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检索条件"机构=Image Processing and Intelligent System Laboratory"

共 173 条记录，以下是151-160 订阅

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4D wavelet noise suppression of MR diffusion tensor data

4D wavelet noise suppression of MR diffusion tensor data

引用

International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Hesamoddin Jahanian Azadeh Yazdan-Shahmorad Hamid Soltanian-Zadeh Department of Radiology Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA Department of Biomedical Engineering University of Michigan Ann Arbor MI USA Controll and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Diffusion tensor imaging (DTI) is known to be promising for providing anatomical information about white-matter fiber bundles that cannot be obtained by other non-invasive in vivo imaging methods. However, its application is limited because of its low signal-to-noise ratio and significant imaging artifacts. To improve the accuracy of tissue structural and architectural characterization with diffusion tensor imaging 4D wavelet denoising technique is used to improve the signal to noise ratio (SNR) of diffusion tensor images. To evaluate the proposed method, a high SNR data set is built by repeating and averaging the data acquisition several times and is compared to the denoised data. Our results revealed that wavelets would effectively reduce the noise in DTI data with less blurring of tissue types, especially in the white matter. It would suggest that by using the 4D wavelet noise suppression, one could decrease the acquisition time and still have an acceptable SNR.

关键词： Tensile stress Diffusion tensor imaging Signal to noise ratio Noise reduction Magnetic noise Anisotropic magnetoresistance Eigenvalues and eigenfunctions In vivo Magnetic resonance imaging Wavelet analysis

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

引用

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...

引用

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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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

引用

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system Computer vision Motion detection

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Robotic dynamic target recognition and tracking based on the monocular vision

Robotic dynamic target recognition and tracking based on the...

引用

26th Chinese Control Conference, CCC 2007

作者： Lei, Liu Yongji, Wang Huazhong University of Science and Technology Intelligent and Complex System Laboratory Key Laboratory of Image Processing and Intelligent Control Ministry of Education

ISBN: (纸本)7900719229

Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two-value image segmentation. Calculating the distance between the camera and target by the 3D reconstruction algorithm and sub-control strategy, and raise its veracity by laser information fusion. Furthermore, a vision servo system has been designed and utilized to achieve the robot's dynamic track. At last, some experiments were used to certification its availability.

关键词： Robot applications

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Soft Decision Histogram-Based image Binarization for Enhanced ID Recognition

Soft Decision Histogram-Based Image Binarization for Enhance...

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6th International Conference on Information, Communications & Signal processing (ICICS 2007), part 2

作者： Taekyung Kim Joonki Paik Image Processing and Intelligent System Laboratory Department of Image Engineering Graduate School of GSAIM Chung-Ang University Seoul South Korea

ISBN: (纸本)9781424409822

image binarization is one of the main techniques for image segmentation. It segments an image in to foreground and background. The foreground contains interested objects/characters. Usually binarization is carried out with a threshold found from the histogram of an image automatically. In this paper we formulate binarization using Soft Decision Histogram (SDH). The algorithm effectively integrates color clustering and binary texture analysis, and is capable of handling situations with complex and multiple backgrounds. The (SDH) is able to make a soft decision using image histogram while clustering the pixels for binarization. The main advantage by using soft decision is the occurrence of isolated or outlier pixels are overcome, complex background and noise pixels are removed. The proposed algorithm can be use for retrieving both text and objects. Experiments with images collected from Internet has been carried out and compared with existing techniques, both show the effectiveness of the algorithm.

关键词： Histogram image binarization Recognition

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Evaluation of BOLD Sensitivity Using a Realistic MRI Simulator

Evaluation of BOLD Sensitivity Using a Realistic MRI Simulat...

引用

Joint Meeting of the International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging (NFSI-ICFBI)

作者： Ali-Reza Mohammadi-Nejad G.-Ali Hossein-Zadeh Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran Henry Ford Health System Medical Image Analysis Laboratory Detroit MI USA

MRl simulation is a suitable method to evaluate and acquire understanding of the complex blood oxygenation level dependent (BOLD) effect. To study the observability of BOLD signal, we extended a MRI simulator. This simulator is capable of complete modeling of object (tissue) and main field inhomogeneities. We made a digital phantom in which the magnitude of fractional oxygenation (Y), hematocrit (Hct) values in red blood cells, the diameter of vessels, and also the position of blood vessel within the voxel can be changed. Then we created echo planar imaging (EPI) images of the phantom under resting and activated states using the simulator. Resulting images were analyzed using cross-correlation and t-test analysis for activation detection. Then the effect of various parameters on the detection of BOLD is investigated. These parameters include fractional oxygenation, spatial extent of BOLD effect and the location of vessel inside voxel. This simulation study provides a basis for planning experiments aimed at BOLD contrast detection with EPI pulse sequence.

关键词： Magnetic resonance imaging Red blood cells Medical simulation Biomedical imaging image analysis Magnetic susceptibility Analytical models Imaging phantoms Blood vessels Magnetic properties

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Biometric data-based robust watermarking scheme of video streams

Biometric data-based robust watermarking scheme of video str...

引用

International Conference on Information, Communications and Signal processing

作者： Sooyeun Jung Dongeun Lee Seongwon Lee Joonki Paik Image Processing and Intelligent System Laboratory Department of Image Engineering Graduate School of GSAIM Chung-Ang University Seoul South Korea Dept. of Computer Engineering Kwangwoon University Seoul Korea Department of Computer Engineering Kwangwoon University Seoul South Korea

ISBN: (纸本)9781424409822;1424409829

In this paper we propose a method that identifies users in latest compressed streaming with their biometric watermark. Since the fingerprint is the most economical and the most widely used biometric feature, the digital fingerprint watermark system can be one of the best biometric security system. In this paper we propose a digital fingerprint watermark technique that can survive under very low bit rate compression. The proposed algorithm consists of preprocessing of the fingerprint image, watermark insertion using discrete wavelet transform, and watermark recovery. The damaged watermark by high compression ratio can be effectively restored with preprocessing before watermark insertion and accumulation of extracted watermarks in the stream. The simulation results show that the extraction accuracy increases over 99% in the highly compressed H.264 streaming.

关键词： Biometrics Robustness Watermarking Streaming media Fingerprint recognition image coding Discrete wavelet transforms Video compression Security Bit rate

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A Hierarchical Clustering Based on Mutual Information Maximization

A Hierarchical Clustering Based on Mutual Information Maximi...

引用

IEEE International Conference on image processing

作者： M. Aghagolzadeh H. Soltanian-Zadeh B. Araabi A. Aghagolzadeh Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

Mutual information has been used in many clustering algorithms for measuring general dependencies between random data variables, but its difficulties in computing for small size datasets has limited its efficiency for clustering in many applications. A novel clustering method is proposed which estimates mutual information based on information potential computed pair-wise between data points and without any prior assumptions about cluster density function. The proposed algorithm increases the mutual information in each step in an agglomerative hierarchy scheme. We have shown experimentally that maximizing mutual information between data points and their class labels will lead to an efficient clustering. Experiments done on a variety of artificial and real datasets show the superiority of this algorithm, besides its low computational complexity, in comparison to other information based clustering methods and also some ordinary clustering algorithms.

关键词： Mutual information Clustering algorithms Clustering methods Data mining Data structures Density functional theory Computational complexity Entropy Higher order statistics Probability density function

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Mutiple-view object tracking using metadata

Mutiple-view object tracking using metadata

引用

International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Inho Paek Changhan Park Myeongsuk Ki Kyoungju Park Joonki Paik Image Processing and Intelligent System Laboratory Department of Image Engineering Chung-Ang University Seoul South Korea Advanced Technology Research & Development Center Samsung Thales Company Limited Yongin si Gyeonggi South Korea Digital Broadcasting Research Division ETRI Electronics and Telecommunication Research Institute Daejeon South Korea Next Generation Imaging Contents Laboratory Department of Image Engineering Chung-Ang University Seoul South Korea

In this paper we present a moving object tracking method in a multiple camera tracking system using meta-data. The proposed method acquires image sequences from multiple fixed cameras without a priori camera calibration. The tracking is performed based on object's robust characteristics, such as motion, shape, color, and etc. Elements of meta-data and the optimal tracking method are selected at each frame. Because object's characteristics are affected by camera position and environmental condition, tracking method between individual cameras is selected by optimal metadata. Tracking in a single view can be divided into three classes, such as; optical flow-based moving object detector, active shape model (ASM), color correlation based detector. The proposed method matches objects to most similar object color information, by comparing meta-data and ASM. In the experiment, the proposed multi-camera tracking system is show to be robust for non-rigid objects.

关键词： Cameras Tracking Robot vision systems Surveillance Humans Biological system modeling image analysis Robustness Object detection Active shape model

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