on Signal processing(ICSP’2008)

作者： Alireza Nasiri Avanaki Abolfazl Diyanat Shabnam Sodagari Control and Intelligent Processing Center of Excellence School of ECEUniversity of Tehran P.O.Box 14395-515TehranIran Deparment of Electrical Engineering The Pennsylvania State University University ParkPA 16802USA

Non-local means(***-means) method for image de-noising averages the similar parts of an image to reduce random *** de-noising performance of the algorithm,however,highly depends on the values of its *** this paper,we introduce a method for finding the optimum parameters,present a linear estimation for the h parameter,and demonstrate that the most important parameter in this method is almost independent of the image and depends only on the *** also show that the de-noising performance can be increased by using corner information of noisy *** modifications result in better de-noising performance at less computational cost.

关键词： image Optimum parameter estimation for non-local means image de-noising using corner information

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Fusion Based Quality control Using intelligent Estimation and Modeling in Industrial Process control

Fusion Based Quality Control Using Intelligent Estimation an...

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Asia International Conference on Modeling & Simulation

作者： Amin Ramezani Mohamad Reza Andalibizadeh Soheil Bahrampour Hamed Ramezani Behzad Moshiri School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Electrical and Computer Engineering Shahid Beheshti University Tehran Iran School of ECE and the Control and Intelligent Processing Center of Excellence (CIPCE) University of Tehran Tehran Iran

In this paper, to improve quality control system and being in the competition at a cement production line, we implemented a Local Linear Neuro-Fuzzy Model (LLNFM) and Kalman Filter Information Fusion (KFIF). We proposed a novel approach for model reference control of a cement milling circuit that has previously been studied several times. To do so, first gathered information from Distributed Sensor Network (DSN), deployed in the plant, is used to model under-control process based on the LLNFM approach. This LLNFM is used to prepare data for a KFIF system to derive the form of the control vector with the goal of driving the response of the system to that of a desired model in a noisy operating environment. The paper demonstrates the extraction of the reference models and the derivation of the control laws and the results observed justify the tracking and stability claims of the paper.

关键词： Quality control intelligent control Industrial control Process control Electrical equipment industry Production systems Milling Circuits Working environment noise Data mining

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Comparison of two linear models for estimating brain deformation during surgery using finite element method

Comparison of two linear models for estimating brain deforma...

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International Joint Conference on Neural Networks (IJCNN)

作者： Hajar Hamidian Hamid Soltanian-Zadeh Reza Faraji-Dana Masoumeh Gity Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Radiology University of Tehran Medical School Tehran Iran

This paper presents finite element computation of brain deformation during craniotomy. Two mechanical models are compared for this purpose: linear solid-mechanic model and linear elastic model. Both models assume finite deformation of the brain after opening the skull. We use a test sphere as a model of the brain, tetrahedral finite element mesh, and function optimization that optimizes the modelspsila parameters by minimizing the distance between the resulting deformation and the supposed deformation. Based on the final value of the objective function, we conclude that the accuracy of the solid mechanic model is higher than that of the elastic model. Applications of the methods to the MR images of the brain confirm this finding.

关键词： Brain modeling Brain models Mathematical model Optimization Equations Deformable models Computational modeling

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Reduced Reference Watermark-Based Image Transmission Quality Metric

Reduced Reference Watermark-Based Image Transmission Quality...

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3rd International Symposium on Communications, control, and Signal processing (ISCCSP 2008), vol.1

作者： Mohammad Hosain Kayvanrad Shabnam Sodagari Alireza Nasiri Avanaki Hossein Ahmadi-Noubari Embedded Video (EV) Laboratory Department of ECE National University of Singapore Singapore Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Iran Department of ECE University of British Columbia University of Tehran Iran

A novel reduced reference (RR) method of channel estimation for image transmission through lossy channels is presented. Estimation is based on the amount of distortion the low frequency content of the image or its histogram suffers during transmission. This distortion is computed by sending the low frequency content of the original image or the corresponding histogram to the receiver by means of a robust watermark. Simulations for different types of images and different channel losses yield large amounts of correlation between the estimated Mean Square Error (MSE) and the structural similarity (SSIM) index.

关键词： Image transmission Reduced reference quality assessment Watermarking Two dimensional wavelet transform Histogram

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

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International Conference on Information Fusion

作者： Nima Tajbakhsh Babak N. Araabi Hamid Soltanianzadeh Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Iris Feature extraction Discrete cosine transforms Image recognition Databases Training Humans

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Constrained optimization of nonparametric entropy-based segmentation of brain structures

Constrained optimization of nonparametric entropy-based segm...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi Asl Hamid Soltanian-Zadeh School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

We propose a constrained, three-dimensional, nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capture structural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function, which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, constraints are used to improve segmentation quality. These constraints are extracted from training data. Sample results are given for the segmentation of caudate, hippocampus, and putamen, illustrating highly superior performance of the proposed method compared to the most similar methods in the literature.

关键词： Constraint optimization Brain Iterative algorithms Image segmentation Shape Couplings Magnetic resonance Magnetic resonance imaging Principal component analysis Buildings

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Introducing an Incremental Learning Method for Fuzzy Descriptor Models to Identify Nonlinear Singular Systems

Introducing an Incremental Learning Method for Fuzzy Descrip...

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2008 Mediterranean Conference on control Automation, vol.1

作者： M. Mirmomeni C. Lucas M. Shafiee B. N. Araabi Islamic Azad University슠 Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Eng University of Tehran Tehran Iran School of Cognitive Sciences Institute of studies in theoretical Physics and Mathematics Tehran Iran Electrical Engineering Department Amirkabir University of Technology슠 Tehran Iran

Singular systems have been the subject of interest over the last two decades due to their many practical applications. But it has to be said that system identification of such system is still a challenging area because of the difficulty of identification of such systems for their complex structures. In addition, it seems that by developing a useful method for identification of singular system, one can use the useful property of such systems in describing the natural complex phenomena. This paper presents a novel methodology for identifying nonlinear singular systems from empirical data. Singular systems are idealized models for systems with slow and quick modes of change. However, their identification is a challenging problem even for the linear case. A new learning method, generalized locally linear model tree (GLoLiMoT) algorithm is introduced. The contribution of this paper is to provide a method for adjusting the parameters of fuzzy descriptor model, e.g. the splitting ratio and the standard deviation, the number of locally linear neurons or the number of linear singular systems for the consequent part in fuzzy descriptor model as well as the order of the singular system. By these modifications an accurate model of nonlinear singular system is obtained which is compared with several other methods in two case studies. Results depict the power of the proposed approach in describing nonlinear complex phenomena.

关键词： Automation Conferences

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Select Reliable Strategy in Multi-Agent Systems Using Fuzzy Logic-Based Fusion

Select Reliable Strategy in Multi-Agent Systems Using Fuzzy ...

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Asia International Conference on Modeling & Simulation

作者： Amin Ramezani Mohamad Reza Andalibizadeh Soheil Bahrampour Hamed Ramezani Behzad Moshiri PhD student School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Electrical and Computer Engineering Shahid Beheshti University Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran School of ECE and the Control and Intelligent Processing Center of Excellence (CIPCE) University of Tehran Tehran Iran

In this paper we implemented a fully knowledge base approach for determine the attack/defense strategies of a team of soccer robots as a multi agent system which are playing two cooperative and non-cooperative games in a battle field simultaneously. First two teams play in non-cooperative game and find their equilibrium point and payoff then all players in a team tries reaching to this position. As there are several decision about team strategy in non-cooperative game and player strategy in cooperative game, our novel approach to use Fuzzy Integral Operators (F10) to fuse sensory information enables designer to softly change team strategy and play the most likelihood game to a real game. Selecting the shape of FIO affect directly on the team strategy and players' position and be reviewed in this paper. This approach will be imported in both, cooperative and non-cooperative game when we face to a multi- hypothesis structure. Results justified successfully the improved performance in team action.

关键词： Multiagent systems Fuzzy logic Fuzzy systems Robot sensing systems Reliability engineering intelligent robots Game theory Asia Computational modeling Computer simulation

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Multiple Heterogeneous Ant Colonies with Information Exchange

Multiple Heterogeneous Ant Colonies with Information Exchang...

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Congress on Evolutionary Computation

作者： Arash Arami Bijan Rahmizadeh Rofoee Caro Lucas Control and Intelligent Processing Center of Excellence (CIPCE) school of Electrical and Computer Engineering University of Tehran Tehran Iran Electrical and Computer Engineering Department Tabriz University Tabriz Iran School of Cognitive Science Institute of Studies in Theoretical Physics and Mathematics Tehran Iran CIPCE school of Electrical and Computer Engineering University of Tehran Tehran Iran

The method of multiple heterogeneous ant colonies with information exchange (MHACIE) is presented in this paper with emphasis on the speed of finding the optimal solution and the corresponding computational complexity. The proposed method which is inspired by biology and psychology has a structure composed of several ant colonies. These colonies participate in solving problems in a concurrently manner and also exchange information with each other in communicational steps. Each ant colony is considered as an intelligent agent with behavioral traits. These behavioral traits play a key role in the solving procedure, in interrelation circumstances and in installation of relations. Faster solutions have been achieved using different employments of agents in the algorithm structure. Experimental results show the superiority of Multiple heterogeneous ant colonies algorithm in comparison to the standard ant colony system (ACS) and particle swarm optimization (PSO) algorithms on different benchmarks. A dynamic, control engineering benchmark is also provided in order to gain a more complete evaluation of the proposed algorithm.

关键词： Benchmark testing Evolution (biology) Optimization Heuristic algorithms Evolutionary computation Electronic mail Educational institutions

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Volumetric Non-rigid Registration via Thin-plate Spline Model

Volumetric Non-rigid Registration via Thin-plate Spline Mode...

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第七届亚太地区医学与生物学工程学术年会

作者： F.Babapour A.Abbaspour R.Zoroofi S.H.Akhlaghpoor Engineering Faculty Science and Research Campus Islamic Azad University P. O. Box 14515-775 Tehran Iran Control and Intelligent Processing Center of Excellence Elec. and Comp. Eng. Department University of Tehran Tehran 14399 Iran Department of Radiology Faculty of Medicine Tehran University of Medical Sciences Tehran Iran

Registration and warping are essential steps in volumetric data fusion. Medical images are of major parts in diagnosing and treatment and actually are considered a total evaluation of work. In resent years medicines have been using diagnosing devices contain computers as a complementary in detecting harms, evaluating the amount of harm deciding the way of treatment. By quick developing in construction of three dimensional medical imaging devices, high resolution modali-ties could be used to produce lots of images. This issue is cru-cial specially in case of medical imaging like Ultrasound, CT and MRI which helps medicines in diagnosing, treatment and investigations. In radiation therapy these information includes surface tex-ture, extracting specified object area in image, and detecting of tumor which can increase the power of medical doctor diag-nosing power and usage of image processing techniques will become important in these area. Finding the exact location of target with enough magnification is one of the primary needs in effective radiation therapy. Results show that a Thin Plate Spline is a sufficient model for a volumetric non-rigid registration. The technique is evalu-ated by mapping of a sphere to a cube and then on a medical object. Experimental result declares that the employed tech-nique is robust in the presence of the noise, changing the num-ber of control points and works effectively in different object resolutions.

关键词： Registration, Warping, Thin-plate Spline.

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